Cord blood markers and model for identifying early onset neonatal sepsis

Abstract

Disclosed are methods, kits, and models for identifying early onset sepsis (EOS) in a subject based on the levels of at least three proteins selected from CRP, EBP, SAA1, LRG1, and SERPINA3 or RNAs encoding said proteins.

Description

CORD BLOOD MARKERS AND MODEL FOR IDENTIFYING EARLY ONSETNEONATAL SEPSISCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of and priority to U.S. Provisional Application No. 63 / 642,385 filed on May 3, 2024. The contents of which are herein incorporated by reference in their entireties.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under grant number AI139337 awarded by the National Institutes of Health. The government has certain rights in the invention.BACKGROUND

[0003] Early-onset neonatal sepsis (EOS) results in significant morbidity and mortality with a disproportionate burden in preterm infants. Clinical management of EOS is complicated by underlying uncertainty in the diagnosis due to undifferentiated symptoms, common risk factors, and lack of timely, reliable diagnostics. This uncertainty drives early antibiotic use in infants with any suspicion of sepsis. Antibiotics are the most prescribed medication in neonatal intensive care units, with substantial variation by practice, and most antibiotic exposures occur in infants who have negative bacterial cultures (z.e., presumed, culture-negative sepsis). In addition to growing antimicrobial resistance, preterm neonates exposed to antibiotics without proven infection face increased near-term risks of fungal infection, late-onset sepsis, necrotizing enterocolitis, and death. Early antibiotic exposure may also cause long-term morbidity driven by resultant microbiome alterations (dysbiosis) and attendant immunologic and metabolic dysregulation. More accurate and timely diagnostics are needed to identify or rule out EOS in neonates to reduce the burden of antibiotic use in this vulnerable population.SUMMARY

[0004] In a first aspect, provided herein is a method comprising: (a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agentsdetect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPTNA3, or RNAs encoding said proteins; and (b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents. In embodiments, the at least three proteins or RNAs encoding said proteins are CRP, SAA1, and LBP. In embodiments, the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins.

[0005] In embodiments, detection agents are antibodies. In embodiments, the detection agents are nucleic acids reagents.

[0006] The subject may have at least one symptom of early-onset sepsis (EOS), or at least one risk factor for EOS. The sample may be obtained from the subject within 72 hours after its birth. In embodiments, the subject has not received antibiotic treatment for EOS before the sample is obtained.

[0007] In embodiments, the method further comprises treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to a control cord blood plasma sample from a control subj ect, wherein the control subj ect does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth. In embodiments, the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0008] In embodiments, the method further comprises: (c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and (d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth. In embodiments, the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0009] The method may further comprise treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to the levels of proteins or RNAs encoding said proteins in the control sample.

[0010] In another aspect, provided herein is a kit for detecting early-onset sepsis (EOS) in a subject, the kit comprising: a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding saidproteins. In embodiments, the panel of detection agents consists of detection agents that detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins. In embodiments, the detection agents detect each of the CRP, LBP, SAA1, LRG1, and SERPINA3 proteins or RNAs encoding said proteins. In some embodiments, the panel of detection agents consists of detection agents that detect each of the CRP, LBP, SAA1, LRG1 and SERPINA3 proteins, or RNAs encoding said proteins.

[0011] In embodiments, the detection agents are antibodies. The antibodies may be bound to a substrate. In embodiments, the detection agents are nucleic acid reagents.

[0012] The kit may further comprise a control sample, the control sample comprising a cord blood plasma sample obtained from a subject that does not have EOS, wherein the sample is obtained from the subject within the first 72 hours after its birth. The control sample may be stored at about -80°C.

[0013] In another aspect, provided herein is a method comprising: collecting biomarker data from a cord blood plasma sample obtained from a subject, wherein the biomarker data are collected by measuring levels of at least three proteins selected from CRP, LBP, SAA1, LRG1, and SERPINA3, or RNAs encoding said proteins in the cord blood plasma sample; obtaining clinical data for the subject, wherein the clinical data comprise at least one of gestational age, sex, route of delivery, presence of clinical chorioamnionitis, prolonged rupture of membranes, multiple gestation, and preeclampsia; and predicting the likelihood of EOS in the subject by inputting the biomarker data and the clinical data to a random forest classifier model, generating an output as a predictive score indicating a likelihood of EOS in the subject based on the clinical data and the measured levels of protein or RNAs encoding said proteins in the cord blood plasma sample.

[0014] Measuring the levels of the at least three proteins may comprise: (a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect at the least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and (b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents. The at least three proteins are CRP, SAA1, and LBP. In embodiments, the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins. Inembodiments, the detection agents are antibodies. In embodiments, the detection agents are nucleic acids reagents.

[0015] The subject has at least one symptom of early-onset sepsis (EOS), or at least one risk factor of EOS. The sample may be obtained from the subject within 72 hours after its birth. In embodiments, the subject has not received antibiotic treatment for EOS before the sample is obtained.

[0016] The method may further comprise (c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and (d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth. In embodiments, the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0017] The method may further comprise treating the subject for EOS if the predictive score indicates a likelihood of EOS.BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIGS. 1A-1C. Proteomic identification of differentially abundant proteins in early onset sepsis cord blood. FIG. 1A. Diagram of workflow. FIG. IB. Hierarchically clustered heat map of protein abundance in cord blood for EOS and control specimens. Specimens are clustered by gestational age category, sex, and sample type. Missing values were imputed. FIG. 1C. Plot of mean abundance of proteins in EOS and control specimens. Black points were significant by Mann-Whitney U test with Benjamini -Hochberg false discovery rate adjustment (p < 0.05).

[0019] FIGS. 2A-2C. Details of differentially abundant proteins. FIG. 2A. PCA and FIG. 2B. clustered heatmap of EOS and control specimen values for the five differentially abundant proteins. For FIG. 2B, missing protein abundance values were imputed. FIG. 2C. Distribution of protein abundance in EOS and control specimens for each protein. Box plots show median and interquartile range. Whiskers extend to the last point within 1.5x interquartile range of the box. Bee swarms show individual samples. Comparisons were significant by Mann-Whitney U test with Benjamini-Hochberg false discovery rate adjustment.

[0020] FIGS. 3A-3C. Quantitative multiplex immunoassay detection of potential EOS biomarkers. FIG. 3 A. Diagram of experimental procedure. FIG. 3B. Distribution of protein concentration inmg / mL in EOS and control specimens for each protein. Box plots show median and interquartile range. Whiskers extend to the last point within 1.5x interquartile range of the box. Bee swarms show individual samples. Comparisons were significant by Mann-Whitney U test with Benjamini- Hochberg false discovery rate adjustment. FIG. 3C. PCA of EOS and control specimen protein abundance based on MSD data.

[0021] FIGS. 4A-4B. Modeling of EOS risk using biomarkers. FIG. 4A. Model fit parameters for random forests models trained with (amber) or without (black) cord blood biomarker concentrations as a factor. Metrics are calculated with EOS as the positive class. Points represent performance for a single run of the model. Box plots show the median and interquartile range. Whiskers extend to the last point within the 1.5x interquartile range of the box. FIG. 4B. Permutation variable importance for variables in the random forest model with cord blood biomarker concentrations included. Box plots show median and interquartile range. Whiskers extend to the last point within 1.5x interquartile range of the box. Points mark outliers.

[0022] FIGS. 5A-5B. Presumed sepsis cases categorized by random forest model. Biomarker concentrations in cord blood from presumed sepsis cases were measured by immunoassay; cases were then categorized as either predicted EOS (pEOS) or predicted control (pControl). FIG. 5A. PCA plot of biomarker concentrations in cases colored by status. FIG. 5B. concentration of biomarker proteins in predicted EOS and predicted control cases. Box plots show median and interquartile range. Whiskers extend to the last point within the 1.5x interquartile range of the box. Points are individual samples. Wide red lines show the median value for ascertained EOS cases; wide blue lines show the median value for ascertained controls. Comparisons were significant by Mann-Whitney U test with Benjamini -Hochberg false discovery rate adjustment.

