Methods of diagnosing and treating mood and psychotic disorders using lymphocyte biomarkers

Abstract

Blood-based biomarkers involving evaluation of membrane protein clustering (MPC) on peripherally circulating lymphocytes can identify individuals experiencing depression, schizophrenia, or bipolar disorder, while differentiating those that will respond to treatment from those that will not respond to treatment within the depressed populations. These markers can help diagnose and treat depression, schizophrenia, or bipolar disorder. Further, this diagnostic tool can identify individuals with treatment-resistant depression earlier. The disclosed automated method improves the throughput of blood-based biomarkers and can be standardized across multiple sites of blood collection / analysis. The automated approach performs similarly to human scorers for each method of blood smear collection in accurately obtaining cluster size means for each sample.

Description

[0001] METHODS OF DIAGNOSING AND TREATING MOOD AND PSYCHOTIC DISORDERS USING LYMPHOCYTE BIOMARKERS

[0002] CROSS REFERENCE TO RELATED APPLICATIONS

[0003] This application claims priority to U.S. Provisional Application No. 63 / 562,846, filed March 8, 2024, which is incorporated by reference in its entirety.

[0004] FIELD

[0005] This relates to methods of treating and diagnosing mood and psychotic disorders such as depression, schizophrenia, and bipolar disorder using biomarkers found on lymphocytes.

[0006] BACKGROUND

[0007] Mood and psychotic disorders are one of the largest sources of disability in the world. Although numerous interventions exist, many individuals remain resistant to treatment. Longer durations of illness prior to treatment are associated with lower remission rates, therefore it is important patients receive optimal treatment as early as possible. Although advances in electrophysiology, neuroimaging and functional imaging have expanded our understanding of mood and psychotic disorders, inaccessibility of these techniques limits applications as screening tools for initial diagnosis and treatment selection. Self-report questionnaires are the current standard of care for initial diagnosis and treatment selection for mood and psychotic disorders. However, self -report questionnaires are limited by concerns of accuracy and validity, as patients may not remember, understand, or report their conditions correctly. They may also be influenced by social desirability, mood, or expectations, and give answers that are not truthful or consistent. Patients may interpret questions differently than intended, or have different definitions of the terms used. Thus, the need exists for standardized diagnostic tools for mood and psychotic disorders.

[0008] There are different treatment options available for mood and psychotic disorders, depending on the type, severity, and duration of the symptoms, as well as the individual’s preferences and needs. Psychotherapy is a type of talk therapy that involves a trained mental health professional who helps the person understand and cope with their problems. There are different types of psychotherapy for mood and psychotic disorders, such as cognitive-behavioral therapy, interpersonal psychotherapy, and family therapy. However, psychotherapy has limited effectiveness for particular disorders. Thus, the need exists to quickly identify patients with disorders who may benefit from more aggressive treatment. SUMMARY

[0009] Biomarkers for mood and psychotic disorders identifying patient subtypes are being developed to improve prediction of treatment outcomes, such as evaluation of genomics, proteomics, transcriptomics, metabolomics, microRNA profiles and even machine learning evaluation of voice and gait. Blood-based biomarkers are candidates for large-scale screening of neuropsychiatric diseases.

[0010] Serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), and Prion cellular protein (PrPc) are identified herein as a blood-based biomarker for depression that differentiate depressed populations, schizophrenia populations, or bipolar disorder populations from healthy controls through analysis of membrane bound on peripheral lymphocytes. Furthermore, analysis of membrane protein clustering (MPC) of these biomarkers within treatment naive depressed populations can be used to reliably differentiate groups based upon future treatment efficacy. Increased SERT cluster size is also seen in experimental rodent models of chronic stress alongside depression-like behavior and associated neurobiological alterations [25, 29, 30-33].

[0011] The time-consuming nature of image analysis prevents rapid turnover of results, which is an important feature for any large-scale screening tool. The various stages of processing MPC include collection of blood smears, immunohistochemistry to label the biomarker of interest, imaging, and analysis of clustering. The imaging and analysis of clustering is highly time consuming, involving manual analysis of each lymphocyte. Initial assessments of 100 lymphocytes per subject were reduced to just 50 to accommodate time demands associated with manual cluster scoring, which requires 2-5 minutes per lymphocyte, from time of image upload to pasting raw data to Excel™. Automating the analysis vastly reduces the turnover of results and standardize the analysis across researchers.

[0012] Disclosed herein is a method of treating a mood or psychotic disorder, including obtaining membrane protein cluster count and / or membrane protein cluster size from a subject using a lymphocyte sample. The the membrane protein can include serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), and / or Prion cellular protein (PrPc). The method may include comparing the membrane protein cluster count to a membrane protein cluster count control and / or comparing the membrane protein cluster size to a membrane protein cluster size control, and identifying the subject as having a schizophrenia phenotype, a bipolar disorder phenotype, a depression phenotype, a D-I phenotype, and / or a D-II phenotype based on the results of the comparing. In some examples the method includes administering a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament to the subject. In a further example, the method is a method of treating depression including obtaining SERT membrane protein cluster count and / or SERT membrane protein cluster size from a subject using a lymphocyte sample, comparing the SERT membrane protein cluster count to a SERT membrane protein cluster count control and con ' ’ ""’IT membrane protein cluster size to a SERT membrane protein cluster size control, identifying the subject as having a D-I phenotype based on the results of the comparing, and administering a tricyclic agent to the subject identified as having the D-I phenotype.

[0013] Further disclosed herein is a method of treating a mood or psychotic disorder including obtaining lymphocyte(s) from a subject, culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, measuring membrane protein cluster count and membrane protein cluster size on the medicament cultured lymphocyte(s), comparing the membrane protein cluster count and membrane protein cluster size to a control, and identifying the subject as a schizophrenia phenotype subject, a bipolar disorder phenotype subject, a depression phenotype subject, a D-I phenotype subject, or a D-II phenotype subject. In some examples, the method further includes administering the schizophrenia medicament, the bipolar disorder medicament, the depression medicament, the D-I phenotype medicament, or the D-II medicament. In some examples, the membrane protein includes SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc.

[0014] Further disclosed herein is a method including, with a computer, in an image of a sample from a subject, identifying a region depicting a lymphocyte, identifying patterns representing protein clusters within the region, the identified patterns forming a set, determining values of two or more parameters of the set of identified patterns, and identifying the subject based on the values of the parameters, where the identifying classifies the subject as schizophrenia phenotype, bipolar phenotype, depression phenotype, D-I phenotype, or D-II phenotype. In some examples, the method further includes administering or prescribing a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I medicament, or a D-II medicament.

[0015] The foregoing and other objects and features of the disclosure will become more apparent from the following detailed description, which proceeds with reference to the accompanying figures.

[0016] BRIEF DESCRIPTION OF THE DRAWINGS

[0017] FIGs. 1A-1G: Example of serial steps for calculating lymphocyte clustering data. FIG. 1A: Parent in image demonstrating a single lymphocyte surrounded by background staining within the red channel. FIG. IB: Binary recreation of the threshold in which the lymphocyte was first detected, which can be used to define a region of interest for the lymphocyte. FIG. 1C: Extracted lymphocyte from the parent image prior to thresholding and re-orienting demonstrating clusters of SERT. FIG. ID: Demonstration of circularization of region of interest and removal of background outside the defined region of interest. FIG. IE: Demonstration of SERT clusters post-thresholding which was automatically conducted to reduce the number of clusters detected. FIG. IF: Binary outlines of detected clusters from the original image (i.e. FIG. ID), demonstrating the original cluster count was well above the pre-defined limit of 115 clusters per lymphocyte. FIG. 1G: Binary outlines of detected clusters from the threshold image (i.e. FIG. IE), demonstrating the first brightness adjustment of the original image resi:'':~ ' -1-"TCOunt within the range of 30-115. FIGs. 2A-2C. Example of a multi-channel image of a lymphocyte and non-lymphocyte staining in the red channel, demonstrating how Hoestch (blue channel) can be used to detect lymphocytes and SERT (red channel) for analyzing clustering. FIG. 2A: Parent image including both blue and red channels. There is substantial overlap in blue and red channel staining on the right, circular region of staining but only red channel staining is visible on the left region of staining. FIG. 2B: Binary output of the blue channel, can be used to identify the location of the lymphocyte within the parent image. No blue staining is detected where the non-lymphocyte is detected in the red channel, allowing for differentiation of background and nonlymphocytes from circulating lymphocytes expressing SERT. FIG. 2C: Binary output of the red channel for identifying the SERT clusters. Additional staining is observed in a non-lymphocyte within the red channel.

[0018] FIGs. 3A-3D: Correlations obtained from analyzing manual scores against automatically generated data. FIG. 3A: Correlation obtained between manually analyzed isolated lymphocytes against automated data analyzing the same images (r=0.935, p<.001; n=19). FIG. 3B: Correlation between manually analyzed blood smears fixed prior to freezing / transport against automatically generated data obtained when analyzing the same images (r=0.849, p<.001; n=22). FIG. 3C: Correlation between manually analyzed blood smears fixed post-freezing / transport against automatically generated data obtained when analyzing the same images (r=0.942, p<.001; n=15). FIG. 3D: Correlation between manually analyzed samples of all sources against automatically generated data obtained when analyzing the same images (r=0.92, p<.001; n=56).

[0019] FIGs. 4A-4D. Correlations for evaluating inter-rater reliability comparing novel scores to original human scores. FIG. 4A: Correlation for cluster size means obtained by the original manual analysis for isolated lymphocytes against novel scoring of the same images (r=0.874, p<.0001; n=15). FIG. 4B: Correlation for cluster size means obtained by the original manual analysis for blood smears fixed prior to freezing / transport against novel scoring of the same images (r=0.836, p<.001; n=15). FIG. 4C: Correlation for cluster size means obtained by the original manual analysis for blood smears fixed post-freezing / transport against novel scoring of the same images (r=0.962, p<.0001; n=15). FIG. 4D: Correlation between original mean cluster sizes across all methods against novel scoring of the same images (r=0.913, p<.0001; n=45).

[0020] FIGs. 5A-5D. Qualitative data of lymphocyte detection / inclusion for each method analyzing 500 images selected at random. FIG. 5A: Demonstration of program success rate when analyzing isolated lymphocytes. FIG. 5B: Demonstration of program success rate when analyzing blood smears frozen before fixation. FIG. 5C: Demonstration of program success rate when analyzing blood smears fixed prior to freezing / transport. FIG. 5D: Demonstration of program success rate when analyzing blood smears fixed prior to freezing, but images were re-obtained with an additional color channel (blue) for identifying and isolating lymphocytes.

[0021] FIGs. 6A-6B. FIG. 6A shows the socio-demographic data of the naive population cohort included in the differential diagnosis and therapeutic efficacy study. FIG. 6B shows differences in the clinical characteristics between depression and bipolar groups before treatment. FIG 7. shows the treatment associated with patients with different diagnosis. There were differences in treatment for different disorders but there are no associations between treatment and biological or clinical parameters. Antidepressant Drugs (AD); Anxiolytic Drugs (ANX); Antipsychotic Drugs (ANTPS); Mood Stabilizers (MST).

[0022] FIGs. 8A-8E. FIG. 8A shows representative images of SERT clustering in lymphocytes extracted from control, major depression, bipolar disorder, or schizophrenia patients. SERT clusters are shown as gray dots and are amenable to image analysis. FIGs. 8B, 8C, and 8D show bar graphs of biological parameters evaluating SERT protein clustering (% modal peak SERT clusters, number of SERT clusters, and size of SET clusters) in lymphocytes in naive patients (D-I, D-II, Bipolar Disorder, and Schizophrenia) in comparison with the control group. FIG. 8E details the differences in SERT protein clustering among the naive patient populations and control cohort.

[0023] FIG. 9. Graphical representation of the distribution of SERT clusters size in lymphocytes from control, depression I, depression II, and bipolar disorder native cohorts (average of measurements before pharmacological treatment). Note decrease of clusters within the modal peak of depression II patients.

[0024] FIGs. 10A-10C. FIG. 10A is a graphical representation of the number of SERT clusters (Y axis) and the average size of SERT clusters (X axis). Each dot represents the average measure of SERT analysis in lymphocytes of one individual patient. Patients with different diagnosis tend to be scored in different areas of the graphs. FIG. 10B is a graphical representation of SERT clusters after pharmacological treatment. Data points are now observed closer to the control population. The general movement of the dots along the X / Y axis is shown by arrows and correlates with the improvement in psychological scales, indicating that analysis of SERT protein clustering can also be considered a biomarker of therapeutic efficacy not just for major depression, but also for bipolar disorder, and schizophrenia. FIG. IOC is an exemplary diagnostic matrix for SERT clustering biomarker efficacy. The table reflects the statistical data evaluating the sensitivity, specificity, and accuracy, of the analysis of SERT clusters size and number as a biomarker of differential diagnosis between major depression, bipolar disorder, and schizophrenia.

[0025] FIGs. 11A-11G. indicate changes in the psychological scales upon pharmacological treatment. FIG. 11A indicates the global changes in the self-assessment anhedonia scale (SAAS), while FIGs. 11B, 11C, and 11D detail the changes in the three axes evaluated in SAAS (intensity, frequency, and change). FIG. HE evaluates changes in the HDRS for depression and bipolar patients. FIG. HF shows before / after alterations in the positive and Negative Symptoms in Schizophrenia scale. PANNSP (positive symptoms), PANNSN (negative symptoms), PANNSC (cognitive symptoms), PANNSG (global scores). FIG. 11G shows correlations between changes in psychological scales and SERT clustering in lymphocytes after pharmacological treatment. For D-II patients there is a correlation between increases in SERT numbers and clinical response in psychological scales, as well as a decrease in SERT numbers and clinical response in psychological scales in bipolar disorder. FIGs. 12A-12I show histograms representing SERT clustering analyses before and after pharmacological treatment. Distinct changes in SERT clusters parameters are observed for depression, bipolar disorder, and schizophrenia. FIGs. 12A-12C show percentage of clusters within the size modal peak, number of cluster per lymphocyte, and average clusters size for depression subjects. FIGs. 12D-12F show percentage of clusters within the size modal peak, number of cluster per lymphocyte, and average clusters size for bipolar disorder subjects. FIGs. 12G-12I show percentage of clusters within the size modal peak, number of cluster per lymphocyte, and average clusters size for schizophrenia subjects.

[0026] FIGs. 13A-13H show the result of incubating rodent lymphocytes with corticosterone (CORT) and antidepressant drugs, followed by evaluation of serotonin transporter (SERT) clustering. FIGs. 13A and 13B depict alterations in SERT clustering numbers and size upon incubation with CORT using different concentrations and times. Use of ImM CORT for one or two hours mimics the increases in SERT cluster size that are observed in naive depression patients. Statistical significance with respect to control samples is denoted by “a” (p<0.05). FIGs. 13C and 13D depict alterations in SERT clusters numbers and size upon coincubation with ImM CORT and different concentrations / times of the selective serotonin recapture inhibitor drug (SSRI) fluoxetine. Most low concentrations of fluoxetine (Ih incubation) lower SERT cluster size. 12 and 24 mM fluoxetine completely reversed the changes induced by CORT. Statistical significance with respect to control samples is denoted by “a” (p<0.05). FIGs. 13E and 13F depict alterations in SERT cluster numbers and size upon co-incubation with ImM CORT and different concentrations / times of the tricyclic antidepressant drug (TCA) imipramine. Most low concentrations of fluoxetine (Ih incubation) lower SERT clusters size. 3, 12 and 24 mM completely reversed the changes induced by CORT. Statistical significance with respect to control samples is denoted by “a” (p<0.05). FIGs. 13G and 13H depict alterations in SERT clusters number and size upon co-incubation with ImM CORT and different concentrations / times of the antidepressant drug Ketamine. 0.5 mM ketamine for one hour lowered the increase in SERT clusters induced by CORT. Statistical significance with respect to control samples is denoted by “a” (p<0.05).

[0027] FIG. 14 is a block diagram of an example computing system in which described examples can be implemented.

[0028] FIG. 15 depicts an exemplary method of diagnosing a subject with a mood or psychotic disorder. A region depicting a lymphocyte is identified in an image of a sample (1502). Patterns representing protein clusters are identified (1504). Values of two or more parameters are determined (1506). The subject can then be identified (1508). In some examples, steps 1502, 1504, 1506, and 1508 are carried out on a computer. In some examples, steps 1502, 1504, and 1506 are carried out on a computer. In some examples, the method further includes prescribing or administering a suitable medicament. This can be performed by a supervising clinician. FIG. 16 depicts an exemplary method of identifying a region depicting a lymphocyte. Parameters for size, opacity, and / or shape are set (1602) and a graphics library function is called with the set parameters (1604). The graphics library function may accomplish this by scanning the image until an edge of an object is found (1612) determining an outline of the object (1616) and checking whether the object matches the set parameters (1620). Steps 1612, 1616, and 1620 may be recurred until the region is identified. The library may then return the object matching the set parameters.

[0029] FIG. 17 depicts an exemplary method of identifying patterns representing protein clusters within a region depicting a lymphocyte. Pattern parameters can be set, such as for at least size (1704). A graphics library function can be called with the set parameters to identify patterns matching the set parameters (1708). That graphics card library can scan an image until the edge of a pattern candidate is found (1712), determine and outline of the pattern candidate (1716), and check whether the pattern candidate matches the set pattern parameters (1720). Steps 1712, 1716, and 1720 may be recurred until the pattern parameters are matched. The pattern candidate matching the set parameters can then be returned to identify a given pattern (1724).

[0030] FIG. 18 depicts an exemplary method identifying a lymphocyte. A first file location can be identified, and a file list can be created (1802). An image can be selected, such as from the first file location (1804). The image can be duplicated, and the channels split (1808). The image can be converted to binary, and particle analysis can be performed on at least one image channel (1812). The minimum brightness threshold can be serially increased, and duplicate images can be created, nulling existing ROIs until a minimum threshold is identified (1816).

[0031] FIG. 19 depicts an exemplary method of obtaining MPC number and / or size on an identified lymphocyte. A duplicate ROI image can be created (1902). The duplicate ROI can be circularized (1904). Background can be removed with the rolling ball function (1908). The image can be converted to binary (1912). Outlier pixels can be removed beyond a set radius (1916). Despeckle and watershed can be performed (1920). Particle analysis can be performed to obtain MPC count and / or MPC size (1924). In some examples, if the obtained MPC count and / or MPC size are outside of accepted parameters alternative maximum brightness settings can be applied (1926). The results of the particle analysis and an image of at least one channel can be saved to a file location (1928).

[0032] FIG. 20 describes clinical characteristics of naive subjects discussed in Example 6.

[0033] FIGs. 21A-21X describes clinical characteristics of subjects discussed in Example 8 before and after treatment. FIG. 21A shows clinical characteristics of the schizophrenia cohort. FIG. 21B shows episode clinical characteristics and biological parameters. FIG. 21C shows substance clinical characteristics and biological parameters. FIG. 21D shows antipsychotic clinical characteristics and biological parameters.

[0034] FIG. 21E shows episode clinical characteristics and PANSS. FIG. 21F shows substance clinical characteristics and PANSS. FIG. 21G shows antipsychotic clinical characteristics and PANSS. FIG. 21H shows average PANSS score before treatment. FIG. 211 shows episode clinical characteristics and SAAS. FIG. 21J shows substance clinical characteristics and SAAS. FIG. 21K shows antipsychotic clinical characteristics and SAAS. FIGs. 21L-21O each depict SAAS before treatment. FIG. 21P shows average PANSS score after treatment. FIG. 21Q shows PANSS before-after. FIG. 21R shows SAAS after treatment. FIG. 21S shows biological variables after treatment. FIG. 21T shows diagnostic biomarker correlations. FIG. 21U shows response biomarker correlations. FIG. 21V shows HDRS naive. FIG. 21W shows HDRS before-after treatment. FIG. 21X shows PANSS before-after.

[0035] FIGs. 22A-22B depict SERT cluster size before and after treatment among depression, schizophrenia, and bipolar groups.

[0036] DETAILED DESCRIPTION

[0037] I. Introduction

[0038] An automated method was developed to analyze large numbers of lymphocytes. This method can detect lymphocytes through serial thresholding to identify shapes fitting the characteristics of circulating B- lymphocytes and conduct particle analysis on each detected shape to generate cluster data for entire folders of images. After detecting and analyzing clusters, the program can evaluate whether the number of clusters is within a normal range, excluding results obtained beyond reasonable outliers, which have been defined by past results. Results can be written to any exemplary medium, such as an Excel™ spreadsheet. Results can be excluded if the number of clusters is beyond the set limit, and if so, the lymphocyte can be re-analyzed with altered brightness settings. This method can be implemented as a program, for example which prompts the user to select two folders: the first folder containing the images and the second folder for raw data and binary outputs. The user can then return after analysis has completed to manually verify, through visual inspection, whether the lymphocytes detected truly represent lymphocytes.

