WO2020252365A1

WO2020252365A1 - Systems and methods to predict increased risk for adverse cardiovascular events in human immunodeficiency virus (hiv)-infected subjects

Info

Publication number: WO2020252365A1
Application number: PCT/US2020/037565
Authority: WO
Inventors: Dominic W. Chung; Xiaoyun Fu; Jose Aron Lopez; Junmei Chen; Yi Wang
Original assignee: Bloodworks
Priority date: 2019-06-14
Filing date: 2020-06-12
Publication date: 2020-12-17

Abstract

The current disclosure provides systems and methods to predict increased risk of adverse cardiovascular events in subjects infected with human immunodeficiency virus (HIV) at risk for cardiovascular events. The systems and methods measure levels of one or more of glutathione peroxidase-3 (GPX-3), platelet factor 4 (PF4), platelet basic protein (PBP), thrombospondin-1 (TSP-1), plasma kallikrein (KLKB1), serotonin, factor V (coagulation factor V), protein C (PROC), protein C inhibitor (PCI), C-reactive protein (CRP), linoleic acid (LA), arachidonic acid (AA), 12-hydroxyeicosatetraenoic acid (12-HETE), lysophosphatidylserine (LysoPS) 18:0, lysoPS 18:1, lysoPS 20:4, Cysteine (Cys), and/or protein bound Cysteine (P-ss-Cys). If an increased risk is detected, a therapeutic intervention can be initiated.

Description

SYSTEMS AND METHODS TO PREDICT INCREASED RISK FOR ADVERSE

CARDIOVASCULAR EVENTS IN HUMAN IMMUNODEFICIENCY VIRUS (HIV)-INFECTED

SUBJECTS

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of priority to U.S. Provisional Patent Application No. 62/861 ,913 filed June 14, 2019, which is incorporated herein by reference in its entirety as if fully set forth herein.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under grant HL129526 awarded by the National Heart Lung and Blood Institute, National Institutes of Health. The government has certain rights in the invention.

FIELD OF THE DISCLOSURE

[0003] The current disclosure provides systems and methods to predict increased risk of adverse cardiovascular events in individuals infected with human immunodeficiency virus (HIV). The systems and methods measure levels of biomarkers including glutathione peroxidase-3 (GPX-3), platelet factor 4 (PF4), platelet basic protein (PBP), thrombospondin-1 (TSP-1), plasma kallikrein (KLKB1), serotonin, factor V (coagulation factor V), protein C (PROC), protein C inhibitor (PCI), C-reactive protein (CRP), linoleic acid (LA), arachidonic acid (AA), 12- hydroxyeicosatetraenoic acid (12-HETE), lysophosphatidylserine (LysoPS) 18:0, lysoPS 18:1 , lysoPS 20:4, Cysteine (Cys), and/or protein bound Cysteine (P-ss-Cys). If an increased risk is detected, a therapeutic intervention can be initiated.

BACKGROUND OF THE DISCLOSURE

[0004] Cardiovascular disease accounts for at least 30% of deaths globally. People can be vulnerable to cardiovascular events due to a number of risk factors including age, tobacco use, unhealthy diet, physical inactivity, elevated blood pressure, abnormal blood lipids, and diabetes. A population known to be at risk for cardiovascular events are individuals infected with human immunodeficiency virus (HIV).

[0005] Over 35 million people worldwide are infected and living with HIV. Improvements in anti retroviral therapy have converted HIV infection to a manageable chronic disease. As life expectancy of HIV-infected patients is prolonged, however, these patients show a high incidence of cardiovascular diseases, including myocardial infarction, ischemic stroke, arterial and venous thrombosis, hypertension, and atherosclerosis; type 2 diabetes mellitus; metabolic syndrome; and chronic kidney disease. There is evidence that both the chronic HIV infection itself as well as anti-retroviral therapy regimens contribute to the development of a pro- thrombotic state that promotes adverse cardiovascular events. However, there is no known method of identifying which HIV-infected patients are at risk of developing cardiovascular complications. Biomarkers that allow prediction of occurrence of adverse cardiovascular events would be useful in initiating preventive medical treatments.

SUMMARY OF THE DISCLOSURE

[0006] The current disclosure provides systems and methods to predict the occurrence of adverse cardiovascular events (CVE) in individuals infected with human immunodeficiency virus (HIV). Particular embodiments include initiating treatments before such adverse events occur in HIV-infected individuals identified to be at risk.

[0007] Particular embodiments identify an HIV-infected subject as at risk for an adverse CVE by detecting the level of at least one primary biomarker and the levels of at least nine secondary biomarkers in a biological sample obtained from the subject where at least one of the secondary biomarkers is lysophosphatidylserine (lysoPS) 18:1 or lysoPS 20:4. In particular embodiments, primary biomarkers include glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); and plasma kallikrein (KLKB1); and secondary biomarkers include serotonin; factor V (coagulation factor V); protein C (PROC); protein C inhibitor (PCI); C-reactive protein (CRP); linoleic acid (LA); arachidonic acid (AA); 12- hydroxyeicosatetraenoic acid (12-HETE); lysoPS 18:0; lysoPS 18: 1 ; lysoPS 20:4; Cysteine (Cys); and protein bound Cysteine (P-ss-Cys).

[0008] In particular embodiments, if the levels of all primary biomarkers tested indicate that the HIV-infected subject does not have an increased risk of an adverse CVE, and the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is infected with HIV, then the combination of those results (all “negative” primary biomarkers and at least nine “confirmatory” secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4) indicates or predicts that the HIV-infected subject does not have an increased risk of an adverse CVE. However, if levels of fewer than nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is HIV-infected, then the otherwise negative primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE. [0009] In particular embodiments, if the level of at least one primary biomarker indicates that the HIV-infected subject has an increased risk of an adverse CVE (even if one or more of the other primary markers are negative), and the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is infected with HIV, then the combination of those results (at least one“positive” primary biomarker and at least nine“confirmatory” secondary biomarkers where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4) indicates or predicts that the HIV- infected subject has an increased risk of an adverse CVE. However, if levels of fewer than nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is HIV-infected, then the otherwise positive primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE.

[0010] In particular embodiments, if the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, indicate a confirmatory result, and the levels of 4 or fewer secondary biomarkers indicate a non-confirmatory result, then the combination of those results (at least nine confirmatory secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and 4 or fewer non- confirmatory secondary biomarkers) indicates that the primary biomarker result is predictive of whether or not the subject has an increased risk of an adverse CVE.

[0011] If neither the level of lysoPS 18:1 nor the level of lysoPS 20:4 confirm that a subject is infected with HIV, then even if the level(s) of 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 other secondary biomarkers are confirmatory, then the otherwise positive primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE.

[0012] In particular embodiments, an HIV-infected subject can be identified as at risk for an adverse CVE based on one or more of: a decrease in GPX-3 level; an increase in PF4 level; an increase in PBP level; an increase in TSP-1 level; and/or a decrease in KLKB1 level, so long as at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is infected with HIV. By way of example, those secondary biomarkers in certain embodiments will be: an increase in serotonin level; an increase in factor V level; a decrease in PROC level; a decrease in PCI level; an increase in CRP level; an increase in LA level; an increase in AA level; an increase in 12-HETE level; an increase in lysoPS 18:0 level; an increase in lysoPS 18:1 level; an increase in lysoPS 20:4 level; a decrease in Cys level; and/or an increase in P-ss-Cys level, in a biological sample obtained from the subject. [0013] As disclosed herein, changes in levels of one or more primary biomarkers can predict risk of adverse CVE in HIV patients if levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that a subject is infected with HIV, such that the detection of the biomarkers can lead to therapeutic interventions before an adverse CVE occurs.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0014] FIG. 1. Relative levels of glutathione peoxidase-3 (GPX-3) determined by proteomic analysis, quantifying at least two peptides from GPX-3. The study cohort for FIGs. 1-9B is described in Example 1. Levels of GPX-3 drop in HIV-infected subjects; the levels drop further in HIV-infected subjects with subsequent adverse CVE.

[0015] FIGs. 2A-2C. Levels of (FIG. 2A) platelet factor 4 (PF4), (FIG. 2B) platelet basic protein (PBP), and (FIG. 2C) thrombospondin-1 (TSP-1) were determined by proteomic analysis of depleted plasma. The biomarkers are elevated in HIV-infected subjects with subsequent adverse CVE.

[0016] FIG. 3. Relative levels of plasma kallikrein (KLKB1) determined by proteomic analysis of depleted plasma.

[0017] FIG. 4. Levels of serotonin were determined by targeted metabolomic analysis using liquid chromatography-tandem mass spectrometry with multiple reaction monitoring (LC- MS/MS-MRM).

[0018] FIG. 5A-5C. Relative levels of (FIG. 5A) factor V (coagulation factor V), (FIG. 5B) protein C (PROC), and (FIG. 5C) protein C inhibitor (PCI) determined by proteomic analysis of depleted plasma.

[0019] FIG. 6. Levels of C-reactive protein (CRP) determined by proteomic analysis of depleted plasma.

[0020] FIGs. 7A-7C. Concentrations of (FIG. 7A) linoleic acid (LA), (FIG. 7B) arachidonic acid (AA), and (FIG. 7C) 12-hydroxyeicosatetraenoic acid (12-HETE) in normal control and HIV- infected subjects without CVE, determined by targeted metabolomic analysis using mass spectrometry.

[0021] FIGs. 8A-8C. Levels of (FIG. 8A) lysophosphatidylserine (lysoPS) 18:0, (FIG. 8B) lysoPS 18:1 , and (FIG. 8C) lysoPS 20:4 determined by targeted metabolomic analysis.

[0022] FIGs. 9A-9C. Levels of (FIG. 9A) cysteine and (FIG. 9B) protein bound Cysteine (P-ss- Cys) determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) using multiple reaction monitoring (MRM), as described in Fu et al. (2019) Scientific reports, 9(1): 115 and PCT/US2015/042318. Thiols in a biological sample can be blocked with N-ethylmaleimide (NEM), which minimizes both artefactual oxidation and thiol- disulfide exchange. FIG. 9C shows exemplary workflows to quantify individual small molecule thiols and disulfides, total small molecule thiols (reduced and disulfide forms), and total thiols (including protein-bound forms) in biological samples. Isotopically labeled internal standards were used for absolute quantification. Proteins in the samples were precipitated with methanol and the supernatants were analyzed. The disulfides and thiol-NEM adducts were separated by UPLC and detected by LC-MS/MS-MRM. Product ions from the analyte were quantified by comparison to analogous ions derived from isotopically labeled internal standards. To determine total small molecular thiols and disulfides in supernatant, the sample is reduced with dithiothreitol (DTT) and then new thiols are blocked with NEM before LC-MS/MS. TO determine total thiol concentration, a new sample aliquot is reduced with DTT, and then all thiols are blocked with NEM before methanol extraction (FIG. 9C). Protein bound thiol can be calculated by subtracting total unbound small molecular thiols from total thiol or by subtracting the sum of free and all unbound disulfides from total thiol. Adapted from Fu et al. (2019) Scientific reports, 9(1): 115.