[0023] FIG. 6. Non-imputed heat map of protein abundance. Hierarchically clustered heat map of protein abundance in cord blood for EOS and control specimens. Proteins with missing mass spectrometry data were imputed with zeroes. Specimens are clustered by gestational age category, sex, and sample type.

[0024] FIG. 7. Correlation of variables. Heat map of Spearman’s rho of variables used for modelling of EOS risk.DETAILED DESCRIPTION

[0025] This disclosure provides methods related to diagnosing early-onset sepsis in a subject. Early-onset sepsis (EOS) is a condition in which a subject has systemic dysfunction caused by a dysregulated host response to infection. Systemic dysfunction may result in clinical or laboratory abnormalities. The abnormalities can include symptoms of infection and / or systemic dysfunction. The inventors have found five cord blood biomarkers for risk stratifying infants for EOS. Identification of EOS in a subject using the methods and kits for identifying these biomarkers described herein is less invasive than traditional approaches and allows for medical intervention without overusing antibiotics in the treatment of subjects with presumed cases of EOS.

[0026] In a first aspect, this disclosure provides methods for identifying biomarkers for EOS in a sample. The method comprises (a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and (b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents.

[0027] Cord blood plasma is the liquid portion of umbilical cord blood. Cord blood plasma from a subject may be isolated from cord blood according to methods known in the art. The sample may be obtained at the time of delivery of the subject when the umbilical cord is clamped.

[0028] As used herein, the terms “measure” and “measuring” refer to identifying a quantitative level of the material to be measured. As used herein, the term measuring with regard to a protein refers to both detecting and determining a relative and / or absolute amount of the protein in a sample. Standard detection and measuring methods for proteins include, but are not limited to, immunoassays, including quantitative immunoassays, radioisotope immunoassay, an enzyme- linked immunosorbent assay (ELISA), flow cytometry, SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies), mass spectrometry, immunofluorescence assays, Western blot, affinity chromatography (e.g. affinity ligand bound to a solid phase), fluorescent antibody assays, immunochromatography, and in situ detection with labeled antibodies. As used herein, the term measuring with regard to RNA refers to both detecting and determining a relative and / or absolute amount of the RNA in a sample. Standard detection and measuring methods for RNA include, but are not limited to, reverse transcription polymerase chain reaction (RT-PCR),including quantitative RT-PCR (RT-qPCR), Northern blotting, nuclease protection assay (NPA), in situ hybridization, and RNA sequencing.

[0029] C-reactive protein (CRP) is a ring-shaped pentameric protein found in blood plasma, whose circulating concentrations rise in response to inflammation. Lipopolysaccharide-binding protein (LBP) is a soluble acute-phase protein that binds to bacterial lipopolysaccharide to elicit immune responses. Serum amyloid Al (SAA1) is a major acute-phase protein mainly produced by hepatocytes in response to infection, tissue injury, and malignancy. Leucine-rich alpha-2- glycoprotein 1 (LRG1) is a protein involved in promoting neovascularization. Serine proteinase inhibitor A3 (SERPINA3) is a protease inhibitor that plays a role in inflammation and antiviral response.

[0030] In embodiments, the at least three proteins or RNAs encoding said proteins are CRP, SAA1, and LBP. In embodiments, the method comprises measuring only CRP, SAA1, and LBP.

[0031] In embodiments, the detection agents detect at least four of CRP, LBP, SAA1, and LRG1 proteins or RNAs encoding said proteins; and step (b) comprises measuring the levels of at least four of CRP, LBP, SAA1, SERPINA3 and LRG1 proteins or RNAs encoding said proteins. In embodiments, the method comprises measuring only four of CRP, LBP, SAA1, SERPINA3 and LRG1.

[0032] In other embodiments, the detection agents detect each of CRP, LBP, SAA1, and LRG1 proteins or RNAs encoding said proteins; and step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3 and LRG1 proteins or RNAs encoding said proteins. In embodiments, the method comprises measuring only CRP, LBP, SAA1, SERPINA3 and LRG1.

[0033] As used herein, the terms “protein” or “polypeptide” or “peptide” may be used interchangeably to refer to a polymer of amino acids. Typically, a “polypeptide” or “protein” is defined as a longer polymer of amino acids, of a length typically of greater than 50, 60, 70, 80, 90, or 100 amino acids. A “peptide” is defined as a short polymer of amino acids, of a length typically of 50, 40, 30, 20 or less amino acids.

[0034] A “protein” as contemplated herein typically comprises a polymer of naturally or non- naturally occurring amino acids (e.g., alanine, arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine). The proteins contemplated herein may be further modified in vitro or in vivo to include non-amino acid moieties. These modificationsmay include but are not limited to acylation (e.g., O-acylation (esters), N-acylation (amides), S- acylation (thioesters)), acetylation (e.g., the addition of an acetyl group, either at the N-terminus of the protein or at lysine residues), formylation lipoylation (e.g., attachment of a lipoate, a C8 functional group), myristoylation (e.g., attachment of myristate, a C14 saturated acid), palmitoylation (e.g., attachment of palmitate, a C16 saturated acid), alkylation (e.g., the addition of an alkyl group, such as an methyl at a lysine or arginine residue), isoprenylation or prenylation (e.g., the addition of an isoprenoid group such as farnesol or geranylgeraniol), amidation at C- terminus, glycosylation (e.g., the addition of a glycosyl group to either asparagine, hydroxy lysine, serine, or threonine, resulting in a glycoprotein). Distinct from glycation, which is regarded as a nonenzymatic attachment of sugars, polysialylation (e.g., the addition of polysialic acid), glypiation (e.g., glycosylphosphatidylinositol (GPI) anchor formation, hydroxylation, iodination (e.g., of thyroid hormones), and phosphorylation (e.g., the addition of a phosphate group, usually to serine, tyrosine, threonine or histidine).

[0035] The term “amino acid residue” also may include amino acid residues contained in the group consisting of homocysteine, 2-Aminoadipic acid, N-Ethylasparagine, 3-Aminoadipic acid, Hydroxylysine, P-alanine, P-Amino-propionic acid, allo-Hydroxylysine acid, 2-Aminobutyric acid, 3 -Hydroxyproline, 4-Aminobutyric acid, 4-Hydroxyproline, piperidinic acid, 6- Aminocaproic acid, Isodesmosine, 2-Aminoheptanoic acid, allo-Isoleucine, 2-Aminoisobutyric acid, N-Methylglycine, sarcosine, 3-Aminoisobutyric acid, N-Methylisoleucine, 2-Aminopimelic acid, 6-N-Methyllysine, 2,4-Diaminobutyric acid, N-Methylvaline, Desmosine, Norvaline, 2,2'- Diaminopimelic acid, Norleucine, 2,3 -Diaminopropionic acid, Ornithine, and N-Ethylglycine.

[0036] As used herein, the term "nucleic acid" or "polynucleotide" refers to deoxyribonucleic acid (DNA), ribonucleic acid (RNA) and DNA / RNA hybrids. Polynucleotides may be single- stranded or double-stranded. RNA includes, but is not limited to, pre-messenger RNA (pre-mRNA) and messenger RNA (mRNA).

[0037] As used herein, the term “detection agent” refers to any agent suitable for detecting the presence of a protein or an RNA. The panel of detection agents may include at least one agent suitable for detecting the presence of a protein, at least one agent suitable for detecting an RNA, or both at least one agent suitable for detecting the presence of a protein and at least one agent suitable for detecting an RNA.

[0038] In embodiments, the detection agent is an antibody.