[0039] To demonstrate the value of these methods, consider a small study requiring analysis of 500 samples. This would require analysis of 25,000 lymphocytes, or approximately 800 hours of manual analysis. In contrast, this analysis could be completed with approximately 30 seconds of user input via the disclosed automated method. Furthermore, if large projects are to be completed in a variety of labs, standardization through automating the analysis could provide more consistent findings across different groups.

[0040] To validate whether the results produced by the automated method are similar to human scorers, a subset of 750 lymphocyte images were analyzed. To determine whether results were comparable, data from the automated method was correlated against manually obtained data. Three sets of samples were selected using different blood collection methods to investigate whether one method of collection outperforms another when results are automated. Inter -rater reliability of manual analysis was evaluated from each method to establish whether the differences in automated versus manual were similar to human-human variability. To accomplish this, a person was tr?'11^ w v™, SERT clustering before blindly analyzing SERT clustering from 50 lymphocytes associated with 15 samples from each of the 3 blood collection methods, corresponding to 2250 lymphocytes. Next, the program was evaluated for consistency across methods in terms of proportion of images without a detectable lymphocyte, number of lymphocytes detected, analyzed, and manually rejected. To accomplish this, 500 random images from each method were collected and analyzed with the automated approach, adjusting the program to record and report these values upon completion, and counting the number of manually rejected.

[0041] In some examples, the imaging methods include multi-channel imaging of blue (460 nm), red (568 nm) and / or green (532 nm) channels. In some examples, the imaging method include capturing the red channel corresponding to SERT signal via secondary antibody fluorescence. Blue can be used to identify B- lymphocytes by shape and size from other white blood cells and red blood cells. The lymphocyte detection method within the method was then adjusted to use the blue channel to identify lymphocytes and create regions of interest (ROI) and the red channel to identify SERT clustering before analyzing these 500 images.

[0042] Strong correlations were obtained when comparing manually obtained results against automatically generated data when analyzing samples from each source of lymphocyte collection. The method with the lowest correlation obtained with samples frozen prior to fixation [r=.84 (p< .001)] and the highest correlation occurred in samples fixed prior to freezing [r=.94 (p< .001)] (as shown in FIGs. 3A-3D). This demonstrates the automated method is viable and produces similar results to that produced by human scorers. A strong correlation of r=.92 (p<.001) was found when amalgamating methods into a single analysis. No single method drastically outperformed another in terms of consistency in results, indicating any of the methods applied here for collecting and analyzing lymphocytes is viable for obtaining reliable results with automation.

[0043] Two unexpected patterns emerged. The program tended to be more consistent with manual scoring when cluster size means were low (ex. 0.05-0.1) relative to high (0.1+). Additionally, no samples with cluster size means above 0.1 obtained by fixation prior to freezing were included in this analysis (as seen in FIGs. 3A-3D). These combined features relate to a slightly inflated correlation for this method relative to the other methods. When considering the magnitude of difference between automated and manual scores and comparing to the literature regarding the magnitude difference between depressed and non-depressed controls, only 3 values had a difference beyond 0.02um2, with a mean difference between scores of 0.0014 between automated and manually obtained across all scores. In contrast, the group difference for cluster means for depressed from non-depressed was approximately 0.06 um2in early study of SERT clustering (Rivera-Baltanas et al., Journal of Affective Disorder, 163:47-55m 2014), indicating the minor differences between automated and manual results would not likely impact group effects. This is especially true as the automated results do not tend to vary consistently above or consistently below the manually obtained results, suggesting the automated system is not resulting in biased results one way or another. A significant positive correlation for each method of blood collection independently and collectively was observed, indicating the automated method can be used to expedite lymphocyte clustering analysis in an accurate and reliable manner. To improve the comparisons of blood sample collection methods and to expand the number of researchers included in correlational analyses, new human scorers were trained to analyze a new subset of lymphocytes and were asked to analyze a subset of images derived from each method of blood smear collection. The correlations against the previously obtained manual result and the automatically generated result were evaluated. This result indicates each method can effectively provide accurate SERT clustering results, and also that an additional human scoring does not result in considerable change to correlation strength for any given method relative to comparisons of automated versus the original scores. Given two human-derived results are comparable to human-derived results against automated results, in terms of correlation strength, these results demonstrate that the disclosed automated SERT clustering analysis can be used to expedite the analysis. Optimizing throughput for the SERT clustering analysis reduces the duration to obtain meaningful results, which is a factor in the context of depression-related biomarkers.

[0044] II. Abbreviations

[0045] 5 -HT : 5 -hydroxy-tryptamine AD: Antidepressant Drugs ANTPS: Antipsychotic Drugs ANX: Anxiolytic Drugs BD: Bipolar Disorder Beta2AR: Beta 2 adrenergic receptor CORT: Corticosterone DAT: Dopamine transporter HDRS: Hamilton Depression Rating Scale MDD: Major Depressive Disorder MPC: Membrane protein clustering MST: Mood Stabilizers

[0046] NR2B: NMD A receptor 2B subunit

[0047] PANNS: Positive and Negative Syndrome Scale PNX1: Pannexin 1

[0048] PrPc: Prion cellular protein ROI: Region of interest SAAS: Social Appearance Anxiety Scale SCZ: Schizophrenia

[0049] SERT: Serotonin Transporter Protein SSRI: Selective serotonin reuptake inhibitors

[0050] III. Summary of Terms

[0051] Unless otherwise noted, technical terms are used according to conventional usage. Definitions of many common terms in molecular biology may be found in Krebs et al. (eds.), Lewin ’s genes XII, published by Jones & Bartlett Learning, 2017. As used herein, the singular forms “a,” “an,” and “the,” refer to both the singular as well as plural, unless the context clearly indicates otherwise. For example, the term “a cluster” includes singular or plural clusters and can be considered equivalent to the phrase “at least one cluster.” As used herein, the term “comprises” means “includes.” Although many methods and materials similar or equivalent to those described herein can be used, particular exemplary methods and materials are described herein. In case of conflict, the present specification, including explanations of terms, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting. To facilitate review of the various aspects, the following explanations of terms are provided:

[0052] About: Unless context indicated otherwise, “about” refers to plus or minus 5% of a reference value. For example, “about” 100 refers to 95 to 105.

[0053] Administering (or Administration): To provide or give a subject an agent, including a pharmaceutical preparation of an agent, such as an SSRI, by any effective route. Administration can be local or systemic. Exemplary routes of administration include, but are not limited to, injection (such as subcutaneous, intramuscular, intradermal, intraperitoneal, intrathecal, and intravenous), oral, sublingual, rectal, transdermal, intranasal, vaginal, topical, and inhalation routes.

[0054] Beta 2 Adrenergic Receptor (Beta2AR): A cell membrane beta-adrenergic receptor that binds adrenaline. Beta2AR signaling activates the G protein Gs, ultimately resulting in modulation of various downstream proteins such as protein kinase A, ion channels, and transcription factors. Encoded by the gene ADRB2. Beta2AR is also known as ADRB2R, ADRBR, B2AR, BAR, BETA2AR, and adrenoceptor beta 2. OMIM: 109690. NCBI Gene IDs: 154 (human), 11555 (Mus musculus), 397357 (Sus scrofa).

[0055] Bipolar Disorder: A mental illness that can cause unusual shifts in a subject’s mood, energy, activity levels, and concentration. Subjects with bipolar disorder can experience periods characterized by elated, irritable, or energized behavior (manic episodes) and periods characterized by feelings of depression or hopelessness (depressive episodes). Subjects with bipolar disorder can be further classified into those with bipolar I disorder, bipolar II disorder, and cyclothymic disorder (see Miller et al., Clin Psychol (2009) 16:188-201).

[0056] The disclosed methods can be used to diagnose and treat bipolar disorder. Currently available objective tests used to determine whether an individual has bipolar disorder and to measure and assess the success of a particular treatment schedule or regimen include the Structured Clinical Interview for DSM- IV (SCID), which assess diagnostic criteria againvln<JM.TV (seeSpitzer Arch Gen Psychiatry (1992) 49:624-29). Another exemplary method is the Schedule for Affective Disorders and Schizophrenia (SADS), which assesses diagnostic criteria against the Research Diagnostic Criteria (RDC) (Endicott & Spitzer, Arch Gen Psychiatry (1978) 35:837-44).

[0057] Cluster Count: An amount derived from the number of cell surface protein clusters of a protein of interest (such as SERT), which are observable on the surface of a subject cell via a technique such as immunocytochemistry. “Cluster count” can be used with reference to a single cell, such as to represent the number of clusters observed on that single cell. “Cluster count” can be used with reference to a patient, or a patient population, to represent an aggregate value, such as an average number of clusters observed on a cell population of interest.

[0058] A “whole cell” cluster count refers to the number of clusters on a cell in total. This number may be greater than a cluster count derived from a single image, because a cluster count only measures cell surface protein clusters from a single perspective.

[0059] Cluster Size: An amount derived from the size of cell surface protein clusters for a protein of interest (such as SERT). “Cluster size” can be used with reference to a single cluster. More commonly, “cluster size” can refer to the aggregate, such as an average, cluster size on a single cell, a population of cells, or a population of cells aggregated from different patients.

[0060] Control: A reference standard. In some examples, the control is a negative control sample, such as a sample from a healthy patient (e.g., known to not have a particular mood or psychotic disorder). In other examples, the control is a positive control sample, such as a sample from a patient known to have a particular mood or psychotic disorder. In some examples the control is a historical control or standard reference value or range of values (such as a previously tested control sample). In some examples, the control is a range of values indicative of diagnosis with a particular mood or psychotic disorder, or a range of values indicative of a patient phenotype indicating that they will respond to a particular treatment.

[0061] A difference between a test sample and a control can be an increase or conversely a decrease. The difference can be a qualitative difference or a quantitative difference, for example a statistically significant difference. In some examples, a difference is an increase or decrease, relative to a control, of at least about 5%, such as at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 100%, at least about 150%, at least about 200%, at least about 250%, at least about 300%, at least about 350%, at least about 400%, at least about 500%, or greater than 500%.

[0062] Contacting: Placement in direct physical association; includes both in solid and liquid form.

[0063] Detectable Label (or Label): A detectable compound or composition that is conjugated directly or indirectly to another molecule, such as an antibody or a protein, to facilitate detection of that molecule. Specific, non-limiting examples of labels include fluorescent tags, enzymatic linkages, radionuclides (such as radionuclides bound to a chelator) and radioa Examples of labels for polypeptides include, but are not limited to, the following: radioisotopes or radionuclides (such as35S,nC,13N,15O,18F,19F,99nlTc,131I,3H,14C,15N,90Y, "Tc,lnIn, and125I), fluorescent labels, enzymatic labels (such as horseradish peroxidase, beta-galactosidase, luciferase, alkaline phosphatase), chemiluminescent markers, biotinyl groups, predetermined polypeptide epitopes recognized by a secondary reporter (such as a leucine zipper pair sequences, binding sites for secondary antibodies, metal binding domains, epitope tags), or magnetic agents, such as gadolinium chelates. In some examples, labels are attached by spacer arms of various lengths to reduce potential steric hindrance.

[0064] Methods for using detectable markers and guidance in the choice of detectable markers appropriate for various purposes are discussed for example in Green and Sambrook (Molecular Cloning: A Laboratory Manual, 4thed., New York: Cold Spring Harbor Laboratory Press, 2012) and Ausubel et al. (Eds.) (Current Protocols in Molecular Biology, New York: John Wiley and Sons, including supplements, 2017).

[0065] Examples of “fluorescent labels” include, but are not limited to, Pacific Blue, AF488, AF568, FITC, PE, APC, PerCP, and PerCP-Cy5.5.

[0066] Depression (or Depressive disorder): A mood disorder characterized by a predominantly sad or depressed mood, typically but not always of two or more weeks' duration. A depressive disorder also has other signs or symptoms accompanying a sad or depressed mood, including one or more of: decreased energy, appetite changes, weight gain or loss, insomnia or hypersomnia, recurrent thoughts or death, thoughts of suicide, loss of interest in usual activities, slowed thinking or cognitive speed, increased speech latency, decreased volume of speech, excessive or inappropriate guilt, diminished concentration, feeling sluggish, and slower than normal motor activity (such as gross motor, fine motor, speech). Depressive disorders can be accompanied by perceptual disturbances. Depressive disorders can be caused by a medical disorder (e.g., endocrine disorders, lupus), medication side-effect (e.g., interferon), substance use disorder, neurologic disorder (e.g., seizure disorder, traumatic brain injury), or have no clear cause.

[0067] Depression includes feelings of sadness considered to be normal (mild depression), dysthymia, and major depression. Depression can resemble the grief and mourning that follows bereavement, and there are often feelings of low self esteem, guilt and self reproach, withdrawal from interpersonal contact and somatic symptoms such as alterations in eating habits and sleep disturbances.

[0068] The disclosed methods can be used to diagnose and treat depression. Currently available objective tests used to determine whether an individual is depressed and to measure and assess the success of a particular treatment schedule or regimen include the Self- Assessment Anhedonia Scale (SAAS) scale, which is a 27-item scale that scores the “intensity” and “frequency” of specific anhedonia symptoms, as well as the “changes” in those symptoms as perceived by the patient (Olivares et al., Neurology, Psychiatry, and Brain Research, (2005) 12: 121-134). Other exemplary methods include the Physical Anhedonia (PA) and Social Anhedonia (SA) scale (Chapman et al., Journal of Abnormal Psychology, (1976) 85, 374-382) and the Snaith-Hamilton pleasure scale (SHAPS) (Snaith et al., The British Journal of Psychiatry (1995) 167, 99- 103).

[0069] Diagnosing (or Diagnostic): Identifying the presence or nature of a pathologic condition, such as a mood or psychotic disorder. While a particular diagnostic method may not provide a definitive diagnosis of a condition, it suffices if the method provides a positive indication that aids in diagnosis.

[0070] Dopamine Transporter (DAT): A membrane protein encoded by the SLC6A3 gene. DAT pumps dopamine out of the synaptic cleft into the cytosol. DAT is also known as solute carrier family 6 (neurotransmitter transporter), member 3, DAT1, PKDYS, solute carrier family 6 member 3, Dopamine transporter, and PKDYS1. OMIM 126455. NCBI Gene IDs: 6531 (human), 13162 (Mus musculus), 100521346 (Sus scrofa)

[0071] D-I Phenotype: A subset of subjects with depression. D-I patents are less likely than D-II patients to show improvement following psychopharmacological treatment than D-II patients.

[0072] D-II Phenotype: A subset of subjects with depression. D-II patients show marked improvement by self-assessment of anhedonia following psychopharmacological treatment, such as 8 weeks of psychopharmacological treatment (Rivera-Baltanas et. al., Annals of Gen. Psy., (2015) 14:45).

[0073] Effective amount: The amount of a medicament, or agent (such as an SSRI disclosed herein) that is sufficient to effect beneficial or desired results. An effective amount (also referred to as a therapeutically effective amount) may vary depending upon one or more of: the subject and disease condition being treated, the weight and age of the subject, the severity of the disease condition, the manner of administration and the like. The specific therapeutically effective dose level for any particular patient will depend upon a variety of factors including the disorder being treated and the severity of the disorder; the specific composition employed; the age, body weight, general health, sex and diet of the patient; the time of administration; the route of administration; the rate of excretion of the specific compound employed; the duration of the treatment; drugs used in combination or coincidental with the specific compound employed and like factors.

[0074] The beneficial therapeutic effect can include enablement of diagnostic determinations; amelioration of a disease, symptom, disorder, or pathological condition; reducing or preventing the onset of a disease, symptom, disorder or condition; and generally counteracting a disease, symptom, disorder or pathological condition.

[0075] In one aspect, an “effective amount” of a therapeutic agent (e.g., an SSRI) is an amount sufficient to reduce self-reported symptoms of a mood or psychotic disorder, reduce the incidence of cognitive impairment, reduce the incidence of psychotic episodes, reduce sleep disturbances, reduce abnormal sleep patterns, reduce weight gain, reduce weight loss, reduce feelings of anxiety, reduce paranoia, reduce grandiosity, reduce cognitive disorganization, reduce magical thinking, reduce persecutory ideation, reduce suicidal ideation, or reduce of hallucinations, reduce feelings of depression, and / or reduce delusions, by at least 5%, at least 10%, at least 15%, at least 20? ' at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 90%, at least 95%, or at least 99% (as compared to a exemplary control, such as no administration of the therapeutic agent).

[0076] In one aspect an effective amount of a therapeutic agent (e.g., an SSRI) is an amount sufficient to improve memory retention, improve energy, or improve appetite by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 90%, at least 95%, or at least 99% (as compared to a exemplary control, such as no administration of the therapeutic agent).

[0077] Inhibiting or treating a disease: Inhibiting the full development of a disease or condition, for example, in a subject who is at risk for a disease such a mood or psychotic disorder. “Treatment” refers to a therapeutic intervention that ameliorates a sign or symptom of a disease or pathological condition after it has begun to develop. The term “ameliorating,” with reference to a disease or pathological condition, refers to any observable beneficial effect of the treatment. Inhibiting a disease can include preventing or reducing the risk of the disease, such as preventing or reducing the risk of developing a mood or psychotic disorder. The beneficial effect can be evidenced, for example, by a delayed onset of clinical symptoms of the disease in a susceptible subject, a reduction in severity of some or all clinical symptoms of the disease, a slower progression of the disease, a reduction in symptoms on a self -reported questionnaire, an improvement in the overall health or well-being of the subject, or by other parameters that are specific to the particular disease. A “prophylactic” treatment is a treatment administered to a subject who does not exhibit signs of a disease or exhibits only early signs for the purpose of decreasing the risk of developing pathology.

[0078] The term “reduces” is a relative term, such that an agent reduces a disease or condition if the disease or condition is quantitatively diminished following administration of the agent, or if it is diminished following administration of the agent, as compared to a reference agent. Similarly, the term “prevents” does not require that an agent completely eliminates the disease or condition, so long as at least one characteristic of the disease or condition is reduced or eliminated. Thus, a composition that reduces or prevents a mood or psychotic disorder, can, but does not necessarily completely, eliminate the mood or psychotic disorder, so long as the mood or psychotic disorder is measurably diminished, for example, by at least about 50%, such as by at least about 70%, or about 80%, or even by about 90% of the mood or psychotic disorder in the absence of the agent, or in comparison to a reference agent.

[0079] Isolated: An isolated host cell (or populations of cells) (such as an isolated lymphocyte) includes cells purified by standard purification methods from the organism or tissue in which they typically reside. An isolated host cell can be at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, at least 99.9%, or at least 99.99% pure.

[0080] Mood disorder: A medical, neurologic, or psychiatric disorder with the primary sign or symptom as an alteration in mood. Mood disorders are usually classified as depressive (e.g., principal mood symptom is a sustained sad or depressed mood) or manic (e.g., principal mood symptom is a sustained expansive, elevated, or irritable mood). Symptoms or signs beyond the mood state proper may be required to diagnose a mood disorder.

[0081] NMDA Receptor 2B Subunit (NR2B): A subunit protein which forms part of an ionotropic glutamate receptor NMDA, which has a role in the plasticity of synapses. An NMDA receptor channel is a heterotrimer including two molecules of NR1 and two drawn from the other subunits, such as NR2A, NR2C, and NR2D. The 2B subunit is encoded by the GRIN2B gene. Also known as GluN2B, MRD6, NMDAR2B, NR2B, hNR3, EIEE27, glutamate ionotropic receptor NMDA type subunit 2B, NR3, and DEE27. OMIM: 138252. NCBI Gene IDs: 2904 (human), 14812 (Mus musculus), 100626022 (Sus scrofa).

[0082] Pharmaceutically acceptable carriers: The pharmaceutically acceptable carriers of use are conventional. Remington’ s Pharmaceutical Sciences, by E. W. Martin, Mack Publishing Co., Easton, PA, 19th Edition, 1995, describes compositions and formulations suitable for pharmaceutical compositions, which include one or more SSRIs.

[0083] Examples of fluid carriers include pharmaceutically and physiologically acceptable fluids such as water, physiological saline, balanced salt solutions, aqueous dextrose, glycerol or the like as a vehicle. Examples of solid carriers include pharmaceutical grades of mannitol, lactose, starch, or magnesium stearate. Such compositions may be present in a sealed vial, or lyophilized for subsequent solubilization.

[0084] Pannexin 1 (PNX1): Protein belonging to the innexin family, which form structural components of gap junctions. Abundantly expressed in the central nervous system. Also known as PANXI, MRS1; OOMD7; OZEMA7; and UNQ2529. OMIM: 608420.NCBI Gene IDs: 24145 (human), 55991 (Mus musculus), 100738603 (Sus scrofa).

[0085] Prion Cellular Protein (PrPc): A membrane glycosylphosphatidylinositol-anchored glycoprotein that tends to aggregate into rod-like structures. PrPc is ubiquitously expressed in the brain. Also known as PRNP, CJD, GSS, PrP, ASCR, KURU, PRIP, CD230, AltPrP, p27-30, PrP27-30, and PrP33-35C. OMIM: 176640. NCBI Gene IDs: 5621 (human), 19122 (Mus musculus), and 494014 (Sus scrofa).

