Methods for monitoring and diagnosing diseases

Abstract

Disclosed herein are methods for making a healthy transcriptome-wide expression profile of a biological sample and identifying biomarkers that can be used to diagnose, monitor the onset, monitor the progression, and assess the recovery of a risk, complication or disease in a subject.

Description

[0001] METHODS FOR MONITORING AND DIAGNOSING DISEASES

[0002] CROSS REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of U. S. Provisional Application No. 63 / 713,871, filed October 30, 2024. The content of this earlier filed application is hereby incorporated byreference herein in their entirety.

[0004] STATEMENT REGARDING FEDERALLY FUNDED RESEARCH

[0005] This invention was made with government support under HL 145237 awarded by the National Institutes of Health. The government has certain rights in the invention.

[0006] FIELD OF THE INVENTION

[0007] The present disclosure relates to medical diagnostics in the context of women's health. More specifically, the present disclosure relates to compositions and methods for identifying women at high risk of developing complications during pregnancy. The technology finds applications in a range of diseases, including but not limited to infectious diseases, cancers, autoimmune diseases, hematologic diseases, reproductive diseases, CNS diseases, genetic diseases, endocrine diseases, neurological disorders, and cardiovascular diseases, as well as disease affecting women, including but not limited to ovarian cancer, breast cancer, pregnancy complications, and con ical cancer.

[0008] BACKGROUND

[0009] Disease diagnostics, especially in women's health, often require the identification of specific gene expression signatures associated with the condition of interest. Traditional methods for selecting these gene signatures are hampered by issues of repeatability-, scalability, and sensitivity. Additionally, the use of large sample sizes in clinical studies can be expensive and time-consuming. Current diagnostic testing approaches often rely on invasive and / or relatively expensive methods which may not provide comprehensive, accurate, or timely information. Current diagnostic testing approaches also are platformdependent, limiting transportability- and scalability- across health care and laboratory- settings. These methods are limited in their ability to accurately and adequately monitor disease progression, remission, recurrence and response to therapy, predict complications and often fail to detect subtle changes that could indicate a problem. These methods are also not amenable to home-based blood collection or medical care, thus, limiting access for some patients and adding to overall health care costs. As a result, complications can go undetected until they become severe, leading to adverse outcomes for both the mother and the fetus. More precise “healthy” or informative references are needed for diagnostic testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] FIG. 1 shows an overview of the methods disclosed herein and approach to developing a diagnostic classifier using longitudinal gene stability data.

[0011] FIGS. 2A-D show an example of three cancer types (stage I / II ovarian cancer (FIGS.

[0012] 2A-B), non-small cell lung cancer (FIG. 2C), and glioblastoma multiforme (FIG. 2D), where incorporation of longitudinal gene stability (blue) improves diagnostic performance compared to standard approaches, where stable and unstable genes are used (red).

[0013] FIG. 3 shows a gene set list with relative weight (y-axis) of each gene in the classifier diagnosing stage I ovarian cancer using longitudinal gene expression stability. Blue bars denote genes identified with the methods disclosed herein and red bars denote genes identified without using the disclosed methods (e.g., comparator approach) improvise diagnostic performance compared to standard approaches. The gene list includes PANXI, GUCY1A1, TGB3BP. ENSG00000236304. KALRN. CCTY, LTB, LMo2, ZNF385D.

[0014] AMD1, MXD1, CTDSP1, MANBA, EIF4ENIF1, Cl lort21, ACTN4, PRKCH, MAT2A, DOK6, NIDI, ZZEF1, USP24, HABP4, SERF2, TBC1D13, ITGA2B, IFITM3, OSBP2, CAV2, ANK1, HPK2, HBB, NFKB1A, ANK3, CASP1, CD69, COPS7A, FECH, HPS3, MBD4, METAP1, MPP7, SLC66A3, and TBL1X.

[0015] FIG. 4 shows a heat map of platelet RNA expression changes in women followed longitudinally during the course of their pregnancy. Visit 1 = prior to pregnancy; visit 2 = 1sttrimester; visit 3 = 2ndtrimester; visit 4 = 3rdtrimester; visit 5 = post-partum.

[0016] FIG. 5 shows an intersection plot of platelet RNA expression changes in women followed longitudinally during the course of their pregnancy. Visit 1 = prior to pregnancy; visit 2 = 1sttrimester; visit 3 = 2ndtrimester; visit 4 = 3rdtrimester; visit 5 = post-partum. Dots and lines show concordant changes between visits. Bars (left and top) show the number of genes in each comparison.

[0017] FIG. 6 shows platelet functional responses in women longitudinally followed during uncomplicated pregnancy. Each panel is a different agonist used to activate platelet functional responses at either high dose (red) or low dose (green). Visit 1 = prior to pregnancy; visit 2 = 1sttrimester; visit 3 = 2ndtrimester; visit 4 = 3rdtrimester; visit 5 = postpartum. Red dots and lines show concordant changes between visits.

[0018] FIGS. 7A-B show the recruitment timeline and demographics. FIG. 7A shows the study timeline: women were screened prior recruitment and blood was drawn at each visit before, during and after pregnancy. FIG. 7B shows the demographics of the recruited women. FIGS. 8A-E show platelet aggregation changes during and after pregnancy. Integrin allbp3 activation in whole blood at baseline (FIG. 8A) and in response to PAR-1 peptide (2.5pM) (FIG. 8B). Maximal aggregation response in washed platelets in response to (FIG.

[0019] 8C) 2MeSADP (50 nM), (FIG. 8D) collagen (2pg / mL) and (FIG. 8E) thrombin (0.05U / mL). N=20.

[0020] FIG. 9 shows that differentially expressed genes peak during 3rd trimester. Gene expression profiles of top differentially expressed genes at visit 1 (pre-pregnancy), visit 2 (1st trimester), visit 3 (2nd trimester), visit 4 (3rd trimester) and visit 5 (postpartum). N=20. The genes evaluated include ARMC7, CASP4, CDR2L, CPAMD8, CSH1, CSH2, FCGR2A, HDGF, HGD, HPSE, MAP3K7CL, MISP3, MMP1, OSBP2, PDIA3, PLAC4, SLC25A30, SNHG7, YOD1, and YPEL3.

[0021] FIG. 10 shows that the platelet metabolome during the 3rd trimester is altered.

[0022] Volcano plot of metabolomics analysis for 57 platelet metabolites measured by mass spectrometry.

[0023] FIGS. 11A-C show the glutathione metabolism changes that are observed both at the metabolic and transcriptomic levels. FIG. 11 A shows metabolomic / transcriptomic joint analysis using the MetaboAnalyst online tool reveals that modifications in the glutathione metabolism pathway are prevalent during pregnancy. FIG. 1 IB shows the oxidized glutathione quantification in platelets by mass spectrometry. N=20. FIG. 11 C shows the glutathione pathway schematic representation. Genes are represented by rectangles. The green rectangles are differentially expressed genes within the pathway between the 3rd trimester and pre-pregnancy.

[0024] FIG. 12 shows the relative importance of explanatory factors in platelet transcriptomic signatures. The bar plot depicts the relative importance of each explanatory variable. While disease status is the dominant factor, age, GC bias and leukocyte residual genes (LRG) are important contributions.

[0025] FIGS. 13A-B show an example of covariate balance with platelet RNA datasets. Top panels show representative histograms for the distribution of (FIG. 13A) age and (FIG. 13B) GC content bias between platelet RNA datasets from patients with cancer (orange) or patients without cancer (green). Bottom panels show resulting histograms following balancing for age and GC bias.

[0026] FIG. 14 shows stable genes that are significantly preferred in unconstrained analyses. Companson of platelet RNA profiles from n=115 cancer patients vs. n=l 13 matched healthy controls (p=2.15 x 10'96). FIG. 15 shows that Stability Enhanced Transcriptional Analytics (SENTRY) identifies a 22 gene panel that accurately classifies ovarian cancer. Shown are the names of each gene (x-axis) and the relative weight that the platelet RNA expression of each gene contributes to the diagnostic classifier (y-axis). Data from n=36 women with stage I ovarian cancer vs. n=39 age, gender, and race-matched healthy women.

[0027] FIG. 16 shows a schematic depicting inclusion of platelet RNA data with confounding covariates, as then applied to Stability Enhanced Transcriptional Analytics (SENTRY) enables the development of diagnostic assays.

[0028] FIG. 17 shows a heat map of a gene panel that accurately classifies stage I ovarian cancer. Shown are the names of each gene (x-axis) and the relative weight that the platelet RNA expression of each gene contributes to the diagnostic classifier (y-axis). Data from n=36 women with stage I ovarian cancer vs. n=39 age, gender, and race-matched healthy women.

[0029] FIG. 18 shows ROC curves showing that using the most stable genes differentiates two types of cancer (GBM, glioblastoma multiforme vs. NSCLC, non-small cell lung cancer) better than using all genes or the least stable genes.

[0030] FIG. 19 shows a schematic illustrating the concept of applying gene stability to differentiating healthy from disease states.

[0031] FIG. 20 shows a schematic illustrating the concept of applying gene stability to improving upon current diagnostic (Dx) limitations.

[0032] FIG. 21 shows a 16 gene panel that accurately classifies non-small cell lung cancer compared to healthy controls.

[0033] FIG. 22 shows a heat map (top) and quantifies RNA expression data (bottom) showing that platelet RNA transcriptomics identifies S100A8 and S100A9 genes as significantly increased in patients with autoimmune disorders. Here is shown GPA (granulomatosis with polyangiitis).

[0034] FIG. 23 is a table showing confounder influences in platelet RNA data sets across diseases.

[0035] FIG. 24 shows a schematic (left) illustrating the concept that numerous confounding variables interact with and influence the primary analysis of interest with is D (disease)

[0036]

[0037] E (expression) and a table (right) listing the confounding factor and its definition.

[0038] FIG. 25 shows an example of non-small cell lung cancer (NSCLC) using 522 unique platelet RNA datasets from patients with NSCLC and where incorporation of longitudinal gene stability using the most stable genes from a clinical reference cohort of asymptomatic, healthy, non-cancer patients improves diagnostic performance compared to standard approaches, where stable and unstable genes from a reference cohort are used. The diagnostic performance in NSCLC is shown when the least stable genes from a reference cohort are used. Each curve reflects the area under the curve (AUC).

[0039] FIG. 26 shows the performance, measured as the area under the curve (AUC), when incorporation of longitudinal gene stability' is used to diagnose Stage I-IV ovarian cancer. The AUC of the classifier for each ovarian cancer stage is shown along with the number of women assessed at each stage.

[0040] FIG. 27 shows the performance, measured as the area under the curve (AUC), when incorporation of longitudinal gene stability' from a clinical reference cohort is used to diagnose any stage of ovarian cancer.

[0041] FIG. 28 shows the improvement in performance measured as the area under the curve (AUC), yvhen incorporation of longitudinal gene stability from a clinical reference cohort is used to diagnose stage I-IV of ovarian cancer.