[0039] As used herein, the term "antibody" refers to a naturally occurring immunoglobulin molecule with varying structures. Typically, antibodies are gamma globulin proteins that can be found in blood or other bodily fluids of vertebrates and are used by the immune system to identify foreign materials, such as bacteria, viruses, and toxins. Antibodies bind, by non-covalent interactions, with high affinity to other molecules or structures known as antigens. This binding is specific in the sense that an antibody molecule will only bind to a specific structure with high affinity. The unique part of the antigen recognized by an antibody molecule is called an epitope, or antigenic determinant. The part of the antibody molecule binding to the epitope is sometimes called paratope and resides in the so-called variable domain, or variable region (Fv) of the antibody. The variable domain comprises three complementary-determining regions (CDR's) spaced apart by framework regions (FR's). There are at least five major classes of antibodies: IgA, IgD, IgE, IgG, and IgM, and several of these may be further divided into subclasses (isotypes), e.g. , IgGl, IgG2, IgG3, IgG4, IgAl, and IgA2. They are typically made of basic structural units — each with two large heavy chains and two small light chains — to form, for example, monomers with one unit, dimers with two units or pentamers with five units. Non-limiting examples of antibodies include any known class and / or isotype, such as, e.g., IgA (e.g. IgAl, IgA2, and slgA), IgD, IgE, IgG (e.g. IgGl, IgG2, IgG3, or IgG4), and IgM. The “class” of an antibody may refer to the type of constant domain or constant region possessed by its heavy chain. For example, heavy chain constant domains may be used to classify different classes of immunoglobulins, such as, e g., a, y, 6, 8, and p. The light chain of an antibody may be assigned to certain types, e g. kappa and lambda, based on the amino acid sequence of its constant domain. In some embodiments, the antibody being measured is IgA or IgG. The antibody may be multi-specific, e.g. bispecific, trispecific, and may detect more than one of CRP, LBP, SAA1, LRG1 and SERPINA3.

[0040] In embodiments, the detection agent is a nucleic acid reagent. As used herein, the term “nucleic acid reagents” comprise reagents suitable for detecting an RNA by any suitable RNA detection and / or quantification methods. In embodiments, the nucleic acid reagents include primers and / or probes. As used herein, “primer” refers to a single-stranded polynucleotide or analog thereof that is capable of selectively hybridizing to a target nucleic acid or “template”, a target region flanking sequence or to a corresponding primer-binding site of an amplification product; from which the synthesis of a sequence complementary to the corresponding polynucleotide template may begin. Typically, a primer can be between about 10 to 100nucleotides in length and can provide a point of initiation for template-directed synthesis of a polynucleotide complementary to the template, which can take place in the presence of appropriate enzyme(s), cofactors, substrates such as nucleotides (dNTPs) and the like. The term “probe” as used herein refers to a polynucleotide that comprises a specific portion designed to hybridize in a sequence-specific manner with a complementary region of a specific nucleic acid sequence, e.g., a target nucleic acid sequence. The probe may be labeled, such as with a fluorescent probe.

[0041] The term “subject” or “patient” are used herein interchangeably to refer to a mammal. “Mammals” means any member of the class Mammalia including, but not limited to, humans, nonhuman primates such as chimpanzees and other apes and monkey species; farm animals such as cattle, horses, sheep, goats, and swine; domestic animals such as rabbits, dogs, and cats; laboratory animals including rodents, such as rats, mice, and guinea pigs; and the like. The subject may be a human.

[0042] The subject may have at least one symptom of EOS. The symptoms may include, but are not limited to, fever; irregular heart rate; irregular breathing; vomiting; diarrhea; reduced feeding; swollen abdomen; cold hands and feet; clammy skin; jaundice; and reduced activity.

[0043] The subject may have at least one risk factor for EOS. Risk factors for EOS include, but are not limited to: maternal factors such as maternal infections, maternal fever, chorioamnionitis, premature rupture of membranes (PROM), and low maternal age (e.g. less than 20 years); neonatal factors such as preterm birth, low birthweight, low apgar score (e.g. below 7 at 5 minutes), and prolonged hospitalization; and delivery-related factors such as multiple gestation and cesarean section. The subject may have both at least one symptom and at least one risk factor for EOS.

[0044] The sample may be obtained from the subject within 72 hours after its birth. In embodiments, the subject has not received antibiotic treatment for EOS before the sample is obtained. In such embodiments described herein, while the subject has not been directly treated for EOS, in some cases, the subject may have indirectly received antibiotics given to its mother during labor.

[0045] The method may further comprise treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to a control cord blood plasma sample from a control subject, wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth. In embodiments, the control subject has not received antibiotic treatment for EOS before the controlcord blood plasma sample is obtained. A control subject may be of the same species as the subject under examination.

[0046] The term “elevated” refers to an increased level of a protein or an RNA encoding said protein in the subject in comparison to the level of the protein or RNA encoding said protein in the control subject. Elevated levels may be observed in one or more proteins or RNAs encoding said proteins when compared to the control sample. In some examples, the SAA concentration is about 490 pg / mL; the LBP concentration is about 35 pg / mL; and the CRP is about 325 pg / mL.

[0047] In embodiments, the method further comprises: (c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and (d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth. In embodiments, the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0048] The method may further comprise treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to the levels of proteins or RNAs encoding said proteins in the control sample. Treatment for EOS includes, but is not limited to, administration of antibiotics.

[0049] As used herein, the terms “treat,” “treatment,” and “treating” refer to reducing the amount or severity of a particular condition, disease state, or symptoms thereof, in a subject presently experiencing or afflicted with the condition or disease state. The terms do not necessarily indicate complete treatment (e.g., total elimination of the condition, disease, or symptoms thereof). "Treatment,” encompasses any administration or application of a therapeutic or technique for a disease (e.g., in a mammal, including a human), and includes inhibiting the disease, arresting its development, relieving the disease, causing regression, or restoring or repairing a lost, missing, or defective function; or stimulating an inefficient process. As used herein, the term "administering" an agent, such as a therapeutic entity to an animal or cell, is intended to refer to dispensing, delivering or applying the substance to the intended target.

[0050] In a second aspect, provided herein is a kit for detecting early-onset sepsis (EOS) in a subject, the kit comprising: a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1, and SERPINA3, or RNAs encoding said proteins. In some embodiments, the panel of detection agents consists of detection agents thatdetect at least three proteins selected from CRP, LBP, SAA1, LRG1 , and SERPTNA3, or RNAs encoding said proteins. In embodiments, the detection agents detect at least four of the CRP, LBP, SAA1, LRG1, and SERPINA3 proteins or RNAs encoding said proteins. In embodiments, the detection agents detect each of the CRP, LBP, SAA1, LRG1, and SERPINA3 proteins or RNAs encoding said proteins. In embodiments, the detection agents consist of agents that detect at least three of, at least four of, or each of CRP, LBP, SAA1, LRG1 and SERPINA3. In embodiments, the detection agents comprise or consist of agents that detect CRP, SAA1, and LBP.

[0051] The detection agents may include at least one antibody. The detection agents may include at least one nucleic acid reagent. The detection agents in the kit may comprise both at least one antibody and at least one nucleic acid reagent. In embodiments wherein the detection agent is an antibody, the antibody may be bound to a substrate. As used herein, the term “substrate” refers to a surface to which the antibody can be bound, either reversibly or irreversibly. Non-limiting examples of substrates include, without limitation, a bead, plate, slide, flow chamber, chip, cartridge, flow cell, etc. The solid support may be formed from glass, ceramic, polymers (e.g., plastic, latex, polystyrene, polyacrylamide, polyvinylchloride, polypropylene, polyethylene, polylactic acid), cellulose (e.g., paper).

[0052] The kit may further comprise a control sample, the control sample comprising a cord blood plasma sample obtained from a subject that does not have EOS, wherein the sample is obtained from the subject within the first 72 hours after its birth. The control sample may be stored at about -80°C.

[0053] In embodiments, a diagnostic model is used to combine clinical and biomarker data for EOS detection. The diagnostic model may utilize a random forest classifier to integrate multiple inputs and generate a prediction of EOS. As an example, the random forest classifier may include an ensemble of decision trees. Each decision tree in the forest may be trained on a random subset of the input features and data samples.

[0054] When constructing individual decision trees, a random subset of features may be considered at each split point. This feature randomness may help to decorrelate the trees and further reduce overfitting. The number of features considered at each split may be a hyperparameter that can be tuned. In some implementations, the random forest classifier used for EOS diagnosis may contain 50-100 decision trees. The maximum depth of the trees may be limited to 4-6 levels to prevent overfitting. Each leaf node may be required to contain at least 2-3 samples. The randomforest classifier may handle class imbalance by assigning higher weights to a minority class during training. For example, EOS cases may be given 10 times the weight of control cases.