[0023] FIG. 10. Exemplary biomarker distribution in HIV-infected patients with and without CVE. A primary biomarker gives a positive result when the level of each primary biomarker is significantly increased or decreased (depending upon the biomarker) as compared to the average of patients with CVE. A secondary biomarker gives a confirmatory result when the level of each secondary biomarker is significantly increased or decreased as compared to the average of normal controls (i.e. , subjects who are not infected with HIV). Primary biomarkers: GPX-3, glutathione peroxidase-3; PF4, platelet factor 4; PBP, platelet basic protein; TSP-1 thrombospondin-1 ; KLKB1 , plasma kallikrein. Secondary biomarkers: Serotonin; Factor V; PROC, protein C; PCI, protein C inhibitor; CRP, C-reactive protein; LA, linoleic acid; AA, arachidonic acid; 12-HETE, 12-hydroxyeicosatetraenoic acid; LysoPS18:0, lysophatidylserine 18:0; LysoPS18:1 , lysophatidylserine 18:1 ; LysoPS20:4, lysophatidylserine 20:4; Cys, Cysteine; P-ss-Cys, protein-bound Cys.

DETAILED DESCRIPTION

[0024] Cardiovascular disease is the leading cause of death for women and men in the U.S. and accounts for at least 30% of deaths globally. The general population can be vulnerable to cardiovascular events due to a number of risk factors including age, tobacco use, unhealthy diet, physical inactivity, elevated blood pressure, abnormal blood lipids, and diabetes. A population known to be at risk for cardiovascular events are individuals infected with human immunodeficiency virus (HIV).

[0025] Over 35 million people worldwide are infected and living with human immunodeficiency virus (HIV). Improvements in anti-retroviral therapy have converted HIV infection to a manageable chronic disease. As life expectancy of HIV-infected patients is prolonged, however, these patients show a high incidence of cardiovascular diseases, including myocardial infarction, ischemic stroke, arterial and venous thrombosis, hypertension, and atherosclerosis; type 2 diabetes mellitus; metabolic syndrome; and chronic kidney disease. There is evidence that both the chronic HIV infection itself as well as anti-retroviral therapy regimens contribute to the development of a pro-thrombotic state that promotes thrombosis. However, there is no known method of identifying which HIV-infected patients are at risk of developing cardiovascular complications.

[0026] The current disclosure provides systems and methods to predict the risk of occurrence of adverse cardiovascular events (CVE) in patients infected with human immunodeficiency virus (HIV). Particular embodiments include initiating (or modifying) treatments before such adverse events occur in individuals identified to be at risk. “CVE” and “adverse CVE” are used interchangeably herein.

[0027] Particular embodiments identify an HIV-infected subject as at risk for an adverse CVE by detecting the level of at least one primary biomarker and the levels of at least nine secondary biomarkers in a biological sample obtained from the subject where at least one of the secondary biomarkers is lysophosphatidylserine (lysoPS) 18:1 or lysoPS 20:4. In particular embodiments, primary biomarkers include glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); and plasma kallikrein (KLKB1); and secondary biomarkers include serotonin; factor V (coagulation factor V); protein C (PROC); protein C inhibitor (PCI); C-reactive protein (CRP); linoleic acid (LA); arachidonic acid (AA); 12- hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine (lysoPS) 18:0; lysoPS 18:1 ; lysoPS 20:4; Cysteine (Cys); and protein bound Cysteine (P-ss-Cys).

[0028] If the levels of all primary biomarkers tested indicate that the HIV-infected subject does not have an increased risk of an adverse CVE (a“negative” result; Table 1), and the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is infected with HIV (a “confirming” or “confirmatory” result; Table 2), then the combination of those results (all“negative” primary biomarkers and at least nine“confirmatory” secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4) indicates (or predicts) that the HIV- infected subject does not have an increased risk of an adverse CVE. However, if levels of fewer than nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is HIV-infected (a“non-confirmatory” result; Table 2), then the otherwise negative primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE.

[0029] If the level of at least one primary biomarker indicates that the HIV-infected subject has an increased risk of an adverse CVE (a“positive” result; see Table 1) (even if one or more of the other primary markers are negative), and the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is infected with HIV (a“confirming” or“confirmatory” result; see Table 2), then the combination of those results (at least one “positive” primary biomarker and at least nine “confirmatory” secondary biomarkers) indicates (or predicts) that the HIV-infected subject has an increased risk of an adverse CVE. However, if levels of less than nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that the subject is HIV-infected (a“non-confirmatory” result; Table 2), then the otherwise positive primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE.

[0030] If the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, indicate a confirmatory result, and the levels of 4 or fewer secondary biomarkers indicate a non-confirmatory result, then the combination of those results (at least nine confirmatory secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and 4 or fewer non-confirmatory secondary biomarkers) indicates that the primary biomarker result is predictive of whether or not the subject has an increased risk of an adverse CVE.

[0031] If neither the level of lysoPS 18:1 nor the level of lysoPS 20:4 confirm that a subject is infected with HIV, then even if the level(s) of 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11 other secondary biomarkers are confirmatory, then the otherwise positive primary biomarker result is not predictive of whether or not the subject has an increased risk of an adverse CVE.

[0032] Table 1 shows each primary biomarker and the change (or lack of change) in level of each primary biomarker that may be indicative (or not indicative) of whether a subject has an increased risk of an adverse CVE.

[0033] Table 1. Change in level of a primary biomarker in a subject to indicate whether the subject has an increased risk of an adverse CVE

sample”) is compared to a reference level of that primary biomarker (for instance, the reference level can be an average of levels of the primary biomarker from a group of subjects who have HIV and who have had or who do have CVE).

[0034] Table 2 shows each secondary biomarker and the change (or lack of change) in level of each secondary biomarker that is confirmatory (or not confirmatory) of an HIV infection in a subject.

[0035] Table 2. Change in level of a secondary biomarker in a subject to indicate HIV infection status of the subject

sample”) is compared to a reference level of that secondary biomarker (for instance, the reference level can be an average of levels of the secondary biomarker from a group of subjects who are not infected with HIV).

[0036] In particular embodiments, an HIV-infected subject can be identified as at risk for an adverse CVE based on one or more of: a decrease in GPX-3 level; an increase in PF4 level; an increase in PBP level; an increase in TSP-1 level; and/or a decrease in KLKB1 level, in those circumstances where at least nine of the following secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, from the same subject confirm that the subject is infected with HIV: an increase in serotonin level; an increase in factor V level; a decrease in PROC level; a decrease in PCI level; an increase in CRP level; an increase in LA level; an increase in AA level; an increase in 12-HETE level; an increase in lysoPS 18:0 level; an increase in lysoPS 18:1 level; an increase in lysoPS 20:4 level; a decrease in Cys level; and/or an increase in P-ss-Cys level, in a biological sample obtained from the subject.

[0037] As disclosed herein, changes in levels of primary biomarkers precede the onset of adverse CVE in HIV-infected patients, such that their detection can lead to therapeutic interventions before an adverse CVE occurs.

[0038] Aspects of the current disclosure are now described in more detail. The description is organized into the following sections: (i) Biomarkers; (ii) Biological Samples; (iii) Assays for detection and quantification of biomarkers; (iv) Reference levels; (v) Methods of Use; (vi) Kits; and (vii) Biomarker variants.

[0039] (i) Biomarkers. A biomarker of the present disclosure is a molecule expressed and/or released from a cell in (or from) a subject, which is useful for identification or prediction. Such biomarkers are molecules (e.g., proteins, small molecules, nucleic acids, lipids, and carbohydrates) that can be differentially expressed (e.g., overexpressed or underexpressed), differentially functioning, or differentially released (e.g., released from a cell) in response to a health condition of a subject. In particular embodiments, biomarkers can refer to the biochemical compounds and/or proteins disclosed herein, which are increased or decreased, for instance, 1- fold, 2-fold, 3-fold, 4-fold, 5-fold or more, in HIV-infected subjects who have or will have adverse CVE versus HIV-infected subjects who do not have or will not have adverse CVE.

[0040] Primary Biomarkers. The following biomarkers are referred to as primary biomarkers within the current disclosure: GPX-3, PF4, PBP, TSP-1 , and KLKB1. In particular embodiments, primary biomarkers can distinguish between HIV-infected subjects who are at an increased risk of having adverse CVE and HIV-infected subjects who are not at an increased risk of having adverse CVE, given that levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, confirm that each subject is infected with HIV. Each of these primary biomarkers is described below.

[0041] Glutathione peroxidase-3 (GPX-3). GPX-3 is also known as GPx-P, GSHPx-3, and GSHPx-P. GPX-3 belongs to the glutathione peroxidase family. It protects cells against oxidative damage by catalyzing the reduction of organic hydroperoxides, lipid peroxides, and hydrogen peroxide (H2O2) by glutathione. GPX-3 is secreted from cells and is abundantly found in plasma. GPX-3 is also a selenoprotein, containing the rare amino acid selenocysteine (Sec) at its active site. Downregulation of expression of the gene encoding GPX-3 by promoter hypermethylation has been observed in a wide spectrum of human malignancies, including thyroid cancer, hepatocellular carcinoma and chronic myeloid leukemia. GPX-3 is highly expressed in tissues that include kidney and thyroid. In particular embodiments, human GPX-3 has an amino acid sequence of UniProt ID P22352, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_002084.4, nucleotides 244-924.

[0042] Platelet factor 4 (PF4). PF4 is also known as PF-4, CXCL4, and SCYB4. PF4 is a member of the CXC chemokine family. This chemokine is released from the alpha granules of activated platelets in the form of a homotetramer which has high affinity for heparin and is involved in platelet aggregation. This protein serves as a chemotactic signal for cells such as neutrophils, fibroblasts, and monocytes, and also functions as an inhibitor of hematopoiesis, angiogenesis and T-cell function. The protein also exhibits antimicrobial activity against Plasmodium falciparum. PF4 is highly expressed in tissues that include bone marrow and spleen. In particular embodiments, human PF-4 has an amino acid sequence of UniProt ID P02776, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_002619.3, nucleotides 172-477.