[0042] FIG. 29 shows a gene set list with relative weight (y-axis) of each gene in the classifier diagnosing stage I and all-stage ovarian cancer using longitudinal gene expression stability. Blue bars denote genes identified with our IP and red bars denote genes identified yvithout our IP (e.g., comparator approach) improves diagnostic performance compared to standard approaches. The gene list includes PANXI, GUCY1A1, TGB3BP, ENSG00000236304. KALRN, CCTY, LTB, LMo2, ZNF385D. AMD1, MXD1, CTDSP1. MANBA, EIF4ENIF1. Cllort21, ACTN4, PRKCH, MAT2A, D0K6, NIDI, ZZEF1, USP24, HABP4, SERF2, TBC1D13, ITGA2B, IFITM3, OSBP2, CAV2, ANK.1, HPK2, HBB, NFKB1A, ANKA, CASP1, CD69, COPS7A, FECH, HPSE, MBD4, MET API, MPP7, SLC66A3, and TBLIX.

[0043] FIG. 30 shows that platelet trans criptomes exhibit greater differential expression than WBC transcriptomes across MPN subtypes. Bar chart comparing the number of significantly differentially expressed genes (adjusted p<0.05, |log2 fold change|>l) between platelet (dark red) and WBC (blue) transcriptomes in essential thrombocythemia (ET), polycythemia vera (PV). and primary myelofibrosis (MF) patients versus healthy controls. Each bar represents the total number of genes meeting differential expression criteria in independent DESeq2 analyses. Numbers above bars indicate gene counts. Red fold-difference values above each disease category show the ratio of platelet to WBC differentially expressed genes. MF demonstrates the greatest divergence (3.2-fold), with 3,453 platelet genes versus 1.069 WBC genes significantly dysregulated, indicating that platelet trans criptomes capture more extensive disease-related transcriptional changes than WBC transcriptomes, particularly in advanced fibrotic disease.

[0044] FIG. 31 shows that distinct transcriptional signatures distinguish platelet and WBC responses to myelofibrosis. Side-by-side heatmaps displaying log2 -transformed normalized expression values for the top 25 most significantly differentially expressed genes (MF vs CTRL, padjO. Ol, |log2FC|>l.5) in platelet (left panel) and WBC (right panel) transcriptomes. Each column represents one patient from the matched 76-patient cohort; rows represent individual genes ranked by statistical significance. Color intensity reflects absolute gene expression levels (blue=low, white=intermediate, red=high) without z-score normalization. Top annotation bar indicates MPN disease subtype (yellow=CTRL, green=ET, teal=PV, dark blue=MF). Hierarchical clustering (Euclidean distance, complete linkage) applied independently to rows and columns reveals clear disease-based sample segregation in both compartments. Platelet samples demonstrate tighter clustering of MF patients with pronounced upregulation of proteostasis genes (CALR, CREB3L1, STAC, HMGA1) and downregulation of metabolic genes (PLCL1, GDF15, CCNB2). WBC samples show more heterogeneous expression patterns with mixed up- and down-regulation across immune-related genes (DAP, HPSE, FCGR2A upregulated; HJV, SH3GL2, HSPB8 downregulated). Gene sets are non-overlapping between compartments, indicating divergent biological pathways captured by each cell type.

[0045] FIG. 32 shows that platelet trans criptomes outperform WBC transcriptomes in myelofibrosis classification. Receiver operating characteristic (ROC) curves comparing four multinomial LASSO regression models for binary classification of myelofibrosis (MF) versus non-MF samples (CTRL, ET, PV combined). Blue curve: platelet transcriptome-based classifier (AUROC=0.85, 95% CI: 0.76-0.94). Red curve: WBC transcriptome-based classifier (AUROC=0.77, 95% CI: 0.66-0.88). Green cune: combined platelet+WBC transcriptome classifier (AUROC=0.80, 95% CI: 0.70-0.90). Black curve: baseline clinical model using age, sex, and mutation status (AUROC=0.59, 95% CI: 0.46-0.72). Gray dashed diagonal line represents chance performance (AUROC=0.50). The platelet-only model demonstrates superior discriminatory power compared to WBC, clinical, and combined models. Notably, the combined model fails to improve upon platelet-only performance, indicating that platelet features capture the dominant MF-associated signal and WBC features provide complementary but non-additive information. The transcriptomic models substantially outperform clinical parameters alone, confirming that RNA-based biomarkers capture disease biology beyond traditional predictors. FIG. 33 shows differential expression concordance between platelet and WBC transcriptomes in myelofibrosis. Scatterplot comparing log2 fold changes (MF vs CTRL) for all detected genes in platelet (x-axis) and WBC (y-axis) datasets. Genes are color-coded by significance: dark red = significant in both compartments (padj<0.05, |log2FC|>l); orange = significant only in platelets; blue = significant in WBCs; gray = not significant in either. Dashed lines indicate fold change thresholds (±1). Genes significant in both compartments show concordant directionality (clustering along the diagonal), while platelet-specific genes (orange) vastly outnumber WBC-specific genes (blue), consistent with the 3.2-fold difference in differential expression magnitude.

[0046] SUMMARY

[0047] Disclosed herein are methods for improving disease diagnostics. Disclosed herein are methods for improving disease diagnostics in women's health. The methods disclosed can apply longitudinal gene stability signatures from reference cohorts, providing several advantages in platform-independent diagnostic accuracy, scalability, and cost-effectiveness. The measurement of longitudinal gene stability and its subsequent quantification is called the ■‘repeatability index.” The methods can include the following. Modifying the Repeatability Index: The repeatability index is modified from 0.99 to any desired threshold above 0.00 to fine-tune the diagnostic gene expression signature as shown in the left extracted code. The tuning can enhance the diagnostic sensitivity, making it more robust and precise. Utilizing Longitudinal Gene Stability: Longitudinal gene stability is used to select genes that are biologically relevant to the specific condition of interest ensuring that the selected genes contribute meaningfully to the diagnostic signature. This method also results in a smaller panel of platform-independent genes for a meaningful diagnostic signature, enabling the development of higher-throughput, lower-cost diagnostic tests. Improving Therapeutic Selection: Longitudinal gene stability is leveraged to identify biologically-relevant genes that can also be relevant for therapeutic selection, thereby enhancing personalized treatment options for patients. Deriving and Validating Diagnostic Classifiers with Smaller Sample Sizes: Longitudinal gene stability enables the derivation and validation of diagnostic classifiers with smaller sample sizes, thereby reducing the complexity and cost of clinical studies, thereby increasing the scalability and speed of clinical development and validation efforts.

[0048] Disclosed herein are methods for making a healthy pregnancy transcriptome-wide expression profile, the methods comprising: a) measuring the expression levels of one or more genes present in a first biological sample, wherein said measuring comprises RNA sequencing; b) determining the expression levels of the one or more genes from the measured expression levels obtained in step a); c) combining the results of steps a) and b) to produce a transcriptome-wide expression profile; and d) providing the transcriptome-wide expression profile as a data set, wherein the first biological sample consists of isolated platelets; and wherein the first biological sample is obtained from a female subject.

[0049] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods comprising: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a) by: i. collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii. adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii. suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv. magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v. transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv. magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets; c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; and f) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

[0050] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods comprising: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; and f) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

[0051] Disclosed herein are methods for monitoring disease progression, disease recurrence, remission, or relapse in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby monitoring disease progression, disease recurrence, remission, or relapse in the subject.

[0052] Disclosed herein are methods for determining minimal residual disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points: b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal trans cnptome-wi de expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject.

[0053] Disclosed herein are methods for diagnosing a disease or characterizing a disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby diagnosing the disease or characterizing the disease in the subject.

[0054] Disclosed herein are methods for identifying a drug target, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the drug target.

[0055] Disclosed herein are methods for informing a therapeutic selection or indicating a change in therapy in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby informing the therapeutic selection or indicating the change in therapy in the subject. Disclosed herein are methods for providing a disease prognosis in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject; thereby providing the disease prognosis in the subject.

[0056] Disclosed herein are methods for identifying a therapeutic target or pathway for drug development or other therapeutic selection, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the therapeutic target or pathway for drug development or other therapeutic selection.

[0057] Disclosed herein are methods for identifying a predisposition or risk for a disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject thereby identifying the predisposition or risk for the disease in the subject.

[0058] Disclosed herein are methods for identifying a predisposition or risk for a disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject thereby identifying the predisposition or risk for the disease in the subject.

[0059] Disclosed herein are methods for identifying, developing, or validating a diagnostic panel of biomarkers, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove highly-variable (e.g., least stable) genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying, developing, or validating a diagnostic panel of biomarkers.

[0060] Disclosed herein are methods for determining the health of a fetus or risk or presence of a disease in a fetus, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating one or more platelets from the two or more biological samples obtained in a); c) measuring the expression levels of one or more genes present in the isolated platelets obtained from the two or more biological samples, wherein said measuring comprises RNA sequencing; d) determining the expression levels of the one or more genes from the measured expression levels obtained in step c); e) identifying the least stable genes and identifying the most stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from first and second time points; and g) calculating a repeatability index for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the health of the fetus or risk or presence of the disease in the fetus.

[0061] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods comprising: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a) by: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets; c) measuring the expression levels of a plurality of genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

[0062] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods comprising: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

[0063] Disclosed herein are methods for monitoring disease progression, disease recurrence, remission, or relapse in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby monitoring disease progression, disease recurrence, remission, or relapse in the subject.

[0064] Disclosed herein are methods for determining minimal residual disease in a subject, said method comprising: making a longitudinal transcriptome-w ide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points: b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject. Disclosed herein are methods for diagnosing a disease or characterizing a disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby diagnosing the disease or characterizing the disease in the subject.

[0065] Disclosed herein are methods for identifying a drug target, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the drug target.

[0066] Disclosed herein are methods for informing a therapeutic selection or indicating a change in therapy in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby informing the therapeutic selection or indicating the change in therapy in the subject. Disclosed herein are methods for providing a disease prognosis in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject; thereby providing the disease prognosis in the subject.

[0067] Disclosed herein are methods for identifying a therapeutic target or pathway for drug development or other therapeutic selection, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the therapeutic target or pathway for drug development or other therapeutic selection.

[0068] Disclosed herein are methods for identifying a predisposition or risk for a disease in a subject, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-w ide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject thereby-identifying the predisposition or risk for the disease in the subject.

[0069] Disclosed herein are methods for identifying, developing, or validating a diagnostic panel of biomarkers, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality- of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and h) using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying, developing, or validating a diagnostic panel of biomarkers.

[0070] Disclosed herein are methods for determining the health of a fetus or risk or presence of a disease in a fetus, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality- of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality’ of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the health of the fetus or risk or presence of the disease in the fetus.

[0071] Disclosed herein are methods for identifying abnormal developments in a fetus, said methods comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, yvherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality’ of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality’ of genes, one or more genes yvith the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability’ for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying abnormal developments in the fetus.

[0072] Disclosed herein are methods for making a healthy pregnancy transcriptome-wide expression profile, the methods comprising: a) measuring the expression levels of a plurality genes present in a first biological sample, wherein said measuring comprises RNA sequencing; b) analyzing the expression levels of the plurality of genes from the RNA sequencing in step a); c) identifying from the plurality- of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and d) calculating the repeatability for the stable genes identified in c); thereby making the longitudinal transcriptome-wide expression profile, wherein the first biological sample consists of isolated platelets and / or leukocytes; and wherein the first biological sample is obtained from a female subject.