[0055] To determine the importance of different features, the random forest classifier may use a technique called permutation importance. This technique may randomly shuffle the values of a single feature and measure the resulting decrease in model performance. Features that lead to larger decreases in performance when permuted may be considered more important.

[0056] Inputs to the diagnostic model may include both clinical variables and biomarker measurements. The clinical data inputs may include gestational age, sex, route of delivery, presence of clinical chorioamnionitis, prolonged rupture of membranes, multiple gestation, and preeclampsia. Gestational age may be provided in weeks. Sex may be encoded as a binary variable (e.g., male orfemale). Route of delivery may be categorized as vaginal delivery, caesarean delivery with labor, or caesarean delivery without labor. The presence of clinical chorioamnionitis, prolonged rupture of membranes, multiple gestation, and preeclampsia may each be encoded as binary variables (e.g., present or not present). Prolonged rupture of membranes may be more specific to hours of rupture. The biomarker inputs may include quantitative measurements of at least three of CRP, LBP, SAA1, LRG1, and SERPINA3, or RNAs encoding said proteins in the cord blood sample. In some cases, these biomarker concentrations may be measured in picograms per milliliter.

[0057] Prior to input into the model, the clinical and biomarker data may undergo preprocessing. Categorical variables like sex and route of delivery may be one-hot encoded. Continuous variables such as gestational age and biomarker concentrations may be normalized using techniques like z- score normalization or min-max scaling to ensure all inputs are on a similar scale. In some cases, biomarker concentrations may undergo log transformation to account for potential non-linear relationships. Missing data may be handled through imputation techniques. For clinical variables, mode imputation may be used for categorical variables and median imputation for continuous variables. For biomarker measurements below the limit of detection, values may be imputed as half the lower limit of quantification.

[0058] In some implementations, feature selection techniques may be applied to identify the most informative subset of clinical and biomarker inputs. This may involve methods such as recursive feature elimination or principal component analysis to reduce dimensionality while retaining predictive power.

[0059] The preprocessed and selected features may then be combined into a single input vector for each subject, which may be fed into the diagnostic model for early-onset sepsis prediction. To make a prediction on new data, the random forest classifier may pass the input through each decision tree in the forest. Each tree may independently make a prediction. The final prediction of the random forest may then be determined by taking a majority vote of the predictions from all the trees for classification tasks.

[0060] The output of the random forest classifier may be a probability score indicating the likelihood of EOS. These scores may represent the model's confidence in its prediction, with values closer to 1 indicating higher confidence of EOS presence and values closer to 0 indicating higher confidence of EOS absence.

[0061] In some cases, the random forest classifier may output a binary classification result indicating whether EOS is predicted to be present or absent for a given input sample. The model may produce this classification by aggregating votes from multiple decision trees in the forest. Additionally or alternatively, a threshold may be applied to probability scores generated by the random forest classifier to generate a binary classification of EOS or no EOS.

[0062] In some implementations, the model may provide feature importance scores for the input variables used in classification. These scores may indicate the relative contribution of each feature (e.g., biomarker concentrations or clinical factors) to the decision-making process of the random forest classifier. Features with higher importance scores may have greater influence on the final classification output.

[0063] Miscellaneous

[0064] As used in this specification and the claims, the singular forms “a,” “an,” and “the” include plural forms unless the context clearly dictates otherwise. Thus, the indefinite articles "a" and "an," as used herein in the specification and in the claims should be understood to mean "at least one", unless clearly indicated to the contrary.

[0065] As used herein, “about”, “approximately,” “substantially,” and “significantly” will be understood by persons of ordinary skill in the art and will vary to some extent on the context in which they are used. If there are uses of the term which are not clear to persons of ordinary skill in the art given the context in which it is used, “about” and “approximately” will mean up to plus or minus 10% of the particular term and “substantially” and “significantly” will mean more thanplus or minus 10% of the particular term. Where ranges are stated, the endpoints are included within the range unless otherwise stated or otherwise evident from the context.

[0066] The phrase “such as” should be interpreted as “for example, including.” Moreover, the use of any and all exemplary language, including but not limited to “such as”, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.

[0067] In those instances where a convention analogous to “at least one of A, B and C, etc.” is used, in general such a construction is intended in the sense of one having ordinary skill in the art would understand the convention (e.g., “a system having at least one of A, B and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together.). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description or figures, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or ‘B or “A and B.” Multiple elements listed with "and / or" should be construed in the same fashion, i.e., "one or more" of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the "and / or" clause, whether related or unrelated to those elements specifically identified.

[0068] As used herein in the specification and in the claims, "or" should be understood to have the same meaning as "and / or" as defined above. For example, when separating items in a list, "or" or "and / or" shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as "only one of or "exactly one of," or, when used in the claims, "consisting of," will refer to the inclusion of exactly one element of a number or list of elements. In general, the term "or" as used herein shall only be interpreted as indicating exclusive alternatives (i.e. "one or the other but not both") when preceded by terms of exclusivity, such as "either," "one of," "only one of," or "exactly one of "Consisting essentially of," when used in the claims, shall have its ordinary meaning as used in the field of patent law.

[0069] All language such as “up to,” “at least,” “greater than,” “less than,” and the like, include the number recited and refer to ranges which can subsequently be broken down into ranges and subranges. A range includes each individual member. Thus, for example, a group having 1-3members refers to groups having 1 , 2, or 3 members. Similarly, a group having 6 members refers to groups having 1, 2, 3, 4, or 6 members, and so forth.

[0070] The modal verb “may” refers to the preferred use or selection of one or more options or choices among the several described embodiments or features contained within the same. Where no options or choices are disclosed regarding a particular embodiment or feature contained in the same, the modal verb “may” refers to an affirmative act regarding how to make or use and aspect of a described embodiment or feature contained in the same, or a definitive decision to use a specific skill regarding a described embodiment or feature contained in the same. In this latter context, the modal verb “may” has the same meaning and connotation as the auxiliary verb “can.”

[0071] In the foregoing description, it will be readily apparent to one skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention. Thus, it should be understood that although the present invention has been illustrated by specific embodiments and optional features, modification and / or variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention. It should be understood that descriptions of exemplary embodiments are not intended to limit the invention to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the invention as defined by the appended claims. It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context.EMBODIMENTS

[0072] Embodiment 1. A method comprising: (a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and (b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents.

[0073] Embodiment 2. The method of embodiment 1, wherein the at least three proteins or RNAs encoding said proteins are CRP, SAA1, and LBP.

[0074] Embodiment 3. The method of embodiment 1 or 2, wherein the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and wherein step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins.

[0075] Embodiment 4. The method of any one of embodiments 1-3, wherein the detection agents are antibodies.

[0076] Embodiment 5. The method of any one of embodiments 1-3, wherein the detection agents are nucleic acids reagents.

[0077] Embodiment 6. The method of any one of embodiments 1-5, wherein the subject has at least one symptom of early-onset sepsis (EOS).

[0078] Embodiment 7. The method of any one of embodiments 1-6, wherein the sample is obtained from the subject within 72 hours after its birth.

[0079] Embodiment 8. The method of any one of embodiments 1-7, wherein the subject has not received antibiotic treatment for EOS before the sample is obtained.

[0080] Embodiment 9. The method of any one of embodiments 1-8, further comprising treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to a control cord blood plasma sample from a control subject, wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

[0081] Embodiment 10. The method of embodiment 9, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0082] Embodiment 11. The method of any one of embodiments 1-8, further comprising: (c) contacting a control cord blood plasma sample obtained from a control subject with the panel ofdetection agents, and (d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

[0083] Embodiment 12. The method of embodiment 11, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0084] Embodiment 13. The method of embodiment 11 or 12, further comprising treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to the levels of proteins or RNAs encoding said proteins in the control sample.

[0085] Embodiment 14. A kit for detecting early-onset sepsis (EOS) in a subject, the kit comprising: a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins.