[0043] Platelet basic protein (PBP or b-thromboglobulin). PBP is also known as pro-platelet basic protein, b-thromboglobulin (b-TG), PBP, TC1 , TC2, TGB, LDGF, MDGF, TGB1 , B-TG1 , CTAP3, CXCL7, NAP-2, SCYB7, THBGB, LA-PF4, THBGB1 , CTAPIII, and CTAP-III. PBP is a platelet-derived growth factor that belongs to the CXC chemokine family. This growth factor is a potent chemoattractant and activator of neutrophils. It has been shown to stimulate various cellular processes including DNA synthesis, mitosis, glycolysis, intracellular cAMP accumulation, prostaglandin E2 secretion, and synthesis of hyaluronic acid and sulfated glycosaminoglycan. It also stimulates the formation and secretion of plasminogen activator by synovial cells. PBP is also an antimicrobial protein with bactericidal and antifungal activity. PBP is highly expressed in tissues that include bone marrow and spleen. In particular embodiments, human b-thromboglobulin has an amino acid sequence of UniProt ID P02775, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_002704.3, nucleotides 88-474.

[0044] Thrombospondin-1 (TSP-1). TSP-1 is also known as TSP, THBS, TSP1 , THBS1 , and THBS-1. TSP-1 is a subunit of a disulfide-linked homotrimeric protein. This protein is an adhesive glycoprotein that mediates cell-to-cell and cell-to-matrix interactions. This protein can bind to fibrinogen, fibronectin, laminin, type V collagen and integrin alpha-V/beta-1. TSP-1 has roles in platelet aggregation, angiogenesis, and tumorigenesis. TSP-1 is broadly expressed in tissues that include appendix, gall bladder, ovary, prostate, lung, placenta, kidney and platelets. In particular embodiments, human TSP-1 has an amino acid sequence of UniProt ID P07996-1 , encoded by the nucleotide sequence of NCBI Ref Sequence: NM_003246, nucleotides ISO- 3692.

[0045] Plasma kallikrein (KLKB1). KLKB1 is also known as Fletcher factor, kininogenin, and plasma prekallikrein. Blood clots quickly when it comes in contact with foreign surfaces through a process known as contact activation. Contact activation is initiated by the binding of factor XII (Hageman factor) in plasma to negatively charged surfaces, which leads to activation of plasma prekallikrein (Fletcher factor, KLKB1) to the active protease plasma kallikrein. Plasma kallikrein then reciprocally activates factor XII to factor XI la in a reaction that leads to amplification of the surface-dependent reactions. Plasma kallikrein also cleaves high molecular weight kininogen to release the vasoactive peptide bradykinin, which is a pharmacological agent that dilates blood vessels, lowers blood pressure, increases blood vessel permeability, and causes pain and inflammation. Plasma prekallikrein is synthesized in the liver and secreted into the circulation as a single polypeptide chain with an apparent molecular weight of 88,000 daltons. It is present in plasma at a concentration of 35-45 pg/ml and circulates as a non-covalent complex with high molecular weight kininogen. Plasma prekallikrein is 58% identical in amino acid sequence to coagulation factor XI. In particular embodiments, human KLKB1 has an amino acid sequence of UniProt ID P03952-1 , encoded by the nucleotide sequence of NCBI Ref Sequence: NM_000892.4, nucleotides 119-2035.

[0046] Secondary Biomarkers. The following biomarkers are secondary biomarkers within the current disclosure: serotonin, Factor V, protein C (PROC), protein C inhibitor (PCI), C-reactive protein (CRP), linoleic acid (LA), arachidonic acid (AA), 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cysteine (Cys), and protein bound Cysteine (P-ss-Cys). Results from at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are used to confirm whether a subject is infected with HIV and thus indicate when at least one positive primary biomarker is predictive of the HIV-infected subject having an increased risk of an adverse CVE or indicate when at least one negative primary biomarker is not predictive of the HIV-infected subject having an increased risk of an adverse CVE. Each of these secondary biomarkers is described below.

[0047] Serotonin. Serotonin, also known as 5-hydroxytryptamine (5-HT), has the following structure:

Serotonin is a monoamine neurotransmitter derived from the amino acid tryptophan. Serotonin is primarily found in the enteric nervous system located in the gastrointestinal (Gl) tract, where it is used to regulate intestinal movements. However, it is also produced in the central nervous system (CNS) in the Raphe nuclei located in the brainstem, where it can regulate mood, appetite, sleep memory, and learning. This indoleamine molecule is thought to contribute to feelings of well-being and happiness. Additionally, serotonin is stored in blood platelets and is released during agitation and vasoconstriction, where it then acts as an agonist to other platelets.

[0048] Factor V. Coagulation factor V is also known as blood coagulation factor V, factor V, activated protein C cofactor, and proaccelerin, labile factor. Factor V is an essential cofactor in the coagulation system, which is a series of chemical reactions that forms blood clots in response to injury. Factor V circulates in an inactive form in plasma and is activated upon an injury that damages blood vessels. Activated factor V forms a complex with activated coagulation factor X (designated factor Va and factor Xa, respectively), and the fVa/fXa complex converts an important coagulation protein called prothrombin to its active form, thrombin. Thrombin then converts a protein called fibrinogen into fibrin, which is the material that forms the clot. Factor V also has a role in regulating the coagulation system through its interaction with a protein called activated protein C (APC). The cutting of factor Va at specific sites by APC inactivates factor V, which slows down the clotting process and prevents clots from growing too large. In people with the inherited blood clotting disorder factor V Leiden thrombophilia, factor Va cannot be inactivated normally by APC. As a result, the clotting process remains active longer than usual, increasing the chance of developing abnormal blood clots that could occlude blood vessels. Deficiency of Factor V is associated with a rare mild form of bleeding disorder termed parahemophilia or Owren parahemophilia. Factor V protein is made primarily by cells in the liver. In particular embodiments, human Factor V has an amino acid sequence of UniProt ID P12259, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_000130.4, nucleotides 146-6820.

[0049] Protein C. Protein C is also known as anticoagulant protein C, autoprothrombin IIA and blood coagulation factor XIV. Protein C is a serine protease that controls blood clotting by blocking the activity of two proteins that promote the formation of blood clots, activated factor V (factor Va) and activated factor VIII (factor Villa). Inactive protein C is converted to activated protein C (APC) by thrombin in the presence of a cofactor thrombomodulin. As discussed above, APC is responsible for inactivating factor Va. Protein C is a vitamin K-dependent glycoprotein that is also involved in regulating inflammation, cell death, and maintaining the permeability of blood vessel walls. Deficiency of protein C leads to a disorder that increases the risk of developing abnormal blood clots. Protein C is made in the liver and then released into the bloodstream. In particular embodiments, human Protein C has an amino acid sequence of UniProt ID P04070, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_000312.3, nucleotides 95-1480.

[0050] Protein C Inhibitor. Protein C inhibitor is also known as PCI, SERPINA5, and plasminogen activator inhibitor-3 (PAI-3). It is a serine protease inhibitor that limits the activity of activated protein C (APC) to regulate the anticoagulant protein C pathway and fibrinolysis. The inhibitor is a 52 kDa glycoprotein and belongs to the serine protease inhibitor (Serpin) super family of proteins. Protein C Inhibitor was initially identified as an inhibitor of APC; however, this inhibitor can regulate other coagulation factors, such as thrombin and factor Xa. Its inhibitory activity is modulated by binding of glycosaminoglycans and/or phospholipids. Protein C Inhibitor regulates mammalian fertilization by inhibiting prostate-specific antigen and sperm acrosin (a serine protease). It may also function in lung remodeling, tissue regeneration, vascular permeability, proteolysis in the kidney and tumor invasion. Protein C inhibitor is found in most tissues and fluids, including blood plasma, seminal plasma and urine of human. In particular embodiments, human Protein C inhibitor has an amino acid sequence of UniProt ID P05154, encoded by the nucleotide sequence of NCBI Ref Sequence: NM_000624.5, nucleotides 236- 1456.

[0051] C-Reactive Protein (CRP). CRP is also known as PTX1. The protein belongs to the pentaxin family. It is involved in several host defense related functions based on its ability to recognize foreign pathogens and damaged cells of the host. It can promote agglutination, bacterial capsular swelling, phagocytosis and complement fixation through its calcium- dependent binding to phosphorylcholine. The level of this protein in plasma increases greatly during the acute phase response to tissue injury, infection, or other inflammatory stimuli. CRP is highly expressed in tissues including the liver. In particular embodiments, human CRP has an amino acid sequence of UniProt ID P02741-1 , encoded by the nucleotide sequence of NCBI Ref Sequence: NM_001329057.1 , nucleotides 105-779.

[0052] Linoleic Acid. Linoleic acid is also known as: (9Z,12Z)-octadeca-9,12-dienoic acid; 9 trans,12 trans octadecadienoic acid; 9,12 octadecadienoic acid; acid, 9,12-octadecadienoic; cis,cis-9,12-octadecadienoic Acid; linoelaidic acid; linoelaidic acid, (E,Z)-isomer; linoleate; linoleic acid, (E,E)-isomer; linoleic acid, (Z,E)-isomer; linoleic acid, (Z,Z)-isomer; linoleic acid, (Z,Z)-isomer; linolelaidic acid; and trans, trans-9,12-octadecadienoic acid. The molecular formula for linoleic acid is C18H32O2. Linoleic acid has the following structure:

[0053] Linoleic acid is an essential polyunsaturated fatty acid (PUFA) that must be supplied by the diet since it cannot be synthesized by the body. Rich sources of linoleic acid include nuts, fatty seeds, and their derived vegetable oils, such as safflower, sunflower, corn, and soybean oils. Linoleic acid has essential functions in maintaining the epidermal water barrier of the skin. Linoleic acid is also important as a precursor of the long chain PUFAs (LCPUFAs) that are incorporated into cell membranes in the form of phospholipids and other lipid components which maintain normal membrane fluidity, structure, and function. Omega-6, or n-6, fatty acids (having a double bond at the sixth carbon position counting from the methyl end of the fatty acid) are derived from linoleic acid and serve as storage fatty acids in adipose tissue, and in liver, kidney, and muscle cells. Linoleic acid-derived fatty acids found in cell membranes also have interactive roles with regulatory proteins that are important for cell metabolism and signaling.