[0073] DETAILED DESCRIPTION

[0074] The present disclosure can be understood more readily by reference to the following detailed description of the invention, the figures and the examples included herein.

[0075] Before the present methods and gene expression panels are disclosed and described, it is to be understood that they are not limited to specific synthetic methods unless otherwise specified, or to particular reagents unless otherwise specified, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, example methods and materials are now described.

[0076] Moreover, it is to be understood that unless otherwise expressly stated, it is in no wayintended that any method set forth herein be construed as requiring that its steps be performed in a specific order. Accordingly, where a method claim does not actually recite an order to be followed by its steps or it is not otherwise specifically stated in the claims or descriptions that the steps are to be limited to a specific order, it is in no way intended that an order be inferred, in any respect. This holds for any possible non-express basis for interpretation, including matters of logic with respect to arrangement of steps or operational flow, plain meaning derived from grammatical organization or punctuation, and the number or type of aspects described in the specification.

[0077] All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided herein can be different from the actual publication dates, which can require independent confirmation.

[0078] DEFINITIONS

[0079] As used in the specification and the appended claims, the singular forms "a." “an” and “the” include plural referents unless the context clearly dictates otherwise.

[0080] The word “or” as used herein means any one member of a particular list and also includes any combination of members of that list.

[0081] Ranges can be expressed herein as from “about” or “approximately” one particular value, and / or to “about” or “approximately” another particular value. When such a range is expressed, a further aspect includes from the one particular value and / or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” or “approximately,” it will be understood that the particular value forms a further aspect. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint and independently of the other endpoint. It is also understood that there are a number of values disclosed herein and that each value is also herein disclosed as “about” that particular value in addition to the value itself. For example, if the value “10” is disclosed, then “about 10” is also disclosed. It is also understood that each unit between two particular units is also disclosed. For example, if 10 and 15 are disclosed, then 11, 12, 13, and 14 are also disclosed.

[0082] As used herein, the terms “optional” or “optionally” mean that the subsequently described event or circumstance may or may not occur and that the description includes instances where said event or circumstance occurs and instances where it does not.

[0083] As used herein, the term “sample” is meant a tissue or organ from a subject; a cell (either within a subject, taken directly from a subject, or a cell maintained in culture or from a cultured cell line); a cell lysate (or lysate fraction) or cell extract; or a solution containing one or more molecules derived from a cell or cellular material (e.g. a polypeptide or nucleic acid), which is assayed as described herein. A sample may also be any body fluid or excretion (for example, but not limited to, blood, urine, stool, saliva, tears, bile) that contains cells or cell components. As used herein, the term “subject” refers to the target of administration, e.g., a human. Thus, the subject of the disclosed methods can be a vertebrate, such as a mammal, a fish, a bird, a reptile, or an amphibian. The term “subject” also includes domesticated animals (e.g., cats, dogs, etc.), livestock (e.g., cattle, horses, pigs, sheep, goats, etc.), and laboratory animals (e.g., mouse, rabbit, rat, guinea pig, fruit fly, etc.). In some aspects, a subject is a mammal. In some aspects, a subject is a human. The term does not denote a particular age or sex. Thus, adult, child, adolescent and newborn subjects, as well as fetuses, whether male or female, are intended to be covered.

[0084] As used herein, the term “patient” can refer to a subject afflicted with a disease or disorder or be a healthy subject. The term “patient” includes human and veterinary' subjects. In some aspects of the disclosed methods, the “patient” has been diagnosed with a need for treatment for a disease, such as, for example, prior to the administering step. In some aspects, the terms “patient,” “subject,” “individual,” and the like are used interchangeably herein, and refer to any animal, or cells thereof whether in vitro or in situ, amenable to the methods described herein. In some aspects, the patient, subject or individual is a human. In some aspects, the subject is a female human. In some aspects, the subject is a pregnant, prepregnant (before a pregnancy) or postpartum female.

[0085] As used herein, the term “comprising” can include the aspects “consisting of’ and “consisting essentially of.”

[0086] As used herein, the term “normal” or “healthy” refers to an individual, a sample or a subject that does not have a disease or disorder or does not have an increased susceptibility' of developing a disease or disorder.

[0087] As used herein, the term “susceptibility ” refers to the likelihood of a subject being clinically diagnosed with a disease. For example, a human subject with an increased susceptibility' for a disease or a pregnancy-related complication can refer to a human subject with an increased likelihood of a subject being clinically diagnosed w ith a disease or a pregnancy -related complication. In some aspects, the disease can be cancer. In some aspects, the disease can be ovarian cancer, breast cancer, and cervical cancer. In some aspects, the disease can be an autoimmune disease. In some aspects, the autoimmune disease can be multiple sclerosis or rheumatoid arthritis. In some aspects, the pregnancy-related complication can be gestational diabetes, iron deficiency, anemia, hemorrhage or bleeding, preeclampsia, gestational hypertension, hyperemesis gravidarum, venous or arterial thrombosis, venous or arterial embolism, cardiomyopathy or other heart conditions, infections, depression, anxiety, impaired placental development, intrauterine growth restriction, pre-term labor, stillbirth, miscarriage, and ectopic pregnancy.

[0088] As used herein, the term “pre-pregnancy” can refer to the period of time before and between pregnancies. In some aspects, the term “pre-pregnancy” can be used interchangeably with “preconception”. In some aspects, “pre-pregnancy” can be the time period of 12 w eeks or 3 months before pregnancy or conception.

[0089] As used herein, the term “postpartum” can refer to the period of time soon after or immediately after the delivery of a baby. In some aspects, the postpartum period can be about 1 day to 8 weeks after the delivery’ of a baby.

[0090] As used herein, the term “polypeptide” refers to any peptide, oligopeptide, polypeptide, gene product, expression product, or protein. A polypeptide is comprised of consecutive amino acids. The term “polypeptide” encompasses naturally occurring or synthetic molecules. As used herein, the term “amino acid sequence” refers to a list of abbreviations, letters, characters or words representing amino acid residues.

[0091] As used herein, the terms “peptide,” “polypeptide.” and “protein” are used interchangeably, and refer to a compound comprising amino acid residues covalently linked by peptide bonds. A protein or peptide must contain at least two amino acids, and no limitation is placed on the maximum number of amino acids that can comprise a protein's or peptide’s sequence. Polypeptides include any peptide or protein comprising two or more amino acids joined to each other by peptide bonds. As used herein, the term refers to both short chains, which also commonly are referred to in the art as peptides, oligopeptides and oligomers, for example, and to longer chains, which generally are referred to in the art as proteins, of which there are many types. “Polypeptides” include, for example, biologically active fragments, substantially homologous polypeptides, oligopeptides, homodimers, heterodimers, variants of polypeptides, modified polypeptides, derivatives, analogs, fusion proteins, among others. The polypeptides include natural peptides, recombinant peptides, synthetic peptides, or a combination thereof.

[0092] As used herein, the term “gene” refers to a region of DNA encoding a functional RNA or protein. “Functional RNA” refers to an RNA molecule that is not translated into a protein. Generally, the gene symbol is indicated by using italicized styling while the protein symbol is indicated by using non-italicized styling.

[0093] The phrase “nucleic acid” as used herein refers to a naturally occurring or synthetic oligonucleotide or polynucleotide, whether DNA or RNA or DNA-RNA hybrid, singlestranded or double-stranded, sense or antisense, w hich is capable of hybridization to a complementary' nucleic acid by Watson-Crick base-pairing. Nucleic acids of the invention can also include nucleotide analogs (e.g., BrdU), and non-phosphodiester intemucleoside linkages (e.g., peptide nucleic acid (PNA) or thiodiester linkages). In particular, nucleic acids can include, without limitation, DNA, RNA, cDNA, gDNA, ssDNA, dsDNA or any combination thereof.

[0094] Nucleic acids may also include any polymer or oligomer of pyrimidine and purine bases, preferably cytosine, thymine, and uracil, and adenine and guanine, respectively.

[0095] Indeed, the present invention contemplates any deoxyribonucleotide, ribonucleotide or peptide nucleic acid component, and any chemical variants thereof, such as methylated, hydroxymethylated or glycosylated forms of these bases, and the like. The polymers or oligomers may be heterogeneous or homogeneous in composition, and may’ be isolated from naturally occurring sources or may be artificially or synthetically produced. In addition, the nucleic acids may be DNA or RNA, or a mixture thereof, and may exist permanently or transitionally in single-stranded or double-stranded form, including homoduplex, heteroduplex, and hybrid states.

[0096] An '‘oligonucleotide’’ or “polynucleotide” is a nucleic acid ranging from at least 2, preferably at least 8, 15 or 25 nucleotides in length, but may be up to 50, 100, 1000, or 5000 nucleotides long or a compound that specifically hybridizes to a polynucleotide.

[0097] Polynucleotides include sequences of deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) or mimetics thereof which may’ be isolated from natural sources, recombinantly produced or artificially synthesized. A further example of a polynucleotide of the present invention may be a peptide nucleic acid (PNA). (See U. S. Pat. No. 6,156,501 which is hereby incorporated by reference in its entirety.) The invention also encompasses situations in which there is a nontraditional base pairing such as Hoogsteen base pairing which has been identified in certain tRNA molecules and postulated to exist in a triple helix.

[0098] “Polynucleotide” and “oligonucleotide” are used interchangeably in this disclosure. It will be understood that when a nucleotide sequence is represented herein by a DNA sequence (e.g., A, T, G, and C), this also includes the corresponding RNA sequence (e.g., A. U, G, C) in which “U” replaces “T”.

[0099] As used herein, “polynucleotide” includes cDNA, RNA, DNA / RNA hybrid, antisense RNA, ribozy me, genomic DNA, synthetic forms, and mixed polymers, both sense and antisense strands, and may be chemically or biochemically modified to contain non-natural or derivatized, synthetic, or semi-synthetic nucleotide bases. Also, contemplated are alterations of a wild type or synthetic gene, including but not limited to deletion, insertion, substitution of one or more nucleotides, or fusion to other polynucleotide sequences.

[0100] By "‘isolated polypeptide’’ or '‘purified polypeptide” is meant a polypeptide (or a fragment thereof) that is substantially free from the materials with which the polypeptide is normally associated in nature. The polypeptides of the invention, or fragments thereof, can be obtained, for example, by extraction from a natural source (for example, a mammalian cell), by expression of a recombinant nucleic acid encoding the polypeptide (for example, in a cell or in a cell-free translation system), or by chemically synthesizing the polypeptide. In addition, polypeptide fragments may be obtained by any of these methods, or by cleaving full length polypeptides.

[0101] By “isolated nucleic acid” or “purified nucleic acid” is meant DNA that is free of the genes that, in the naturally -occurring genome of the organism from which the DNA of the invention is derived, flank the gene. The term therefore includes, for example, a recombinant DNA which is incorporated into a vector, such as an autonomously replicating plasmid or virus; or incorporated into the genomic DNA of a prokaryote or eukaryote (e.g., a transgene); or which exists as a separate molecule (for example, a cDNA or a genomic or cDNA fragment produced by PCR, restriction endonuclease digestion, or chemical or in vitro synthesis). It also includes a recombinant DNA which is part of a hybrid gene encoding additional polypeptide sequence. The term “isolated nucleic acid” also refers to RNA, e.g., an mRNA molecule that is encoded by an isolated DNA molecule, or that is chemically synthesized, or that is separated or substantially free from at least some cellular components, for example, other types of RNA molecules or polypeptide molecules.