[0086] Psychotic (or Psychotic Disorder): A psychiatric condition in its broadest sense, as defined in the DSM-IV (Kaplan, ed. (1995) supra). Different disorders which have a psychotic component comprise different aspects of this definition of “psychotic.” For example, in schizophreniform disorder, schizoaffective disorder and brief psychotic disorder, the term “psychotic” refers to delusions, any prominent hallucinations, disorganized speech, or disorganized or catatonic behavior. In psychotic disorder due to a general medical condition and in substance-induced psychotic disorder, “psychotic” refers to delusions or only those hallucinations that are not accompanied by insight. Finally, in delusional disorder and shared psychotic disorder, “psychotic” is equivalent to “delusional” (see DSM-IV, supra, page 273).

[0087] The disclosed methods can be used to diagnose and treat a psychotic disorder. Currently available objective tests can be used to determine whether an individual is psychotic and to measure and assess the success of a particular treatment schedule or reg teasuring changes in cognitive ability aids in the diagnosis and treatment assessment of the psychotic patient. One example is the “Wallach Test,” which assesses recognition memory (see below, Wallach, J. Gerontol. 35:371-375, 1980). Another example of an objective text that can be used to determine whether an individual is psychotic and to measure efficacy of an anti-psychotic treatment is the Stroop Color and Word Test (“Stroop Test”) (see Golden, C. J., Cat. No.

[0088] 30150M, in A Manual for Clinical and Experimental Uses, Stoelting, Wood Dale, Ill.). The Stroop Test is an objective neuropsychiatric test that can differentiate between individuals with psychosis and those without.

[0089] Sample (or biological sample): A biological specimen containing cells, genomic DNA, RNA, or protein, or combinations thereof, obtained from a subject. Examples include, but are not limited to, peripheral blood, plasma, sputum, tissue, cells, urine, saliva, tissue biopsy, fine needle aspirate (such as a lymph node aspirate), surgical specimen, and autopsy material. In one example, the sample is a blood sample or fraction thereof, such as one that includes lymphocytes.

[0090] Subject: Living multi-cellular vertebrate organisms, a category that includes human and nonhuman mammals, such as non-human primates, cows, dogs, cats, rodents, horses, and the like. In a particular example, the subject is a human. In a particular example the subject is a dog. In a particular example the subject is a cat. In an additional example, a subject is selected due to being suspected of having a mood or psychotic disorder. In another example, a subject has been diagnosed with a mood or psychotic disorder, and confirmation is desired. In another example, a subject is being treated for a mood or psychotic disorder, such as with a pharmaceutical compound.

[0091] Schizophrenia: A mental illness characterized by psychotic symptoms, hallucinations, delusions, thought disorders, and / or movement disorders. Schizophrenia can impair a subject’s ability to function in various domains of life, such as work, education, relationships, and health. The causes of schizophrenia are not fully understood, but may involve genetic, environmental, and neurobiologic al factors. Schizophrenia is usually diagnosed in late adolescence or early adulthood and can be treated with medication and psychosocial interventions.

[0092] The disclosed methods can be used to diagnose and treat schizophrenia. Currently available objective tests can be used to determine whether an individual has schizophrenia and to measure and assess the success of a particular treatment schedule or regimen include the Structured Clinical Interview for DSM- IV (SCID), which assess diagnostic criteria against the DSM-IV (see Spitzer Arch Gen Psychiatry (1992) 49:624-29)and the Schedule for Affective Disorders and Schizophrenia (SADS), which assesses diagnostic criteria against the Research Diagnostic Criteria (RDC) (Endicott & Spitzer, Arch Gen Psychiatry (1978) 35:837-44).

[0093] Serotonin Transporter (SERT): A monoamine transporter protein that can transport serotonin from the synaptic cleft back into the neuron. SERT is encoded by the SLC6A4 gene. SERT is expressed by neurons, platelets, lymphocytes, mast cells, and monocytes. The function of SERT on lymphocytes is not well defined. SERT is also known as sodium-dependent serotonin transporter, solute carrier family 6 member 4, SLC6A4, 5-HTT, 5HTT, HTT, OCD1, SERT1, hSERT, and 5-HTTLPR. OMIM: 182138. NCBI Gene IDs: 6532 (human); 15567 (Mus musculus) 100517307 (Sus scofa).

[0094] 5HT2A Receptor: A subtype of the 5-HT2 receptor, which is a serotonin receptor and G-protein coupled receptor. Typically an excitatory receptor for serotonin, though its function is context dependent, and can be inhibitory. Encoded by HTR2A. Also known as 5-HT2A, HTR2, and 5 -hydroxy tryptamine receptor 2A. OMIM: 182135. NCBI Gene IDs: 3356 (Human) 15558 (Mus musculus), 397432 (Sus scrofa).

[0095] IV. Overview

[0096] Although there are individual differences in the time to manually analyze lymphocytes, the present methods reduce the total duration of manual involvement by aboutl / 25th-l / 50thof that with an entirely manual process. This automated technique analyzes each image in approximately 20-22 seconds (and researchers do not need to be present). Aside of the time to select a folder of images to analyze and to select a folder for results, each individual lymphocyte can be visually validated in about 1-2 seconds. Each image removed may add an additional 15-20 seconds to the manual labor, involving a quick search in the associated file using the image data label (such as a .csv file), which can take the format [Study Label] - [Subject ID]-[image magnification] -[image number]. Although this duration is miniscule, reducing the number of manual removals is important in the context of improving researcher efficiency and in terms of reducing user-input, which could lead to differences between researchers if a sufficient number are arbitrarily removed from analysis. Data shows imaging techniques were able to be altered to reduce the number of non-lymphocytes requiring manual removal through multi-channel imaging which included the SERT clustering (Red Channel) and Hoestch staining (Blue Channel) and adjusting the method in which the program detects lymphocytes, as shown in FIG. 5D. The data indicates the disclosed imaging method altered the number of non-lymphocytes detected and rejected, percentage of images without a detectable lymphocyte, and total number of lymphocytes detected across 500 images. Despite these subtle differences, results shown in FIGs. 3A-3C and FIGs. 4A-4D demonstrate the automated method is an effective method for accurately scoring SERT clustering irrespective of collection method.

[0097] The time demand for manual scoring limits additional scoring for validating past results and limited the sample sizes available for assessing inter-rater reliability. Additionally, the method of sequentially reducing thresholds can result in non-lymphocytes being picked up by the program and treated as a lymphocyte. This occurs when the size and circularity of the recognized object is within the criterions applied to isolate lymphocytes and tended to occur frequently in the sample fixed before freezing, as seen in FIG. 5D. Although most of these non-lymphocyte images result in cluster counts outside the acceptable range, and therefore were not included in the image data file or statistical analyses, it is possible that non- lymphocytes are introduced into the analysis, therefore this method can include manual scanning. Conveniently, the follow-up manual scan is extremely brief relative to the traditional manual method as the binary outputs of SERT clustering from background images appears uncharacteristic to the orientation of clusters produced when analyzing lymphocytes and can be very quickly identified. Furthermore, the number of lymphocytes requiring manual removal were further reduced by relying on the blue channel, which identified Hoestch staining, for identification of ROIs representing lymphocytes (as seen in FIGs. 2A-2C). Conversely, it is possible some lymphocytes are being missed by the program, potentially when adjacent lymphocytes are directly adjacent and the thresholding results in a singular non-circular shape. The impact of these few missed lymphocytes is likely minimal, given the cause for being unrecognizable by the program is unrelated to the clustering sizes relevant to analysis. Overall, the data indicates the automated method improved lymphocyte selectivity in an unbiased manner through maintaining rigid morphological criterion for acceptance of lymphocytes into analysis.

[0098] The development of this automated technique vastly reduces the human hours to analyze lymphocyte MPC. Lymphocytes have receptors for a variety of brain and disease relevant molecules and it is sensible that combining assessments of multiple proteins will improve prediction reliability or specificity of this technique as a putative biomarker, as previous work evaluating protein clustering in rats exposed to chronic stress found changes to not only SERT clustering, but also to clustering of the dopamine transporter protein, the 02 adrenergic receptor, NMDA receptor 2B, pannexin-1 and prion cellular protein (Romay- Tallon, Front Pharmacol, 9:1149, 2018). Thus, in addition to or as an alternative to SERT, these markers can be analyzed with the disclosed methods. This automated analysis, which can be applied to numerous proteins expressed on lymphocytes, can be used to expand protein clustering biomarker research.

[0099] Imaging programs can permit manual measurements of cluster size and cluster count using a nucleator function. Dorph-Petersen, J Microsc. (1999) 195:79. An optical fractionator workflow can be used to produce an estimate of cluster counts per region (i.e. a lymphocyte) using this technique. However, this approach is limited because using the nucleator approach each individual cluster must be measured, so a random subset are typically selected for measurement and inferences are drawn rather than looking at all available clusters. Further, counts are manually counted using the optical fractionator workflow.

[0100] In conclusion, these results support the use of a semi-automated quantification method for quickly and accurately quantifying SERT clustering across large sets of images. This approach has at least two advantages over the manual approach: (1) consistency in which results are produced, as regardless of which individual runs the program, results are perfectly equal and (2) the automated approach reduces the time spent to obtain quantified results, requiring far less human interaction than manual scoring, which improves the throughput of SERT, and can be used to expand the method to identify additional neuropsychiatric disease. The results demonstrates from a conceptual standpoint that automation of the SERT clustering is a valid approach.

[0101] Disclosed herein is a method of treating a mood or psychotic disorder, including obtaining membrane protein cluster count and membrane protein cluster size from a subject using a lymphocyte sample. In some examples, the membrane protein includes one or more of SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc. In some examples, the method includes comparing the membrane protein cluster count to a membrane protein cluster count control and / or comparing the membrane protein cluster size to a membrane protein cluster size control. In some examples, the method includes identifying the subject as having a schizophrenia phenotype based on the results of the comparing, identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, identifying the subject as having a depression phenotype based on the results of the comparing, identifying the subject as having a D-I phenotype based on the results of the comparing, and / or identifying the subject as having a D-II phenotype based on the results of the comparing. In some examples, the method includes administering an agent, thereby treating the subject. In some examples, the method includes administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, administering a depression medicament to the subject identified as having the depression phenotype, administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, and / or administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0102] In some examples, the obtaining the membrane protein cluster count and / or membrane protein cluster size includes measuring membrane protein cluster count and membrane protein cluster size. In some examples the measuring the membrane protein cluster count and / or the membrane protein cluster size includes labeling the membrane protein in the lymphocyte sample with a detectable label. In some examples, the measuring membrane protein cluster count and / or the membrane protein cluster size includes labeling the membrane protein in the lymphocyte sample with an antibody and / or an antigen binding fragment conjugated to the detectable label. In some example the detectable label includes a fluorescent label, biotin, a radiolabel, an enzyme, a luminescent label, and / or a colorimetric label. In some examples, the measuring the membrane protein cluster count and / or the membrane protein cluster size includes performing immunocytochemistry, immunohistochemistry, and / or immuno-electron microscopy. In some examples, the obtaining the membrane protein cluster count and / or membrane protein cluster size includes receiving a magnified image of the lymphocyte sample and / or taking the magnified image of the lymphocyte sample. In some examples, the lymphocyte sample includes a whole blood sample, a blood smear, and / or a purified lymphocyte sample. In some examples, the lymphocyte sample includes a fixed lymphocyte sample. In some examples, the lymphocyte sample was previously frozen, optionally at -80°C. In some examples the method further includes isolating the lymphocyte sample from the subject. In some examples, the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte sample was isolated from the subject.

[0103] In some examples, the identifying the subject includes identifying the subject as having the schizophrenia phenotype based on the results of the comparing. In some examples, the identifying the subject includes identifying the subject as having the bipolar disorder phenotype based on the results of the comparing. In some examples, the administering includes administering the schizophrenia medicament to the subject identified as having the schizophrenia phenotype. In some examples the administering includes administering the bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype. In some examples, the identifying includes identifying the subject as having schizophrenia and / or bipolar disorder and further identifying the subject as having the depression phenotype based on the results of the comparing. In some examples, the identifying includes identifying the subject as having schizophrenia and / or bipolar disorder and further identifying the subject as having the D-I phenotype based on the results of the comparing. In some examples, the identifying includes identifying the subject as having schizophrenia and / or bipolar disorder and further identifying the subject as having the D-II phenotype based on the results of the comparing. In some examples, the administering includes administering a schizophrenia medicament and / or a bipolar disorder medicament and further administering the depression medicament to the subject identified as having the depression phenotype. In some examples, the administering includes administering a schizophrenia medicament and / or a bipolar disorder medicament and further administering the D-I phenotype medicament to the subject identified as having the D-I phenotype. In some examples, the administering includes administering a schizophrenia medicament and / or a bipolar disorder medicament and further administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0104] In some examples, the subject is suspected of having a mood or psychotic disorder. In some examples, the subject is suspected of having depression, schizophrenia, or bipolar disorder. In some examples, the membrane protein cluster count control and the membrane protein cluster size control include healthy controls. In some examples, the method includes identifying the subject as having the schizophrenia phenotype when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and / or when the membrane protein cluster size is elevated compared to the membrane protein cluster size control. In some examples, the method includes identifying the subject as having bipolar disorder when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and / or when the membrane protein cluster size is substantially similar to the membrane protein cluster size control. In some examples the method includes identifying the subject as having depression when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and / or when the membrane protein cluster size is slightly elevated or elevated compared to the membrane protein cluster size control. In some examples the method includes identifying the subject as having the D-I phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and / or when the membrane protein cluster size is slightly elevated compared to the membrane protein cluster size control. In some examples, the method includes identifying the subject as having the D-II phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and / or when the membrane protein cluster size is elevated compared to the membrane protein cluster size control. In some examples, the membrane protein includes SERT. In some examples, the method includes identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is greater than 60 and / or when (ii) the membrane protein cluster size is greater than or equal to 0.18pm2. In some examples the method includes identifying the subject as having bipolar disorder when (i) the membrane protein cluster count is greater than 60 and / or when (ii) the membrane protein cluster size is less than 0.18pm2. In some examples the method includes identifying the subject as having depression when (i) the membrane protein cluster count is less than or equal to 60. In some examples the method includes identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is less than or equal to 60 and / or when (ii) the membrane protein cluster size is less than 0.18pm2. In some examples the method includes identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is less than or equal to 60 and / or when (ii) the membrane protein cluster size is greater than or equal to 0.18pm2.

[0105] In some examples, the schizophrenia medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples the bipolar disorder medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples, the D-I phenotype medicament includes a tricyclic. In some examples the depression medicament includes a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, and / or a neurosteroid.

[0106] Further disclosed herein is a method of treating depression including obtaining membrane protein cluster count and / or membrane protein cluster size from a subject using a lymphocyte sample, where the membrane protein includes serotonin transporter (SERT). In some examples, the method includes comparing the membrane protein cluster count to a membrane protein cluster count control and / or comparing the membrane protein cluster size to a membrane protein cluster size control and identifying the subject as having a D-I phenotype based on the results of the comparing. In some examples, the method includes administering a tricyclic agent to the subject identified as having the D-I phenotype.

[0107] Also disclosed herein is a method of treating a mood or psychotic disorder including obtaining lymphocyte(s) from a subject, culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, thereby generating medicament cultured lymphocyte(s), measuring membrane protein cluster count and membrane protein cluster size from the medicament cultured lymphocyte(s), where the membrane protein includes SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc. In some examples, the method includes comparing the membrane protein cluster count and membrane protein cluster size to a control. In some examples, the method includes identifying the subject as having a schizophrenia phenotype based on the results of the comparing. In some examples, the method includes identifying the subject as having a bipolar disorder phenotype based on the results of the comparing. In some examples, the method includes identifying the subject as having a depression phenotype based on the results of the comparing. In some examples, the method includes identifying the subject as having a D-I phenotype based on the results of the comparing. In some examples, the method includes identifying the subject as having a D-II phenotype based on the results of the comparing. In some examples the method includes administering the schizophrenia medicament to the subject identified as having the schizophrenia. In some examples, the method includes administering the bipolar disorder medicament to the subject identified as having bipolar disorder. In some examples, the method includes administering the depression medicament to the subject identified as having depression. In some examples, the method includes administering the D-I phenotype medicament to the subject identified as having the D-I phenotype. In some examples, the method includes administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0108] In some examples, the method further includes measuring a pre-culture membrane protein cluster count and pre-culture membrane protein cluster size from the lymphocytes. In some examples, the control includes the pre-culture membrane protein cluster count and the pre-culture membrane protein cluster size. In some examples, the method includes identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and / or when (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size.

[0109] In some examples, the method includes identifying the subject as having the bipolar disorder phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and / or when (ii) the membrane protein cluster size is substantially similar relative to the pre-culture membrane protein cluster size. In some examples, the method includes identifying the subject as having the depression phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and / or when (ii) the membrane protein cluster size is decreased or slightly decreased relative to the pre-culture membrane protein cluster size. In some examples, the method includes identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and / or when (ii) the membrane protein cluster size is slightly decreased relative to the pre-culture membrane protein cluster size. In some examples, the method includes identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is substantially similar relative to the preculture membrane protein cluster count and / or when (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size.

[0110] In some examples the control includes a historical control. In some examples, the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte(s) were isolated from the subject. In some examples, the schizophrenia medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples, the bipolar disorder medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples, the D-I phenotype medicament includes a tricyclic. In some examples, the depression medicament includes a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMDAR antagonist, and / or a neurosteroid.

[0111] Also disclosed herein is a method, including, with a computer, in an image of a sample from a subject, identifying a region depicting a lymphocyte, determining values of two or more parameters of the set of identified patterns, and / or identifying the subject based on the values of the parameters, wherein the identifying classifies the subject as at least one of: schizophrenia phenotype, bipolar phenotype, depression phenotype, D-I phenotype, or D-II phenotype. In some examples, the method further includes administering a schizophrenia medicament to the schizophrenia phenotype subject, administering a bipolar medicament to the bipolar phenotype subject, administering a depression medicament to the depression subject, administering a D-I medicament to the D-I phenotype subject, or administering a D-II medicament to the D- II phenotype subject. In some examples, identifying a phenotype of the subject based on the values of the parameters, wherein the identifying distinguishes a depression phenotype from one or more other mental health phenotypes. In some examples, the one or more other mental health phenotypes include one or more of: a schizophrenia phenotype, a bipolar phenotype, a D-I phenotype, or a D-II phenotype.

[0112] In some examples, the method includes identifying a region, and this includes setting parameters for size, opacity, and / or shape, and / or calling a graphics library function with the set parameters to identify the region, where the identified region matches the set parameters. In a particular example, parameters for size and shape are set. In some examples, the set parameter for size is in a range 100-350 pm, the set parameter for opacity is in a range 0.8-1.0, the set parameter for shape identifies circularity in a range 0.32-1.0; and / or the set parameter for shape identifies roundness in a range 0.75-1.0. In some examples, the called graphics library function repeats (a), (b), and / or (c) until the set parameters are matched, (a) scanning the image until an edge of an object is found, (b) determining an outline of the object, (c) checking whether the object matches the set parameters. In some examples, the method returns the object matching the set parameters to identify the region.

[0113] In some examples, the method includes determining the outline, which includes determining a target pixel attribute intermediate between a first pixel attribute representative of an interior of the object and / or a second pixel attribute representative of the image outside the object. In some examples, the method includes starting from a first pixel on the edge of the object, following successive neighboring pixels having respective pixel attributes within a predetermined tolerance of the target pixel attribute, until returning to the first pixel. In some examples, the method includes determining the outline based on the first pixel and the successive neighboring pixels.

[0114] In some examples, the image includes multiple channels. In some examples, the graphics library function is called on a subset of the multiple channels. In some examples, the method further includes nulling pixels of the image in a most recently identified region and / or identifying another region depicting another lymphocyte. In some examples, these steps are performed successively. In some examples, the method includes progressively increasing an image intensity threshold over the successive nulling and identifying actions, until a limiting value of the image intensity threshold is reached and / or until no further regions depicting lymphocytes are found. In some examples, the method includes calling a second graphics library function to increase circularity of the region, nulling pixels of the image outside the identified region, converting pixels within the image to binary values, despeckling the image inside the identified region, and / or delineating fused objects within the region. In some examples, these steps can be performed subsequent to the identifying a region and / or prior to the identifying patterns. In some examples, the increasing circularity, nulling pixels, converting pixels, despeckling, and delineating actions are performed in that order.

[0115] In some examples, the method includes identifying patterns, which includes setting pattern parameter(s) for at least size and / or calling a third graphics library function with the set pattern parameter(s) to identify the patterns matching the set pattern parameters. In some examples, the set pattern parameter for size is at least 0.05 pm. In some examples, the called third graphics library function repeats (d), (e), and / or (f) until the set pattern parameters are matched, (d) scanning the image until an edge of a pattern candidate is found, (e) determining an outline of the pattern candidate, (f) checking whether the pattern candidate matches the set pattern parameter(s). In some examples, the method returns the pattern candidate matching the set pattern parameter(s) to identify a given pattern of the patterns.