[0054] Arachidonic Acid. Arachidonic acid is also known as: (5Z,8Z,11Z,14Z)-icosa-5,8,11 ,14- tetraenoic acid; (all-Z)-5,8,11 ,14-eicosatetraenoic acid; c/s-5,8,11 ,14-eicosatetraenoic acid; arachidonate; and vitamin F. The molecular formula for arachidonic acid is C20H32O2. Arachidonic acid has the following structure:

[0055] Arachidonic acid is an important LCPUFA produced from linoleic acid, and it is a major cell membrane fatty acid and a precursor of certain types of eicosanoids. The eicosanoids are a diverse group of 20-carbon substances that are produced and released from cell membranes in response to physical or chemical trauma. Eicosanoids have local effects upon immune and inflammatory responses. The four primary types of eicosanoids are the prostaglandins, prostacyclins, thromboxanes, and leukotrienes. A number of enzymes metabolize arachidonic acid to these eicosanoids and eicosanoid metabolites. The enzymes cyclooxygenase- 1 and cyclooxygenase-2 metabolize arachidonic acid to prostaglandin G2 and prostaglandin H2, which in turn may be converted to various prostaglandins, prostacyclin, and thromboxanes. The enzyme arachidonate 5-lipoxygenase metabolizes arachidonic acid to 5- hydroperoxyicosatetraenoic acid (5-HPETE), which in turn is metabolized to various leukotrienes, as well as to 5-hydroxyicosatetraenoic acid (5-HETE). The enzymes arachidonate 15-lipoxygenase-1 and arachidonate 15-lipoxygenase-2 metabolize arachidonic acid to 15- hydroperoxyicosatetraenoic acid (15-HPETE), which may then be further metabolized to 15- hydroxyicosatetraenoic acid (15-HETE) and lipoxins. The enzyme arachidonate 12- lipoxygenase metabolizes arachidonic acid to 12-hydroperoxyeicosatetraenoic acid (12-HPETE) which may then be metabolized to 12-hydroxyeicosatetraenoic acid (12-HETE) and to hepoxilins. Arachidonic acid is found in animal and human fat as well as in the liver, brain, skeletal muscle, and glandular organs, and is a constituent of animal phosphatides.

[0056] 12-hydroxyeicosatetraenoic acid (12-HETE). The "S" stereoisomer of 12-HETE is also known as: (5Z,8Z,10E,12S,14Z)-12-hydroxyicosa-5,8,10,14-tetraenoic acid; 12(S)-hydroxy- (5Z,8Z, 10E, 14Z)-eicosatetraenoic acid; (S)-12-HETE; 12(S)-HETE; and 12S-HETE. The "R" stereoisomer of 12-HETE, 12(R)-hydroxy-5Z,8Z,1QE,14Z-eicosatetraenoic acid, is also known as 12(R)~HETE or 12R-HETE 12-HETE, as used in the present disclosure, refers to the“S” stereoisomer of 12-HETE, the“R” stereoisomer of 12-HETE, or both stereoisomers of 12-HETE. The molecular formula for 12-HETE is C20H32O3. 12S-HETE has the following structure:

[0057] 12-HETE is a derivative of the 20-carbon polyunsaturated fatty acid, arachidonic acid, containing a hydroxyl residue at carbon 12 and a 5Z,8Z,10E,14Z cis-trans isomerism configuration (Z=cis, E=trans) in its four double bonds. The "S" stereoisomer is made by arachidonate 128-lipoxygenase in platelets. The "R" stereoisomer, 12(R)-hydroxy- 5Z,8Z.10E,14Z-eicosatetraenoic acid (also termed 12(R)~HETE or 12R-HETE) made by other tissues through their arachidonate 12R-!ipoxygenase enzyme. The two isomers, either directly or after being further metabolized, have been suggested to be involved in a variety of human physiological and pathological conditions including inflammation. 12S-HETE has been implicated in cancer, diabetes, and high blood pressure. These arachidonic acid metabolites may act locally to regulate the behavior of ceils from which they originate or of nearby cells.

[0058] Lysophosphatidylserine (lysoPS). Lysophosphatidylserine (lysoPS) is a lysophospholipid mediator that is derived from hydrolysis of an acyl chain (deacylation) from the phospholipid phosphatidylserine (PS) by phosphatidylserine-specific phospholipase A1 (PS- PLAi) or phospholipase A2 (PS-PLA2) enzymes at the sn- 1 and sn-2 positions of PS, respectively. The enzyme ABHD16a also exhibits PS lipase activity, and Abhd16a deficiency results in reduced LysoPS levels in vivo. LysoPS is upregulated by various inflammatory stimuli. LysoPS has been detected after injury to tissues (tumor growth, graft rejection, burns). When cells are damaged, lysoPS can be generated by a reaction dependent on activation of the NADPH oxidase. It may play a role in resolution of inflammation by enhancing clearance of activated and dying neutrophils. In particular, sn- 2-lysoPS stimulates degranulation of mast cells. LysoPS may have cell signaling functions, for example, in regulating calcium flux and stimulating immune cells through specific receptors that have been identified in mice and humans. Negatively charged lysoPS species tend to organize in non-bilayer structures and are believed to facilitate folding of certain membrane proteins in situ better than bilayer-forming lipids. LysoPS species vary by acyl chain length and saturation, among which the 16:0, 18:0, and 18:1 isoforms are the most abundant in brain, heart, kidney, and lung tissues. PS-PLA1, ABHD6, and ABHD12 can catalyze the degradation of lysoPS, and genetic deficiencies in the latter two enzymes have been linked to metabolic syndrome and inflammatory neurodegenerative disease, respectively. LysoPS also has been linked to certain cancers and to night blindness.

[0059] LysoPS 18:0. Lysophosphatidylserine 18:0 is also known as: lysoPS; lysophosphatidyl- L-serine; 1 -octadecanoyl-sn-glycero-3-phosphoserine; 1 -stearoyl-sn-glycero-3-phosphoserine; 1-stearoyl-sn-glycero-3-phospho-L-serine; 1-octadecanoyl-sn-glycero-3-phospho-L-serine; O- {hydroxy[(2R)-2-hydroxy-3-(octadecanoyloxy)propoxy]phosphoryl}-L-serine; 1-stearoyl-2- hydroxy-sn-glycero-3-phospho-L-serine and (2S)-2-amino-3-[hydroxy-[(2R)-2-hydroxy-3- octadecanoyloxypropoxy]phosphoryl]oxypropanoic acid. The molecular formula for LysoPS 18:0 is C24H48NO9P. LysoPS 18:0 has the following structure. The 18:0 denotes that the remaining acyl group contains 18 carbons and zero double bonds:

[0060] LysoPS 18:1. Lysophosphatidylserine 18:1 is also known as: 1-oleoyl-sn-glycero-3- phosphoserine; 1-(9Z)-octadecenoyl-sn-glycero-3-phosphoserine; 1-(9Z-octadecenoyl)-sn- glycero-3-phospho-L-serine; 1-Ci_8:i(w-9)-lysophosphatidylserine; and 1-oleoyl (18:1) lysoPS. The molecular formula for LysoPS 18:1 is C24H46NO9P. LysoPS 18:1 has the following structure. The 18:1 denotes that the remaining acyl group contains 18 carbons and one double bond:

[0061] LysoPS 20:4. Lysophosphatidylserine 20:4 is also known as: 1-(5Z,8Z,11Z,14Z- eicosatetraenoyl)-sn-glycero-3-phosphoserine, (2S)-2-amino-3-[hydroxy-[(2R)-3-

[(5Z,8Z,11Z,14Z)-icosa-5,8,11 ,14-tetraenoyloxypropoxy]phosphoryl]oxypropanoic acid, 1- arachidonoyl-sn-glycero-3-phosphoserine, 1-C_20:4(w-6,9,12,15)-lysophosphatidylserine, and 1- arachidonoyl (20:4) lysoPS). The molecular formula for LysoPS 20:4 is C26H44NO9P. LysoPS 20:4 has the following structure. The 20:4 denotes that the remaining acyl group contains 20 carbons and four double bonds:

[0062] Cysteine. Cysteine is also known as L-cysteine. The molecular formula for cysteine is C₃H7NO2S. Cysteine has the following structure:

[0063] Cysteine is a non-essential thiol-containing amino acid in humans. The enzyme cystathionine b-synthase catalyzes condensation of homocysteine with serine to form cystathionine, which is deaminated and hydrolyzed by cystathionine b-lyase to form cysteine and a-ketobutyrate. Cysteine has numerous biological functions due to the nucleophilic nature of its thiol group. The formation of disulfide linkages between the thiol groups of cysteine residues helps to stabilize the tertiary and quaternary structure of proteins. Cysteine is important for protein synthesis, detoxification, and diverse metabolic functions. Found in beta-keratin, the main protein in nails, skin, and hair, cysteine is important in collagen production, skin elasticity, and skin texture. Cysteine is important in the manufacture of amino acid taurine and plays a role in the metabolism of essential biochemicals such as coenzyme A, heparin, and biotin. Cysteine is the limiting precursor of the major intracellular antioxidant glutathione. Cysteine, homocysteine and other aminothiols exist in plasma in reduced, oxidized, and protein-bound forms, interacting with each other through redox pathways. Individuals with lower cysteine levels are more prone to damage from reactive oxygen species, which are generally removed either by thiols or by glutathione-linked enzymes. An elevated level of total cysteine can predict adverse outcomes such as cardiovascular diseases and metabolic syndromes. Oxidized cysteine is known as cystine.

[0064] Protein bound Cysteine (P-ss-Cys). Protein bound Cysteine (P-ss-Cys) refers to cysteine covalently bound to a protein via a disulfide linkage.

[0065] Table 3 summarizes the primary and secondary biomarkers of the present disclosure. For each primary biomarker, the following are indicated: the type of molecule; whether an increase or a decrease in the level of each primary biomarker predicts occurrence of CVE in HIV-infected subjects, and representative assays to detect each primary biomarker. For each secondary biomarker, the following are indicated: the type of molecule; whether an increase or a decrease in the level of each secondary biomarker confirms that a subject is infected with HIV, and representative assays to detect each secondary biomarker. The representative assays are described below.

[0066] Table 3. Primary and secondary biomarkers of the present disclosure and representative assays to detect them

[0067] (ii) Biological samples. Biological samples of the present disclosure can include blood, plasma, serum, saliva, and urine. In particular embodiments, a biological sample includes cells. In particular embodiments, the biological sample is plasma. In particular embodiments, the plasma is depleted of high abundant proteins including albumin, IgG, a1 -antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein A1 , apolipoprotein All, complement C3 and transthyretin. In particular embodiments, the plasma is depleted of high abundant proteins including albumin, IgG, IgA, transferrin, haptoglobin, and a1 -antitrypsin. In particular embodiments, a control sample includes pooled normal plasma which can be obtained commercially from, e.g., George King Bio-Medical Inc. (#0010-0, Overland Park, KS), Precision BioLogic Inc. (CRYOcheck™, #CCN-10, Dartmouth, Nova Scotia, CA), and Innovative Research (#IPLA-N, Novi, Michigan). Pooled normal plasma (PNP) can include citrated plasma from at least 5, at least 10, at least 20, or at least 30 or more carefully screened human donors. Individual donor units that form a PNP can be subjected to viral testing and only included in the PNP if found negative for, e.g., HBsAg, HCV, HIV-1 , HIV-2, HIV-1Ag or HIV 1-NAT, ALT, and syphilis by FDA-approved methods. A PNP can be platelet poor with no buffers or preservatives. A PNP can include approximately equal number of male and female donors. The donors for the PNP can be aged 18 to 66. A Certificate of Analysis typically accompanies each shipment of PNP. This lot-specific Certificate of Analysis certifies the normalcy of the PNP satisfying regulatory guidelines. Assay values can be assigned and reported on the Certificate of Analysis for Prothrombin Time (PT) and activated Partial Thromboplastin Time (aPTT). Fibrinogen, prothrombin and Factors V, VII, VIII, IX, X, XI and XII can be assayed and certified to be within the normal range.