[0102] By “specifically binds” is meant that an antibody recognizes and physically interacts with its cognate antigen and does not significantly recognize and interact with other antigens; such an antibody may be a polyclonal antibody or a monoclonal antibody, which are generated by techniques that are w ell known in the art.

[0103] By “probe,” “primer,” or oligonucleotide is meant a single-stranded DNA or RNA molecule of defined sequence that can base-pair to a second DNA or RNA molecule that contains a complementary sequence (the “target”). The stability of the resulting hybrid depends upon the extent of the base-pairing that occurs. The extent of base-pairing is affected by parameters such as the degree of complementarity betw een the probe and target molecules and the degree of stringency of the hybridization conditions. The degree of hybridization stringency is affected by parameters such as temperature, salt concentration, and the concentration of organic molecules such as formamide, and is determined by methods known to one skilled in the art. Probes or primers specific for a particular nucleic acid (for example, genes and / or mRNAs) can have at least 80%-90% sequence complementarity, preferably at least 91%-95% sequence complementarity, more preferably at least 96%-99% sequence complementarity, and most preferably 100% sequence complementarity to the region of the nucleic acid to which they hybridize. Probes, primers, and oligonucleotides may be detectably-labeled, either radioactively, or non-radioactively, by methods well-known to those skilled in the art. Probes, primers, and oligonucleotides are used for methods involving nucleic acid hybridization, such as: nucleic acid sequencing, reverse transcription and / or nucleic acid amplification by the polymerase chain reaction, single stranded conformational polymorphism (SSCP) analysis, restriction fragment polymorphism (RFLP) analysis, Southern hybridization, Northern hybridization, in situ hybridization, electrophoretic mobility shift assay (EMSA).

[0104] As used herein, the term “probe’’ refers to an oligonucleotide (i.e., a sequence of nucleotides), whether occurring naturally as in a purified restriction digest or produced synthetically, recombinantly or by PCR amplification, that is capable of hybridizing to another oligonucleotide of interest. A probe may be single-stranded or double-stranded. Probes are useful in the detection, identification and isolation of particular gene sequences.

[0105] The term “primer” refers to an oligonucleotide capable of acting as a point of initiation of synthesis along a complementary strand when conditions are suitable for synthesis of a primer extension product. The synthesizing conditions include the presence of four different deoxyribonucleotide triphosphates and at least one polymerization-inducing agent such as reverse transcriptase or DNA polymerase. These are present in a suitable buffer, which may include constituents which are co-factors or which affect conditions such as pH and the like at various suitable temperatures. A primer is preferably a single strand sequence, such that amplification efficiency is optimized, but double stranded sequences can be utilized.

[0106] By “specifically hybridizes” is meant that a probe, primer, or oligonucleotide recognizes and physically interacts (that is, base-pairs) with a substantially complementary nucleic acid (for example, a nucleic acid of interest) under high stringency conditions, and does not substantially base pair with other nucleic acids.

[0107] By “high stringency conditions” is meant conditions that allow hybridization comparable with that resulting from the use of a DNA probe of at least 40 nucleotides in length, in a buffer containing 0.5 M NaHPO₄, pH 7.2, 7% SDS, 1 mM EDTA, and 1% BSA (Fraction V), at a temperature of 65°C, or a buffer containing 48% formamide, 4.8X SSC, 0.2 M Tris-Cl, pH 7.6, IX Denhardt’s solution, 10% dextran sulfate, and 0.1% SDS, at a temperature of 42°C. Other conditions for high stringency hybridization, such as for PCR. Northern, Southern, or in situ hybridization, DNA sequencing, etc., are well-known by those skilled in the art of molecular biology. (See, for example, F. Ausubel et al., Current Protocols in Molecular Biology, John Wiley & Sons, New York, NY, 1998).

[0108] The term “abnormal'’ is used to refer to organisms, tissues, cells or components thereof that differ in at least one observable or detectable characteristic (e.g., age, treatment, time of day, etc.) from those organisms, tissues, cells or components thereof that display the “normal’' (expected) respective characteristic. Characteristics which are normal or expected for one cell or tissue type, might be abnormal for a different cell or tissue type.

[0109] The term “amplification” refers to the operation by which the number of copies of a target nucleotide sequence present in a sample is multiplied.

[0110] The term “antibody,” as used herein, refers to an immunoglobulin molecule which is able to specifically bind to a specific epitope on an antigen. Antibodies can be intact immunoglobulins derived from natural sources or from recombinant sources and can be immunoreactive portions of intact immunoglobulins. The antibodies in the present invention may exist in a variety of forms including, for example, polyclonal antibodies, monoclonal antibodies, intracellular antibodies (“intrabodies”), Fv, Fab and F(ab)2, as well as single chain antibodies (scFv), heavy chain antibodies, such as camelid antibodies, synthetic antibodies, chimeric antibodies, and humanized antibodies (Harlow et al., 1999, Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, N. Y.; Harlow et al., 1989, Antibodies: A Laboratory Manual, Cold Spring Harbor, N. Y.; Houston et al., 1988, Proc. Natl. Acad. Sci. USA 85:5879-5883; Bird et al.. 1988, Science 242:423-426).

[0111] As used herein, an “immunoassay” refers to any binding assay that uses an antibody capable of binding specifically to a target molecule to detect and quantify the target molecule.

[0112] The term “coding sequence,” as used herein, refers to a sequence of a nucleic acid or its complement, or a part thereof that can be transcribed and / or translated to produce the mRNA and / or the polypeptide or a fragment thereof. Coding sequences include exons in a genomic DNA or immature primary RNA transcripts, which are joined together by the cell's biochemical machinery to provide a mature mRNA. The anti-sense strand is the complement of such a nucleic acid, and the coding sequence can be deduced therefrom. In contrast, the term “non-coding sequence,” as used herein, refers to a sequence of a nucleic acid or its complement, or a part thereof that is not translated into amino acid in vivo, or where tRNA does not interact to place or attempt to place an amino acid. Non-coding sequences include both intron sequences in genomic DNA or immature primary RNA transcripts, and gene-associated sequences such as promoters, enhancers, silencers, and the like.

[0113] As used herein, the terms “complementary” or “complementarity” are used in reference to polynucleotides (i.e., a sequence of nucleotides) related by the base-pairing rules. For example, the sequence “A-G-T,” is complementary to the sequence “T-C-A.” Complementarity may be “partial,” in which only some of the nucleic acids’ bases are matched according to the base pairing rules. Or, there may be “complete” or “total” complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands has significant effects on the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions, as well as detection methods that depend upon binding between nucleic acids.

[0114] As used herein, the term “diagnosis” refers to the determination of the presence of a disease or disorder. In some aspects, methods for making a diagnosis are provided which permit determination of the presence of a particular disease or disorder.

[0115] A “disease” is a state of health of an animal wherein the animal cannot maintain homeostasis, and wherein if the disease is not ameliorated then the animal's health continues to deteriorate. In contrast, a “disorder” in an animal is a state of health in which the animal is able to maintain homeostasis, but in which the animal's state of health is less favorable than it would be in the absence of the disorder. Left untreated, a disorder does not necessarily cause a further decrease in the animal's state of health.

[0116] As used herein, the term “encoding” refers to the inherent property of specific sequences of nucleotides in a polynucleotide, such as a gene, a cDNA, or an mRNA, to serve as templates for synthesis of other polymers and macromolecules in biological processes having either a defined sequence of nucleotides (i.e., rRNA, tRNA and mRNA) or a defined sequence of amino acids and the biological properties resulting therefrom. Thus, a gene encodes a protein if transcription and translation of mRNA corresponding to that gene produces the protein in a cell or other biological system. Both the coding strand, the nucleotide sequence of which is identical to the mRNA sequence and is usually provided in sequence listings, and the non-coding strand, used as the template for transcription of a gene or cDNA, can be referred to as encoding the protein or other product of that gene or cDNA.

[0117] As used herein, the term “hybridization” is used in reference to the pairing of complementary nucleic acids. Hybridization and the strength of hybridization (i.e., the strength of the association between the nucleic acids) is impacted by such factors as the degree of complementarity between the nucleic acids, stringency of the conditions involved, the Tm of the formed hybrid, and the G: C ratio within the nucleic acids. A single molecule that contains pairing of complementary nucleic acids within its structure is said to be “selfhybridized.” A single DNA molecule with internal complementarity could assume a variety of secondary structures including loops, kinks or, for long stretches of base pairs, coils. “Instructional material,” as that term is used herein, includes a publication, a recording, a diagram, or any other medium of expression which can be used to communicate the usefulness of the nucleic acid, peptide, and / or compound of the invention in the kit for identifying, diagnosing or alleviating or treating the various diseases or disorders recited herein. Optionally, or alternately, the instructional material may describe one or more methods of identifying, diagnosing or alleviating the diseases or disorders in a cell or a tissue of a subject. The instructional material of the kit may. for example, be affixed to a container that contains one or more components of the invention or be shipped together with a container that contains the one or more components of the invention. Alternatively, the instructional material may be shipped separately from the container with the intention that the recipient uses the instructional material and the components cooperatively.

[0118] The term “isolated” means altered or removed from the natural state. For example, a nucleic acid or a peptide naturally present in a living animal is not “isolated,” but the same nucleic acid or peptide partially or completely separated from the coexisting materials of its natural state is “isolated.” An isolated nucleic acid or protein can exist in substantially purified form, or can exist in a non-native environment such as. for example, a host cell.

[0119] The term “label” as used herein refers to a detectable compound or composition that is conjugated directly or indirectly to a probe to generate a “labeled” probe. The label may be detectable by itself (e.g., radioisotope labels or fluorescent labels) or, in the case of an enzymatic label, may catalyze chemical alteration of a substrate compound or composition that is detectable (e g., avidin-biotin). In some instances, primers can be labeled to detect a PCR product.

[0120] The terms “microarray” and “array” refers broadly to “DNA microarrays,” “DNA chip(s).” “protein microarrays” and “protein chip(s)” and encompasses all art-recognized solid supports, and all art-recognized methods for affixing nucleic acid, peptide, and polypeptide molecules thereto. Preferred arrays typically comprise a plurality of different nucleic acid or peptide probes that are coupled to a surface of a substrate in different, known locations. These arrays, also described as “microarrays” or colloquially “chips” have been generally described in the art, for example, U. S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195, 5,800,992, 6,040,193, 5,424,186 and Fodor et al., 1991, Science, 251:767-777, each of which is incorporated by reference in its entirety for all purposes. Arrays may generally be produced using a variety of techniques, such as mechanical synthesis methods or light directed synthesis methods that incorporate a combination of photolithographic methods and solid phase synthesis methods. Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, e.g., U. S. Pat. Nos. 5,384,261, and 6,040,193, which are incorporated herein by reference in their entirety for all purposes. Although a planar array surface is preferred, the array may be fabricated on a surface of virtually any shape or even a multiplicity of surfaces. Arrays may be nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate. (See U. S. Pat. Nos. 5,770.358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992, which are hereby incorporated by reference in their entirety for all purposes.) Arrays may be packaged in such a manner as to allow for diagnostic use or can be an all-inclusive device; e.g., U. S. Pat. Nos.