[0086] Embodiment 15. The kit of embodiment 14, wherein the panel of detection agents consists of detection agents that detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins.

[0087] Embodiment 16. The kit of embodiment 14, wherein the detection agents detect each of the CRP, LBP, SAA1, LRG1, and SERPINA3 proteins or RNAs encoding said proteins.

[0088] Embodiment 17. The kit of embodiment 16, wherein the panel of detection agents consists of detection agents that detect each of the CRP, LBP, SAA1, LRG1 and SERPINA3 proteins, or RNAs encoding said proteins.

[0089] Embodiment 18. The kit of any one of embodiments 14-17, wherein the detection agents are antibodies.

[0090] Embodiment 19. The kit of embodiment 18, wherein the antibodies are bound to a substrate.

[0091] Embodiment 20. The kit of any one of embodiments 14-17, wherein the detection agents are nucleic acid reagents.

[0092] Embodiment 21. The kit of any one of claims 14-20, further comprising a control sample, the control sample comprising a cord blood plasma sample obtained from a subject that does not have EOS, wherein the sample is obtained from the subject within the first 72 hours after its birth.

[0093] Embodiment 22. The kit of claim 21, wherein the control sample is stored at about -80°C.

[0094] Embodiment 23. A method comprising: collecting biomarker data from a cord blood plasma sample obtained from a subject, wherein the biomarker data are collected by measuring levels of at least three proteins selected from CRP, LBP, SAA1, LRG1, and SERPINA3, or RNAs encoding said proteins in the cord blood plasma sample; obtaining clinical data for the subject, wherein the clinical data comprise at least one of gestational age, sex, route of delivery, presence of clinical chorioamnionitis, prolonged rupture of membranes, multiple gestation, and preeclampsia; and predicting the likelihood of EOS in the subject by inputting the biomarker data and the clinical data to a random forest classifier model, generating an output as a predictive score indicating a likelihood of EOS in the subject based on the clinical data and the measured levels of protein or RNAs encoding said proteins in the cord blood plasma sample.

[0095] Embodiment 24. The method of embodiment 23, wherein measuring the levels of the at least three proteins comprises: (a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and (b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents.

[0096] Embodiment 25. The method of embodiment 23 or 24, wherein the at least three proteins are CRP, SAA1, and LBP.

[0097] Embodiment 26. The method of embodiment 24 or 25, wherein the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and wherein step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins.

[0098] Embodiment 27. The method of any one of embodiments 24-26, wherein the detection agents are antibodies.

[0099] Embodiment 28. The method of any one of embodiments 24-26, wherein the detection agents are nucleic acids reagents.

[0100] Embodiment 29. The method of any one of embodiments 23-28, wherein the subject has at least one symptom of early-onset sepsis (EOS), or at least one risk factor of EOS.

[0101] Embodiment 30. The method of any one of embodiments 23-29, wherein the sample is obtained from the subject within 72 hours after its birth.

[0102] Embodiment 31. The method of any one of embodiments 23-30, wherein the subject has not received antibiotic treatment for EOS before the sample is obtained.

[0103] Embodiment 32. The method of any one of embodiments 24-31, further comprising: (c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and (d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

[0104] Embodiment 33. The method of e mbodiment 32, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

[0105] Embodiment 34. The method of any one of embodiments 23-33, further comprising treating the subject for EOS if the predictive score indicates a likelihood of EOS.EXAMPLES

[0106] The following examples are illustrative and should not be interpreted to limit the scope of the claimed subject matter.

[0107] Several approaches to improve the rapid, accurate diagnosis of early-onset neonatal sepsis (EOS) have been devised15,16. Molecular pathogen diagnostics and placental pathology are valuable tools; however, they often suffer from delays in result times, low positive predictive value, and limited availability.17. Laboratory markers of infection, including hematologic indices and markers of inflammation [such as C-reactive Protein (CRP) and procalcitonin]18have poor specificity and can be elevated due to non-infectious causes early in life, potentially leading to overtreatment with antibiotics19,20. Vital signs and heart rate variability monitoring algorithms have shown some benefits in triggering evaluations for late-onset sepsis occurring after the first 72 hours of life but not for EOS21,22. More holistic tools for risk assessment have also been developed. For example, the Kaiser Permanente Sepsis calculator accounts for various clinical risk factors, including intrapartum antibiotic prophylaxis, duration of rupture of membranes, gestational age, and clinical status. This tool has reduced antibiotic exposure for newborns but can only be applied to infants greater than 34 weeks gestational age (GA) at birth, excluding low birth weight or more preterm infants who are at highest risk of EOS, EOS-related morbidity and mortality, and harms of antibiotic overuse23.

[0108] Several studies have investigated specific markers in umbilical cord blood that might improve the diagnosis of EOS. In most cases of EOS, an ascending infection typically affects the placenta, amniotic fluid, and fetus prior to birth, especially in the setting of spontaneous preterm labor. Umbilical cord blood reflects the intrauterine environment where EOS is seeded and the infant’s state at birth, unaffected by postnatal stressors and physiology. This, along with the ready availability of cord blood, makes it an attractive target for diagnostics. Previous studies by our group have demonstrated elevated levels of CRP, serum amyloid A (SAA), and haptoglobin in culture-proven EOS and in a small subset of presumed sepsis (PS) cases24. Premature expression of haptoglobin in cord blood was similarly associated with EOS by another group23. Other studies have implicated potential biomarkers, including presepsin (a soluble CD 14 fragment released by myeloid cells during an immunological response) and CD6426’28. However, this research was limited to investigating a priori-se ec A markers and pooled analysis of culture-proven EOS and presumed sepsis (PS) specimens.

[0109] Our objective was to use unbiased mass spectrometry proteomics to identify proteins that were differentially abundant in cord blood of infants with EOS compared to infants without EOS. After immunoassay validation, these data were used to develop a machine learning diagnostic model incorporating cord blood biomarkers and clinical factors to accurately identify and rule out EOS in newborn infants.

[0110] Results

[0111] Identification of EOS biomarkers in cord blood. To identify potential cord blood biomarkers of EOS, we selected three cohorts of neonates with banked cord blood from a prospective study of infants bom at Northwestern Prentice Women’s Hospital between 2008 and 2019: 14 who were treated for microbially-confirmed EOS, 56 who were treated for EOS with negative culture results (presumed sepsis, PS), and 150 control infants with no suspicion of sepsis (cohort previously described29). EOS infants had clinical sepsis defined by blood culture positivity with a true EOS pathogen (i.e., not a coagulase-negative staphylococcal species, corynebacterium, or other nonpathogenic species) within the first 72 hours of life and were treated with a >7-day antibiotic course. Presumed sepsis infants had clinical illness and no positive cultures (either blood, cerebrospinal fluid, or respiratory), yet received a >7-day antibiotic treatment course for culturenegative presumed EOS. Control infants had no positive culture and received no antibiotic treatment course within the first 72 hours of life. Infants with a positive culture soon after 72 hours(i.e., within the first week of life) or with congenital abnormalities, such as cardiac anomalies or diaphragmatic hernia, were excluded from this analysis. Presumed sepsis infants were frequency- matched within the cohort by gestational age (±2 weeks), route of delivery, and sex (Table 1).

[0112] Table 1. Demographics and clinical covariates.

[0113] Among the EOS cohort, known risk factors for EOS development were overrepresented. EOS infants had lower gestational ages as compared to the control cohort (mean 30.7±3.3 weeks vs. 33.6±4.5 weeks; 0% >37 weeks vs. 27% of controls) and were less frequently female (36% female vs. 49% female). Chorioamnionitis (43% vs. 0.7%), prolonged rupture of membranes(PROM) (64% vs. 1 1.3%), and vaginal delivery (71% vs. 51%) were likewise more common in EOS patients compared to controls. The PS cohort resembled the EOS cohort with a greater frequency of prematurity, chori oamnionitis, and PROM than the controls. Confirmed pathogens in blood culture included Escherichia coli (n=8), Streptococcus agalactiae (n=2), Klebsiella oxytoca (n=l), Proteus mirabilis (n=l), Haemophilus influenzae (n=l), and Listeria monocytogenes (n=l).