[0068] In particular embodiments, a control sample includes sample(s) derived from subject(s) who do not have HIV infection and who do not have known cardiovascular disease at the time of blood donation or other provision of the sample(s). Particular embodiments provide control samples derived from subjects who: do not have HIV infection; are gender-matched to HIV- infected subjects; are aged 24-33; are nonsmokers; do not have hypertension (systolic < 140 and diastolic <80 mm Hg); are non-anemic; do not have a blood disorder or cancer; do not have a cold or influenza; are not taking any anti-coagulation, anti-platelet, or anti-inflammation medication; and/or have no known cardiovascular disease at the time of blood donation or other provision of the sample(s). In particular embodiments, a control sample includes sample(s) derived from subject(s) who do not have HIV infection. [0069] In particular embodiments, a control sample includes sample(s) derived from subject(s) who have HIV infection and who have had or who do have an adverse CVE at the time of blood donation or other provision of the sample(s).

[0070] In particular embodiments, a biological sample is derived from a subject or source. Particular embodiments of “derived from” refer to a biological sample being obtained from a subject or other source and including any modification to the sample, addition to the sample, or removal from the sample, as long as biomarkers of the present disclosure can be measured from the sample using the systems and methods of the present disclosure.

[0071] (iii) Assays for detection and quantification of biomarkers. Up- or down-regulation of the biomarkers, as indicated elsewhere herein for particular biomarkers, can be assessed by comparing a measured value (from a test or subject sample) to a relevant reference level. For example, the quantity of one or more biomarkers can be indicated as a value. The value can be expressed numerically and result from assaying a sample, and can be derived, e.g., by measuring level(s) of the biomarker(s) in the sample by an assay performed in a laboratory, by measuring the ratio or ratios of the levels of two or more of the biomarkers, or from a dataset obtained from a provider such as a laboratory, or from a dataset stored on a server. The biomarkers disclosed herein can be a protein biomarker, or a nucleic acid biomarker (e.g., gene encoding the protein biomarker) and/or a small molecule.

[0072] In the broadest sense, the value may be qualitative or quantitative. As such, where detection is qualitative, the systems and methods provide a reading or evaluation, e.g., assessment, of whether or not the biomarker is present in the sample being assayed. In yet other embodiments, the systems and methods provide a quantitative detection of whether the biomarker is present in the sample being assayed, i.e. , an evaluation or assessment of the actual amount or relative abundance of the biomarker in the sample being assayed. In such embodiments, the quantitative detection may be absolute or, if the method is a method of detecting two or more different biomarkers in a sample, relative. As such, the term“quantifying” when used in the context of quantifying a biomarker in a sample can refer to absolute or to relative quantification. Absolute quantification can be accomplished by inclusion of known concentration(s) of one or more control biomarkers and referencing, e.g., normalizing, the detected level of the biomarker with the known control biomarkers (e.g., through generation of a standard curve). Alternatively, relative quantification can be accomplished by comparison of detected levels or amounts between two or more different biomarkers to provide a relative quantification of each of the two or more biomarkers, e.g., relative to each other. The actual measurement of values of the biomarkers can be determined using any method known in the art. In some embodiments, a biomarker is detected by contacting a sample with reagents (e.g., antibodies or nucleic acid primers), generating complexes of reagent and biomarker(s), and detecting the complexes.

[0073] The reagent can include a probe. A probe is a molecule that binds a target, either directly or indirectly. The target can be a biomarker, a fragment of the biomarker, or any molecule that is to be detected in particular embodiments, the probe includes a nucleic acid or a protein. As an example, a protein probe can be an antibody. An antibody can be a whole antibody or a binding fragment of an antibody. A probe can be labeled with a detectable label. Examples of detectable labels include fluorescent chromophores, chemiluminescent emitters, dyes, enzymes, enzyme substrates, enzyme cofactors, enzyme inhibitors, enzyme subunits, metal ions, and radioactive isotopes.

[0074] "Protein" detection includes detection of full-length proteins, mature proteins, pre proteins, polypeptides, isoforms, mutant forms, post-translationally modified proteins and variants thereof, and can be detected in any suitable manner. The following biomarkers discussed herein are proteins: GPX-3, PF4, PBP, TSP-1 , KLKB1 , Factor V, Protein C, Protein C inhibitor, CRP, and P-ss-Cys.

[0075] Those skilled in the art will be familiar with numerous specific immunoassay formats and variations thereof which can be used to carry out the methods disclosed herein. See, e.g., E. Maggio, Enzyme-Immunoassay (1980), CRC Press, Inc., Boca Raton, Fla; and U.S. Pat. Nos. 4,727,022; 4,659,678; 4,376,110; 4,275,149; 4,233,402; and 4,230,797.

[0076] Antibodies can be conjugated or immobilized to a solid support suitable for a diagnostic assay (e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding. Antibodies can be conjugated to detectable labels or groups such as radioisotopes (e.g., ³⁵S, ¹²⁵l, ¹³¹1), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine) in accordance with known techniques.

[0077] Examples of suitable immunoassays include immunoblotting, immunoprecipitation, immunofluorescence, chemiluminescence, electro-chemiluminescence (ECL), and/or enzyme- linked immunosorbent assays (ELISA). In particular embodiments, GPX-3, PF4, PBP, TSP-1 , KLKB1 , serotonin, factor V, protein C, protein C inhibitor, CRP, and P-ss-Cys can be measured by ELISAs or by immunoprecipitation.

[0078] In particular embodiments, biomarker levels can be assessed by a protein activity assay. Exemplary protein activity assays include protease assays, kinase assays, phosphatase assays, and reductase assays, among many others. Within the context of the current disclosure, a protein activity assay could include, e.g., assays of oxidative damage (GPX-3); platelet aggregation (PF4); neutrophil activation (PBP); cell-to-matrix interactions (TSP-1); platelet activation (serotonin); etc.

[0079] Up- or down-regulation of genes also can be detected using, for example, cDNA arrays, cDNA fragment fingerprinting, cDNA sequencing, clone hybridization, differential display, differential screening, fluorescence resonance energy transfer (FRET) detection, liquid microarrays, PCR, RT-PCR, quantitative real-time RT-PCR analysis with TaqMan assays, molecular beacons, microelectric arrays, oligonucleotide arrays, polynucleotide arrays, serial analysis of gene expression (SAGE), and/or subtractive hybridization. In particular embodiments, nucleic acid sequences that correspond to nucleic acids encoding biomarkers can be used to construct primers and probes for detecting and/or measuring biomarker nucleic acids. The following biomarkers discussed herein are considered to be measurable by measuring one or more nucleic acids: GPX-3, PF4, PBP, TSP-1 , KLKB1 , Factor V, Protein C, and Protein C inhibitor, and CRP.

[0080] As an example, Northern hybridization analysis using probes which specifically recognize one or more biomarker nucleic acid sequences can be used to determine gene expression. Alternatively, expression can be measured using RT-PCR; e.g., polynucleotide primers specific for the differentially expressed biomarker mRNA sequences are used to reverse-transcribe the mRNA into complementary DNA, which is then amplified in PCR and can be visualized and quantified. Biomarker RNA can also be quantified using, for example, other target amplification methods, such as transcription mediated amplification (TMA), strand displacement amplification (SDA), and nucleic acid sequence based amplification (NASBA), or signal amplification methods (e.g., bDNA), and the like. Ribonuclease protection assays can also be used, using probes that specifically recognize one or more biomarker mRNA sequences, to quantify gene expression.

[0081] Further hybridization technologies that may be used are described in, for example, U.S. Pat. Nos. 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661 ,028; and 5,800,992 as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280.

[0082] Proteins and nucleic acids can be conjugated to or immobilized on chips, such as microarray chips. See, for example, U.S. Pat. Nos. 5,143,854; 6,087,112; 5,215,882; 5,707,807; 5,807,522; 5,958,342; 5,994,076; 6,004,755; 6,048,695; 6,060,240; 6,090,556; and 6,040,138. Microarray refers to a solid carrier or support that has a plurality of molecules bound to its surface at defined locations. The solid carrier or support can be made of any material. As an example, the material can be hard, such as metal, glass, plastic, silicon, ceramics, and textured and porous materials; or soft materials, such as gels, rubbers, polymers, and other non-rigid materials. The material can also be nylon membranes, epoxy-glass and borofiuorate-glass. The solid carrier or support can be flat, but need not be and can include any type of shape such as spherical shapes (e.g., beads or microspheres). The solid carrier or support can have a fiat surface as in slides and micro-titer plates having one or more wells. In particular embodiments, an array or microarray can include small molecules.

[0083] Binding to proteins or nucleic acids on microarrays can be detected by scanning the microarray with a variety of laser or CCD-based scanners, and extracting features with software packages, for example, Imagene (Biodiscovery, Hawthorne, CA), Feature Extraction Software (Agilent), Scanalyze (Eisen, M. 1999. SCANALYZE User Manual; Stanford Univ., Stanford, Calif. Ver 2.32.), or GenePix (Axon Instruments).

[0084] In particular embodiments, levels, amounts, or ratios of lipids of the present disclosure can be measured by an enzyme-based assay that converts a lipid to an intermediate that can be detected by a probe.

[0085] In particular embodiments, levels, amounts, or ratios of biomarkers of the present disclosure can be measured by chromatography, a process in which a chemical mixture carried by a liquid or gas is separated into components as a result of differential distribution of the chemical entities as they flow around or over a stationary liquid or solid phase. In particular embodiments, the chromatography is liquid chromatography (LC), a process of selective retardation of one or more components of a fluid solution as the fluid uniformly percolates through a column of a finely divided substance, or through capillary passageways. The retardation results from the distribution of the components of the mixture between one or more stationary phases and the bulk fluid, (i.e., mobile phase), as this fluid moves relative to the stationary phase(s). Liquid chromatography includes reverse phase liquid chromatography (RPLC), high performance liquid chromatography (HPLC) and high turbulence liquid chromatography (HTLC). In HPLC the degree of separation is increased by forcing the mobile phase under pressure through a stationary phase, typically a densely packed column. The following biomarkers discussed herein are contemplated as being measured using chromatography: serotonin, linoleic acid, arachidonic acid, 12-HETE, LysoPS 18:0, LysoPS 18:1 , and LysoPS 20:4.