[0121] 5,856,174 and 5,922,591 incorporated in their entirety by reference for all purposes. Arrays are commercially available from, for example, Affymetrix (Santa Clara, Calif.) and Applied Biosystems (Foster City. Calif), and are directed to a variety of purposes, including genotyping, diagnostics, mutation analysis, marker expression, and gene expression monitoring for a variety of eukaryotic and prokaryotic organisms. The number of probes on a solid support may be varied by changing the size of the individual features. In some aspects, the feature size is 20 by 25 microns square, in other aspects, features may be. for example, 8 by 8. 5 by 5 or 3 by 3 microns square, resulting in about 2,600,000. 6,600,000 or 18,000.000 individual probe features.

[0122] Assays for amplification of the known sequence are also disclosed. For example, primers for PCR may be designed to amplify regions of the sequence. For RNA, a first reverse transcriptase step may be used to generate double stranded DNA from the single stranded RNA. The array may be designed to detect sequences from an entire genome; or one or more regions of a genome, for example, selected regions of a genome such as those coding for a protein or RNA of interest; or a conserved region from multiple genomes; or multiple genomes, arrays and methods of genetic analysis using arrays is described in Cutler, et al., 2001, Genome Res. 11(11): 1913-1925 and Warrington, et al., 2002, Hum Mutat 19:402-409 and in US Patent Pub No 20030124539, each of which is incorporated herein by reference in its entirety.

[0123] As used herein, the term “polymerase chain reaction” (“PCR") refers to the method of K. B. Mullis (U. S. Pat. Nos. 4,683,195 4,683,202, and 4,965,188, hereby incorporated by reference), which describe a method for increasing the concentration of a segment of a target sequence in a mixture of genomic DNA without cloning or purification. This process for amplifying the target sequence consists of introducing a large excess of two oligonucleotide primers to the DNA mixture containing the desired target sequence, followed by a precise sequence of thermal cycling in the presence of a DNA polymerase. The two primers are complementary to their respective strands of the double stranded target sequence. To effect amplification, the mixture is denatured and the primers then annealed to their complementary sequences within the target molecule. Following annealing, the primers are extended with a polymerase so as to form a new pair of complementary strands. The steps of denaturation, primer annealing and polymerase extension can be repeated many times (i.e., denaturation, annealing and extension constitute one "cycle"; there can be numerous “cycles”) to obtain a high concentration of an amplified segment of the desired target sequence. The length of the amplified segment of the desired target sequence is determined by the relative positions of the primers with respect to each other, and therefore, this length is a controllable parameter. By virtue of the repeating aspect of the process, the method is referred to as the “polymerase chain reaction” (hereinafter “PCR”). Because the desired amplified segments of the target sequence become the predominant sequences (in terms of concentration) in the mixture, they are said to be “PCR amplified”. As used herein, the terms “PCR product,” “PCR fragment,” “amplification product” or “amplicon” refer to the resultant mixture of compounds after two or more cycles of the PCR steps of denaturation, annealing and extension are complete. These terms encompass the case where there has been amplification of one or more segments of one or more target sequences.

[0124] The term “abnormal” when used in the context of organisms, tissues, cells or components thereof, refers to those organisms, tissues, cells or components thereof that differ in at least one observable or detectable characteristic (e.g., age, treatment, time of day. etc.) from those organisms, tissues, cells or components thereof that display the “normal” (expected) respective characteristic. Characteristics which are normal or expected for one cell or tissue type, might be abnormal for a different cell or tissue type.

[0125] The term “amplification” refers to the operation by which the number of copies of a target nucleotide sequence present in a sample is multiplied.

[0126] The invention described herein solves a number of problems related to the early, noninvasive diagnosis and monitoring of diseases in the field of women’s health, including but not limited to cancer and pregnancy related complications. Current diagnostic testing approaches are invasive and expensive and are not comprehensive or accurate, and take too long to provide detailed information. Current methods to develop and validate diagnostic tests often require large cohort studies that may take years to complete, often with negative results. These methods also are not sensitive or precise enough to detail small changes that can lead to a significant problem or complication that can become severe, leading to adverse outcomes for the mother and / or the fetus. As such, these tests may never make it into clinical settings nor make any meaningful impact on women’s health.

[0127] Advancements in minimally invasive diagnostics such as liquid biopsies and biomarker analysis can be used to detect pregnancy complications at an early stage and female cancers with higher accuracy and precision, but are not without limitations. Most existing solutions test maternal DNA, non-specific biomarkers, or use imaging for screening and diagnosis. For pregnancy complications, Illumina has developed various products, including the VeriSeq NIPT Solution, which is a non-invasive prenatal testing (NIPT) technology. This solution utilizes next-generation sequencing to analyze cell-free DNA from the mother's blood to screen for chromosomal abnormalities in the fetus, such as Down syndrome (trisomy 21), Edwards syndrome (trisomy 18), and Patau syndrome (trisomy 13). NIPT has demonstrated high sensitivity and specificity in detecting these chromosomal abnormalities. Another company is Natera, which has developed the Panorama test. The Panorama test is an NIPT technology that analyzes cell-free DNA in maternal blood to screen for common chromosomal abnormalities, including trisomy 21, trisomy 18, trisomy 13, and monosomy X (Turner syndrome). It also provides information about fetal sex and can detect certain microdeletions associated with genetic disorders. For ovarian cancer, the most commonly used solutions are the CA-125 blood test and transvaginal ultrasound. The CA-125 blood test measures the level of a protein called CA-125 in the blood, which is often elevated in women with ovarian cancer. However, the CA-125 test has several limitations. First, the test is not specific to ovarian cancer, as elevated CA-125 levels can also occur in other conditions, such as endometriosis, pregnancy, and liver disease. Therefore, false positives are common, which can lead to unnecessary diagnostic tests and anxiety for patients. Second, the CA-125 test has low sensitivity for early-stage ovarian cancer, meaning that it may not detect the cancer when it is most treatable. Third, the CA-125 test is not recommended for women at average risk of ovarian cancer, as it has not been shown to reduce mortality. Ultrasound is another screening test for ovarian cancer that uses high-frequency sound waves to create images of the ovaries. Transvaginal ultrasound, which involves inserting a small ultrasound probe into the vagina, is the preferred method for ovarian cancer screening. However, like the CA-125 test, ultrasound also has limitations. First, ultrasound can detect abnormalities that are not cancerous, leading to false positive results and unnecessary' follow-up tests. Second, the sensitivity of ultrasound for early-stage ovarian cancer is also limited, and some ovarian cancers may be missed. Third, ultrasound is operator-dependent, meaning that the quality of the images can vary depending on the experience and skill of the sonographer. Thus, while CA-125 and ultrasound are currently the most commonly used screening tests for ovarian cancer, they have several limitations. False positives and limited sensitivity for early-stage ovarian cancer can lead to unnecessary diagnostic tests and anxiety for patients. In response to the need for better ovarian cancer screening tools, several products have been developed. First, the RosettaGX Reveal® test is used in patients with ovarian, fallopian tube, or primary' peritoneal cancer who have undergone surgical resection of their tumor and have tissue samples available for analysis. It uses next-generation sequencing (NGS) technology to analyze the DNA of tumor samples (obtained by biopsy or during surgery) and identify genetic alterations that may be driving the cancer. The test can detect mutations, copy number alterations, and rearrangements in up to 500 genes that are known to be relevant to cancer. Second, Natera offers the Panorama non-invasive prenatal test (NIPT). This test uses RNA sequencing to analyze gene expression patterns in fetal DNA to identify the risk of chromosomal abnormalities in the fetus, such as Down syndrome, Edwards syndrome, and Patau syndrome. This test, however, does not currently provide information on maternal risks for pregnancy complications. Third, AOADX utilizes Al-based glycolipid diagnostics to early detect ovarian CA. Finally, a search of registered clinical trials identifies several ongoing studies using CA-125. ultrasound, and blood-based DNA and protein biomarkers to detect ovarian cancer. Within non-clinical academic or research settings, some groups have used platelet RNA expression changes to classify cancer versus non-cancer subjects. To solve these problems and overcome the limitations of the currently available tests, a method that applies gene stability into algorithm development has been developed and described herein. For example, ‘‘gene stability’’ can be determined by determining or calculating a “repeatability index”. In some aspects, the repeatability index refers to a measurement that indicates how close together repeated measurements of the same thing are taken under the same conditions. As described herein, the method uses platelet RNA expression for early cancer diagnostics. In some aspects, the methods use platelet RNA expression for early cancer diagnostics in women (e.g., ovarian, breast, and others) or uses platelet RNA expression to monitor pregnancy and pregnancy associated complications in women.

[0128] By analyzing specific markers in maternal blood or other bodily fluids, these techniques can provide valuable insights into a woman's health status and identify potential risk factors or complications before they manifest clinically and when they are still readily prevented and / or treatable. Early identification enables healthcare providers to intervene promptly, initiate appropriate treatments, and closely monitor the pregnancy, thereby reducing the risk of fetal morbidity and maternal complications. Early identification and intervention will also help prevent severe complications that may require expensive and intensive treatments, reducing the burden on healthcare resources and saving dollars in the long term. Ultimately, the integration of these innovative diagnostic approaches into routine prenatal care can revolutionize women's healthcare, providing personalized and proactive care that prioritizes the well-being of both mother and baby. For example, ovarian cancer, often referred to as the “silent killer"’ because it can be difficult to detect in its early stages when it is most treatable, ranks 5th in cancer death among women, accounting for more deaths than any other cancer of the female reproductive cancers. In 2023, about 19,710 women received a new diagnosis of ovarian cancer in the United States, and about 13,270 women will die from ovarian cancer. Unfortunately, no guidelines currently recommend routinely used screening strategies for detecting early-stage ovarian cancer in most women. Due to the absence of evidence-supported screening strategies, approximately 75% of ovarian cancer cases are diagnosed in women at advanced stages, when the cancer has already spread to other organs in the body (e.g., metastasized).

[0129] According to the American Cancer Society, the 5-year survival rate for ovarian cancer is 93% for women diagnosed at the localized stage (stage 1-2), while the survival rate drops to 30% for women diagnosed with distant stage disease (stage 3-4). Early diagnosis is important for improving outcomes in ovarian cancer. Early detection allows for more targeted and less invasive treatments, such as surgery and chemotherapy, which can be more effective when the cancer is still confined to the ovaries. For example, if it is assumed that the current rate of early detection of ovarian cancer is around 20%, then improving this rate to 50% would result in a 2.5-fold increase in the number of women detected at the early stage and an estimated 30-50% reduction in mortality due to ovarian cancer. Furthermore, early diagnosis and non-invasive methods for more frequent surveillance would help detect recurrences and metastases earlier, and significantly reduce overall health care costs.