[0116] In some examples, the method includes nulling pixels of the image in a most recently identified pattern and / or identifying another pattern of the patterns. In some examples, these steps are performed successively. In some examples, the protein clusters include one or more of SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc. In some examples, the protein clusters include SERT. In some examples, the parameters include two or more of a cardinality of the set of identified patterns, an average of respective diameters of the identified patterns, a width of a distribution of the diameters of the identified patterns, and / or a diameter corresponding to a percentile range of the distribution of the diameters of the identified patterns. In some examples, the method includes measuring a diameter of the respective identified pattern, such as for each of the identified patterns. In some examples, the identifying the subject or the phenotype of the subject includes: comparing one or more of the determined values with respective threshold(s), comparing one or more of the determined values with representative values for respective phenotypes; and / or inputting the determined values to a trained machine learning classifier and obtaining the identification as output from the trained machine learning classifier. In some examples, the method further includes establishing a geometric scale of the image, such as prior to the identifying the region. In some examples, the subject is undiagnosed and the method is applied for screening. In some examples, the subject has been diagnosed according to a given mental health phenotype, and the method is performed to guide future treatment and / or evaluate past treatment.

[0117] Further disclosed herein is one or more computer-readable media storing instructions which, when executed by one or more hardware processors, cause the hardware processors to perform computer- implemented actions, such as the methods disclosed herein. Also disclosed herein is a system including one or more hardware processors with memory coupled thereto and / or one or more computer-readable media storing instructions which, when executed by one or more hardware processors, cause the hardware processors to perform the computer-implemented actions, such as the methods disclosed herein.

[0118] V. Lymphocyte Collection and Purification

[0119] Lymphocytes can be obtained from a subject by any exemplary sampling method, such as blood sampling, lymph sampling, lymph node biopsy, bone marrow aspiration and / or biopsy, lumbar puncture, non-lymphoid tissue sampling, urine sampling, salivary sampling, fecal sampling, or sampling of any other exemplary bodily fluid or product. A sample can be obtained from any exemplary subject, such as a vertebrate, or a mammal, such as a human. In some specific examples, the sample is obtained from a mouse, pig, dog, or cat.

[0120] Blood can be obtained from the subject by any exemplary method, such as collection by a medical professional (for example a nurse or a veterinarian). In further examples, the blood is collected by the subject, such as via a finger prick. In further examples, the blood is collected by the guardian of the subject, such as by legal guardian of a human, or the owner of an animal, such as a pig, dog, or cat. Blood can be collected by any exemplary method, such as arterial sampling, venipuncture, or fingerstick sample.

[0121] Exemplary Methods of Whole Blood Lymphocyte Isolation

[0122] Blood can drawn by a trained medical professional with the use of a 10 ml glass tube containing 1.5 ml ADC solution (tri-sodium citrate (22 g / 1), citric acid (8 g / 1), and dextrose (24.5 g / 1)). The sample is then diluted 1: 1 in phosphate buffered saline (PBS) prior to lymphocyte isolation by centrifugation at 20°C in a gradient of Ficoll-Paque Plus (Cytiva # 17144003) at 400 g for 30^10 min. The band containing the lymphocytes is extracted and rinsed with PBS. Subsequently, cells are centrifuged at 1000 g for 10 min. This step is repeated three times. Cells can then be fixed by any exemplary method, such as fixation with 1% paraformaldehyde solution in 0.1 M phosphate buffer for 1 min. Fixed lymphocytes can be stored at 4°C. If longer term storage is desired, cells may be stored at -80°C in a cryoprotectant solution (Dimethylsulfoxide 10%; Fetal bovine serum 10% and RMPi-1640).

[0123] To obtain peripheral lymphocytes from a non-human vertebrate, blood can be drawn directly from a vein. In some examples, blood might be drawn by heart puncture (up to 3 ml in total, when animals were sacrificed for other research purposes) or directly from the tail vein (up to 1 ml). Blood might also be collected from a facial vein, or from a paw prick. Blood can be collected in a collection container, such as a 5 ml Eppendorf tube containing blood and ADC solution in a 1:7 proportion. Centrifugation of samples, extraction and fixation of lymphocytes was carried out as explained for humans. Exemplary Methods of Blood Smear Isolation

[0124] Blood can be collected via blood smear. In some examples, this permits home blood collection, as opposed to blood collection by a medical professional. Medical professionals can also collect blood by blood smear. A human blood smear can be collected via a prick on the tip of the forefinger, or any other exemplary location. In a nonhuman subject, a blood smear can be collected by a prick of an area, such as the tail vein, or paw. Optionally, a small volume of blood can be collected from the prick, and be provided to a trained professional to perform the smear. In another example, the smear is performed immediately. A thin smear can be spread on microscope slides, such as Super-Frost Plus slides (Fisher Scientific # 12-550- 15), and dried. The sample can be dried at such as at room temperature, -80°, -20°, 4°, 12°, and 20°C, for at least 10 minutes, at least 20 minutes, at least 30 minutes, or at least an hour. After being dried the sample can be stored under a variety of conditions, such as 4°, -20°, or -80°C until used.

[0125] VI. Imaging Biomarker MPC

[0126] Exemplary Methods of Associating Detectable Labels with Proteins of Interest

[0127] Various fixation conditions can be used to prepare for association of a detectable label with a protein of interest. For example, formalin 10% incubated for a minute, methanol incubated for 2 min, precooled acetone incubated at -20C for 10 min and at 4C for 2. In a particular example, blood smears may be fixed with 0.5 ml of 1% PFA for 5 min at room temperature. Fixation may be performed on dry slides or wet slides. The slides can optionally be washed and dried, and optionally stored at -80 °C. In another example, fixation can be performed at room temperature, and allowed to dry.

[0128] Immunocytochemistry or immunolabeling can be directly performed on a sample, such as a sample of isolated lymphocytes, a whole blood sample, or a blood smear sample. In some examples the lymphocyte is a peripheral blood lymphocyte. A blood smear may include whole blood sample, which can contain red blood cells, platelets and white blood cells.

[0129] In preparation for immunolabeling, a sample from storage can be re-suspended in PBS and brought to room temperature, followed by centrifugation at 100 g for 10 min. In some cases the use of a smear or whole blood results in more unspecific background with the immunolabelling. Preincubation with human IgG or rat IgG diluted in BSA and PBS can reduce unspecific background. Preincubation can be for an exemplary period of time, such as 15 minutes, 30 minutes, 45 minutes, or 1, 2, 3, 4, 5 or 6 or more hours. Preincubation can be under exemplary conditions such as, such as 4°, 20°, or 37°C. In one example, preincubation is 1 hour at room temperature. In one example, 10% human IgG is used, diluted in 1% BSA. In another example, 3% human IgG is used. In another example, 3% rat IgG is used. Exemplary concentrations of rat or human IgG that can be used include 0.5%, 1.0%, 1.5%, 2.0%, 2.5%, 3.0%, 3.5%, 4.0%, 4.5%, 5.0%, 5.5%, 6.0%, 6.5%, 7.0%, 7.5%, 8.0%, 8.5%, 9.0%, 9.5%, 10.0%, 10.5%, 11.0%, 12%, 13%, 14% or 15% IgG. These reagents are commercially available, such as from Sigma (#12511, #14131, #3059-100Gr).

[0130] To accomplish immunocytochemistry, samples can be incubated for periods of time, such as 15 minutes, 30 minutes, 45 minutes or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or up to 24 hours with primary antibody (e.g., anti-SERT). The incubation can occur exemplary temperatures, such as 4°, 20°, or 37°C. In one example, the primary antibody is incubated overnight at 4°C. On exemplary primary antibody is rabbit polyclonal antibody which recognizes both human and rat SERT (commercially available from Millipore #AB10514P). The primary antibody can be incubated at dilutions such as 1: 10, 1:20, 1:30, 1:40, 1:50, 1:60, 1:70, 1:80, 1:90, 1: 100, 1: 150, 1:200, 1:250, 1:300, 1:400, 1:500, 1:600, 1:700, 1:800, 1:900, or 1:1000. In a specific example, the primary antibody is incubated at 1:250. The primary antibody can be diluted using 1% BSA in PBS.

[0131] Following incubation a sample may be rinsed with PBS, such as for 10 min 3 times. In some examples, the primary antibody is itself conjugated to a detectable label, such as a fluorescent label, biotin, a radiolabel, an enzyme, a luminescent label, and / or a colorimetric label. Under such conditions, it may be possible to deposit the sample on a slide in preparation for image acquisition at this point. The sample may be incubated to attach a detectable label to the primary antibody. For example, the sample can be incubated with a secondary antibody conjugated to a fluorescent label, biotin, a radiolabel, an enzyme, a luminescent label, and / or a colorimetric label. In one example, the secondary antibody is a fluorescent secondary, such as Alexa Fluor 568, goat anti rabbit (Molecular Probes A- 11008). The secondary antibody can be incubated for periods of time such as 15 minutes, 30 minutes, 45 minutes or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or up to 24 hours) with primary antibody. The incubation can occur at temperatures, such as 4°, 20°, or 37°C. In one example, the secondary antibody is incubated 2 hours at room temperature. Following incubation, samples can be rinsed with PBS, such as by centrifuging 3 times, 10 min each, at 100 g). Optionally, this step, or any step involving a fluorescent probe, can be performed in the dark.

[0132] Optionally, to facilitate the identification of the lymphocytes, a nuclear marker can be applied, such as Hoechst 33258 (Invitrogen #H3569). This can be applied at concentrations, for a period of time, such as 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, or 5.0pg / ml, 5, 10, 15, 20, 25, 30 minutes, or longer, and 37°, 20°, or 4°C. In one example Hoechst is applied at, 2 pg / ml for 15 min at room temperature. After nuclear labeling, samples can be rinsed with PBS, such as by centrifuging 3 times, 10 min each, at 100 g) and resuspended in PBS, such as 100-200 pl of PBS. A volume of the resulting sample can be deposited on slides for image acquisition, such as 20 pl, coverslipped, and optionally stored at -20 °C. Exemplary slides include SuperFrost Plus slides from Menzel-Glaser.

[0133] The methods of labeling with a detectable marker can depend on the biomarker to be detected on the cell surface. Exemplary antibodies for detection of 5HT2A include polyclonal antibodies (Alomone Labs Cat. # ASR-033-200UL). Exemplary antibodies for detection of DAT include clone CL3123 (Sigma- Aldrich Cat. # AMAB91125). Exemplary antibodies for detection of Beta2AR include polyclonal antibodies (Sigma-Aldrich Cat. # SAB4500576 (human Beta2AR); Sigma- Aldrich Cat. # SAB 1306036 (rat Beta2AR)). Exemplary antibodies for detection of NR2B include clone N59 / 20 (Antibodieslnc Cat. # 75- 097). Exemplary antibodies for detection of PNX1 include clone 11HCLC (Invitrogen Cat. # 710184). Exemplary antibodies for detection of PrPc include clone DRM2-118 (Sigma-Aldrich Cat. # MABN768).

[0134] In some examples, the methods disclosed herein include measuring MPC cluster count for one or more of SERT, 5HT2A, DAT, Beta2AR, NR2B, PNX1 and / or PrPc. In some examples the methods disclosed herein include measuring a specific combination of SERT, 5HT2A, DAT, Beta2AR, NR2B, PNX1 and / or PrPc, such as SERT and 5HT2A.

[0135] Exemplary Methods of Image Acquisition

[0136] Images can be obtained with an Zeiss Imager.M2 epifluorescence microscope at 63X or 100X magnification. A 385 nm LED-module through a 96 HE reflector (excites at 390 / 40 and collects emissions at 450 / 40) can be used for the blue channel. The DsRed filter involving a 567 nm LED-module and a 43 HE reflector (excites at 550 / 25 and collects emissions at 605 / 70) can be used for the red channel. In some examples images are taken in monochrome. In some examples, a first monochrome images is taken in a first channel, and a second monochrome image is taken in a second channel, and so on. In some examples, images are taken in color. In some examples, a portion of the light spectrum is excluded from a color image. Channels can be capture in sequence and overlayed together using a multichannel imaging technique such that each channel is combined into a single image within Stereoinvestigator such that each channel can be removed from the original in ImageJ without affecting the opposing channel. In some examples, it is possible to analyze MPC manually with a nucleator function (such as is available within Stereoinvestigator and other programs). With this method, the size of each individual cluster can be determined by placing a dot in the center of the cluster and drawing lines to 3 edges of the cluster. This can be repeated for at least 10, at least 50, at least 100, at least 200, at least 300, at least 400, at least 500, or at least 1000 clusters.

[0137] Images can be acquired by any exemplary methods such as immunocytochemistry or immunohistochemistry. Methods of immunocytochemistry and immunohistochemistry are described in Renshaw, Simon (2017). Immunohistochemistry and Immunocytochemistry : Essential Methods, Second Edition. John Wiley & Sons, Ltd. Exemplary magnifications used for image magnification can include lOx, 20x, 30x, 40x, 50x, 60x, 63x, 70x, 80x, 90x, lOOx, HOx, 120x, 130x, 140x, 150x, 160x, 170x, 180x, 190x, 200x, 300x, 400x, 500x, 600x, 700x, 800x, 900x, lOOOx, 2000x, 3000x, 4000x, 5000x, 6000x, 7000x, 8000x, 9000x, or lOOOOx.

[0138] Any number of lymphocyte images can be acquired for further analysis. In some examples, a single lymphocyte is imaged. In some examples, at leastlO, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000 or more lymphocytes are imaged. In some examples, no more than 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 lymphocytes are imaged. In some examples, multiple lymphocytes are captured in a single image. In some examples, each image includes a single lymphocyte.

[0139] In some examples, the methods include single channel imaging of the blue or red channels. In some examples, the imaging methods included multi-channel imaging of blue and red channels. In some examples, the blue channel is about (460 nm). In some examples, the red channel is about (567 nm). In some examples, the methods include measuring blue and / or red fluorescence. Blue fluorescence can include wavelengths of about 380nm to 500nm, or about 450nm to 495nm. Red fluorescence can include wavelengths of about 633nm to 647nm.

[0140] VII. Image Analysis

[0141] Exemplary Manual Methods of MPC Image Analysis

[0142] The methods below are described with respect to SERT (‘SERT cluster count’ or ‘SERT cluster size’), but the same methods can be used to measure MPC cluster count and cluster size of an exemplary biomarker, such as 5HT2A, DAT, Beta2AR, NR2B, PNX1 and / or PrPc. MPC can be analyzed on lymphocytes from blood smears derived from any subject, such as a human, or a rodent. In one example, images are obtained at lOOx magnification. In one example, images are obtained from 100 individual lymphocytes per sample using a fluorescence microscope. Images obtained can be analyzed using software, such as the ImageJ software. Other exemplary software includes Adobe Photoshop, Photopea, and Fiji. Image software, such as ImageJ, often performs the measurements in pixels, so the program can be calibrated to convert pixels to real values for metrics such as SERT cluster count or SERT cluster size. This process introduces a known distance to the program to establish equivalence in pixels to the distance given in pm. Then, background conditions can be adjusted in ImageJ to facilitate cluster analysis. In ImageJ this can be accomplished using menu Process Subtract background and in Rolling Ball Radius indicating the size of the smallest particle which is not background (for example approximately 5-10 for isolated lymphocytes, and 1-3 for smears). When working with blood smears, it can be helpful to remove small dots from the analysis that might interfere in the analysis resulting in overestimation of the number of clusters or an underestimation of the size. In ImageJ this can be accomplished using Remove Outliers: Radius 1 and Threshold 50. Following this step, a binary can be created where the clusters are easily quantified. However, if two clusters appear too close, this could mistakenly be interpreted as a single cluster, thus underestimating cluster count and overestimating size. In ImageJ this can be avoided using Process Binary Watershed. Next, the clusters will be measured and quantified. In ImageJ this is accomplished using Analyze -^Measure and Analyze Analyze Particles to obtain a number and measure of the clusters. It can be helpful to indicate the minimum particle size to be analyzed by these processes to avoid incorrect measurements. In ImageJ, 0.05-Infinite provides an accurate measure of the clusters. From the binary image, two sets of measurements can be derived: the number of SERT expressing clusters, the size of those clusters. The measurements from each lymphocyte in a sample can be averaged, and these average can be used to compare results between groups of interest. For example, results can be compared between a control patient, and a patient in need of diagnosis and treatment. In another example, the results can be compared between a sample of purified lymphocytes, and a sample blood smear.

[0143] Once a set of usable conditions are established, they can be kept constant to make results comparable across multiple treatment conditions, for example to compare a blood sample obtained from peripheral blood to a blood sample obtained from a smear.

[0144] Exemplary Automated Methods ofMPC Image Analysis: Exemplary Computing Systems

[0145] FIG. 13 depicts an example of a suitable computing system 1300 in which the described innovations can be implemented. For example, the computing system 1300 can be used in the diagnostic methods, treatments, and systems described herein. The computing system 1300 is not intended to suggest any limitation as to scope of use or functionality of the present disclosure, as the innovations can be implemented in diverse computing systems.

[0146] With reference to FIG. 14, the computing system 1300 includes one or more processing units 1310, 1315 and memory 1320, 1325. In FIG. 13, this basic configuration 1330 is included within a dashed line. The processing units 1310, 1315 execute computer-executable instructions, such as for implementing the features described in the examples herein. A processing unit can be a general-purpose central processing unit (CPU), processor in an application-specific integrated circuit (ASIC), or any other type of processor. In a multi-processing system, multiple processing units execute computer-executable instructions to increase processing power. For example, FIG. 13 shows a central processing unit 1310 as well as a graphics processing unit or co-processing unit 1315. The tangible memory 1320, 1325 can be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g., ROM, EEPROM, flash memory, etc.), or some combination of the two, accessible by the processing unit(s) 1310, 1315. The memory 1320, 1325 stores software 1380 implementing one or more innovations described herein, in the form of computer-executable instructions suitable for execution by the processing unit(s) 1310, 1315.

[0147] A computing system 1300 can have additional features. For example, the computing system 1300 includes storage 1340, one or more input devices 1350, one or more output devices 1360, and one or more communication connections 1370, including input devices, output devices, and communication connections for interacting with a user. An interconnection mechanism (not shown) such as a bus, controller, or network interconnects the components of the computing system 1300. Typically, operating system software (not shown) provides an operating environment for other software executing in the computing system 1300, and coordinates activities of the components of the cr'n™,tir,rr'riem 1300. The tangible storage 1340 can be removable or non-removable, and includes magnetic disks, magnetic tapes or cassettes, CD-ROMs, DVDs, or any other medium which can be used to store information in a non-transitory way and which can be accessed within the computing system 1300. The storage 1340 stores instructions for the software implementing one or more innovations described herein.

[0148] The input device(s) 1350 can be an input device such as a keyboard, mouse, pen, or trackball, a voice input device, a scanning device, touch device (e.g., touchpad, display, or the like) or another device that provides input to the computing system 1300. The output device(s) 1360 can be a display, printer, speaker, CD-writer, or another device that provides output from the computing system 1300.

[0149] The communication connection(s) 1370 enable communication over a communication medium to another computing entity. The communication medium conveys information such as computer-executable instructions, audio or video input or output, or other data in a modulated data signal. A modulated data signal is a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media can use an electrical, optical, RF, or other carrier.

[0150] The innovations can be described in the context of computer-executable instructions, such as those included in program modules, being executed in a computing system on a target real or virtual processor (e.g., which is ultimately executed on one or more hardware processors). Generally, program modules or components include routines, programs, libraries, objects, classes, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The functionality of the program modules can be combined or split between program modules as desired in various examples. Computerexecutable instructions for program modules can be executed within a local or distributed computing system.

[0151] For the sake of presentation, the detailed description uses terms like “determine” and “use” to describe computer operations in a computing system. These terms are high-level descriptions for operations performed by a computer, and where context indicates, they should not be confused with acts performed by a human being. The actual computer operations corresponding to these terms vary depending on implementation .

[0152] Exemplary Automated Methods ofMPC Image Analysis: Exemplary Computer-Readable Media

[0153] Any of the computer -readable media herein can be non-transitory (e.g., volatile memory such as DRAM or SRAM, nonvolatile memory such as magnetic storage, can be implemented by storing in one or more computer-readable media (e.g., computer-readable storage media or other tangible media). Any of the things (e.g., data created and used during implementation) described as stored can be stored in one or more computer-readable media (e.g., computer-readable storage media or other tangible media). Computer- readable media can be limited to implementations not consisting of a signal. Any of the methods described herein can be implemented by computer-executable instructions in (e.g., stored on, encoded on, or the like) one or more computer-readable media (e.g., computer-readable storage media or other tangible media) or one or more computer-readable storage devices (e.g., memory, magnetic storage, optical storage, or the like). Such instructions can cause a computing device to perform the method. The technologies described herein can be implemented in a variety of programming languages.

[0154] Exemplary Automated Methods ofMPC Image Analysis: Exemplary Implementations

[0155] Although the operations of some of the disclosed methods are described in a particular, sequential order for convenient presentation, such manner of description encompasses rearrangement, unless a particular ordering is required by specific language set forth herein. For example, operations described sequentially can in some cases be rearranged or performed concurrently.