[0086] In particular embodiments, the chromatography is gas chromatography (GC), a process in which a sample mixture is vaporized and injected into a stream of carrier gas (such as nitrogen or helium) moving through a column containing a stationary phase composed of a liquid or a particulate solid and is separated into its component compounds according to the affinity of the compounds for the stationary phase.

[0087] In particular embodiments, the chromatography is thin layer chromatography. Thin layer chromatography separates compounds on a thin layer of adsorbent material typically including a coating of silica gel on a glass plate or plastic sheet.

[0088] In particular embodiments, levels, amounts, or ratios of biomarkers of the present disclosure can be measured by UV spectroscopy, which measures the attenuation of a beam of light after it passes through a sample or after the light is reflected from the sample surface. The absorption measurements can be at a single wavelength of light or can be over a spectral range.

[0089] In particular embodiments, levels, amounts, or ratios of biomarkers of the present disclosure can be measured by capillary electrophoresis, which separates molecules in submillimeter diameter capillaries, microfluidic, or nanofluidic channels containing electrolyte solutions under the influence of an electric field. Capillary electrophoresis can include gel electrophoresis, capillary isoelectric focusing, capillary isotachophoresis, and micellar electrokinetic chromatography. Separated molecules appear as peaks with different retention times in an electropherogram, which reports detector response as a function of time.

[0090] In particular embodiments, levels, amounts, or ratios of biomarkers of the present disclosure can be measured by mass spectrometry. Mass spectrometry (MS) refers to an analytical technique to identify compounds by their mass. MS technology generally includes (1) ionizing the compounds to form charged compounds; and (2) detecting the molecular weight of the charged compound and calculating a mass-to-charge ratio (m/z). The compound may be ionized and detected by any suitable means. A“mass spectrometer” generally includes an ionizer and an ion detector. See, e.g., US 6,204,500; US 6,107,623; US 6,268,144; US 6,124,137; Wright et al. , Prostate Cancer and Prostatic Diseases 2:264-76 (1999); and Merchant and Weinberger, Electrophoresis 21 :1164-67 (2000).

[0091] Samples may be processed or purified to obtain preparations that are suitable for analysis by mass spectrometry. Such purification will usually include chromatography, such as liquid chromatography, and may also often involve an additional purification procedure that is performed prior to chromatography. Various procedures may be used for this purpose depending on the type of sample or the type of chromatography. Examples include filtration, extraction, precipitation, centrifugation, delipidization, dilution, combinations thereof and the like. Protein precipitation is one preferred method of preparing a liquid biological sample, such as serum or plasma, for chromatography. Such protein purification methods are well known in the art, e.g., Poison et al., Journal of Chromatography B 785: 263-275 (2003). Protein precipitation may be used to remove most of the protein from the sample leaving compounds of interest soluble in the supernatant. The samples can be centrifuged to separate the liquid supernatant from the precipitated proteins. The resultant supernatant can then be applied to liquid chromatography and subsequent mass spectrometry analysis. In particular embodiments, the protein precipitation involves adding one volume of the liquid sample (e.g. plasma) to four volumes of methanol. In particular embodiments, the method involves (1) performing a protein precipitation of the sample of interest; and (2) loading the supernatant directly onto an HPLC- mass spectrometer.

[0092] Embodiments disclosed herein can be used with high throughput screening (HTS). Typically, HTS refers to a format that performs at least 100 assays, at least 500 assays, at least 1000 assays, at least 5000 assays, at least 10,000 assays, or more per day. When enumerating assays, either the number of samples or the number of protein, nucleic acid, or other biomarkers assayed can be considered.

[0093] Generally HTS methods involve a logical or physical array of either the subject samples, or the protein or nucleic acid biomarkers, or both. In particular embodiments, an array can include small molecules. Appropriate array formats include both liquid and solid phase arrays. For example, assays employing liquid phase arrays, e.g., for hybridization of nucleic acids, binding of antibodies or other receptors to ligand, etc., can be performed in multiwell or microtiter plates. Microtiter plates with 96, 384, or 1536 wells are widely available, and even higher numbers of wells, e.g., 3456 and 9600 can be used. In general, the choice of microtiter plates is determined by the methods and equipment, e.g., robotic handling and loading systems, used for sample preparation and analysis.

[0094] HTS assays and screening systems are commercially available from, for example, Zymark Corp. (Hopkinton, MA); Air Technical Industries (Mentor, OH); Beckman Instruments, Inc. (Fullerton, CA); Precision Systems, Inc. (Natick, MA), etc. These systems typically automate entire procedures including all sample and reagent pipetting, liquid dispensing, timed incubations, and final readings of the microplate in detector(s) appropriate for the assay. These configurable systems provide HTS as well as a high degree of flexibility and customization. The manufacturers of such systems provide detailed protocols for the various methods of HTS.

[0095] (iv) Reference levels. A "dataset" as used herein is a set of numerical values resulting from evaluation of a sample (or population of samples) under a desired condition. The values of the dataset can be obtained, for example, by experimentally obtaining measures from a sample and constructing a dataset from these measurements. As is understood by one of ordinary skill in the art, the reference level can be based on e.g., any mathematical or statistical formula useful and known in the art for arriving at a meaningful aggregate reference level from a collection of individual datapoints; e.g., mean, median, median of the mean, etc. Alternatively, a reference level or dataset to create a reference level can be obtained from a service provider such as a laboratory, or from a database or a server on which the dataset has been stored. In certain embodiments of the present disclosure, a dataset of values is determined by measuring biomarkers from a healthy population which can provide a quantitative measure of adverse CVE risk in a subject.

[0096] Reference levels can be obtained from one or more relevant datasets. A reference level from a dataset can be derived from previous measures derived from a population. A "population" is any grouping of subjects or samples of like specified characteristics. The grouping could be according to, for example, clinical parameters, clinical assessments, therapeutic regimens, disease status, severity of condition, etc.

[0097] Reference levels can include "normal" or "control" levels or values, defined according to, e.g., discrimination limits or risk defining thresholds, in order to define cut-off points and/or abnormal values for adverse CVE risk. The reference level then is the level of one or more biomarkers or combined biomarker indices typically found in a subject who is not infected with HIV. Other terms for "reference levels" include "index," "baseline," "standard," "healthy," "uninfected,"“normal,” etc. Such normal levels can vary, based on whether a biomarker is used alone or in a formula combined with other biomarkers to produce a score. Alternatively, the reference level can be a database of biomarker patterns from previously tested subjects who were not infected with HIV over a clinically relevant time period. Reference levels can also be derived from, e.g., a control subject or population whose infection status is known. In particular embodiments, the reference value can be derived from one or more subjects who have been exposed to HIV, or from subjects who have shown improvements in biomarker levels disclosed herein as a result of exposure to a treatment. In particular embodiments the reference level can be derived from one or more subjects who have not been exposed to treatment. In particular embodiments, a reference level is an average of levels of a primary biomarker from a group of subjects who have HIV and who have had or who do have an adverse CVE. In particular embodiments, a reference level is an average of levels of a secondary biomarker from a group of subjects who are not infected with HIV. A reference level can also be derived from disease activity algorithms or computed indices from population studies.

[0098] In further embodiments, “reference level” can refer to a standardized value for a biomarker disclosed herein which represents a level not associated with any infection; a level associated with recent infection (e.g., less than 2 years); or a level associated with a chronic infection (e.g., more than 2 years). The reference level can be a universal reference level which is useful across a variety of testing locations. In particular embodiments, in the context of measuring biomarkers disclosed herein in a subject from the general population to predict risk for occurrence of CVE, the reference level and/or reference weighted score is derived from (i) an individual who is characterized as not having cardiovascular disease; (ii) a group of individuals who are characterized as not having cardiovascular disease; (iii) plasma from an individual or pooled plasma from a group of individuals characterized as not having cardiovascular disease. Characterization of subjects as having or not having cardiovascular disease can include consideration of: any symptoms of cardiovascular disease (e.g., fainting, slow or fast heartbeat, chest tightness, chest pain, shortness of breath, and/or sudden swelling in legs, feet, ankles or abdomen); physical exam and blood tests to measure, e.g., total cholesterol, low density lipoprotein (LDL) cholesterol, high density lipoprotein (HDL) cholesterol, triglycerides and/or CRP; results from non-invasive tests including blood pressure test, an electrocardiogram, an echocardiogram, stress test, carotid ultrasound, Holter monitor to continuously monitor heart abnormalities, a chest X-ray, a tilt table test, a CT scan, and/or heart magnetic resonance imaging (MRI); results from invasive procedures including coronary angiography and cardiac catheterization and/or an electrophysiology study; family history of heart disease; history of smoking; presence or absence of obesity; diet; age; and/or lifestyle. In particular embodiments, in the context of measuring biomarkers disclosed herein in a subject infected with HIV to predict risk for occurrence of CVE, the reference level and/or reference weighted score is derived from (i) an individual who is not infected with HIV; (ii) a group of individuals who are not infected with HIV; (iii) a subject before diagnosis with HIV; (iv) a subject at the time of diagnosis, at the beginning of a treatment regimen for HIV infection or at particular time points during a treatment; (v) pooled normal plasma (PNP) available commercially from, e.g., George King Bio-Medical Inc. (#0010-0, Overland Park, KS), Precision BioLogic Inc. (CRYOcheck™, #CCN-10, Dartmouth, Nova Scotia, CA), and Innovative Research (#IPLA-N, Novi, Michigan); (vi) an individual who is not infected with HIV and does not have cardiovascular disease at the time of blood donation; (vii) a group of individuals who are not infected with HIV and do not have cardiovascular disease at the time of blood donation; (viii) individual(s) gender- matched to HIV-infected subjects; (ix) individual(s) aged 24-33; (x) nonsmokers; (xi) individual(s) who do not have hypertension (systolic < 140 and diastolic <80 mm Hg); (xii) individual(s) who are non-anemic; (xiii) individual(s) who do not have a blood disorder or cancer; (xiv) individual(s) who do not have a cold or influenza; (xv) individual(s) who are not taking any anti-coagulation, anti-platelet, or anti-inflammation medication; and/or (xvi) individual(s) who have no known cardiovascular disease at the time of blood donation. Reference levels for a subject can also be related to time points of a subject not undergoing treatments to monitor the natural progression or regression of the disease.