[0114] To assess protein abundance, we performed liquid chromatography with tandem mass spectrometry (LC-MS-MS) on sera isolated from frozen, banked blood specimens from our control and EOS cohorts (FIG. 1A). Spectra were analyzed using MaxQuant for label-free quantification of protein abundance29. Peptides corresponding to 437 proteins were detected. After batch normalization, we visualized the protein abundance of the 255 most commonly detected proteins (present in >20% of specimens) across all 164 specimens using a hierarchically clustered heat map. Missing values were imputed separately for EOS and control specimens either by iterative imputation for proteins in >70% or by sampling from the lowest decile of protein abundance for proteins in <70% of specimens. When visualized using hierarchical clustering, there are no clear changes in the serum proteome that cluster by gestational age, sex, or specimen type (i.e., EOS or control) (FIG. IB). Clustering with naive imputation of zeros for all missing values revealed similar results (FIG. 6).

[0115] These data suggest that any changes in the serum proteome during EOS would be driven by a small number of proteins as opposed to global restructuring. To assess per protein changes in abundance, we plotted the mean abundance of each of the 255 most commonly detected proteins in our control specimens versus our EOS specimens (FIG. 1C). Five proteins were significantly enriched in the serum of infants with culture-confirmed EOS: CRP, lipopolysaccharide-binding protein (LBP), SAA1, leucine-rich alpha-2-glycoprotein 1 (LRG1), and serine proteinase inhibitor A3 (SERPINA3) (FIG. 1C). These are all acute phase reactant proteins that are upregulated in the serum in response to inflammation. A sensitivity analysis was performed repeating differential abundance analysis between EOS specimens and gestational age-matched controls (excluding the full-term group >37 weeks gestation), and the results were consistent with the same 5 proteins significantly elevated in the EOS specimens. Due to the small number of female infants with EOS (n = 4), statistical power was not adequate to detect differences of plausible magnitude for each sex.

[0116] As EOS specimens were much fewer than control specimens, proteins found exclusively or predominantly in EOS cord blood could be excluded by our removal of proteins present in <20% of samples (n = 182 proteins). As these proteins might be superior predictors of EOS, we also assessed differential presence and absence of these less frequently detected proteins. Of the 182 proteins detected in fewer than 20% of specimens, only 3 were more often found in EOS specimens: SAA2, which was observed in 71% of EOS specimens, but 2% of controls; haptoglobin / haptoglobin-related protein, which was observed in 43% of EOS specimens, but 17% of controls; and lipocalin-2 (LCN2), which was observed in 36% of EOS specimens, but 9% of controls. Notably, these proteins are also all acute phase reactants, with SAA2 sequence and function largely redundant with SAA1. Given their rarity in the control specimens, we could not statistically compare their abundance across cohorts, so we focus on the 5 acute phase reactants identified above.

[0117] EOS cord blood samples contain higher levels of acute phase reactant proteins. Principal component analysis (PCA) of the protein abundance data for CRP, LBP, SAA1, LRG1, and SERPIN3A resulted in a clear separation of most of the EOS and control specimens, with axes explaining 84% of the variance (FIG. 2A). Hierarchical clustering by the abundance of these 5 proteins likewise shows a clear EOS cluster, though with a few control specimens interspersed (FIG. 2B). Protein abundance for all 5 proteins was significantly different between the EOS and control specimens (FIG. 2C). However, the distributions for CRP overlapped more than the other proteins. These data suggest that the measurement of one or more of these putative biomarkers in cord blood might be sufficient to differentiate healthy infants from those with EOS.

[0118] Quantitative immunoassays confirm elevated CRP, SAA, and LBP in EOS cord blood specimens. Though useful for target discovery, shotgun proteomic data cannot be used to rule out the presence of a protein in a specimen, nor is it a clinically feasible approach. Therefore, we next sought to validate these findings using commercially available, quantitative immunoassay kits to detect CRP, SAA1 / SAA2, and LBP (FIG. 3A). Once again, the concentrations of the three biomarkers were significantly elevated in the EOS compared to the control specimens, though for each biomarker three EOS specimens had lower concentrations more comparable to the control samples (FIG. 3B). PCA of these data demonstrated that though most of the EOS specimens formed a distinct cluster, three EOS specimens clustered with the controls (FIG. 3C). These three infants had different gestational ages at birth (245 / 7, 33 5 / 7, and 343 / 7) and blood cultures yieldedtypical septic pathogens (E. coli, E. coli, and K. oxytoca, respectively) (Table 2). Notably, however, these three infants had the longest intervals between birth and a positive blood culture (drawn at 65, 55, and 62 hours of life, respectively). The two infants with E. coli had a negative blood culture in the first day of life, whereas the infant with K. oxytoca developed emesis and increased abdominal girth on day 3 of life with an abdominal radiograph concerning for pneumatosis, prompting a septic work-up. The other 11 EOS infants had a positive blood culture that was drawn within the first few hours of life.

[0119] Table 2. Clinical characteristics of EOS cases.

[0120] Predictive modeline of EOS. To assess the predictive value of these new, putative biomarkers versus currently referenced clinical variables, we made a series of small logistic regression models containing sex, gestational age, and either a single biomarker or single clinical variable (Table 3). Clinical variables analyzed included serum protein concentration, multiple gestations, chorioamnionitis, preeclampsia, PROM, route of delivery, labor, and a delivery sum score factoring in both the delivery route and if the mother went into labor. In the logistic models, each biomarker yielded the lowest Akaike information criteria (AIC), with the best-performing clinical variable being the presence of clinical chorioamnionitis.

[0121] Table 3. Logistic regression of EOS risk.

[0122] To determine whether the putative biomarkers improve upon EOS detection or screening above baseline clinical metrics, we next produced random forest models with or without the biomarker concentrations. Random forest modeling was chosen above logistic regression owing to the challenge of model selection with multiple, co-linear, small-cardinality categorical variables(FIG. 7) and the small size of the EOS specimen set. Random forest models that included the three biomarker concentrations outperformed models with only clinical variables in precision, recall, receiver operating characteristics (ROC), and Fl score (FIG. 4A). Importantly, addition of these biomarker data improved recall, consistent with the clinical importance of early identification of every EOS case, and had greater precision, consistent with the clinical goal of minimizing unnecessary antibiotic treatment in infants who will not go on to develop sepsis. However, recall remained below 100%, indicating that complete sepsis identification requires strategies beyond this set of clinical variables and cord blood biomarkers.

[0123] To further characterize the value of cord blood biomarker levels, we measured variable importance by permutation (FIG. 4B). In this strategy, the value of specific variables of interest in the dataset are randomized across multiple runs of the model. Degradation of model performance is thus interpretable as the percentage contribution of each variable to model accuracy. SAA concentration had the greatest contribution to model performance, highlighting the value of this biomarker, followed by LBP and CRP concentration. Omission of any single biomarker from the model decreased accuracy. Serum protein concentration and gestational age were the most important of the clinical markers, consistent with changing neonatal susceptibility to sepsis over gestational age. The RF model performed better than the best multi-featured logistic regression models with fewer false negatives, which is important given the clinical importance of negative predictive value and risk of missing true EOS (Table 3). These data suggest that cord blood biomarkers may be useful adjuncts to clinical risk factors in EOS management.

[0124] Assessment of biomarkers in infants with presumed sepsis. Most infants receiving antibiotics early in life do not have positive blood cultures and so are treated as presumed sepsis. PS infants presumably include a mixture of infants with and without sepsis. To assess the outcome of our model in predicting sepsis in this population, we performed the same immunoassays on cord blood specimens from PS infants. Of the 53 PS infants, our machine learning model predicted 42 to resemble the healthy control infants, and 11 were predicted to resemble the EOS infants. PCA of the immunoassay data confirmed a clear clustering of the 11 PS infants predicted to have EOS with the true EOS infants, while the other 42 clustered cleanly with the controls (FIG. 5A). The predicted EOS infants had significantly higher levels of CRP, SAA1, and LBP than the predicted control infants, with median values near or exceedingly that of the true EOS infants (FIG. 5B). That a majority of the PS infants would potentially not have sepsis would be consistent with therisk averse paradigm of prolonged empiric antibiotic administration upon clinical suspicion of sepsis.