[0156] In some examples, the method includes selecting a plurality locations in a file system, such as a first folder and a second folder. An image from the plurality of locations, such as the first folder, can be opened in using an image analysis program. In one example, the image analysis program is described herein, alternatively it can be a commercially available program such as ImageJ.

[0157] Disclosed herein is a method of treating a mood or psychotic disorder. In some examples, the method includes obtaining an image of a subject’s lymphocyte sample, or obtaining an image of a subject’s lymphocyte. In some examples, the image is provided to a computer, which performs the method. In some examples, the image is acquired by a camera associated with a computer, which performs the method. In some examples, the lymphocyte sample, or the lymphocyte was or is labeled with a fluorescent marker for a membrane protein, such as one or more of SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc.

[0158] In some examples, the method includes defining region(s) of interest (ROI)(s) in the image. In some examples, the regions of interest are defined by (a) conducing particle analysis to identify an object in the image of the blood sample which is the size of a lymphocyte and which is substantially circular and (b) reducing the maximum brightness threshold and reducing the minimum brightness threshold. In some examples, the steps (a) and (b) are iteratively performed until the maximum brightness threshold and minimum brightness threshold cannot be reduced. In some examples, the method includes measuring membrane protein cluster count and membrane protein cluster size, for example by using the ROIs. In some examples, the method includes comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control, such as a control value stored on computer-readable media. In some examples, the computer-readable media forms part of the computer which performs the methods disclosed herein. In some examples, the computer readable media is located remotely, and provides control values to the computer which performs the comparison. In some examples, the computer which performs methods disclosed herein, provides measurement values to a remote computer, whichnorf™-™ i h,> comparing. In some examples, the methods include identifying the subject as having a mood or psychotic disorder, or a phenotype associated with a mood or psychotic disorder. This may include identifying the subject as having schizophrenia or a schizophrenia phenotype based on the results of the comparing, identifying the subject as having bipolar disorder, or a bipolar disorder phenotype based on the results of the comparing, identifying the subject as having depression, or a depression phenotype based on the results of the comparing, identifying the subject as being a D-I subject, or as having a D-I phenotype based on the results of the comparing, or identifying the subject as being a D-II subject, or as having a D-II phenotype based on the results of the comparing. In further examples, the method includes prescribing, or administering a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, or a D-II phenotype medicament.

[0159] In some examples, the method includes defining the ROI(s) in the image of the subject lymphocyte sample by splicing the data corresponding to the ROI(s) out of the image of the subject lymphocyte sample to generate an iterated image of the lymphocyte, and continuing to iteratively define the ROI(s) using the iterated image of the lymphocyte sample. In some examples, the method includes conducing particle analysis, such as by identifying objects with size of 55- 195pm2, solidity of .8-100, circularity of .32-1.00, and / or round of 0.75-1.00. In some examples, the method includes performing clustering analysis to identify a ROI membrane protein cluster count and a ROI membrane protein cluster size for each defined ROI. In some examples, the performing clustering analysis to identify a ROI membrane protein cluster count and a ROI membrane protein cluster size for each defined ROI. In some examples, the method includes performing clustering analysis to identify an interim ROI membrane protein cluster count and / or an interim ROI membrane protein cluster size for a defined ROI. In some examples, the method includes, responsive to the interim ROI membrane protein cluster count being 30-115 counts, defining the ROI membrane protein cluster count as the value of interim ROI membrane protein cluster count and / or defining the ROI membrane protein cluster size as the value of the interim ROI membrane protein cluster size. In some examples, the method includes responsive to the interim ROI membrane protein cluster count being outside 30 -115 counts, iteratively performing steps until either the ROI membrane protein cluster count and the ROI membrane protein cluster size are defined, or until the steps have been performed a defined number of times, such as 15 times. In some examples, the steps to be iteratively performed include: responsive to the interim ROI membrane protein cluster count being greater than 115 counts applying alternative thresholding to the defined ROI and performing clustering analysis to identify the interim ROI membrane protein cluster count and the interim ROI membrane protein cluster size for the defined ROI; responsive to the interim ROI membrane protein cluster count being less than 30 counts applying alternative thresholding to the defined ROI and performing clustering analysis to identify the interim ROI membrane protein cluster count and the interim ROI membrane protein cluster size for the defined ROI; responsive to the interim ROI membrane protein cluster count being 30 -115 counts, defining the ROI membrane protein cluster count as the value of interim ROI membrane protein cluster count and defining the ROI membrane protein cluster size as the value of the interim ROI membrane protein cluster size. In some examples, these steps are performed alone as part of the method, and in some examples, they are performed in the listed order. In some examples, the measuring membrane protein cluster count and membrane protein cluster size includes aggregating the ROI membrane protein cluster count and / or the ROI membrane protein cluster size for each defined ROI to measuring the membrane protein cluster count and / or the membrane protein cluster size. In some examples, the measuring membrane protein cluster count and membrane protein cluster size includes averaging the ROI membrane protein cluster count and / or the ROI membrane protein cluster size for each defined ROI to measuring the membrane protein cluster count and the membrane protein cluster size. In some examples, the average is a weighted average, accounting for the difference in cluster count. In some examples, the lymphocyte sample, or the lymphocyte was labeled with a fluorescent marker for nuclei. In some examples, the particle analysis to identify an object in the image of the blood sample includes identifying an object labeled with the fluorescent marker for the nuclei.

[0160] Further contemplated herein is a method of diagnosing or treating a mood or psychotic disorder (1500). As shown in FIG. 15, In some examples, the method includes identifying a region depicting a lymphocyte, such as in an image of a sample from a subject (1502). In some examples, the method includes identifying patterns representing protein clusters within the region, the identified patterns may form a set (1504). In some examples, the method includes determining values of two or more parameters of the set of identified patterns (1506). In some examples, the method then identifies the subject based on the values of the parameters. In some cases, the subject is identified as schizophrenia phenotype, bipolar phenotype, depression phenotype, D-I phenotype, and / or D-II phenotype (1508). The method may further include administering a schizophrenia medicament to the schizophrenia phenotype subject, administering a bipolar medicament to the bipolar phenotype subject, administering a depression medicament to the depression subject, administering a D-I medicament to the D-I phenotype subject, or administering a D-II medicament to the D-II phenotype subject. In some examples, the identifying distinguishes a depression phenotype from one or more other mental health phenotypes.

[0161] As shown in FIG. 16, in some examples, the method includes identifying the region (1600), and this includes setting parameters for size, opacity, and / or shape (1602) and calling a graphics library function with the set parameters to identify the region (1604). In some examples, the region identified matches the set parameters. In some examples, the set parameter for size is in a range 100-350 pm. In some examples, the set parameter for opacity is in a range 0.8-1.0. In some examples the set parameter for shape identifies circularity in a range 0.32-1.0. In some examples the set parameter for shape identifies roundness in a range 0.75-1.0. In further examples, the graphics library function repeats one or more of the following until the set parameters are matched: scanning the image until an edge of an object is found (1612), determining an outline of the object (1616), and checking whether the object matches the set parameters (1620). In further examples, the graphics library function returns the object matching the set parameters to identify the region (1624). In some examples, determining the outline includes determining a target pixel attribute intermediate between a first pixel attribute representative of an interior of the object and a second pixel attribute representative of the image outside the object. In some examples, it also includes starting from a first pixel on the edge of the object, following successive neighboring pixels having respective pixel attributes within a predetermined tolerance of the target pixel attribute, until returning to the first pixel. In some examples, the determines the outline based on the first pixel and the successive neighboring pixels. In some examples the image includes multiple channels and the graphics library function is called on a subset of the multiple channels. In some examples, the method includes successively nulling pixels of the image in a most recently identified region and identifying another region depicting another lymphocyte. In some examples, the method includes progressively increasing an image intensity threshold over the successive nulling and identifying actions, until a limiting value of the image intensity threshold is reached or until no further regions depicting lymphocytes are found. In some examples, the method includes, subsequent to the identifying a region and prior to the identifying patterns, calling a second graphics library function to increase circularity of the region, nulling pixels of the image outside the identified region, converting pixels within the image to binary values, despeckling the image inside the identified region; and / or delineating fused objects within the region. In some examples, the increasing circularity, nulling pixels, converting pixels, despeckling, and delineating actions are performed in that order.

[0162] As shown in FIG. 17, in some examples, the identifying patterns representing protein clusters within the region (1700) includes setting pattern parameter(s) for at least size (1704). In some examples, the identifying patterns includes calling a graphics library function with the set pattern parameter(s) to identify the patterns matching the set pattern parameters (1708). In some examples, the set pattern parameter for size is at least 0.05 pm. In some examples, the graphics library function repeats one or more of the following steps until the set parameters are matched: scanning the image until an edge of a pattern candidate is found (1712), determining an outline of the pattern candidate (1716), and checking whether the pattern candidate matches the set pattern parameter (1720).

[0163] Further contemplated is a method of identifying a lymphocyte, or a region of interest depicting a lymphocyte (1800). As shown in FIG. 18, in some examples the methods include selecting a first file location. In some examples, the methods include creating a file list for all files in the first file location (1802). In some examples an image is selected from the first file location (1804). The image can be duplicated, and the channels split in the duplicate image (1808). In some examples the image is converted to binary, such as presented in black and white. In some examples, particle analysis performed on a first image channel after converting to binary (1812). In some examples, the method includes serially increasing minimum brightness thresholds. In some examples, the method includes generating additional duplicate images. In some examples, existing ROIs are nulled until a minimum threshold is reached (1816).

[0164] Also contemplated are methods of obtaining MPC number and / or size on an identified lymphocyte, or region of interest depicting a lymphocyte (1900). As shown in FIG. 19, in some examples, the method includes obtaining MPC number and / or size on an identified lymphocyte. In some examples, the method includes creating a duplicate ROI and splitting the channels (1902). In some examples, the method includes circularizing the ROI (1904). In some examples, background is removed with the rolling ball function (1908). In some examples, the image is converted to binary (1912). In some examples, outlier pixels beyond a radius of 2 are removed (1916). In some examples, despeckle and watershed are performed (1920). In some examples, particle analysis is performed to identify MPC count and MPC size (1924). In some examples, if the identified MPC count and / or MPC size are outside of accepted parameters, alternative maximum brightness settings are applied (1926). In some examples, the results of particle analysis are saved. In some examples, an image of at least one channel is saved (1928).

[0165] In some examples, the method returns the pattern candidate matching the set pattern parameter(s) to identify a given pattern of the patterns. In some examples the method includes nulling pixels of the image in a most recently identified pattern and identifying another pattern of the patterns. In some examples, these steps are performed successfully. In some examples, the protein clusters include SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1, and / or PrPc protein clusters. In some examples, the parameters include at least one, at least two, at least three, or all of: a cardinality of the set of identified patterns, an average of respective diameters of the identified patterns, a width of a distribution of the diameters of the identified patterns, and / or a diameter corresponding to a percentile range of the distribution of the diameters of the identified patterns. In some examples, the method further includes for each of the identified patterns measuring a diameter of the respective identified pattern. In some examples identifying the subject of the phenotype of the subject includes comparing one or more of the determined values with respective threshold(s), comparing one or more of the determined values with representative values for respective phenotypes, and / or inputting the determined values to a trained machine learning classifier and obtaining the identification as output from the trained machine learning classifier. In some examples, the method includes establishing a geometric scale of the image prior to identifying the region.

[0166] In some examples, the subject is undiagnosed and the method is applied for screening. In some examples, the subject has been diagnosed according to a given mental health phenotype, and the method is performed to guide future treatment; and / or evaluate past treatment. In some examples, the schizophrenia medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples, the schizophrenia medicament includes at least one agent disclosed as an exemplary medicament for treating schizophrenia herein. In some examples, the bipolar disorder medicament includes an antidepressant, an antipsychotic, and / or a mood stabilizer. In some examples, the bipolar disorder medicament includes at least one agent disclosed as an exemplary medicament for treating bipolar disorder herein. In some examples, the D-I phenotype medicament includes a tricyclic. In some examples, the D-I medicament includes at least one agent disclosed as an exemplary medicament for treating a D-I phenotype subject herein. In some examples, the D-II medicament includes at least one agent disclosed as an exemplary agent for treating a D-II subject herein. In some examples, the depression medicament includes a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, and / or a neurosteroid. In some examples, the depression medicament includes at least one agent disclosed as an exemplary medicament for treating depression herein. In some examples, the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the sample was isolated from the subject.

[0167] Further contemplated herein are one or more computer -readable media storing instructions which, when executed by one or more hardware processors, cause the hardware processors to perform the computer-implemented actions disclosed as methods above. Also disclosed herein is a system, including one or more hardware processors with memory coupled thereto and / or one or more computer-readable media storing instructions. In some examples, the computer-readable media storing instructions cause the hardware processors to perform the computer-implemented actions disclosed above.

[0168] VIII. Methods of Treating Mood or Psychotic Disorders

[0169] Methods for treating mood or psychotic disorders are disclosed herein. The method can include administering a therapeutically effective amount of one or more agents, such as one or more agents specific for a subject with depression, schizophrenia, bipolar disorder, D-I phenotype, or D-II phenotype. The methods can include identifying or selecting subjects having one of the preceding disorders or phenotypes, and administering the treatment to them.

[0170] Diagnostic Criteria

[0171] The number and / or size of MPCs on a cell’s surface, such as a lymphocytes surface can be used to identify and / or diagnose a subject as having a control phenotype, D-I phenotype, D-II phenotype, schizophrenia phenotype, and / or bipolar phenotype. In some examples, the membrane protein includes SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1 and / or PrPc. In a specific example, the membrane protein is SERT. In some examples, the subject is identified and / or diagnosed based on the membrane protein cluster count and / or the membrane protein cluster size.

[0172] In some examples, the method includes identifying or diagnosing the subject as having a control phenotype, D-I phenotype, D-II phenotype, schizophrenia phenotype, and / or bipolar phenotype by comparing the subject to a control, such as a historical control value, or such as a healthy control. In some examples, the method includes identifying the subject as having schizophrenia when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control. In some examples the method includes identifying the subject as having bipolar when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is substantially similar to the membrane protein cluster size control. In some examples the method includes identifying the subject as having depression when lh'’ ^mi->rt>neprotein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated or elevated compared to the membrane protein cluster size control. In some examples, the method includes identifying the subject as having the D-I phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated compared to the membrane protein cluster size control. In some examples, the method includes identifying the subject as having the D-II phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control.

[0173] In some examples, the method includes identifying or diagnosing the subject as having a D-I phenotype, D-II phenotype, schizophrenia phenotype, and / or bipolar phenotype by comparing the subject to MPC cluster count and / or MPC cluster size values, such as but not limited to SERT cluster count and / or SERT cluster size values. In some examples, the method includes identifying the subject as having schizophrenia when (i) the membrane protein cluster count is greater than 60 and less than or equal to 100 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2and less than or equal to 0.30pm2. In further examples, the method includes identifying the subject as having schizophrenia when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2. In some examples, the method includes identifying the subject as having bipolar disorder when (i) the membrane protein cluster count is greater than 60 and less than or equal to 100 and (ii) the membrane protein cluster size is greater than or equal to 0.1pm2and less than 0.18pm2. In further examples, the method includes identifying the subject as having bipolar disorder when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is less than 0.18pm2. In some examples, the method includes identifying the subject as having depression when (i) the membrane protein cluster count is greater than or equal to 30 and less than or equal to 60. In further examples, the method includes identifying the subject as having depression when (i) the membrane protein cluster count is less than or equal to 60. In some examples, the method includes identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is greater than or equal to 30 and less than or equal to 60 and (ii) the membrane protein cluster size is greater than or equal to 0.1pm2and less than 0.18pm2. In further examples, the method includes identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is less than 0.18pm2. In some examples, the method includes identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count greater than or equal to 30 and less than or equal to 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2and less than or equal to 0.30pm2. In further examples the method includes identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2. In some examples treatment is altered based on the results of a posttreatment membrane protein cluster count and / or a posttreatment membrane protein cluster size measurement. In some examples the method includes adjusting dosage or medicament administered to the patient based on follow-up membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements. In some examples, the method includes obtaining a posttreatment membrane protein cluster count and a posttreatment membrane protein cluster size from the patient. Optionally the patient may be receiving treatment for a mood or psychotic disorder, such as one diagnosed and / or treated by the methods disclosed herein. Optionally, the patient may currently be being administered a schizophrenia medicament, a bipolar disorder medicament, and / or a depression medicament. In some examples, the patient is treated for the same mood or psychotic disorder at both stages of the process.

[0174] In some examples the method includes selecting a different diagnosis based on posttreatment membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements. In some examples, posttreatment membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements are taken some number of weeks after beginning administration a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, and / or a D-II phenotype medicament, such as within or greater than 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, 1 week, 2 week, 3 weeks, 4 weeks, 5 week, 6 weeks, 7 weeks, 8 weeks, 3 months, 4 months, 5 months, 6 months, 8 months, 10 months, one year, or two years after beginning treatment. In some examples, posttreatment membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements are taken 8 weeks after beginning treatment.

[0175] In some examples, the diagnosis is altered based on the posttreatment membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements and a new treatment is selected based on the different diagnosis. In some examples, the method includes obtaining a posttreatment membrane protein cluster count and a posttreatment membrane protein cluster size from the patient. Optionally the patient may be receiving treatment for a mood or psychotic disorder, such as one diagnosed and / or treated by the methods disclosed herein. Optionally, the patient may currently be being administered a schizophrenia medicament, a bipolar disorder medicament, and / or a depression medicament. In some examples the method includes discontinuing administering the schizophrenia medicament, the bipolar disorder medicament, the depression medicament, and / or the D-II phenotype medicament. In some examples, the patient is diagnosed and treated for schizophrenia and / or bipolar disorder. In some examples, posttreatment membrane protein cluster counts and / or posttreatment membrane protein cluster size measurements are taken, and remain substantively unchanged compared to pretreatment values. In some examples, this rules out schizophrenia and / or bipolar disorder, and the patient is subsequently diagnosed and / or treated for depression and / or D-II phenotype.

[0176] In some examples, the method includes administering a different schizophrenia medicament to the patient when the posttreatment membrane prote' ’ is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different schizophrenia medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a schizophrenia patient, or a healthy control. In some examples, the method includes administering a different dose of the schizophrenia medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different dose of the schizophrenia medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a schizophrenia patient, or a healthy control.

[0177] In some examples, the method includes administering a different bipolar disorder medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different bipolar disorder medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a bipolar disorder patient, or a healthy control. In some examples, the method includes administering a different dose of the bipolar disorder medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different dose of the bipolar disorder medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a bipolar disorder patient, or a healthy control.

[0178] In some examples, the method includes administering a different depression medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different depression medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a depression patient, or a healthy control. In some examples, the method includes administering a different dose of the depression medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different dose of the depression medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a depression patient, or a healthy control.

[0179] In some examples, the method includes administering a different D-I phenotype medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different D-I phenotype medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a D-I phenotype patient, or a healthy control. In some examples, the method includes administering a different dose of the D-I phenotype medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different dose of the D-I phenotype medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a D-I phenotype patient, or a healthy control.

[0180] In some examples, the method includes administering a different D-II phenotype medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different D-II phenotype medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a D-II phenotype patient, or a healthy control. In some examples, the method includes administering a different dose of the D-II phenotype medicament to the patient when the posttreatment membrane protein cluster count is substantively unchanged relative to the pretreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size is substantively unchanged relative to the pretreatment membrane protein cluster size. In some examples, the method includes administering a different dose of the D-II phenotype medicament to the patient based on comparing the posttreatment membrane protein cluster count and / or when posttreatment membrane protein cluster size to an appropriate control, such as a control representing a D-II phenotype patient, or a healthy control.

[0181] Additional Exemplary Diagnostic Methods

[0182] Also disclosed herein is a further method of a mood or psychotic disorder. In some examples, the method is a personalized medicine method of treating the mood or psychotic disorder, wherein the medicament administered or prescribed is specific to the subject. In some examples, the method includes obtaining lymphocyte(s) from a subject. In some examples, the method includes culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament. In some examples, the culturing results in medicament cultured lymphocyte(s). In some examples, the method includes measuring membrane protein cluster count and / or membrane protein cluster size, such as on the medicament cultured lymphocyte(s). In some examples, the membrane protein includes one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc). In further examples, the method includes comparing the membrane protein cluster count and membrane protein cluster size to a control. In some examples, the method includes identifying the subject as having a schizophrenia phenotype based on the results of the comparing, identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, identifying the subject as having a depression phenotype based on the results of the comparing, identifying the subject as having a D-I phenotype based on the results of the comparing, and / or identifying the subject as having a D-II phenotype based on the results of the comparing. In some examples, the method includes diagnosing the subject with one or more of schizophrenia, bipolar disorder, depression, a D-I phenotype and / or a D-II phenotype based on the identifying. In further examples, the method includes administering the schizophrenia medicament to the subject identified as having the schizophrenia, administering the bipolar disorder medicament to the subject identified as having bipolar disorder, administering the depression medicament to the subject identified as having depression, administering the D-I phenotype medicament to the subject identified as having the D-I phenotype, and / or administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0183] In further examples, the method further includes measuring a pre-culture membrane protein cluster count and / or pre-culture membrane protein cluster size from the lymphocytes. In some examples, the control includes the pre-culture membrane protein cluster count and the pre-culture membrane protein cluster size. In some examples, the identifying and / or administering is dictated by identifying trend between the membrane protein cluster count and the pre-culture membrane protein cluster count, and / or the trend between the membrane protein cluster size and the pre-culture membrane protein cluster size. In some examples, the identifying and / or administering is dictated by further comparing the trend to a control, such as a healthy control. In some examples, the idei ' " ' " administering is dictated by calculating a vector between the between the membrane protein cluster count and the pre-culture membrane protein cluster count, and / or between the membrane protein cluster size and the pre-culture membrane protein cluster size. Exemplary vectors are shown in FIG. 10B.