[0099] In particular embodiments, obtained biomarker values can be compared to a reference level, and conclusions can be drawn based on whether a sample value is statistically significantly different or not statistically significantly different from a reference level. A measure is not statistically significantly different if the difference is within a level that would be expected to occur based on chance alone. In contrast, a statistically significant difference or increase is one that is greater than what would be expected to occur by chance alone. Statistical significance or lack thereof can be determined by any of various methods well-known in the art. Examples of commonly used measures of statistical significance include the t-test, the p-value, and other tests described herein. The p-value represents the probability of obtaining a given result equivalent to a particular datapoint, where the datapoint is the result of random chance alone. A result is often considered significant (not random chance) at a p-value less than or equal to 0.05.

[0100] In particular embodiments, a patient can be considered to be at risk if at least one of PF4, PBP, and TSP-1 are significantly elevated, provided that at least nine of the disclosed secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and the remaining secondary biomarkers are selected from serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and/or P-ss- Cys, give confirmatory results for HIV infection. In particular embodiments, a patient is considered to be at risk for CVE based on the statistically significant elevation of at least two primary biomarkers, provided that at least nine of the disclosed secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and the remaining secondary biomarkers are selected from serotonin, factor V, PROC, PCI, CRP, LA, AA, 12- HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and/or P-ss-Cys, give confirmatory results for HIV infection; combinations of such primary biomarkers include: PF4 and PBP; PF4 and TSP-1 ; and PBP and TSP-1.

[0101] In particular embodiments, a patient is considered to be at risk for CVE based on the significant elevation of PF4, PBP, and TSP-1 , provided that at least nine of the disclosed secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and the remaining secondary biomarkers are selected from serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and/or P-ss- Cys, give confirmatory results for HIV infection.

[0102]“Significantly elevated” (or significantly up-regulated or significantly increased) in various embodiments refers to an increase of more than 20%, more than 30%, more than 40%, more than 50%, more than 60%, more than 70%, more than 80%, more than 90%, more than 100%, more than 150%, or more than 200% compared to a reference level.

[0103] In particular embodiments, a patient is considered to be at risk for CVE if GPX-3 or KLKB1 is significantly down-regulated (or significantly reduced or significantly decreased), provided that at least nine of the disclosed secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, and the remaining secondary biomarkers are selected from serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and/or P-ss-Cys, give confirmatory results for HIV infection. In particular embodiments, a significant down-regulation of GPX-3 and/or KLKB1 is incorporated into any of the biomarker groupings noted above in order to identify a patient as at risk for an adverse CVE. “Significantly down-regulated” can refer to a decrease of more than 20%, more than 30%, more than 40%, more than 50%, more than 60%, more than 70%, more than 80%, more than 90%, more than 100%, more than 150%, or more than 200% compared to a reference level.

[0104] Table 1 above shows the change in level of a primary biomarker in a subject that is indicative (or not indicative) of whether the subject has an increased risk of an adverse CVE.

[0105] Particular embodiments may also include measuring the levels of at least nine secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4. In particular embodiments, levels of 9, 10, 11 , 12, or 13 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above.

In particular embodiments, levels of 9 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12- HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, P-ss-Cys, and lysoPS 20:4 serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12- HETE, P-ss-Cys, and lysoPS 18:1 serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, P-ss- Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, P-ss-Cys, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, P-ss-Cys, and lysoPS 20:4 are added to particular sets of primary biomarkers described above.

[0106] In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12- HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, P-ss-Cys, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above.

[0107] In particular embodiments, levels of 10 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 18:1 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4 are added to particular sets of primary biomarkers described above.

[0108] In particular embodiments, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 20:4, Cys, and P-ss- Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , Cys, and P-ss- Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are added to particular sets of primary biomarkers described above.

[0109] In particular embodiments, serotonin, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, 12- HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above.

[0110] In particular embodiments, serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are added to particular sets of primary biomarkers described above. In particular embodiments, levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are measured in conjunction with levels of GPX-3 and PF4. In particular embodiments, levels of PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with levels of GPX-3 and KLKB1. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above.

[0111] In particular embodiments, levels of 11 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with levels of TSP-1. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are added to particular sets of primary biomarkers described above. In particular embodiments, levels of serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are measured in conjunction with levels of GPX-3, PF4, PBP, TSP-1 , and KLKB1. In particular embodiments, serotonin, PROC, PCI, CRP, AA, 12- HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, the levels of serotonin, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with the levels of GPX-3, PBP, and KLKB1. Other combinations of 11 of the 13 secondary biomarkers can be discerned by one of ordinary skill in the art.

[0112] In particular embodiments, levels of 12 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above. In particular embodiments, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss- Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, levels of serotonin, factor V, PROC, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with levels of PF4 and TSP-1. In particular embodiments, serotonin, factor V, PROC, PCI, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:1 , lysoPS 20:4, Cys, and P- ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 20:4, Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , Cys, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and P-ss-Cys are added to particular sets of primary biomarkers described above. In particular embodiments, serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys are added to particular sets of primary biomarkers described above.

[0113] In particular embodiments, levels of 13 secondary biomarkers, where at least one of the secondary biomarkers is lysoPS 18:1 or lysoPS 20:4, are measured in conjunction with particular sets of primary biomarkers described above. In particular embodiments, levels of serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with levels of GPX-3 and PBP. In particular embodiments, levels of serotonin, factor V, PROC, PCI, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, Cys, and P-ss-Cys are measured in conjunction with levels of PF4, PBP, TSP-1 , and KLKB1.

[0114] Table 2 shows the change in level of each secondary biomarker that is indicative (or not indicative) of an HIV infection in a subject.

[0115] In particular embodiments, values obtained about the biomarkers and/or other dataset components can be subjected to an analytic process with chosen parameters. The parameters of the analytic process may be those disclosed herein or those derived using guidelines described herein. The analytic process used to generate a result may be any type of process capable of providing a result useful for classifying a sample, for example, comparison of the obtained value with a reference level, a linear algorithm, a quadratic algorithm, a decision tree algorithm, or a voting algorithm. The analytic process may set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least at least 60%, at least 70%, at least 80%, at least 90%, at least 95% or higher.

[0116] "Interpretation functions," as used herein, means the transformation of a set of observed data into a meaningful determination of particular interest; e.g., an interpretation function may be a predictive model that is created by utilizing one or more statistical algorithms to transform a dataset of observed biomarker data into a meaningful determination of adverse CVE risk in an HIV-infected subject.

[0117] In particular embodiments when more than one biomarker is assayed, values of the detected biomarkers can be calculated into a score. Each value can be weighted evenly within an algorithm generating a score, or the values for particular biomarkers can be weighted more heavily in reaching the score. For example, biomarkers with higher sensitivity and/or specificity can be weighted more heavily than biomarkers with lower sensitivity and/or specificity to determine scores. Biomarkers may also be grouped into classes, and each class given a weighted score. For example, primary biomarker values for diagnosing a patient with increased risk of an adverse CVE may be grouped into classes and weighted as follows (from highest weight to lowest weight): Class 1 : PF4, PBP, and TSP-1 ; and Class 2: GPX-3 and KLKB1. Secondary biomarker values for confirming whether a patient is infected with HIV may be grouped into classes and weighted as follows (from highest weight to lowest weight): Class 1 : serotonin and CRP; Class 2: factor V, PROC, and PCI; Class 3: linoleic acid, arachidonic acid, and 12-HETE; Class 4: lysoPS 18:0, lysoPS 18:1 , and lysoPS 20:4; and Class 5: Cys and P-ss- Cys.

[0118] In particular embodiments, weighting scores involves converting the measurement of one biomarker that is identified and quantified in a test sample into one of many potential scores. A receiver operating characteristic (ROC) curve can be used to standardize the scoring between different biomarkers by enabling the use of a weighted score based on the inverse of a false positive % or false negative % defined from the ROC curve. The weighted score can be calculated by multiplying the AUC by a factor for a biomarker and then dividing by the false positive % or false negative % based on a ROC curve. The weighted score can be calculated using the formula:

Weighted Score=(AUC_x X factor)/(1-% specificity_x)

wherein x is the biomarker; the, "factor," is a real number (such as 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25 and so on) throughout a particular set of biomarkers; and the specificity is a chosen value that does not exceed 95%. Multiplication of a factor for the particular set of primary biomarkers allows the user to scale the weighted score.

[0119] (v) Methods of Use. Particular embodiments disclosed herein include obtaining a sample (e.g., blood, plasma, serum, saliva, urine, a sample including cells) derived from a subject; and testing the sample for up- or down-regulation of one or more biomarkers disclosed herein. In particular embodiments, the testing includes measuring the level(s) of the one or more biomarkers disclosed herein using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof. In particular embodiments, methods disclosed herein include obtaining a biological sample derived from an HIV-infected subject; assaying the sample for up- or down-regulation of one or more biomarkers disclosed herein; determining one or more biomarker values based on the assaying; comparing the one or more biomarker values to a reference level; diagnosing or identifying the HIV-infected subject as having an increased risk for an adverse CVE or not at increased risk for an adverse CVE according to the up- or down regulation of biomarkers, as described elsewhere herein.

[0120] In particular embodiments, identifying an HIV-infected subject as having an increased risk for an adverse CVE or not having an increased risk for an adverse CVE includes marking a biological sample appropriately so that the HIV-infected subject (from whom the marked biological sample was derived) receives or does not receive a selected, appropriate treatment or disease management procedure or protocol. The marking can include physically marking a container that the biological sample resides in with appropriate information, or entering such appropriate information about the biological sample into a computer.

[0121] In particular embodiments, a biological sample can be assessed 1 time, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times and every remaining integer up to 100 times or more.

[0122] Particular embodiments include monitoring HIV-infected patients for levels of one or more biomarkers described herein over a period of time. In particular embodiments, an HIV patient is selected for adverse CVE risk screening according to the systems and methods disclosed herein because they have been identified as a patient that would benefit from monitoring for risk of occurrence of CVE. Patients who could benefit from monitoring for risk of occurrence of CVE can include those who have been infected with HIV for more than 2 years and/or have been on retroviral therapies for more than 2 years. In particular embodiments, patients who could benefit from monitoring for risk of occurrence of CVE can include those who have been infected with HIV for more than 6 months and/or have been on retroviral therapies for more than 6 months. In particular embodiments, patients who could benefit from monitoring for risk of occurrence of CVE can include those who have been infected with HIV for more than 1 year and/or have been on retroviral therapies for more than 1 year. In particular embodiments, patients who could benefit from monitoring for risk of occurrence of CVE can include those who have been infected with HIV for more than 5 years and/or have been on retroviral therapies for more than 5 years.