[0125] Discussion

[0126] In this study, we used an unbiased proteomics discovery strategy to identify candidate EOS biomarkers in cord blood at the time of birth, three of which were independently verified by immunoassay and proved useful as predictors in a random forest classifier. Our model, including biomarker data, has a high negative predictive value, which could be used to rule out EOS and help clinicians better target antibiotic treatments to those infants with a high likelihood of culturepositive EOS. Negative findings on cord blood screening for these biomarkers could increase clinical justification for withholding of empiric antibiotics after birth among low-risk infants or early discontinuation among higher-concern infants with negative blood culture results at 1-2 days of life, respectively. This could reduce unnecessary antibiotics exposure among neonates by adding more objective data to the diagnosis and management strategy of EOS.

[0127] Our sample of 14 culture-confirmed EOS cases and gestational age matched controls and PS cases is larger than has previously been used for similar studies, providing power to detect differences in proteomic data. Additionally, our precise categorization of culture-proven EOS versus PS cases further strengthens inferential power by removal of clinically diagnosed but uncertain cases of culture-negative sepsis, which may otherwise dilute candidate biomarker differences between EOS and controls. Importantly, both control and EOS arms of our dataset are enriched in preterm infants, who are most susceptible to EOS, most vulnerable to EOS morbidity, and most vulnerable to adverse consequences of prolonged early antibiotics exposure23. The most widely used EOS screening tool, the Kaiser Permanente Sepsis calculator, is not applicable for infants under 34 weeks’ gestation. Thus, the biomarkers we have identified here meet a significant unmet need for improved EOS screening in the preterm population. Only 20% (11 / 53) of PS infants treated for EOS had biomarker levels consistent with culture-proven EOS cases. While further validation and observational studies are necessary, these results illustrate the potential for a noninvasive test at birth to limit antibiotic exposure to as many as 80% of infants who receive a prolonged empiric treatment course in the setting of negative blood culture.

[0128] We identified five candidate biomarkers of EOS in umbilical cord blood: SAA1, LBP, CRP, LRG1, and SERPINA3. All five are known to be acute phase reactants. The presence of these proteins in cord blood is consistent with known EOS pathology. LBP is a plausible markerbecause it is involved in the acute phase immunologic response to gram-negative bacterial infections, a common EOS cause. CRP and SAA1 / 2 are produced by hepatocytes upon IL-6 and IL- 1 -like cytokine stimulation early in the acute phase response. CRP is widely used in clinical practice, although it is not specific for inflammation of infectious origin and is not routinely measured in cord blood. We previously identified CRP and SAA as potential biomarkers of EOS in a targeted screen of acute phase reactant proteins in cord blood24. Our unbiased proteomic workflow identified an overlapping set of proteins, strengthening the notion that these acute phase reactants may be useful cord blood biomarkers of EOS. An independent serum proteome analysis of sepsis in children previously identified an overlapping panel of biomarkers: SAA1, LRG1, and sCD2530. Several other studies have also pointed to acute phase reactants, including SAA1, as sepsis biomarkers in multiple populations, constituting a consensus that these proteins may be useful for sepsis diagnosis31'34. Here, we extend these findings to the cord blood of a uniquely vulnerable population of premature infants for whom postnatal markers vary due to birth and other noninfectious comorbidities.

[0129] An important caveat to using this candidate set of cord blood biomarkers for EOS diagnosis is that it only identifies EOS developed in iitero. Cord blood markers can only provide information about the state of the infant at the time of delivery and the clamping of the umbilical cord. Although this makes cord blood a valuable source of information about the intrauterine environment where EOS typically develops, it also makes cord blood uninformative for the subset of neonatal sepsis that develops later within the defined 72-hour window for EOS but is not present at the time of birth (i.e., blood culture at birth is negative and infection / necrotizing enterocolitis developed postnatally). Indeed, for the three culture-confirmed EOS cases with low cord blood biomarkers, culture positivity was only observed after a second blood culture was requested after 48 hours of worsening clinical status. If cord blood biomarker screening were adopted, ongoing monitoring of signs, use of clinical judgment, and combination with existing microbiologic tools would remain key for EOS management.

[0130] In both our NU Cord cohort and national studies, the percentage of very low birth weight infants receiving prolonged antibiotic courses (~26%)9far outweighs those with culture-confirmed infection (~1%)3. Though not all authentic sepsis cases may be confirmed by culture owing to pathogen fastidiousness, low sample volume, and maternal antibiotics, this likely reflectssignificant overtreatment. Reducing the duration of exposure to antibiotics could reduce the harms of overtreatment.

[0131] Methods

[0132] Sex as a biological variable. Male and female neonates were both included in the study. Modeling and analysis included both sexes.

[0133] Ethics, Enrollment, Subject Selection. We utilized archived cord blood plasma from an ongoing prospective study of infants born at Northwestern Prentice Women’s Hospital between 2008-2019 (NU Cord). Samples in this investigation were selected from the biorepository based on proven EOS (defined as positive blood culture with true pathogen within 72 hours of life16, clinical sepsis, and antimicrobial treatment >7 days), n=14. Controls were selected based on gestational age and the absence of presumed or proven early-onset neonatal sepsis (i.e., the infant received no antibiotic treatment course for sepsis within the first 72 hours of life and had no positive microbiologic sterile site cultures). A total of 150 infants were frequency matched within each gestational age (GA) category (epochs: 25-28 weeks, 29-32 weeks, 33-36 weeks, 37-42 weeks) with approximately equal numbers by sex, and route of delivery (vaginal delivery vs. caesarean delivery with or without labor). A third group of cord blood was identified from infants with “presumed sepsis” (PS), where there was no positive microbiologic culture in first week of life, yet patient was treated empirically for sepsis with a >7 day antibiotic course starting in first 72 hours of life. This study was approved by the Institutional Review Boards of Northwestern University (STU00201858) and Lurie Children’s Hospital (IRB 2018-2145). Parental informed consent was obtained for use of clinical data and infant cord blood samples. All research activities were performed in accordance with the Declaration of Helsinki.

[0134] Blood & Data Collection. Venous cord blood was collected and refrigerated until centrifugation at 3000 rpm for 10 minutes. Plasma was separated from red blood cell and buffy coat into aliquots stored at -80 degrees Celsius until use. Clinical data including birth weight, comorbid conditions, antenatal corticosteroid administration, and delivery characteristics were abstracted from the electronic medical record.

[0135] Proteomics sample preparation. Banked cord blood samples were thawed and processed for proteomics as previously described29. Briefly, fourteen highly abundant proteins were depleted (Top 14 Abundant Protein Depletion Spin Columns; Thermo Scientific, Rockford, IL, USA) from serum equivalent to 600 pg protein. Proteins were then precipitated, reduced, alkylated, anddigested with trypsin. The resulting peptides were desalted on Cl 8 columns, eluted in acetonitrile and formic acid, and reconstituted in 0.1% formic acid aqueous solution. Peptides were then analyzed by LC-MS / MS on an UltiMate 3000 Rapid Separation nanoLC coupled to an Orbitrap Elite mass spectrometer with data-dependent acquisition of the top 15 precursors. Samples were run in duplicate across four batches with pooled controls to assess batch-to-batch variance. Batches were randomized with a stratified sampling approach to balance distribution of gestational age, sex, and EOS.

[0136] Proteomics data analysis and normalization. Peptides were identified against the SwissProt human database using the Andromeda search engine in MaxQuant (version 1.6.0.16) with FDR <1% for protein identification. Label-free quantification (LFQ) was conducted using MaxLFQ. Log2 transformed label-free quantification values were used for all statistical analyses. To correct for batch effects, batch normalization was performed as previously described.1In summary, proteins detected in only one batch were excluded, and proteins detected in multiple batches were normalized by subtraction of the mean log2 LFQ protein abundance difference in the pooled control samples between the nth batch and the first batch. Batch-normalized protein abundance was then averaged across technical replicates of each sample.