[0184] In some examples, the identifying the subject as having the schizophrenia phenotype based on the results of the comparing includes identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and / or (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size. In some examples, the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing includes identifying the subject as having the bipolar disorder phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and / or (ii) the membrane protein cluster size is substantially similar relative to the pre-culture membrane protein cluster size. In some examples, the identifying the subject as having the depression phenotype based on the results of the comparing includes identifying the subject as having the depression phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and / or (ii) the membrane protein cluster size is decreased or slightly decreased relative to the pre-culture membrane protein cluster size. In some examples the identifying the subject as having the D-I phenotype based on the results of the comparing includes identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and / or (ii) the membrane protein cluster size is slightly decreased relative to the pre-culture membrane protein cluster size. In some examples the identifying the subject as having the D-II phenotype based on the results of the comparing includes identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and / or (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size. In some examples the control includes a historical control. In some examples, the subject the subject was or is not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte(s) were isolated from the subject. In some examples the schizophrenia medicament includes an antidepressant, an antipsychotic, or a mood stabilizer. In some examples, the bipolar disorder medicament includes an antidepressant, an antipsychotic, or a mood stabilizer. In some examples, the D-I phenotype medicament includes a tricyclic. In some examples, the depression medicament includes a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMDAR antagonist, or a neurosteroid. In further examples, the schizophrenia medicament, antidepressant medicament, bipolar disorder medicament, D-I phenotype medicament and / or D-II phenotype medicament includes one or more of the medicament from the following exemplary medicaments. Exemplary Medicaments for Treating Depression

[0185] Pharmaceutical agents can be administered as a treatment for depression. Similar or overlapping agents are also administered for other conditions such as anxiety disorders, obsessive compulsive disorder, chronic pain, attention deficit disorder, substance abuse and sleep disorders. Anti-depressant medications include synthesized chemical compounds as well as naturally occurring or herbal remedies such as St. John's Wort. Generally, these medications are administered orally, but they may also be administered in any form of use to a medical practitioner.

[0186] Examples of antidepressant medications include tricyclic antidepressants, which generally affect the two chemical neurotransmitters, norepinephrine and serotonin. Tricyclics include amitriptyline, amoxapine, desipramine, doxepin, imipramine, nortriptyline, protriptyline, and trimipramine. Monoamine oxidase inhibitors (MAOIs) are also used as antidepressants. MAOIs include isocarboxazid, phenelzine, selegiline, and tranylcypromine. Medications that primarily affect the neurotransmitter serotonin, termed selective serotonin reuptake inhibitors (SSRIs), are also used as antidepressants. These include escitalopram citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, and vilazodone. Additional medications of use affect both norepinephrine and serotonin (SNRIs), for example desvenlafaxine, duloxetine, levomilnacipran, milnacipran, sibutramine, tramadol, venlafaxine. Another example of antidepressant medications is tetracyclic antidepressants, which increase activity in the serotonin and / or noradrenergic neurotransmitter systems. Tetracyclic antidepressants include mirtazapine, maprotiline, and amoxapine. Triazolopyridines are also used as antidepressants, and include trazodone and nefazodone. Another class of antidepressant medications are the aminoketones, which include bupropion. Another class of antidepressant medications is N-methyl-D-aspartate receptor (NMDAR) antagonists, which include ketamine. A further class of antidepressant medications is neurosteroids, such as brexanolone and zuranolone.

[0187] Exemplary Medicaments for Treating Schizophrenia

[0188] Pharmaceutical agents can be administered as a treatment for schizophrenia. Schizophrenia is often treated with antipsychotics, which affect dopamine and serotonin. Antipsychotics are usually taken orally, but some can also be given as injections or implants. There are two main types of antipsychotics: first- generation and second-generation.

[0189] First-generation antipsychotics include chlorpromazine, fluphenazine, haloperidol, perphenazine, thioridazine, thiothixene, and trifluoperazine. Second-generation antipsychotics include aripiprazole, aripiprazole lauroxil, asenapine, brexpiprazole, cariprazine, clozapine, iloperidone, lumateperonee, lurasidone, olanzapine, olanzapine / samidorphan, paliperidone, paliperidone palmitate, quetiapine, risperidone, and ziprasidone. Mood stabilizer medications are sometimes administered to treat schizophrenia, sometimes alongside an anti-psychotic. Mood stabilizers include lamotrigine, lithium, carbamazepine, and valproic acid. Antidepressant medicaments, such as those listed above, are also sometimes administered to subjects with schizophrenia. Often, SSRIs such as citalopram, fluoxetine, paroxetine, sertraline, and escitalopram are efficacious.

[0190] Exemplary Medicaments for Treating Bipolar Disorder

[0191] Pharmaceutical agents can be administered as a treatment for bipolar disorder. Antipsychotics, such as first-generation or second-generation antipsychotics as described herein can be administered to treat bipolar disorder. These can be administered in combination with other medications. Antipsychotics administered can include aripiprazole, asenapine, cariprazine, clozapine, lumateperone, lurasidone, olanzapine, quetiapine, risperidone, ziprasidone. Mood stabilizers such as those described herein can be administered to treat bipolar disorder. Mood stabilizers can include lithium, divalproex, carbamazepine, and lamotrigine. Antidepressants, such as those described herein, are sometimes administered to treat bipolar disorder. Often antidepressants are administered as a combination therapy with a mood stabilizer or antipsychotic. Antidepressants can include citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vilazodone, and vortioxetine. Anxiety medications are sometimes administered for bipolar disorder, such as benzodiazepines. Benzodiazepines include, diazepam, lorazepam, clonazepam, oxazepam, chlordiazepoxide, alprazolam, triazolam, and temazepam. SSRI, SNRIs, and / or Tricyclics, as described herein, are sometimes administered as an anti-anxiety medication for bipolar disorder. SSRIs can include paroxetine, sertraline, fluoxetine, and fluvoxamine. SNRIs can include duloxetine, venlafaxine, and desvenlafaxine. Buspirone can be administered as an anti-anxiety medication for bipolar disorder, sometimes in combination with an antidepressant or mood stabilizer.

[0192] Exemplary Medicaments for Treating D-I Phenotype Patients

[0193] Pharmaceutical agents can be administered as a treatment to a D-I phenotype subject. In some examples, a tricyclic is administered to a D-I phenotype patient. Tricyclics can include, but are not limited to, amitriptyline, amoxapine, desipramine, doxepin, imipramine, nortriptyline, protriptyline, and trimipramine.

[0194] Exemplary Medicaments for Treating D-II Phenotype Patients

[0195] Pharmaceutical agents can be administered as a treatment to a D-II phenotype subject. In some examples, an N-methyl-D-aspartate receptor (NMDAR) antagonist is administered to a D-II patient. NMDAR antagonists include Ketamine. Exemplary Methods of Administering Agents

[0196] The compositions, agents, and medicaments can be administered to a subject in a pharmaceutically acceptable carrier. In some examples, the composition, or the constituents of the pharmaceutically acceptable carrier may be administered to a subject without causing any undesirable biological effects or interacting in a deleterious manner with any of the other components of the pharmaceutical composition. The carrier can be selected to minimize any degradation of the active ingredient and to minimize any adverse side effects in the subject.

[0197] Preparations for parenteral administration include sterile aqueous or non-aqueous solutions, suspensions, and emulsions. Examples of non-aqueous solvents are propylene glycol, polyethylene glycol, vegetable oils such as olive oil, fish oils, and injectable organic esters such as ethyl oleate. Aqueous carriers include water, alcoholic / aqueous solutions, emulsions or suspensions, including saline and buffered media. Parenteral vehicles include sodium chloride solution, Ringer's dextrose, dextrose and sodium chloride, lactated Ringer's, or fixed oils. Intravenous vehicles include fluid and nutrient replenishes, electrolyte replenishers (such as those based on Ringer's dextrose), and the like. Preservatives and other additives may also be present such as, for example, antimicrobials, anti-oxidants, chelating agents, and inert gases and the like.

[0198] Pharmaceutical formulations for topical administration may include ointments, lotions, creams, gels, drops, suppositories, sprays, liquids and powders. Conventional pharmaceutical carriers, aqueous, powder or oily bases, thickeners and the like may be necessary or desirable.

[0199] Pharmaceutical formulations for oral administration include, but are not limited to, powders or granules, suspensions or solutions in water or non-aqueous media, capsules, sachets, or tablets. Thickeners, flavorings, diluents, emulsifiers, dispersing aids or binders may be desirable.

[0200] When administering a pharmaceutical preparation, it may be appropriate to start doses of a compound at levels lower than those required to achieve the desired therapeutic effect and to gradually increase the dosage until the desired effect is achieved. If desired, the effective daily dose can be divided into multiple doses for purposes of administration. Consequently, single dose compositions can contain such amounts or submultiples thereof to make up the daily dose. The dosage can be adjusted by a medical professional in the event of any contraindications. Dosage can vary, and can be administered in one or more dose administrations daily, for one or several days. Guidance can be found in the literature for appropriate dosages for given classes of pharmaceutical products.

[0201] In one example, the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject transdermally, by using an adherent patch, by using iontophoresis, or by using any other suitable method. The medicament can be administered every 3, 4, 5, 6, or 7 days, or once every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 weeks. A medical professional, monitoring a subject’s clinical response and improvement, can determine the frequency and / or dosage of administration of the medicament.

[0202] In another example, the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject intranasally once daily or in divided doses. The medicament can be administered for one day and then stopped if clinical improvement occurs rapidly. The medicament can be administered intranasally daily, or once every 2, 3, 4, 5, 6, or 7 days, or once every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 weeks. A medical professional, monitoring a subject’s clinical response and improvement, can adjust the frequency and / or dosage of administration.

[0203] In another example the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject intramuscularly once daily or in divided doses. The medication can be administered for one day and then stopped if clinical improvement occurs rapidly. The medicament can be administered intranasally daily, or once every 2, 3, 4, 5, 6, or 7 days, or once every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 weeks. A medical professional, monitoring a subject’s clinical response and improvement, can adjust the frequency and / or dosage of administration.

[0204] In another example the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject orally once daily or in divided doses. The medication can be administered for one day and then stopped if clinical improvement occurs rapidly. The medicament can be administered intranasally daily, or once every 2, 3, 4, 5, 6, or 7 days, or once every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 weeks. A medical professional, monitoring a subject's clinical response and improvement, can adjust the frequency and / or dosage of administration.

[0205] Multiple doses of the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject. For example, the compositions can be administered daily, every other day, twice per week, weekly, every other week, every three weeks, monthly, or less frequently. A treating clinician can select an administration schedule based on the subject, the condition being treated, the previous treatment history, and other factors. In some examples, multiple doses are given in a single day, such as twice a day, or three times a day.

[0206] One or more doses of the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) can be administered to a subject. For example, the medicament can be administered, daily, every other day, twice per week, weekly, every other week, every three weeks, monthly, or less frequently. In some examples, the medicament may be administered in cycles, for example, at a set interval (such as weekly or daily) for a set number of intervals, followed by a rest period, then repeated one or more times. In some examples the medicament is administered three times a day, five days a week, with a rest period of two days per week. In some examples, the compound can be administered six times a day, five days a week, with a rest period of two days per week.

[0207] An additional therapeutic (such as any of the medicaments disclosed herein) may be administered substantially simultaneously with the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament). In some examples, the additional therapeutic is administered after to administering the composition, for example, at least 1 day, at least 2 days, at least 3 days, at least 4 days, at least 5 days, at least 6 days, at least 7 days, at least 8 days, at least 9 days, at least 12 days, at least 14 days, at least three weeks, at least four weeks, at least one month, or more after. In some examples, the additional therapeutic is administered prior to administering the composition, for example, at least 1 day, at least 2 days, at least 3 days, at least 4 days, at least 5 days, at least 6 days, at least 7 days, at least 8 days, at least 9 days, at least 12 days, at least 14 days, at least three weeks, at least four weeks, at least one month, or more prior. Multiple doses of the additional therapeutic can be administered to a subject, for example, administered twice daily, once daily, every other day, twice per week, weekly, every other week, every three weeks, monthly, or less frequently. A treating clinician can select an administration schedule based on the subject, the condition being treated, the previous treatment history, and by monitoring a subjects clinical response and improvement.

[0208] In some examples, the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) is administered to a subject soon after the mood or psychotic disorder is diagnosed, such as within 12 hours, within 24 hours, within 2 days, within 3 days, within 5 days, or within 1 week. In some examples the disclosed compound is administered within 2 weeks, within 3 weeks, within 4 weeks, within 6 weeks, within 8 weeks, within 10 weeks, within 12 weeks, within 4 months, within 5 months, within 6 months, or within a year. In some examples the medicament is administered beginning 12 hours, beginning 24 hours, beginning 1 week, beginning 2 weeks, beginning 3 weeks, beginning 4 weeks, beginning 2 months, beginning 3 months, beginning 4 months, beginning 5 months, beginning 6 months, beginning 7 months, beginning 8 months, beginning 9 months, beginning 10 months, beginning 11 months, or beginning 12 months or more after the mood or psychotic disorder is diagnosed.

[0209] XI. Kits

[0210] The compositions used with the methods of the present disclosure can be formulated as kits, which include reagents in separate containers. Kits can be applied for diagnosis, and / or treatment, and can include computer readable media which are related to the methods of this disclosure. For example, kits can include reagents and materials for obtaining and preparing a lymphocyte-containing sample, reagents for detecting one or more target proteins (such as SERT-specific primary antibodies and in some examples labeled secondary antibodies), and optionally one or more agents to treat a mood or psychotic disorder.

[0211] Exemplary Kits for Diagnosis

[0212] Also provided are compositions and kits that can be used with the disclosed methods, such as methods including identifying one or more of the subjects disclosed herein, such as a subject with depression, a subject with schizophrenia, a subject with bipolar disorder, a D-I phenotype subject, or a D-II phenotype subject. The kit can include aspects useful for any of the methods of cell collection or purification, whole blood lymphocyte isolation, blood smear isolation, imaging, association of detectable labels with protein of interest, or acquisition of images of MPC disclosed herein. In some examples, the kit includes implements that assist in blood collection, such as tubes, buffers, and / or needles. In some examples, computer readable media is included includes include instructions that enable a computer to carry out methods disclosed here. In some examples, the computer readable media contain a hyperlink that enables an end user to obtain a copy of a program, or which enables a remote program to carry out the methods disclosed herein. In some examples, the methods are the Automated Methods of MPC Image Analysis disclosed herein.

[0213] Exemplary Kits for Treatment

[0214] Also provided are compositions and kits that can be used with the disclosed methods, such as methods including administering one or more of the medicaments disclosed herein. In some examples, the kit includes the medicament (e.g., the depression medicament, the schizophrenia medicament, the bipolar disorder medicament, the D-I medicament, or the D-II medicament) formulated for administration to a subject. The medicament can be formulated for transdermal, intranasal, intramuscular, oral administration, or any other formulation or route of administration disclosed herein. In some examples, the kit includes an agent or compound disclosed herein, within a container. In some examples, the medicament is within a container configured to dispense a measured dosage of the medicament, such as an inhaler, or dropper. In some examples, a container containing a pharmaceutically acceptable carrier or solvent, is also provided, configured to be mixed with the agent or medicament disclosed herein. In some examples, the pharmaceutically acceptable carrier and the compound disclosed herein are included in a single container, but kept separate until a user mixes them, for example by breaking a divider. In some examples, the container is configured to dispense a measured dose, such as a single tablet, such a single tablet on a particular day. In some examples, the container is configured to dispense a measured spray. In some examples, the container is configured to dispense a measured drop. In some examples, instructions for use are provided with the kit. In some examples, the kit further includes an additional therapeutic (such as any of the medicaments disclosed herein). The additional therapeutic may be formulated for coadministration, such as a single capsule containing both the agent or medicament and the additional therapeutic, or it may be formulated to be administered separately, such as a first tablet including the agent or medicament, and a second tablet including the additional therapeutic.

[0215] X. Additional Aspects

[0216] Clause 1. A method of treating a mood or psychotic disorder, comprising: obtaining membrane protein cluster count and membrane protein cluster size from a subject using a lymphocyte sample, wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control; identifying the subject as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing; and administering, thereby treating the subject, at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0217] Clause 2. A method of diagnosing a subject with a mood or psychotic disorder, comprising: obtaining lymphocyte membrane protein cluster count and lymphocyte membrane protein cluster size from a subject, wherein the membrane protein is one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control; identifying, thereby diagnosing the subject, as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing.

[0218] Clause 3. The method of clause 2, further comprising administering at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0219] Clause 4. The method of any one of clauses 1-3, wherein the obtaining the membrane protein cluster count and membrane protein cluster size comprises measuring membrane protein cluster count and membrane protein cluster size.

[0220] Clause 5. The method of clause 4, wherein the measuring the membrane protein cluster count and the membrane protein cluster size comprises labeling the membrane protein in the lymphocyte sample with a detectable label. Clause 6. The method of clause 5, wherein the measuring membrane protein cluster count and the membrane protein cluster size comprises labeling the membrane protein in the lymphocyte sample with an antibody or an antigen binding fragment conjugated to the detectable label.

[0221] Clause 7. The method of clause 5 or clause 6, wherein the detectable label comprises a fluorescent label, biotin, a radiolabel, an enzyme, a luminescent label, and / or a colorimetric label.

[0222] Clause 8. The method of any one of clauses 4-7, wherein the measuring the membrane protein cluster count and the membrane protein cluster size comprises performing immunocytochemistry, immunohistochemistry, or immuno-electron microscopy.

[0223] Clause 9. The method of any one of clauses 1-8, wherein the obtaining the membrane protein cluster count and membrane protein cluster size comprises receiving a magnified image of the lymphocyte sample or taking the magnified image of the lymphocyte sample.

[0224] Clause 10. The method of any one of clauses 1-9, wherein the lymphocyte sample comprises a whole blood sample, a blood smear, or a purified lymphocyte sample; the lymphocyte sample comprises a fixed lymphocyte sample; or the lymphocyte sample was previously frozen, optionally at -80°C.

[0225] Clause 11. The method of any one of clauses 1-10, further comprising isolating the lymphocyte sample from the subject.

[0226] Clause 12. The method of any one of clauses 1-11, wherein the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte sample was isolated from the subject.

[0227] Clause 13. The method of any one of clauses 1-12, wherein: the identifying the subject comprises: a) identifying the subject as having the schizophrenia phenotype based on the results of the comparing, or b) identifying the subject as having the bipolar disorder phenotype based on the results of the comparing.

[0228] Clause 14. The method of any one of clauses 1, or 3-12, wherein: the administering comprises: a) administering the schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering the bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype.

[0229] Clause 15. The method of clause 13 or clause 14, wherein the identifying the subject further comprises: c) identifying the subject as having the depression phenotype based on the results of the comparing, d) identifying the subject as having the D-I phenotype based on the results of the comparing, or e) identifying the subject as having the D-II phenotype based on the results of the comparing.

[0230] Clause 16. The method of clause 15, wherein the administering further comprises: c) administering the depression medicament to the subject identified as having the depression phenotype, d) administering the D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0231] Clause 17. The method of any one of clauses 1-16, wherein the subject is suspected of having a mood or psychotic disorder.

[0232] Clause 18. The method of clause 17, wherein the subject is suspected of having depression, schizophrenia, or bipolar disorder.

[0233] Clause 19. The method of any one of clauses 1-18, wherein the membrane protein comprises SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1 or PrPc and the membrane protein cluster count control and the membrane protein cluster size control comprise healthy controls; the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having bipolar disorder when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is substantially similar to the membrane protein cluster size control; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having depression when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated or elevated compared to the membrane protein cluster size control; the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated compared to the membrane protein cluster size control; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control.

[0234] Clause 20. The method of any one of clauses 1-18, wherein: the membrane protein comprises SERT; the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having bipolar disorder when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is less than 0.18pm2; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having depression when (i) the membrane protein cluster count is less than or equal to 60; the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is less than 0.18pm2; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2. Clause 21. The method of any one of clauses 1 or 3-20, wherein: the schizophrenia medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the bipolar disorder medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the D-I phenotype medicament comprises a tricyclic; the depression medicament comprises a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, or a neurosteroid.