[0130] A blood-based, non-invasive, platform-independent diagnostic test for ovarian cancer would be highly desirable as it could result in earlier cancer detection, which would both increase patient survival and decrease the cost of cancer treatment. Platelets are blood cells that play an important role in clotting, wound healing, and tissue repair. Platelets also carry RNA and DNA molecules that can be used as biomarkers for various diseases. Changes in platelet RNA expression may reflect both host (e.g.. patient) changes to disease as well as the expression of RNAs and DNAs derived from cancerous or otherwise diseased tissue, cells, or organs. Relatively coarse analyses have suggested that platelet RNA gene expression profiles can be used to discriminate between women diagnosed with ovarian cancer and healthy matched controls. However, current approaches integrating platelet RNA gene expression for ovarian cancer screening require very large gene panels that have not been reproduced or validated. There are also no diagnostic tests that accurately distinguish benign pelvic masses (where surgery is unnecessary) from malignant pelvic masses. As thus, a platelet RNA diagnostic test has not yet entered routine clinical care and are not currently available for direct patient testing. These solutions above are limited in several ways.

[0131] Current solutions for monitoring pregnancy complications face several challenges that limit their effectiveness including but not limited to lack of sensitivity and specificity of diagnostic tests, invasive nature of certain diagnostic tests, and lack of continuous monitoring. Many current monitoring methods lack the ability to accurately detect subtle changes or early signs of complications. For example, traditional blood tests and physical examinations do not provide comprehensive information or may miss important indicators of problems resulting in delayed diagnosis or missed opportunities for early intervention. Some diagnostic tests used for monitoring pregnancy complications, such as amniocentesis or chorionic villus sampling (CVS), are also invasive and carry a small risk of miscarriage or other complications which can deter some women from undergoing these tests, leading to missed opportunities for early detection and intervention. Current monitoring methods often rely on intermittent assessments during prenatal visits, which may not capture dynamic changes in a woman's health status or the fetus's well-being. Also, long intervals between visits or limited access to specialized laboratory testing or gynecological care (for women living in remote or rural areas) can further delay the detection of complications that develop between appointments. As also noted herein, next-generation sequencing for pregnancy complications is limited to genetic testing for fetal abnormalities. The use of CA-125 and ultrasound for ovarian cancer screening in most women is not recommended nor routinely used in the clinic given significant limitations in sensitivity / specificity with high false positive and false negative rates. Other solutions available are either used for monitoring purposes once ovarian cancer has been diagnosed, are invasive (e.g., require tissue biopsy of the cancer itself), or fail to consider gene stability information in their diagnostic platforms. None of these solutions use platelet RNA gene expression, which has significant advantages given the stability of platelet RNA (as platelets are anucleated, which minimizes pre- analytical artifact), their abundance in the blood and ease of access (permitting small volume peripheral blood draw (e.g., 2 mL)), their short half-life of 7 days in humans (allowing for dynamic changes that enhance very early disease detection and frequent surveillance), their rapid response to disease onset (often even before patients are symptomatic), and evidence described herein that changes in platelet RNA expression can be leveraged for robust classifier and diagnostic development.

[0132] The methods described herein integrate gene stability (or variance) into algorithms for the early diagnosis of cancer (e.g., ovarian cancer) and other disease conditions (pregnancy related complications). Machine learning and artificial intelligence based approaches were used to develop unbiased, diagnostic algorithms to detect, and control for, variation in nondisease associated gene expression. By removing this non-disease variation from diagnostic algorithms, the ability to distinguish cancer from non-cancer can be substantially enhanced. The methods disclosed herein also evaluates and controls for confounding bias in the datasets, ensuring that comparisons between cancer and non-cancer (or normal pregnancy from complicated pregnancy) are more robust. Through this approach, the time for developing a diagnostic test can be significantly reduced while diagnostic precision can be substantially increased for these diseases in women. Related technologies do not leverage platelet RNA gene expression and do not incorporate gene stability information into diagnostics. In some aspects, platelet RNA gene expression and platelet RNA gene stability can be combined with leukocyte RNA gene expression and leukocyte RNA gene stability.

[0133] Gene stability signatures have been identified from healthy individuals over time that permit the identification of specific genes and pathways that are altered during disease development and progression. Applying gene stability knowledge to machine learning and artificial intelligence based tools, the methods and proprietary algorithms described herein were developed for using platelet RNA gene expression profiles for diagnostics. Using clinical platelet RNA datasets from patients with cancer, integrated with the disclosed gene stability platform representative cancers show increases in diagnostic precision by about 30% using the disclosed methods, compared to current methods. The data described herein also shows that the method disclosed herein reliably discriminates between different types of diseases (e.g., cancer and non-cancer) and between cancer types. The application of longitudinal signatures can be applicable to numerous diseases and conditions, and, in particular, those related to women's health. To this end, as described herein a platelet gene expression platform in women was developed that defines normal platelet RNA expression during the major stages of uncomplicated pregnancy. This longitudinal sample establishes a baseline of health in women over time, including during pregnancy, for application to the diagnostic signature development for diseases and conditions specific to women. For example, curated and identically processed cancer datasets also integrate 144 samples from patients with ovarian cancer. In addition to ovarian cancer, platelet RNA expression can also be useful as screening, diagnostic, and health monitoring tools for other diseases in women, including breast cancer, complications of pregnancy, multiple sclerosis, and others. For example, during pregnancy, the placenta releases RNA molecules into the mother's bloodstream, which platelets then pick up and incorporate into their RNA profiles. By performing longitudinal sampling of maternal platelets in women prior to pregnancy, repeatedly during each trimester of pregnancy, and post-partum, a platelet stability signature has been identified that defines a normal, healthy pregnancy. It has also been found that platelet gene expression changes in maternal platelets are associated with impaired placental development and intrauterine growth restriction. Therefore, by analyzing the RNA expression patterns in obtained maternal platelets, specific RNA markers can be identified that are associated with pregnancy related complications including but not limited to the health of the fetus and monitoring fetal development. The methods disclosed herein can be used early, is a less invasive test to screen for, diagnose, and / or monitor pregnancy complications. Because platelets are readily accessible in the bloodstream, this method allows for safer, more convenient monitoring of pregnancy compared to tissue biopsy, imaging, or other approaches.

[0134] The methods disclosed herein that use platelet RNA expression stability has certain advantages over both DNA based or tissue-based testing, including but not limited to the following. First, the methods disclosed herein are non-invasive. Platelet RNA expression analysis is a noninvasive diagnostic method that does not require a tissue biopsy. It involves a simple, small volume peripheral blood draw, which is less painful and less risky than a tissue biopsy and can be performed on an outpatient basis or even through at-home collection. Drawing blood is safe during pregnancy. Once blood is drawn, RNA can be easily processed and sequenced using readily available commercially available tools. Analytical tools are already developed, and the algorithm platform disclosed herein can be quickly adapted to many conditions affecting women. Second, the methods disclosed herein are accessible. Platelets are small, circulating cells that can be easily isolated from a woman’s blood sample. In contrast, obtaining tissue biopsies requires invasive procedures that are not be feasible or safe in every patients, such as those with advanced cancer or other medical conditions.

[0135] Transvaginal ultrasound screening for ovarian cancer requires an in office or in hospital procedure, can be uncomfortable for many women, and is more expensive. Third, the methods disclosed herein are more sensitive. Platelet RNA expression analysis can detect disease-related changes in gene expression that is not be evident in tissue biopsies, which samples a small portion of the affected tissue. Changes in platelet RNA expression may occur within days (or hours) of disease onset and even before patients are symptomatic. Platelets also circulate through organs and tissue beds in the body. As such, platelets are positioned to detecting disease-related changes in gene expression originating from any organ or site in the body, whether localized or systemic. By analyzing gene expression patterns in circulating platelets, the methods disclosed herein can provide a more comprehensive and accurate picture of the disease process. This also provides a more cost-effective, safer, and simpler method for diagnosing and monitoring disease status, therapeutic responses, and / or remission and recurrence over time. Fourth, the methods disclosed herein are more specific. The methods disclosed herein integrate longitudinal gene expression during pregnancy and can identify signatures with an increased diagnostic accuracy for diseases and conditions in women, by accounting for biological and technical noise found in samples from women during pregnancy. Fifth, the methods disclosed herein can provide earlier diagnosis. Platelet RNA expression analysis can detect disease-related changes in gene expression earlier than tissue biopsies, leading to an earlier diagnosis and earlier interventions, which is important for improving patient outcomes and increasing the chances of successful treatment. Platelet RNA expression analysis can also be used to identify genomic variants predisposing a subject to cancer risk, including but not limited to BRAC1 / BRAC2.

[0136] In sum, the methods disclosed herein using platelet RNA expression alone or in combinate with leukocyte RNA expression analysis offers several advantages over traditional tissue biopsy for disease diagnosis, making it a diagnostic tool that can be applied for a wide range of diseases, including ovarian cancer and pregnancy complications.

[0137] Disclosed herein are methods that use longitudinal gene stability signatures to enhance disease diagnostics for improving the selection of diagnostic gene expression signatures by modifying the repeatability index, utilizing longitudinal gene stability for selecting biologically relevant genes, improving therapeutic selection, and deriving and validating diagnostic classifiers with smaller sample sizes. These methods can be used in a range of women's diseases, including but not limited to ovarian cancer, breast cancer, pregnancy complications, and cervical cancer.

[0138] Examples of applications in women’s health conditions include but are not limited to ovarian cancer, breast cancer, pregnancy complications, and cervical cancer. Ovarian Cancer'. Ovarian cancer is often diagnosed at an advanced stage due to the lack of sensitive and specific diagnostic tools. Longitudinal gene stability- can enhance the accuracy of early detection, potentially saving lives and improving treatment outcomes. Breast Cancer'. Early detection and personalized therapy selection are important in breast cancer care. The methods disclosed herein can optimize gene expression signatures for better breast cancer diagnostics and treatment tailoring.

[0139] Pregnancy Complications'. The early identification of pregnancy complications, such as preeclampsia, can significantly improve maternal and fetal outcomes. The technology can aid in the development of more accurate and timely diagnostic tools.

[0140] Cervical Cancer'. Cervical cancer screening can benefit from increased sensitivity- and specificity, which can be achieved through the application of longitudinal gene stability in the selection of diagnostic markers. The methods disclosed herein can be applied to other health conditions including but not limited to autoimmune disease, skin disease, eye disease, endocrine disease, neurological disease, and cardiovascular disease to enhance early detection and personalize therapy.