[0137] Immunoassay Biomarker Detection. Quantitative biomarker detection was performed using Meso Scale Discovery (MSD) immunoassay kits: Vascular Injury Panel 2, which measures SAA and CRP; and an R-PLEX singleplex detection assay for LBP (MSD K151K5R). Assays were performed according to manufacturer instructions, in technical duplicate, from lOul cord blood plasma from a subset of the same samples utilized for proteomics (n=14 EOS, n=113 Controls, and n=53 presumed sepsis). Immunoassays were performed in Northwestern University’s Immunotherapy Assessment Core.

[0138] Statistics. For pairwise comparisons between non-normally distributed populations, significance was assessed by Mann- Whitney U test with Benjamini -Hochberg FDR correction. Protein abundance was visualized using hierarchically clustered heatmaps, which were produced using the clustermap function of seaborn (v 0.13.2). Principal component analysis and random forest modeling were performed using scikit-learn (v 1.5.1). For logistic regression metrics, we used the default 0.5 probability threshold for classification. For the random forest classifier, 10 runs using a stratified shuffle split allocation of 50% test and 50% training data were performed. The training data were further subj ected to gridsearch cross validation. EOS samples were assigned10: 1 class weight to mitigate class imbalance. Hyperparameter tuning explored combinations of n-estimators (50, 100), splitting criteria (Gini, entropy), max tree depth (4-6), and minimum samples per leaf (2-3). Variable importance was assessed by permutation importance with 20 repetitions. All analyses were performed in python (v 3.12.7).

[0139] The use of any and all examples provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.

[0140] The cited references are incorporated by reference herein in their entireties. In the event that there is an inconsistency between a definition of a term in the specification as compared to a definition of the term in a cited reference, the term should be interpreted based on the definition in the specification.

[0141] References1. McGovern M, Giannoni E, Kuester H, et al. Challenges in developing a consensus definition of neonatal sepsis. Pediatr Res. Jul 2020;88(l): 14-26. doi: 10.1038 / s41390-020-0785-x2. Stoll BJ, Puopolo KM, Hansen NI, et al. Early-Onset Neonatal Sepsis 2015 to 2017, the Rise of Escherichia coli, and the Need for Novel Prevention Strategies. JAMA Pediatr. Jul 1 2020;174(7):e200593. doi: 10.1001 / jamapediatrics.2020.05933. Schrag SJ, Farley MM, Petit S, et al. Epidemiology of Invasive Early-Onset Neonatal Sepsis, 2005 to 2014. Pediatrics. Dec 2016;138(6)doi: 10.1542 / peds.2016-20134. WHO. Global report on the epidemiology and burden of sepsis: current evidence, identifying gaps and future directions. 2020;5. Flannery DD, Edwards EM, Puopolo KM, Horbar JD. Early-Onset Sepsis Among Very Preterm Infants. Pediatrics. 2021; 148(4)doi: 10.1542 / peds.2021-0524566. Schelonka RL, Chai MK, Yoder BA, Hensley D, Brockett RM, Ascher DP. 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Claims

CLAIMSWe claim:

1. A method compri sing :(a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and(b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents.

2. The method of claim 1, wherein the at least three proteins or RNAs encoding said proteins are CRP, SAA1, and LBP.

3. The method of claim 1 or 2, wherein the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and wherein step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins.

4. The method of any one of claims 1-3, wherein the detection agents are antibodies.

5. The method of any one of claims 1-3, wherein the detection agents are nucleic acids reagents.

6. The method of any one of claims 1-5, wherein the subject has at least one symptom of early-onset sepsis (EOS), or at least one risk factor of EOS.

7. The method of any one of claims 1-6, wherein the sample is obtained from the subject within 72 hours after its birth.

8. The method of any one of claims 1-7, wherein the subject has not received antibiotic treatment for EOS before the sample is obtained.

9. The method of any one of claims 1 -8, further comprising treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to a control cord blood plasma sample from a control subject, wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

10. The method of claim 9, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

11. The method of any one of claims 1-8, further comprising:(c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and(d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

12. The method of claim 11, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

13. The method of claim 11 or 12, further comprising treating the subject for EOS if the levels of the proteins or RNAs encoding said proteins detected by the detection agents are elevated compared to the levels of proteins or RNAs encoding said proteins in the control sample.

14. A kit for detecting early-onset sepsis (EOS) in a subject, the kit comprising: a panel of detection agents, wherein the detection agents detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins.

15. The kit of claim 14, wherein the panel of detection agents consists of detection agents that detect at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins.

16. The kit of claim 14, wherein the detection agents detect each of the CRP, LBP, SAA1 , LRG1, and SERPINA3 proteins or RNAs encoding said proteins.

17. The kit of claim 16, wherein the panel of detection agents consists of detection agents that detect each of the CRP, LBP, SAA1, LRG1 and SERPINA3 proteins, or RNAs encoding said proteins.

18. The kit of any one of claims 14-17, wherein the detection agents are antibodies.

19. The kit of claim 18, wherein the antibodies are bound to a substrate.

20. The kit of any one of claims 14-17, wherein the detection agents are nucleic acid reagents.

21. The kit of any one of claims 14-20, further comprising a control sample, the control sample comprising a cord blood plasma sample obtained from a subject that does not have EOS, wherein the sample is obtained from the subject within the first 72 hours after its birth.

22. The kit of claim 21, wherein the control sample is stored at about -80°C.

23. A method comprising: collecting biomarker data from a cord blood plasma sample obtained from a subject, wherein the biomarker data are collected by measuring levels of at least three proteins selected from CRP, LBP, SAA1, LRG1, and SERPINA3, or RNAs encoding said proteins in the cord blood plasma sample; obtaining clinical data for the subject, wherein the clinical data comprise at least one of gestational age, sex, route of delivery, presence of clinical chorioamnionitis, prolonged rupture of membranes, multiple gestation, and preeclampsia; and predicting the likelihood of EOS in the subject by inputting the biomarker data and the clinical data to a random forest classifier model, generating an output as a predictive scoreindicating a likelihood of EOS in the subject based on the clinical data and the measured levels of protein or RNAs encoding said proteins in the cord blood plasma sample.

24. The method of claim 23, wherein measuring the levels of the at least three proteins comprises:(a) contacting a cord blood plasma sample obtained from a subject with a panel of detection agents, wherein the detection agents detect the at least three proteins selected from CRP, LBP, SAA1, LRG1 and SERPINA3, or RNAs encoding said proteins; and(b) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents.

25. The method of claim 23 or 24, wherein the at least three proteins are CRP, SAA1, and LBP.

26. The method of claim 24 or 25, wherein the detection agents detect each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins; and wherein step (b) comprises measuring the levels of each of CRP, LBP, SAA1, SERPINA3, and LRG1 proteins or RNAs encoding said proteins.

27. The method of any one of claims 24-26, wherein the detection agents are antibodies.

28. The method of any one of claims 24-26, wherein the detection agents are nucleic acids reagents.

29. The method of any one of claims 23-28, wherein the subject has at least one symptom of early-onset sepsis (EOS), or at least one risk factor of EOS.

30. The method of any one of claims 23-29, wherein the sample is obtained from the subject within 72 hours after its birth.31 . The method of any one of claims 23-30, wherein the subject has not received antibiotic treatment for EOS before the sample is obtained.

32. The method of any one of claims 24-31, further comprising: (c) contacting a control cord blood plasma sample obtained from a control subject with the panel of detection agents, and(d) measuring the levels of the at least three proteins or RNAs encoding said proteins detected by the detection agents; wherein the control subject does not have EOS, and wherein the control sample is obtained within 72 hours after the control subject’s birth.

33. The method of claim 32, wherein the control subject has not received antibiotic treatment for EOS before the control sample is obtained.

34. The method of any one of claims 23-33, further comprising treating the subject for EOS if the predictive score indicates a likelihood of EOS.

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