[0235] Clause 22. A method of treating depression, comprising: obtaining membrane protein cluster count and membrane protein cluster size from a subject using a lymphocyte sample, wherein the membrane protein comprises serotonin transporter (SERT); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control and identifying the subject as having a D-I phenotype based on the results of the comparing; administering a tricyclic agent to the subject identified as having the D-I phenotype.

[0236] Clause 23. A method of treating a mood or psychotic disorder, comprising: obtaining lymphocyte(s) from a subject; culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, thereby generating medicament cultured lymphocyte(s); measuring membrane protein cluster count and membrane protein cluster size from the medicament cultured lymphocyte(s), wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count and membrane protein cluster size to a control; identifying the subject as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing; and administering, thereby treating the subject, at least one of: a) administering the schizophrenia medicament to the subject identified as having the schizophrenia, b) administering the bipolar disorder medicament to the subject identified as having bipolar disorder, c) administering the depression medicament to the subject identified as having depression, d) administering the D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0237] Clause 24. A method of diagnosing a subject with a mood or psychotic disorder, comprising: obtaining lymphocyte(s) from a subject; culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, thereby generating medicament cultured lymphocyte(s); measuring membrane protein cluster count and membrane protein cluster size from the medicament cultured lymphocyte(s), wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count and membrane protein cluster size to a control; identifying, thereby diagnosing the subject, as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing.

[0238] Clause 25. The method of clause 24, further comprising administering at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

[0239] Clause 26. The method of any one of clauses 23-25, further comprising measuring a pre-culture membrane protein cluster count and pre-culture membrane protein cluster size from the lymphocytes.

[0240] Clause 27. The method of clause 26, wherein the control comprises the pre-culture membrane protein cluster count and the pre-culture membrane protein cluster size.

[0241] Clause 28. The method of clause 27, wherein: the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having the bipolar disorder phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is substantially similar relative to the pre-culture membrane protein cluster size; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having the depression phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased or slightly decreased relative to the pre-culture membrane protein cluster size; the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is slightly decreased relative to the pre-culture membrane protein cluster size; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size. Clause 29. The method of any one of clauses 23-25, wherein the control comprises a historical control.

[0242] Clause 30. The method of any one of clauses 23-29, wherein the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte(s) were isolated from the subject.

[0243] Clause 31. The method of any one of clauses 23-30, wherein: the schizophrenia medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the bipolar disorder medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the D-I phenotype medicament comprises a tricyclic; the depression medicament comprises a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, or a neurosteroid.

[0244] Clause 1A. A method comprising: with a computer: in an image of a sample from a subject, identifying a region depicting a lymphocyte; identifying patterns representing protein clusters within the region, the identified patterns forming a set; determining values of two or more parameters of the set of identified patterns; and identifying the subject based on the values of the parameters, wherein the identifying classifies the subject as at least one of: schizophrenia phenotype, bipolar phenotype, depression phenotype, D-I phenotype, or D-II phenotype; and administering a schizophrenia medicament to the schizophrenia phenotype subject, administering a bipolar medicament to the bipolar phenotype subject, administering a depression medicament to the depression subject, administering a D-I medicament to the D-I phenotype subject, or administering a D-II medicament to the D-II phenotype subject.

[0245] Clause 2A. A method comprising: with a computer: in an image of a sample from a subject, identifying a region depicting a lymphocyte; identifying patterns representing protein clusters within the region, the identified patterns forming a set; determining values of two or more parameters of the set of identified patterns; and identifying a phenotype of the subject based on the values of the parameters, wherein the identifying distinguishes a depression phenotype from one or more other mental health phenotypes. Clause 3A. The method of clause 2A, wherein the depression phenotype and the one or more other mental health phenotypes comprise one or more of: a schizophrenia phenotype, a bipolar phenotype, a D-I phenotype, or a D-II phenotype.

[0246] Clause 4A. The method of any one of clauses 2A-3A, further comprising: administering, a schizophrenia medicament to the schizophrenia phenotype subject, administering a bipolar medicament to the bipolar phenotype subject, administering a depression medicament to the depression subject, administering a D-I medicament to the D-I phenotype subject, or administering a D-II medicament to the D-II phenotype subject.

[0247] Clause 5A. The method of any one of clauses 1 A-4A, wherein the identifying a region comprises: setting parameters for size, opacity, and / or shape; and calling a graphics library function with the set parameters to identify the region, wherein the identified region matches the set parameters.

[0248] Clause 6A. The method of clause 5A, wherein: the set parameter for size is in a range 100-350 pm2; the set parameter for opacity is in a range 0.8-1.0; the set parameter for shape identifies circularity in a range 0.32-1.0; and / or the set parameter for shape identifies roundness in a range 0.75-1.0.

[0249] Clause 7A. The method of any one of clauses 5A-6A, wherein the called graphics library function: repeats (a), (b), and (c) until the set parameters are matched:

[0250] (a) scanning the image until an edge of an object is found;

[0251] (b) determining an outline of the object; and

[0252] (c) checking whether the object matches the set parameters; and returns the object matching the set parameters to identify the region.

[0253] Clause 8A. The method of clause 7A, wherein the determining the outline comprises: determining a target pixel attribute intermediate between a first pixel attribute representative of an interior of the object and a second pixel attribute representative of the image outside the object; starting from a first pixel on the edge of the object, following successive neighboring pixels having respective pixel attributes within a predetermined tolerance of the target pixel attribute, until returning to the first pixel; and determining the outline based on the first pixel and the successive neighboring pixels. Clause 9A. The method of any one of clauses 5A-8A, wherein the image comprises multiple channels and the graphics library function is called on a subset of the multiple channels.

[0254] Clause 10 A. The method of any one of clauses 1A-9A, wherein the method further comprises, successively: nulling pixels of the image in a most recently identified region; and subsequently identifying another region depicting another lymphocyte.

[0255] Clause 11 A. The method of clause 10A, further comprising: progressively increasing an image intensity threshold over the successive nulling and identifying actions, until a limiting value of the image intensity threshold is reached or until no further regions depicting lymphocytes are found.

[0256] Clause 12 A. The method of any one of clauses 1A-11A, further comprising, subsequent to the identifying a region and prior to the identifying patterns: calling a second graphics library function to increase circularity of the region; nulling pixels of the image outside the identified region; converting pixels within the image to binary values; despeckling the image inside the identified region; and / or delineating fused objects within the region.

[0257] Clause 13A. The method of clause 12A, wherein the increasing circularity, nulling pixels, converting pixels, despeckling, and delineating actions are performed in that order.

[0258] Clause 14 A. The method of any one of clauses 1A-13A, wherein the identifying patterns comprises: setting pattern parameter(s) for at least size; and calling a third graphics library function with the set pattern parameter(s) to identify the patterns matching the set pattern parameters.

[0259] Clause 15A. The method of clause 14A, wherein: the set pattern parameter for size is at least 0.05 pm2;

[0260] Clause 16A. The method of any one of clauses 14A-15A, wherein the called third graphics library function: repeats (d), (e), and (f) until the set pattern parameters are matched: (d) scanning the image until an edge of a pattern candidate is found;

[0261] (e) determining an outline of the pattern candidate; and

[0262] (f) checking whether the pattern candidate matches the set pattern parameter(s); and returns the pattern candidate matching the set pattern parameter(s) to identify a given pattern of the patterns.

[0263] Clause 17 A. The method of any one of clauses 14A-16A, wherein the method further comprises, successively: nulling pixels of the image in a most recently identified pattern; and subsequently identifying another pattern of the patterns.

[0264] Clause 18A. The method of any one of clauses 1A-17A, wherein the protein clusters comprise one or more of: serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc).

[0265] Clause 19A. The method of any one of clauses 1A-18A, wherein the parameters comprise two or more of: a cardinality of the set of identified patterns; an average of respective diameters of the identified patterns; a width of a distribution of the diameters of the identified patterns; or a diameter corresponding to a percentile range of the distribution of the diameters of the identified patterns.

[0266] Clause 20A. The method of any one of clauses 1A-18A, further comprising, for each of the identified patterns: measuring a diameter of the respective identified pattern.

[0267] Clause 21 A. The method of any one of clauses 1A-20A, wherein the identifying the subject or the phenotype of the subject comprises: comparing one or more of the determined values with respective threshold(s); comparing one or more of the determined values with representative values for respective phenotypes; or inputting the determined values to a trained machine learning classifier and obtaining the identification as output from the trained machine learning classifier. Clause 22 A. The method of any one of clauses 1A-21 A, further comprising, prior to the identifying the region: establishing a geometric scale of the image.

[0268] Clause 23 A. The method of any one of clauses 1A-22A, wherein the subject is undiagnosed and the method is applied for screening.

[0269] Clause 24A. The method of any one of clauses 1 A-22A, wherein the subject has been diagnosed according to a given mental health phenotype, and the method is performed to: guide future treatment; or evaluate past treatment.

[0270] Clause 25A. The method of any one of clauses 1A or 4A-24A, wherein: the schizophrenia medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the bipolar disorder medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the D-I phenotype medicament comprises a tricyclic; the depression medicament comprises a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, or a neurosteroid.

[0271] Clause 26A. The method of any one of clauses 1 A-25 A, wherein the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the sample was isolated from the subject.

[0272] Clause 27 A. One or more computer-readable media storing instructions which, when executed by one or more hardware processors, cause the hardware processors to perform the computer-implemented actions of any one of clauses 1A-26A.

[0273] Clause 28A. A system comprising: one or more hardware processors with memory coupled thereto; and one or more computer-readable media storing instructions which, when executed by one or more hardware processors, cause the hardware processors to perform the computer-implemented actions of any one of clauses 1A-26A. EXAMPLE 1: MATERIALS AND METHODS

[0274] Lymphocyte Sources

[0275] To evaluate whether the program works consistently across past studies, a subset of images was collected to evaluate SERT clustering. Images were collected of samples collected by various blood collection methods.

[0276] SERT Immunocytochemistry

[0277] For isolated lymphocytes, successive centrifugation and re-suspension of samples was conducted at each step in the procedure as described in (Rivera et al., Journal of Affective disorders, 163:47-55, 2014). The steps taken for immunocytochemistry were the same for isolated lymphocytes and blood smears. Following collection, samples were fixed for 1 minute in a solution of 1% paraformaldehyde in phosphate buffer solution (PBS) at room temperature. Samples were then blocked through incubation in 10% human IgG and 1% bovine serum albumin in PBS. After 1 hour, samples were placed in rabbit anti-human SERT antibody (Millipore, AB9322) and incubated overnight at -4°C. The following day samples were washed in PBS before incubation in anti-rabbit secondary antibody conjugated with Alexa Fluor 488 (Molecular Probes, Al 1008) diluted to 1:200 in PBS and 1% BSA for 1 hour at room temperature in the dark. Following rinsing, isolated lymphocytes were collected onto Superfrost microscope slides (Fischer Scientific) and mounted with anti-fading mounting medium (Calbiochem®). For blood smears, samples were fixed with paraformaldehyde and rinsed with PBS before immunocytochemistry. After fixation, the same general immunocytochemistry procedures were conducted on blood smears. Following secondary incubation, blood smears were stained with Hoetsch before rinsing and cover- slipping with anti-fading mounting medium (Calbiochem®). Slides were then stored at -20°C until imaging.

[0278] Imaging and Manual Analysis

[0279] Immunolabeling of SERT was conducted on either a spectral confocal microscope (Leica TCS-SP2) or a fluorescent microscope (Zeiss Axio Imager M.2). Images were obtained for 50 lymphocytes per sample at a magnification of 100X and analyzed using the imaging software ImageJ 1.42 (Rasband et al., ImageJ, NIH), wherein the same automatic counting of the size and number of SERT clusters on each imaged lymphocyte was conducted manually.

[0280] To manually analyze the lymphocytes an outline of the lymphocyte was drawn around each lymphocyte identified to create an ROI before conducting a particle analysis. If the binary output matches what the researcher saw on the original image and the count is within a normal range (30-100), the binary output was saved as a .tif file to a folder and raw cluster data is copied into an Excel™ file. When counts do not represent the acceptable range of cluster counts or the clusters produced in the binary are not consistent with the original image, the maximum and minimum brightness threshold were adjusted slightly, which can either reduce oversaturation of clusters appearin ’ ’ righten unaccounted for clusters if too few are identified by the particle analysis. The specific adjustments made by each researcher are specific to each image, which creates the possibility of individual differences presenting when manually scoring clustering.

[0281] Automation with Secondary Validation

[0282] The automated program can isolate lymphocytes from the background before conducting the standard SERT cluster analysis that has previously been conducted manually, also using ImageJ software (Rasband et al., ImageJ, NIH). To find the lymphocytes, the program serially reduced thresholds and conducted a particle analysis at each threshold with parameters for object size and circularity, rejecting objects larger or smaller than the known size of a lymphocyte and any objects lacking the distinct circularity of a lymphocyte. Once a lymphocyte was detected, an ROI was generated. After each threshold following, currently detected ROIs were spliced out of the image to prevent repeat generation of ROIs. Once thresholds were scanned, the program returned to the original image (without thresholding) for clustering analysis for each ROI. Although there may be inclusion of non-lymphocytes in the clustering analysis, knowing the reasonable range of cluster counts within both healthy and clinical populations allowed the program to be restricted to re-analyze SERT clusters until the output is within an acceptable range. Cluster counts ranged from 30 to 100, so the program was restricted to accept results in the range of 30-115 counts (to include reasonable outliers). When results exceed these parameters, alternative thresholding settings were applied, with one alteration for counts that are too high and a different alteration for counts that are too low. When the program failed to obtain an acceptable cluster count within a number of attempts, such as within 5, 14, or 15 attempts, the program ignored the lymphocyte and the analysis of the next will be initiated. This tends to occur when a non-lymphocyte has been detected and sent through clustering analysis and through limiting the number of adjustments, there is a reduction of over-inclusion of non-lymphocytes into analysis that require manual removal. FIGs. 1A-1G demonstrate several steps for the automated method. The output for each lymphocyte includes raw cluster data, summary data and two binary outputs. The first binary output visually demonstrates the lymphocyte location within the original image at the threshold in which the lymphocyte was detected (as seen in FIG. IB). The second binary output shows the cluster locations and the size of each cluster (as seen in FIG. 1G and FIG. 1H). As some non-lymphocytes were detected and treated by the program as lymphocytes and occasionally manage to generate a cluster size within an acceptable range, a human observer can isolate and remove all non-lymphocytes included into analysis using the combination of binary outputs to verify all included lymphocytes are truly derived from lymphocytes. This can easily be identified by the researcher as the binary output of clusters lacks the consistent circular pattern seen in lymphocytes demonstrated in FIGs. 1F-1G. Additionally, the first binary output can be compared against the original to verify the associated ROI corresponds to a lymphocyte found in the original image. Data was only included in analysis after images were validated by a human observer. Validation of Automated Method of SERT Cluster Analysis

[0283] To validate the accuracy of the automated program, images were re-analyzed using the automated technique and results were compared with original manually obtained results for each method of sample collection using Pearson correlations. Following an assessment of each method in isolation, results from each method were combined and analyzed against automated results with a Pearson correlation.

[0284] Evaluating Lymphocyte Acceptance / Rejection Rates For Each Method

[0285] To evaluate whether one method of blood collection was associated with more effective analysis with the automated method compared to another method, the number of lymphocytes obtained and rejected due to poor and rejected due to manual removal (such as when background is accepted into analysis) were quantified. To accomplish this, the program analyzed 500 images of lymphocytes from each method and recorded acceptance and rejection of potential lymphocytes. The ratio of accepted lymphocytes to rejected lymphocytes was reported to demonstrate whether methods perform similarly over larger numbers of images.

[0286] Improving Automation Accuracy

[0287] Following observation that smears fixed pre-freezing had lower acceptance rates, lymphocytes were re-imaged that were collected with this technique, however, the blue channel was included when imaging, which contains the Hoestch staining used to differentiate lymphocytes from other cell types and background staining (see FIG. 2A for example). After minor adjustments, the program was designed to isolate blue and red channels, detect ROIs representing lymphocytes in the blue channel, and then quantify SERT within the red channel within these ROIs (as seen in FIGs. 2B-2C). This allowed a determination whether worse performance across 500 images relates to true issues related to staining or alternatively, relates to individual differences in imaging (i.e. lymphocytes out of focus, overinclusion of background, etc.). Furthermore, this informed on whether imaging methods could be modified to work in conjunction with the automated approach to improve its accuracy. The program was then used to analyze 500 images of SERT-stained lymphocytes imaged with both Hoestch (blue channel) and SERT (red channel) and evaluated whether this improved the ratio of accepted to rejected lymphocytes and increased the number of lymphocytes included in analyses.

[0288] Evaluation of Inter- Rater Reliability

[0289] To evaluate the reliability of manually scored results, researchers were trained to manually analyze SERT clustering and asked to re-analyze a subset of images taken from each of the previously completed studies. The results were correlated against the corresponding manual scores obtained by the original researcher. To determine whether the correlation results varied due to method of collection or due to variable human scoring accuracy, new manually obtained scores were also included in correlations between new results and the automated method.

[0290] Statistical Analyses

[0291] Pearson correlations were conducted using GraphPad, Prism 9, version 9.4.1 to evaluate relationships between manually and automatically generated data and between the two manual scorers. Qualitative results demonstrating number of lymphocytes accepted and rejected when analyzing 500 images with each method were not statistically compared, as any statistical differences would reflect differences between the datasets (ex. species, patient populations and treatments) rather than differences to program effectiveness.

[0292] Human Subjects

[0293] Subjects were recruited by psychiatric clinicians. General inclusion criteria included be at least 18 years of age; have a confirmed diagnosis (by two independent psychiatrist) of MDD, BD, or SCZ, according to DSM-IV-TR; do not present any other psychiatric or neurologic condition; do not have a story of traumatic brain injury; starting the pharmacological treatment at the beginning of the study (i.e., naive patients); and for women not being pregnant or in lactation period.

[0294] Symptoms severity was evaluated by passing of psychological scales (HDRS for MDD and BD patients), (SAAS for MDD, BD, and SCZ patients), and (PANNS for BD and SCZ patients). During the first visit of recruited patients -and upon informed consent - sociodemographic data, scores of psychological scales, and blood samples were collected. During a second interview 8 weeks after initiating psychopharmacological treatment clinical scales and blood samples were again passed. All the scale questionaries were recorded by a trained psychologist blind to the prescribed treatment.

[0295] Control group samples were collected from healthy individuals. The group was composed of individuals of at least 18 years of age. Socio-demographic data was also collected for this group.

[0296] Socio-Demographic Characteristics

[0297] Data was collected on age, sex, civil stage (single, married, divorced, widowed), education, education level, acquis, level, familial support, and work situation. For patient groups data was also collected the following clinical variables: Diagnosis following DSM-IV-TR (including evaluation of axes I, II, III, IV, and V), melancholic patterns, previous episodes (depressive, manic, psychotic), suicidal ideations / attempt, premenstrual syndrome, familiar antecedents of psychiatric disorders, and bereavement. All these characteristics were considered, in order to avoid contamination effects in the analyses of data. Blood Sample Acquisition and Extraction of Lymphocytes

[0298] Whole blood samples were drawn between 8 and 9 a.m., using Vacutainer BD tubes (Ref: 36446). These tubes contain 1.5ml of ACD [A-trisodium citrate (22g / l), citric acid (8g / l), and dextrose (24.5g / l)J as anticoagulant, with a total capacity to collect 8.5 ml of blood. 3 blood tubes were collected from each subject.

[0299] Gradient centrifugation with Ficoll-Paque (Pharmacia Biotech) was used for extraction of lymphocytes. Separation by centrifugation allows recovery of a specific layer after centrifugation that is comprised mostly of lymphocytes. Briefly, whole blood was first diluted 1:1 in saline solution prepared from two main components A (Glucose D-anhidra 0,1%, CaC12 x 2H2O 5.0x10-5 M, MgC12 x 6H2O 9,8xlO-4M, Kcl 5,4x10-3 M, TRIS 0,145 M) and B (NaCl 0,14 M). Final saline solution was obtained by mixing 9 volumes of solution B with 1 volume of solution A. Thereafter, the Ficoll gradient was generated (4ml of blood solution on top of 3 ml Ficoll) and samples were first centrifuged at 400g for 25 minutes RT. After centrifugation, the lymphocyte layer was collected and transferred to centrifuge tubes with 3 volumes of saline solution, and proceeded with centrifugation at 200g for 10 minutes. This last process was repeated a second time, and finally supernatant was collected with the lymphocytes being diluted in 1ml of saline solution. This mix was fixed in 1% paraformaldehyde solution for one minute, and thereafter preserved at 4 degrees Celsius for up to one week, before processing for SERT immunolabeling. SERT immunolabeling and image analysis of MPC was carried out as described above.