[0141] METHODS FOR MAKING A TRANSCRIPTOME- WIDE EXPRESSION PROFILE

[0142] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profiles. In some aspects, said methods can comprise: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a) by: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and v) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets; c) measuring the expression levels of a plurality- of genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability' for the stable genes identified from the leukocytes, and calculating the repeatability' for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA. GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0143] Disclosed herein are methods of making a longitudinal transcriptome-wide expression profile, said methods can comprise: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a) by: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution also comprises leukocytes; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution, wherein the second platelet rich plasma solution also comprises leukocytes; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets; c) measuring the expression levels of a plurality of genes present in the isolated platelets obtained from the plurality of biological samples and measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the one or more genes present in the isolated platelets from the RNA sequencing in step c) and analyzing the expression levels of the plurality genes present in the leukocytes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points from the platelets and leukocytes; and f) calculating the repeatability for the stable genes identified in e) from the platelets and leukocytes; and g) comparing repeatability for the stable genes identified in e) from the platelets and leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the PRP can comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution can comprise platelets and leukocytes. In some aspects, the second platelet rich plasma solution can comprise platelets and leukocytes. In some aspects, the supernatant comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability7for the stable genes identified from the leukocy tes, thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability' for the stable genes identified from the isolated platelets with the repeatability' for the stable genes identified from the leukocytes, and calculating the repeatability’ for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA. GZMB. KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality' of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0144] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods can comprise: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); d) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and d) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocy tes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plural, ty of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability’ for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet nch plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby-creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D. GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal Iran scriptome- ide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcnptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0145] Disclosed herein are methods for making a longitudinal transcriptome-wide expression profile, said methods can comprise: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can comprise leukocytes; c) measuring the expression levels of a plurality’ genes present in the isolated platelets obtained from the plurality of biological samples and measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality’ of genes from the RNA sequencing in step c) and analyzing the expression levels of the plurality genes present in the leukocytes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points from the platelets and leukocytes; and f) calculating the repeatability for the stable genes identified in e) from the platelets and leukocytes; and g) comparing repeatability for the stable genes identified in e) from the platelets and leukocytes, thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality' of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality’ of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point. and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0146] Disclosed herein are methods for monitoring disease progression, disease recurrence, remission, or relapse in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby monitoring disease progression, disease recurrence, remission, or relapse in the subject. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA GZMB KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0147] Disclosed herein are methods for determining minimal residual disease in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality' of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0148] Disclosed herein are methods for diagnosing a disease or characterizing a disease in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby diagnosing the disease or characterizing the disease in the subject. In some aspects, the methods can identify a subtype, a tissue origin, a tumor site of origin, a tumor stage, disease severity, or one or more genetic features of the disease. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can compnse: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0149] Disclosed herein are methods for identifying a drug target. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality’ of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the drug target. In some aspects, the drug target can be in a metabolic pathway. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality' of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality’ of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point. and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0150] Disclosed herein are methods for informing a therapeutic selection or indicating a change in therapy in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby informing the therapeutic selection or indicating the change in therapy in the subject. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA GZMB KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0151] Disclosed herein are methods for providing a disease prognosis in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject; thereby providing the disease prognosis in the subject. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality' of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocy tes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcnptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0152] Disclosed herein are methods for identifying a therapeutic target or pathway for drug development or other therapeutic selection. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining two or more biological samples from a subject, wherein the two or more biological samples comprise whole blood; wherein the two or more biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the therapeutic target or pathway for drug development or other therapeutic selection. In some aspects, the other therapeutic selection can be surgery, radiation therapy or hormone therapy. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP). first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability' for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture: and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD 3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0153] Disclosed herein are methods for identifying a predisposition or risk for a disease in a subject. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality of genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the low est variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject thereby identifying the predisposition or risk for the disease in the subject. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby-making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further compnse comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP: ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD 3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on tw o or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-l) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0154] Disclosed herein are methods for identifying, developing, or validating a diagnostic panel of biomarkers. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and h) using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying, developing, or validating a diagnostic panel of biomarkers. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; lii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96. CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0155] Disclosed herein are methods for determining the health of a fetus or risk or presence of a disease in a fetus. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the health of the fetus or risk or presence of the disease in the fetus. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability’ for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0156] Disclosed herein are methods for identifying abnormal developments in a fetus. In some aspects, said methods can comprise: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points; b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes; c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c); e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; I) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; and g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying abnormal developments in the fetus. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes, and calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA GZMB KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point. In some aspects, the transcriptome-wide expression profiles from the first time point can be compared to the transcriptome-wide expression profiles from the second time point and the third time point, and the second time point can be compared to the transcriptome-wide expression profiles from the third time point.

[0157] Disclosed herein are methods for making a healthy pregnancy transcriptome-wide expression profile. In some aspects, the methods can comprise: a) measuring the expression levels of a plurality genes present in a first biological sample, wherein said measuring comprises RNA sequencing; b) analyzing the expression levels of the plurality of genes from the RNA sequencing in step a); c) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and d) calculating the repeatability for the stable genes identified in c); thereby making the longitudinal transcriptome-wide expression profile, wherein the first biological sample consists of isolated platelets and / or leukocytes; and wherein the first biological sample is obtained from a female subject. In some aspects, the female subject can be pregnant, pre-pregnant, or postpartum. In some aspects, the methods can be repeated at least once. In some aspects, the methods can be repeated on a second biological sample, wherein the second biological sample consists of isolated platelets and / or leukocytes; and wherein the second biological sample can be obtained from a female subject, wherein the female subject can be pregnant, pre-pregnant, or postpartum. In some aspects, the first and second biological samples can be obtained from the same subject or from different subjects. In some aspects, the first and second biological samples can be obtained from the same subject at a first time point and a second time point. In some aspects, the first time point can be within the first trimester of pregnancy of the subject and the second time point can be within the second trimester of pregnancy of the subject. In some aspects, the first time point can be within a pre-pregnancy period of the subject or a postpartum period of the subject. In some aspects, methods can be repeated on a third biological sample, wherein the third biological sample consists of isolated platelets and / or leukocytes; and wherein the third biological sample can be obtained from a female subject, wherein the female subject is pregnant, pre-pregnant. or postpartum. In some aspects, the first, the second, and the third biological samples can be obtained from the same subject or from different subjects. In some aspects, the first, the second, and the third biological samples can be obtained from the same subject at a first time point, a second time point, and a third time point. In some aspects, the first time point can be within the first trimester of pregnancy of the subject, the second time point can be within the second trimester of pregnancy of the subject, and the third time point can be within the third trimester of pregnancy of the subject. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point and the third time point. In some aspects, the transcriptome-wide expression profile from the second time point can be compared to the transcriptome-wide expression profile from the third time point. In some aspects, the steps a)-d) can be repeated on each biological sample. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first, the second, and the third biological samples can be obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples can be obtained at different time points. Also disclosed herein are methods of identifying gene expression differences between two transcriptome-wide expression profiles, the methods can comprise: determining one or more variations in a female subject’s platelet or leukocyte transcriptome using the methods disclosed herein, wherein the female subject can be pregnant, pre-pregnant, or postpartum, and wherein the method can be performed at different time points, thereby identifying a gene expression difference. Further disclosed herein are methods of measuring time dependent gene expression differences in platelets or leukocytes from a female subject, the methods can comprise determining one or more variations in the female subject's platelet or leukocyte transcriptome using the methods disclosed herein, wherein the female subject can be pregnant, pre-pregnant, or postpartum, and wherein the method can be performed at different time points, thereby identifying a gene expression difference; and comparing said time-dependent changes from the healthy female pregnant subject to a reference. In some aspects, the biological samples comprise platelets and leukocytes. In some aspects, the PRP comprises platelets and leukocytes. In some aspects, the first PRP comprises platelets and leukocytes. In some aspects, the second PRP comprises platelets and leukocytes. In some aspects, the first PRP and / or the second PRP comprise platelets and leukocytes. In some aspects, the first platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the second platelet rich plasma solution comprises platelets and leukocytes. In some aspects, the first platelet rich plasma solution and / or the second platelet rich plasma solution comprise platelets and leukocytes. In some aspects, the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes. In some aspects, the methods can further comprise measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes. In some aspects, the methods can further comprise comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability' for the stable genes identified from the leukocytes, and calculating the repeatability' for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile. In some aspects, the steps of isolating a plurality of platelets from the two or more biological samples as described herein can comprise: i) collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP; ii) adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution; iii) suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution; iv) magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture; v) transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; and iv) magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets. In some aspects, the CD45 beads can be coated with a substance capable of binding to a leukocyte present in the PRP of step b) i). In some aspects, the methods can further comprise calculating a leukocyte gene expression score. In some aspects, the leukocyte gene expression score can be calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples. In some aspects, the leukocyte gene expression score can be calculated using PTPRC, CD3D, GZMA. GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof. In some aspects, the longitudinal transcriptome-wide expression profile can be created by: using RNA sequencing data to calculate the leukocyte gene expression score; and incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile. In some aspects, the methods can be repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject. In some aspects, the methods can be repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points. In some aspects, said methods can further comprise repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified. In some aspects, the expression levels can further be measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects. In some aspects, the methods can further comprise repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or more different subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points. In some aspects, the methods can further comprise comparing the longitudinal transcriptome-wide expression profiles from each different subject. In some aspects, the longitudinal transcriptome-wide expression profile can serve as a reference. In some aspects, the repeatability index can be between 0.60 and 0.90. In some aspects, the biological sample can be from a healthy subject. In some aspects, the biological sample can be from a subject suspected of having or having a disease or a disorder. In some aspects, the disease or the disorder can be an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease. In some aspects, the leukocytes can be removed from the biological samples during the step of isolating the plurality of platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets. In some aspects, the transcriptome-wide expression profile from the first time point can be compared to the transcriptome-wide expression profile from the second time point. In some aspects, said methods can further comprise repeating the steps thereof until a validated transcriptome-wide expression profile can be identified. In some aspects, the transcriptome-wide expression profile of the subjects can be compared. In some aspects, the first and second biological samples or the plurality of biolog...

Claims

CLAIMSWHAT IS CLAIMED IS:

1. A method for making a longitudinal transcriptome-wide expression profile, said method comprising:a) obtaining a plurality of biological samples from a subject, wherein the plurality’ of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a) by:i. collecting platelet rich plasma (PRP) from the yvhole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP;ii. adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution;iii. suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution;iv. magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture;v. transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; andvi. magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets;c) measuring the expression levels of a plurality of genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

2. The method of claim 1, wherein the CD45 beads are coated with a substance capable of binding to a leukocyte present in the PRP of step b) i).

3. A method for making a longitudinal transcriptome-wide expression profile, said method comprising:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and f) calculating the repeatability’ for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile.

4. A method for monitoring disease progression, disease recurrence, remission, or relapse in a subject, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples compnse whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality’ of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes yvith the highest variation in expression level as the least stable genes over the first and second time points; and f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile;using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby monitoring disease progression, disease recurrence, remission, or relapse in the subject.

5. A method for determining minimal residual disease in a subject, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject.

6. A method for diagnosing a disease or characterizing a disease in a subject, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by: a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby diagnosing the disease or characterizing the disease in the subject.

7. The method of any one of the preceding claims, wherein the method identifies a subtype, a tissue origin, a tumor site of origin, a tumor stage, disease severity, or one or more genetic features of the disease.

8. A method for identifying a drug target, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality’ of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the drug target.

9. The method of claim 8, wherein the drug target is in a metabolic pathway.

10. A method for informing a therapeutic selection or indicating a change in therapy in a subject, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality’ of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby informing the therapeutic selection or indicating the change in therapy in the subject.

11. A method for providing a disease prognosis in a subject, said method comprising:making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject; thereby providing the disease prognosis in the subject.

12. A method for identifying a therapeutic target or pathway for drug development or other therapeutic selection, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality' of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying the therapeutic target or pathway for drug development or other therapeutic selection.

13. The method of any one of the preceding claims, wherein the other therapeutic selection is surgery, radiation therapy or hormone therapy.

14. A method for identifying a predisposition or risk for a disease in a subject, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby determining the minimal residual disease in the subject thereby identifying the predisposition or risk for the disease in the subject.

15. A method for identifying, developing, or validating a diagnostic panel of biomarkers, said method comprising: making a longitudinal transcriptome-wideexpression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points;g) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and h) using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying, developing, or validating a diagnostic panel of biomarkers.