[0300] Statistical Analysis

[0301] A database was created including sociodemographic, clinical, and biological (SERT clustering) data from patients and control subjects. The sociodemographic variables considered were sex, age, marriage, work, and study levels. The biological variables were average number and size of SERT clusters, and clinical variables were diagnosis, treatment, and scores on psychological scales. Data was initially grouped in tables in SPSS and a first study of descriptive statistics of considered variables was carried out. The general statistical strategy was pursued by a double-entry table, with an axis included all subjects (identified by a numeric code), and in the other all the socio-demographic data specific for each subject, followed by clinical and biological parameters. Data were expressed as the mean plus / minus standard error, and biological significance was established at p<0.05.

[0302] EXAMPLE 2: Correlations between human scoring for each method against automated results

[0303] Pearson correlations were evaluated to compare the automated data against existing manual scores from blood collected from each method. A significant positive correlation was observed when comparing the automatically generated data against past manual generated scores when comparing each method of lymphocyte sample collection (p’s <.001), as se 3C. EXAMPLE 3: Correlations between all human scorers against automated results

[0304] Pearson correlation was evaluated with all methods of lymphocyte collection grouped together to contrast manually obtained results from each original scorer against automated scores. A strong positive correlation was observed between the manual and automated scores, as shown in FIG. 3D. Results suggest the automated program is similarly effective across techniques in obtaining similar results as human scorers.

[0305] EXAMPLE 4: Human Inter-Rater Reliability

[0306] Pearson correlations were evaluated to assess past manual scoring with updating scoring from a second researcher. Results show each method of collection was associated with a strong correlation between original and newly trained image analyzers (p’s<.001) as shown in FIGs. 4A-4D. This was also observed when amalgamating each method of collection into a single analysis, as seen in FIG. 4D.

[0307] EXAMPLE 5: Qualitative Comparisons of Lymphocytes Detected / Removed w / Each Method

[0308] To provide description of the quantities and success rate of the program, the program scanned through 500 images from each method of sample collection. As the number of lymphocytes within these images varies drastically, no statistical comparisons were made, and qualitative summary data is provided. First, the number of images within the 500 evaluated in which the program failed to detect any lymphocytes is shown. As seen in FIG. 5, no lymphocytes were detected in approximately 6% of images from samples frozen prior to fixation, whereas only 1.5% of images from isolated lymphocytes and samples fixed prior to freezing lacked a detectable lymphocyte. For the number of lymphocytes detected but which the program could not obtain an acceptable cluster count, a substantially greater number of lymphocytes that required rejection from samples fixed prior to freezing at approximately 34% was seen, whereas the other two methods performed similarly between 2-5%. When considering the mean number of manually removed lymphocytes per 50 images, all techniques perform similarly, requiring removal of between 3.5-6% of all lymphocytes. When the total number of accepted lymphocytes was assessed in FIG. 5, isolated lymphocytes tended to have many more lymphocytes within each image, whereas both samples frozen prior to fixation and samples fixed prior to freezing appeared to have similar numbers of lymphocytes across the 500 images. As the number of lymphocytes varies across collection methods, statistical comparisons are skewed and could lead to inaccurate conclusions. Finally, the ratio of accepted lymphocytes to manually rejected lymphocytes was assessed to determine if methods performed similarly in relation to the amount of manual researcher involvement to finalize results. The difference equates to a difference of removing 2 nonlymphocytes per subject to removing 3-4 non-lymphocytes per subject (at 50 lymphocytes per subject). Samples fixed prior to freezing again were analyzed after re-imaging the samples using a multi-channel imaging method. Results show by relying on the blue channel opposed to the red channel for identifying lymphocyte to generate ROIs, number of non-lymphocytes being recognized by the program were drastically reduced, but did not result in reasonable cluster counts, and the number of lymphocytes requiring manual removal. Additionally, total percentage of lymphocytes included in analysis was drastically increased when using a multi-channel approach.

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[0347] EXAMPLE 6: Associations Between Sociodemographic Variables and Biological Parameters

[0348] Lymphocytes were extracted from peripheral blood samples to evaluate relations among the membrane clustering of serotonin transporter (SERT) and the diagnosis and pharmacotherapeutic efficacy in mood and psychotic disorders (Major Depressive Disorder -MDD-, Bipolar Disorder -BD- and Schizophrenia (SCZ), as well as to analyze correlations between SERT clustering and clinical scales (Hamilton Depression Rating Scale -HDRS-, Self-Assessment Anhedonia Scale -SAAS- and Positive and Negative Symptoms Scale -PANNS-). This is a non-interventionist, observational, prospective, and longitudinal study with naive (before treatmentj / treated (after treatment) patients diagnosed with MDD, BP, or SCZ, and a control group of non-psychiatric patients.

[0349] The sociodemographic data of subjects recruited for this study is shown in FIG. 6A and the clinical characteristics analysis of mood disorder groups before treatment is shown in FIG. 6B providing evidence that there are no clinical differentiations between naive D-I and D-II MDD patients. Statistical analysis indicates that there are no significant associations between sociodemographic variables and biological parameters (i.e. SERT-MPC). There are no associations between sociodemographic variables and SAAS and PANSS scores. FIG. 20 describes further clinical characteristics of naive patients.

[0350] The pharmacological treatment given to recruited patients is described in FIG. 7. While there are differences in treatment for the three studied mental disorders, there are no associations (i.e., statistically significant differences) between treatment and biological or clinical parameters. The treatment was assigned by clinicians according to accepted clinical practice possible treatment for each individual.

[0351] EXAMPLE 7: Analysis of SERT Clustering in Naive Subjects

[0352] Lymphocytes were extracted from peripheral blood samples from the cohort described in Examples 6 and 7, and SERT clustering was assessed by immunohistochemistry and manual analysis as described in Example 1.

[0353] Images of SERT clustering on representative lymphocytes from naive patients for conditions evaluated is shown in FIG. 8A. Biological parameters from naive patients (D-I, D-II, Bipolar Disorder, and Schizophrenia) are summarized in FIGs. 8B-8D. FIG. 8E details the differences in SERT protein clustering among the naive patient populations and control cohort.

[0354] Table 1 shows mean scores for percentage of clusters within the size modal peak, number, and size for SERT clusters on lymphocytes in naive patients (number of subjects (N), standard error of measurement (SEM)). Table 2 shows statistical significance in SERT analyses associated with differential diagnosis for major depressive disorder, bipolar disorder, and schizophrenia. Table 1: Mean scores on biological variables (SERT clusters in lymphocytes).

[0355] Table 2: Differences in biological variables.

[0356] FIG. 9 shows the distribution of SERT clusters size in lymphocytes from control, depression I, depression II, and bipolar disorder native cohorts (average of measurements before pharmacological treatment). Note the decrease of clusters within the modal peak of depression II patients.

[0357] EXAMPLE 8: MPC as a Diagnostic and Effects after Treatment

[0358] Lymphocytes were extracted from peripheral blood samples from the cohort described in Examples 6 and 7. SERT clustering was assessed by immunohistochemistry and manual analysis as described in Example 1 on lymphocytes from naive and treated (FIG. 7) subjects. FIGs 21A-21X describe clinical characteristics before and after treatment.

[0359] FIG. 10A illustrates data obtained from evaluation of SERT clustering in lymphocytes in naive patients. Each dot represents the average number per lymphocyte and size of SERT clusters in one subject. Different subject populations including controls (white), D-I (angled cross-hatching), D-II (cross-hatching), BD (angled parallel hatching), and SCZ (stippled) are primarily observed in different regions of the graph. FIGs. 22A-22B provide an alternative presentation of this data. FIG. IOC shows statistical evaluation of sensitivity, specificity and accuracy of the test to differentially identify specific diagnosis identifying this test as sensible, specific and accurate for differential diagnosis between MDD, BD, and SCZ patients. Many of the changes in SERT cluster number, size, or percentage of clusters size within the normal peak were statistically significant. Changes in psychological scales upon treatment were also observed for all three disorders studied as shown by FIGs. 11A-1 IF. In D-II patients there is a correlation between increases in SERT numbers and clinical response in psychological scales (FIG. 11G), as well as between a decrease in SERT numbers and clinical response in psychological scales (FIG. 11G).

[0360] No statistically significant correlations were found between biological variables and PANSS scores before treatment. No statistically significant correlations were found between the biological variables and the scores on the SAAS scale before treatment.

[0361] In depression, a statistically significant correlation was observed between the increase in the mean number of clusters and the improvement in the EAA clinical anhedonia scale. In bipolar patients, a significant correlation was observed between the decrease in the mean number of clusters and the improvement in the AAS anhedonia clinical scale and between the decrease in the % of clusters in the modal peak and the improvement in the AAS anhedonia clinical scale. In Schizophrenia, no statistically significant correlations have been found between the improvement in anhedonia and the changes in the biological parameters of SERT.

[0362] FIGs. 12A-12I show differences in SERT percentage of clusters within the size modal peak, number of SERT clusters per lymphocyte, and average SERT cluster size before and after pharmacological treatment among depression, bipolar disorder, and schizophrenia subjects.

[0363] EXAMPLE 9: MPC as a Diagnostic and Effects after Treatment

[0364] Treatment of rodents with the stress hormone CORT results in alterations in SERT protein clustering in lymphocytes membranes that resemble those observed in depression patients (Romay-Tallon et al., 2018; Caruncho et al., 2019; Johnston et al., 2020, 2023). Rat lymphocytes were incubated with corticosterone and different antidepressant drugs in order to ascertain whether in vitro incubation of lymphocytes with CORT results in alterations of SERT clustering that parallel those observed in vivo and in depression patients and to determine if incubation with antidepressant drugs is able to reverse these changes similarly to what happens in depression patients when treatment response is effective. Lymphocytes were isolated with Ficoll-Paque Plus as described above and incubated in FBS 10%, Streptomycin 5%, RPMI. Applied drugs include corticosterone, fluoxetine (example of SSRI), imipramine (example of TCA), and ketamine (new fast-acting ATD). Drugs were dissolved in 10 mM stock: EtoH 30%, DMSO 30%.

[0365] FIGs. 13A and 13B show that use of ImM CORT for one or two hours mimics the increases in SERT cluster size that are observed in naive depression patients. FIGs. 13C and 13D show that low concentrations of fluoxetine (Ih incubation) lower SERT clusters size with 12 and 24 mM, completely reversing the changes induced by CORT. FIGs. 13E and 13F show that low concentrations of imipramine (Ih incubation) lower SERT clusters size with 3, 12 and 24 mM, completely reversing the changes induced by CORT. FIGs. 13G and 13H show that 0.5 mM ketamine for one hour, lowers the increase in SERT clusters induced by CORT.

[0366] EXAMPLE 10: Exemplary Protocol for Analysis of Blood Samples

[0367] The following steps can be executed to analyze SERT clustering on patient blood samples. Whole blood can be collected from subjects, for example by a clinician. Sample IDs can be added to an electronic log of samples received. Circulating lymphocytes can be isolated from the whole blood samples, for example via centrifugation using the Ficoll Paque™ Plus separation method (see, e.g., Cytiva, Isolation of Mononuclear Cells, pgs. 8-10, 2020). Unused portions of blood (i.e., RBC and plasma layers) can be discarded following isolation of lymphocytes. After isolation of lymphocytes, isolated lymphocytes can be fixed, for example with paraformaldehyde. After fixation , immunocytochemistry can be conducted on a subset of the fixed isolated lymphocytes to allow visualization of the serotonin transporter (SERT) protein. Remaining lymphocytes can be frozen at -80C for long-term storage.

[0368] Lymphocytes stained for SERT can be mounted to slides and imaged for SERT clustering using fluorescent microscopy. Photomicrographs of lymphocytes can then be analyzed using automated methods described herein, which can produce an Excel™ file containing clustering data. The clustering data can be added to a digital record containing all clustering data, which can be maintained on an external hard-drive. Clustering data can be uploaded to an online database for analysis.

[0369] It will be apparent that the precise details of the methods or compositions described may be varied or modified without departing from the spirit of the described aspects of the disclosure. We claim all such modifications and variations that fall within the scope and spirit of the claims below.

Claims

We claim:

1. A method of treating a mood or psychotic disorder, comprising: obtaining membrane protein cluster count and membrane protein cluster size from a subject using a lymphocyte sample, wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control; identifying the subject as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing; and administering, thereby treating the subject, at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.2 A method of diagnosing a subject with a mood or psychotic disorder, comprising: obtaining lymphocyte membrane protein cluster count and lymphocyte membrane protein cluster size from a subject, wherein the membrane protein is one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control;identifying, thereby diagnosing the subject, as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing.

3. The method of claim 2, further comprising administering at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

4. The method of any one of claims 1-3, wherein the obtaining the membrane protein cluster count and membrane protein cluster size comprises measuring membrane protein cluster count and membrane protein cluster size.

5. The method of claim 4, wherein the measuring the membrane protein cluster count and the membrane protein cluster size comprises labeling the membrane protein in the lymphocyte sample with a detectable label.

6. The method of claim 5, wherein the measuring membrane protein cluster count and the membrane protein cluster size comprises labeling the membrane protein in the lymphocyte sample with an antibody or an antigen binding fragment conjugated to the detectable label.

7. The method of claim 5 or claim 6, wherein the detectable label comprises a fluorescent label, biotin, a radiolabel, an enzyme, a luminescent label, and / or a colorimetric label.

8. The method of any one of claims 4-7, wherein the measuring the membrane protein cluster count and the membrane protein cluster size comprises performing immunocytochemistry, immunohistochemistry, or immuno-electron microscopy.

9. The method of any one of claims 1-8, wherein the obtaining the membrane protein cluster count and membrane protein cluster size comprises receiving a magnified image of the lymphocyte sample or taking the magnified image of the lymphocyte sample.

10. The method of any one of claims 1-9, wherein the lymphocyte sample comprises a whole blood sample, a blood smear, or a purified lymphocyte sample; the lymphocyte sample comprises a fixed lymphocyte sample; or the lymphocyte sample was previously frozen, optionally at -80°C.

11. The method of any one of claims 1-10, further comprising isolating the lymphocyte sample from the subject.

12. The method of any one of claims 1-11, wherein the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte sample was isolated from the subject.

13. The method of any one of claims 1-12, wherein: the identifying the subject comprises: a) identifying the subject as having the schizophrenia phenotype based on the results of the comparing, or b) identifying the subject as having the bipolar disorder phenotype based on the results of the comparing.

14. The method of any one of claims 1, or 3-12, wherein: the administering comprises: a) administering the schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering the bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype.

15. The method of claim 13 or claim 14, whereinthe identifying the subject further comprises: c) identifying the subject as having the depression phenotype based on the results of the comparing, d) identifying the subject as having the D-I phenotype based on the results of the comparing, or e) identifying the subject as having the D-II phenotype based on the results of the comparing.

16. The method of claim 15, wherein the administering further comprises: c) administering the depression medicament to the subject identified as having the depression phenotype, d) administering the D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

17. The method of any one of claims 1-16, wherein the subject is suspected of having a mood or psychotic disorder.

18. The method of claim 17, wherein the subject is suspected of having depression, schizophrenia, or bipolar disorder.

19. The method of any one of claims 1-18, wherein the membrane protein comprises SERT, 5HT2A, DAT, Beta2 AR, NR2B, PNX1 or PrPc and the membrane protein cluster count control and the membrane protein cluster size control comprise healthy controls; the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having bipolar disorder when the membrane protein cluster count is elevated compared to the membrane protein cluster count control and the membrane protein cluster size is substantially similar to the membrane protein cluster size control; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having depression when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated or elevated compared to the membrane protein cluster size control;the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is slightly elevated compared to the membrane protein cluster size control; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when the membrane protein cluster count is substantially similar to the membrane protein cluster count control and the membrane protein cluster size is elevated compared to the membrane protein cluster size control.

20. The method of any one of claims 1-18, wherein: the membrane protein comprises SERT; the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having bipolar disorder when (i) the membrane protein cluster count is greater than 60 and (ii) the membrane protein cluster size is less than 0.18pm2; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having depression when (i) the membrane protein cluster count is less than or equal to 60; the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is less than 0.18pm2; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is less than or equal to 60 and (ii) the membrane protein cluster size is greater than or equal to 0.18pm2.

21. The method of any one of claims 1 or 3-20, wherein: the schizophrenia medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the bipolar disorder medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the D-I phenotype medicament comprises a tricyclic; the depression medicament comprises a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, or a neurosteroid.

22. A method of treating depression, comprising: obtaining membrane protein cluster count and membrane protein cluster size from a subject using a lymphocyte sample, wherein the membrane protein comprises serotonin transporter (SERT); comparing the membrane protein cluster count to a membrane protein cluster count control and comparing the membrane protein cluster size to a membrane protein cluster size control and identifying the subject as having a D-I phenotype based on the results of the comparing; administering a tricyclic agent to the subject identified as having the D-I phenotype.

23. A method of treating a mood or psychotic disorder, comprising: obtaining lymphocyte(s) from a subject; culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, thereby generating medicament cultured lymphocyte(s); measuring membrane protein cluster count and membrane protein cluster size from the medicament cultured lymphocyte(s), wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count and membrane protein cluster size to a control; identifying the subject as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing; and administering, thereby treating the subject, at least one of: a) administering the schizophrenia medicament to the subject identified as having the schizophrenia, b) administering the bipolar disorder medicament to the subject identified as having bipolar disorder, c) administering the depression medicament to the subject identified as having depression, d) administering the D-I phenotype medicament to the subject identified as having the D-I phenotype, ore) administering the D-II phenotype medicament to the subject identified as having the D-II phenotype.

24. A method of diagnosing a subject with a mood or psychotic disorder, comprising: obtaining lymphocyte(s) from a subject; culturing the lymphocyte(s) with a schizophrenia medicament, a bipolar disorder medicament, a depression medicament, a D-I phenotype medicament, and / or a D-II phenotype medicament, thereby generating medicament cultured lymphocyte(s); measuring membrane protein cluster count and membrane protein cluster size from the medicament cultured lymphocyte(s), wherein the membrane protein comprises one or more of serotonin transporter (SERT), 5HT2A, dopamine transporter (DAT), Beta 2 adrenergic receptor (Beta2 AR), NMDA receptor 2B subunit (NR2B), Pannexin 1 (PNX1), or Prion cellular protein (PrPc); comparing the membrane protein cluster count and membrane protein cluster size to a control; identifying, thereby diagnosing the subject, as at least one of: a) identifying the subject as having a schizophrenia phenotype based on the results of the comparing, b) identifying the subject as having a bipolar disorder phenotype based on the results of the comparing, c) identifying the subject as having a depression phenotype based on the results of the comparing, d) identifying the subject as having a D-I phenotype based on the results of the comparing, or e) identifying the subject as having a D-II phenotype based on the results of the comparing.

25. The method of claim 24, further comprising administering at least one of: a) administering a schizophrenia medicament to the subject identified as having the schizophrenia phenotype, b) administering a bipolar disorder medicament to the subject identified as having the bipolar disorder phenotype, c) administering a depression medicament to the subject identified as having the depression phenotype, d) administering a D-I phenotype medicament to the subject identified as having the D-I phenotype, or e) administering a D-II phenotype medicament to the subject identified as having the D-II phenotype.

26. The method of any one of claims 23-25, further comprising measuring a pre-culture membrane protein cluster count and pre-culture membrane protein cluster size from the lymphocytes.

27. The method of claim 26, wherein the control comprises the pre-culture membrane protein cluster count and the pre-culture membrane protein cluster size.

28. The method of claim 27, wherein: the identifying the subject as having the schizophrenia phenotype based on the results of the comparing comprises identifying the subject as having the schizophrenia phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size; the identifying the subject as having the bipolar disorder phenotype based on the results of the comparing comprises identifying the subject as having the bipolar disorder phenotype when (i) the membrane protein cluster count is decreased relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is substantially similar relative to the pre-culture membrane protein cluster size; the identifying the subject as having the depression phenotype based on the results of the comparing comprises identifying the subject as having the depression phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased or slightly decreased relative to the pre-culture membrane protein cluster size; the identifying the subject as having the D-I phenotype based on the results of the comparing comprises identifying the subject as having the D-I phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is slightly decreased relative to the pre-culture membrane protein cluster size; and / or the identifying the subject as having the D-II phenotype based on the results of the comparing comprises identifying the subject as having the D-II phenotype when (i) the membrane protein cluster count is substantially similar relative to the pre-culture membrane protein cluster count and (ii) the membrane protein cluster size is decreased relative to the pre-culture membrane protein cluster size.

29. The method of any one of claims 23-25, wherein the control comprises a historical control.

30. The method of any one of claims 23-29, wherein the subject was not receiving pharmaceutical treatment for a mood or psychotic disorder when the lymphocyte(s) were isolated from the subject.

31. The method of any one of claims 23-30, wherein:the schizophrenia medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the bipolar disorder medicament comprises an antidepressant, an antipsychotic, or a mood stabilizer; the D-I phenotype medicament comprises a tricyclic; the depression medicament comprises a tricyclic, a MAOI, an SSRI, an SNRI, a tetracyclic, a triazolopyridine, an aminoketone, an NMD AR antagonist, or a neurosteroid.

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