16. A method for determining the health of a fetus or risk or presence of a disease in a fetus, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples compnse whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points:b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expression profile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; therebydetermining the health of the fetus or risk or presence of the disease in the fetus.

17. A method for identifying abnormal developments in a fetus, said method comprising: making a longitudinal transcriptome-wide expression profile, wherein the longitudinal transcriptome-wide expression profile is created by:a) obtaining a plurality of biological samples from a subject, wherein the plurality of biological samples comprise whole blood; wherein the plurality of biological samples are obtained from the same subject at a first time point and a second time point; and wherein the first and second time points are different time points;b) isolating platelets from the plurality of biological samples obtained in a), thereby creating a first platelet rich plasma solution, wherein the first platelet rich plasma solution can optionally comprise leukocytes;c) measuring the expression levels of a plurality genes present in the isolated platelets obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing;d) analyzing the expression levels of the plurality of genes from the RNA sequencing in step c);e) identifying from the plurality' of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points;f) comparing the longitudinal transcriptome-wide expression profiles from the first and second time points; andg) calculating the repeatability' for the stable genes identified in e); thereby making the longitudinal transcriptome-wide expression profile; and using the longitudinal transcriptome-wide expression profile to remove the least stable genes; using the longitudinal transcriptome-wide expressionprofile to retain the most stable genes; and incorporating the longitudinal transcriptome-wide expression profile in gene profile panels; thereby identifying abnormal developments in the fetus.

18. The method of any one of the preceding claims, further comprising calculating a leukocyte gene expression score.

19. The method of any one of the preceding claims, wherein the leukocyte gene expression score is calculated from a RNA sequencing from the leukocytes obtained from the plurality of biological samples.

20. The method of any one of the preceding claims, wherein the leukocyte gene expression score is calculated using PTPRC, CD3D, GZMA, GZMB, KLRB1, CD96, CD86, IGKC or a combination thereof.

21. The method of any one of the preceding claims, wherein the longitudinal transcriptome-wide expression profile is created by:a) using RNA sequencing data to calculate the leukocyte gene expression score;andb) incorporating the leukocyte gene expression score into the longitudinal transcriptome-wide expression profile.

22. The method of any one of the preceding claims, wherein the step of isolating a plurality of platelets from the two or more biological samples in b) comprises: i. collecting platelet rich plasma (PRP) from the whole blood in a first tube and dividing the collected platelet rich plasma into a first PRP and a second PRP;ii. adding prostaglandin El to the first PRP, thereby creating a first platelet rich plasma solution;iii. suspending CD45 beads in the second PRP in a second tube, thereby creating a second platelet rich plasma solution;iv. magnetizing the CD45 beads in the second tube and discarding the supernatant, thereby creating a CD45 bead / PRP mixture;v. transferring the first platelet rich plasma solution into the second tube containing the CD45 bead / PRP mixture; andvi. magnetizing the CD45 bead / PRP mixture and transferring the supernatant comprising isolated platelets.

23. The method of claim 22, wherein the CD45 beads are coated with a substance capable of binding to a leukocyte present in the PRP of step b) i).

24. The method of any of the preceding claims, wherein the method is repeated at least once on two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from a second subject, wherein the biological samples are obtained from the second subject at a first time point and a second time point, wherein the first time point and a second time point are the same time points as the first subject.

25. The method of any of the preceding claims, wherein the method is repeated on a two or more biological samples, wherein the two or more biological samples consist of isolated platelets and / or optionally leukocytes, are obtained from the first subject, and are from different time points.

26. The method of any of the preceding claims, wherein said method further comprises repeating the steps thereof until a validated longitudinal transcriptome-wide expression profile is identified.

27. The method of any of the preceding claims, wherein the expression levels are further measured on a device selected from the group consisting of a microarray, a bead array, and a liquid array.

28. The method of any of the preceding claims, further comprising repeating steps a)-f) or a) to g) on two or more biological samples from two or more additional subjects.

29. The method of any of the preceding claims, further comprising repeating steps a)-f) or a) to g) using two or more biological samples obtained from one or moredifferent subjects, and obtaining additional biological samples from the one or more different subjects, wherein the additional biological samples from each subject are obtained at different time points.

30. The method of claim 29, further comprising comparing the longitudinal transcriptome-wide expression profiles from each different subject.

31. The method any of the preceding claims, wherein the longitudinal transcriptome-wide expression profile serves as a reference.

32. The method any of the preceding claims, wherein the repeatability index is between 0.60 and 0.90.

33. The method of any of the preceding claims, wherein the biological sample is from a healthy subject.

34. The method of any of the preceding claims, wherein the biological sample is from a subject suspected of having or having a disease or a disorder.

35. The method of claim 34, wherein the disease or the disorder is an infectious disease, a cancer, an autoimmune disease, a skin disease, an eye disease, an endocrine disease, a neurological disorder, or a cardiovascular disease.

36. The method of any one of the preceding claims, wherein the leukocytes are removed from the biological samples during the step of isolating the plurality platelets from the biological samples or wherein the leukocytes are removed from the biological samples prior to isolating the plurality platelets.

37. A method for making a healthy pregnancy transcriptome-wide expression profile, the method comprising:a) measuring the expression levels of a plurality genes present in a first biological sample, wherein said measuring comprises RNA sequencing; b) analyzing the expression levels of the plurality of genes from the RNA sequencing in step a);c) identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and d) calculating the repeatability’ for the stable genes identified in c); thereby making the longitudinal transcriptome-wide expression profile, wherein the first biological sample consists of isolated platelets and / or leukocytes; and wherein the first biological sample is obtained from a female subject.

38. The method of claim 37, wherein the female subject is pregnant, pre-pregnant, or postpartum.

39. The method of claim 37, wherein the method is repeated at least once.

40. The method of claim 37, wherein the method is repeated on a second biological sample, wherein the second biological sample consists of isolated platelets and / or leukocytes; and wherein the second biological sample is obtained from a female subject, wherein the female subject is pregnant, pre-pregnant, or postpartum.

41. The method of claim 40, wherein the first and second biological samples are obtained from the same subject or from different subjects.

42. The method of claim 40, wherein the first and second biological samples are obtained from the same subject at a first time point and a second time point.

43. The method of claim 42, wherein the first time point is within the first trimester of pregnancy of the subject and the second time point is within the second trimester of pregnancy of the subject.

44. The method of claim 42, wherein the first time point is within a pre-pregnancy period of the subject or a postpartum period of the subject.

45. The method of any one of the preceding claims, wherein the transcriptome-wide expression profile from the first time point is compared to the transcriptome-wide expression profile from the second time point.

46. The method of claim 37, wherein the method is repeated on a third biological sample, wherein the third biological sample consists of isolated platelets and / or leukocytes; and wherein the third biological sample is obtained from a female subject, wherein the female subject is pregnant, pre-pregnant, or postpartum.

47. The method of claim 46, wherein the first, the second, and the third biological samples are obtained from the same subject or from different subjects.

48. The method of claim 46, wherein the first, the second, and the third biological samples are obtained from the same subject at a first time point, a second time point, and a third time point.

49. The method of claim 48, wherein the first time point is within the first trimester of pregnancy of the subject, the second time point is within the second trimester of pregnancy of the subject, and the third time point is within the third trimester of pregnancy of the subj ect.

50. The method of claim 48, wherein the transcriptome-wide expression profile from the first time point is compared to the transcriptome-wide expression profile from the second time point and the third time point.

51. The method of claim 48, wherein the transcriptome-wide expression profile from the second time point is compared to the transcriptome-wide expression profile from the third time point.

52. The method of any one of the preceding claims, wherein said method further comprises repeating the steps thereof until a validated transcriptome-wide expression profile is identified.

53. The method of any one of the preceding claims, wherein the expression levels are measured on a device selected from the group consisting of a microarray, a bead array, a liquid array, and a nucleic-acid sequence.

54. The method of claim 37, wherein steps a)-d) are repeated on each biological sample.

55. The method of any one of the preceding claims, wherein the transcriptome-wide expression profile of the subjects is compared.

56. The method of any one of the preceding claims, wherein the first and second biological samples are obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples are obtained at different time points.

57. The method of any one of the preceding claims, wherein the first, the second, and the third biological samples are obtained from different subjects, further comprising obtaining additional biological samples from the subjects, wherein the additional biological samples are obtained at different time points.

58. The method of any one of the preceding claims, wherein the transcriptome-wide expression profiles from the first time point is compared to the transcriptome-wide expression profiles from the second time point.

59. The method of any one of the preceding claims, wherein the transcriptome-wide expression profiles from the first time point is compared to the transcriptome-w ide expression profiles from the second time point and the third time point, and the second time point is compared to the transcriptome-wide expression profiles from the third time point.

60. A method of identifying gene expression differences between two transcriptome-wide expression profiles, the method comprising: determining one or more variations in a female subject’s platelet or leukocyte transcriptome using the method of claim 37, wherein the female subject is pregnant, pre-pregnant, or postpartum, and wherein the method is performed at different time points, thereby identifying a gene expression difference.

61. A method of measuring time dependent gene expression differences in platelets or leukocytes from a female subject, the method comprising determining one or more variations in the female subject’s platelet or leukocyte transcriptome using the method of claim 37, wherein the female subject is pregnant, pre-pregnant, or postpartum, and wherein the method is performed at different time points, thereby identifying a gene expression difference; and comparing said time-dependent changes from the healthy female pregnant subject to a reference.

62. The method of any one of the preceding claims, wherein the biological sample comprises platelets and leukocytes.

63. The method of any one of the preceding claims, wherein the first platelet rich plasma solution comprises platelets and leukocytes.

64. The method of any one of the preceding claims, wherein the platelet rich plasma, first platelet rich plasma and / or second platelet rich plasma comprises platelets and leukocytes.

65. The method of any one of the preceding claims, wherein the second platelet rich plasma solution can comprises platelets and leukocytes.

66. The method of any one of the preceding claims, wherein the biological sample, platelet rich plasma (PRP), first PRP, second PRP, first platelet rich plasma solution, and / or second platelet rich plasma solution comprises greater than 98% isolated platelets and less than 2% leukocytes.

67. The method of any one of the preceding claims, further comprising measuring the expression levels of a plurality of genes present in the leukocytes obtained from the plurality of biological samples, wherein said measuring comprises RNA sequencing; analyzing the expression levels of the one or more genes from the RNA sequencing; identifying from the plurality of genes, one or more genes with the lowest variation in expression level as the most stable genes and identifying from the plurality of genes, one or more genes with the highest variation in expression level as the least stable genes over the first and second time points; and calculating the repeatability for the stable genes; thereby making a longitudinal transcriptome-wide expression profile.

68. The method of any one of the preceding claims, further comprising comparing the longitudinal transcriptome-wide expression profile from the isolated platelets with the longitudinal transcriptome-wide expression profile of the leukocytes.

69. The method of any one of the preceding claims, further comprising comparing the repeatability for the stable genes identified from the isolated platelets with the repeatability for the stable genes identified from the leukocytes.

70. The method of claim 69, further comprising calculating the repeatability for the compared stable genes identified from the isolated platelets and the stable genes identified from the leukocytes; thereby making the longitudinal transcriptome-wide expression profile.

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