[0123] In particular embodiments, biological samples can be obtained and assessed from an HIV-infected individual subject weekly, monthly, every 2 months, every 3 months, every 4 months, every 5 months, every 6 months, every 7 months, every 8 months, every 9 months, every 10 months, or every 11 months, yearly, or at longer spaced periods, to determine if the subject has or has developed an increased risk of an adverse CVE.

[0124] A diagnosis or identification of an HIV-infected subject at increased risk for adverse CVE according to the systems and methods disclosed herein can direct a treatment regimen and inform disease management. The results of the methods can be used for clinical decision and support, such as determining whether to defer intervention or treatment, to recommend preventive check-ups (or the frequency of such check-ups) for at-risk patients, to recommend increased (or decreased) visit frequency, to recommend increased (or decreased) testing, and/or to recommend intervention (including in some embodiments the type, frequency, duration, etc. of such intervention). The results of the methods can also be useful for selection of therapy, determining response to treatment, adjustment and dosing of treatment, monitoring ongoing therapeutic efficiency, and indication for change in therapeutic regimens.

[0125] Adverse CVEs can include nonfatal stroke, nonfatal myocardial infarction, heart failure, malignant dysrhythmia, cardiac shock, and cardiovascular death. A stroke is a medical condition in which poor blood flow to the brain results in cell death. Two main types of stroke include: ischemic, referring to lack of blood flow; and hemorrhagic, referring to bleeding. Myocardial infarction (Ml) is commonly known as a heart attack and occurs when blood flow decreases or stops to a part of the heart, causing damage to the heart muscle. Heart failure, also referred to as congestive heart failure, occurs when the heart is unable to pump sufficiently to maintain blood flow to meet the body's needs. Malignant dysrhythmia can result in the loss of contraction of the heart with subsequent lack of blood supply to vital organs like the brain. Cardiac (or cardiogenic) shock is a condition in which the heart suddenly can't pump enough blood to meet the body's needs. The condition is most often caused by a severe heart attack, but not everyone who has a heart attack has cardiogenic shock.

[0126] Treatments to prevent cardiovascular events include the use of aspirin; anti-hypertensive drugs such as beta-blockers (e.g., propranolol, timolol and metoprolol), angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blockers, calcium-channel blockers, thiazide-like diuretics, alpha-blockers, central alpha-agonists, and peripheral alpha-agonists; lipid lowering drugs such as statins, fibrates, and nicotinic acid; and modification of lifestyle related risk behaviors. Lifestyle changes include smoking cessation, reduction in alcohol consumption, weight control, improvements in diet, and increase in physical activity.

[0127] In a patient undergoing treatment for an increased risk of an adverse CVE, biological samples can be obtained and assessed from an individual patient weekly, monthly, every 2 months, every 3 months, every 4 months, every 5 months, every 6 months, every 7 months, every 8 months, every 9 months, every 10 months, or every 11 months, or yearly to determine if the increased risk of an adverse CVE has progressed, regressed, or has been successfully or unsuccessfully treated.

[0128] In particular embodiments,“stable” measures are measures evaluated in relation to a previous comparison in the same patient and denote a stable biomarker level that has not changed significantly (as determined by a statistical measure known in the art such as a t-test or p-value, e.g., p value >0.05) since the last measurement. In particular embodiments,“stable” measures are measures evaluated in relation to a previous comparison in the same patient and denote a biomarker level that has not changed significantly (as determined by a statistical measure known in the art such as a t-test or p-value, e.g., p value >0.05) since an aggregated or averaged group of previous measurements (e.g., the last 3, 4, or 5 measurements).

[0129]“Unchanged” measures are measures evaluated in relation to a previous comparison in the same patient and denote a failure to achieve a statistically significant change (e.g., as determined by a statistical measure known in the art such as a t-test or p-value, e.g., p value >0.05) in a score towards or away from a reference level in the particular subject. In particular embodiments, “unchanged” measures are measures that have not changed in relation to a previous measurement in the same patient or since an aggregated or averaged group of previous measurements in the patient (e.g., the last 3, 4, or 5 measurements).

[0130] (vi) Kits. The systems and methods disclosed herein include kits. Disclosed kits include material(s) and reagent(s) necessary to assay a sample obtained from a subject for one or more biomarkers disclosed herein. The materials and reagents can include those necessary to assay the biomarkers disclosed herein according to any method described herein and/or known to one of ordinary skill in the art.

[0131] Particular embodiments include materials and reagents necessary to assay for up- or down-regulation of a biomarker protein in a sample. In particular embodiments, the kits include antibodies to biomarker proteins and/or aptamers, epitopes or mimotopes or antigens to bind antibodies. Other embodiments additionally or alternatively include oligonucleotides that specifically assay for one or more biomarker nucleic acids based on homology and/or complementarity with biomarker nucleic acids. The oligonucleotide sequences may correspond to fragments of the biomarker nucleic acids. For example, the oligonucleotides can be more than 200, 175, 150, 100, 50, 25, 10, or fewer than 10 nucleotides in length. Collectively, any molecule (e.g., antibody, aptamer, epitope, mimotope, oligonucleotide) that forms a complex with a biomarker is referred to as a biomarker binding agent herein. In particular embodiments, the kits include reagents to measure up- or down-regulation of a small molecule biomarker in assays including liquid chromatography, gas chromatography, thin layer chromatography, UV spectroscopy, capillary electrophoresis, and/or mass spectrometry. In particular embodiments, the kits include reagents to measure up- or down-regulation of a biomarker in activity assays such as oxidation/reduction assays, platelet activation assays, platelet aggregation assays, neutrophil activation assays, endothelial cell activation assays, and/or cell-matrix interaction assays.

[0132] Embodiments of kits can contain in separate containers biomarker binding agents either bound to a matrix, or packaged separately with reagents for binding to a matrix. In particular embodiments, the matrix is, for example, a porous strip. In some embodiments, measurement or detection regions of the porous strip can include a plurality of sites containing biomarker binding agents. In some embodiments, the porous strip can also contain sites for negative and/or positive controls. Alternatively, control sites can be located on a separate strip from the porous strip. Optionally, the different detection sites can contain different amounts of biomarker binding agents, e.g., a higher amount in the first detection site and lesser amounts in subsequent sites. Upon the addition of test sample, the number of sites displaying a detectable signal provides a quantitative indication of the amount of biomarker present in the sample. The detection sites can be configured in any suitably detectable size and shape and can be, e.g., in the shape of a bar or dot spanning the width (or a portion thereof) of a porous strip.

[0133] In some embodiments the matrix can be a solid substrate, such as a "chip." See, e.g., U.S. Pat. No. 5,744,305. In some embodiments the matrix can be a solution array; e.g., xMAP (Luminex, Austin, Tex.), Cyvera (lllumina, San Diego, Calif.), RayBio Antibody Arrays (RayBiotech, Inc., Norcross, Ga.), CellCard (Vitra Bioscience, Mountain View, Calif.) and Quantum Dots' Mosaic (Invitrogen, Carlsbad, Calif.).

[0134] Additional embodiments can include control formulations (positive and/or negative), and/or one or more detectable labels, such as fluorescein, green fluorescent protein, rhodamine, cyanine dyes, dialkylcarbocyanine dyes, Alexa dyes, luciferase, horseradish peroxidase, radiolabels, enzyme reporter, colorimetric label, chemiluminescent label, colored particles, gold nanoparticles, colloids, magnetic bead, or biotin among others. Instructions for carrying out the assay, including, optionally, instructions for generating a score, can be included in the kit; e.g., written, tape, VCR, or CD-ROM.

[0135] In particular embodiments, the kits include materials and reagents necessary to conduct an immunoassay (e.g., ELISA). In particular embodiments, the kits include materials and reagents necessary to conduct hybridization assays (e.g., PCR). In particular embodiments, materials and reagents expressly exclude equipment (e.g., plate readers). In particular embodiments, kits can exclude materials and reagents commonly found in laboratory settings (pipettes; test tubes; buffer solutions, distilled H2O).

[0136] (vii) Biomarker Variants. In particular embodiments, biomarkers include the protein forms of the biomarkers as well as associated nucleic acids, oligonucleotides, and metabolites, together with their related metabolites, mutations, isoforms, variants, polymorphisms, modifications, fragments, subunits, degradation products, elements, and other analytes or sample-derived measures.

[0137] Biomarkers can also include mutated proteins, mutated nucleic acids, variations in copy numbers, and/or transcript variants.

[0138] Variants of the sequences disclosed and referenced herein are also included. Guidance in determining which amino acid residues can be substituted, inserted, or deleted without abolishing biological activity can be found using computer programs well known in the art, such as DNASTAR™ (Madison, Wisconsin) software. Preferably, amino acid changes in the protein variants disclosed herein are conservative amino acid changes, i.e. , substitutions of similarly charged or uncharged amino acids. A conservative amino acid change involves substitution of one of a family of amino acids which are related in their side chains.

[0139] In a peptide or protein, suitable conservative substitutions of amino acids are known to those of skill in this art and generally can be made without altering a biological activity of a resulting molecule. Those of skill in this art recognize that, in general, single amino acid substitutions in non-essential regions of a polypeptide do not substantially alter biological activity (see, e.g., Watson et al. Molecular Biology of the Gene, 4th Edition, 1987, The Benjamin/Cummings Pub. Co., p. 224). Naturally occurring amino acids are generally divided into conservative substitution families as follows: Group 1 : Alanine (Ala), Glycine (Gly), Serine (Ser), and Threonine (Thr); Group 2: (acidic): Aspartic acid (Asp), and Glutamic acid (Glu); Group 3: (acidic; also classified as polar, negatively charged residues and their amides): Asparagine (Asn), Glutamine (Gin), Asp, and Glu; Group 4: Gin and Asn; Group 5: (basic; also classified as polar, positively charged residues): Arginine (Arg), Lysine (Lys), and Histidine (His); Group 6 (large aliphatic, nonpolar residues): Isoleucine (lie), Leucine (Leu), Methionine (Met), Valine (Val) and Cysteine (Cys); Group 7 (uncharged polar): Tyrosine (Tyr), Gly, Asn, Gin, Cys, Ser, and Thr; Group 8 (large aromatic residues): Phenylalanine (Phe), Tryptophan (Trp), and Tyr; Group 9 (non-polar): Proline (Pro), Ala, Val, Leu, lie, Phe, Met, and Trp; Group 11 (aliphatic): Gly, Ala, Val, Leu, and lie; Group 10 (small aliphatic, nonpolar or slightly polar residues): Ala, Ser, Thr, Pro, and Gly; and Group 12 (sulfur-containing): Met and Cys. Additional information can be found in Creighton (1984) Proteins, W.H. Freeman and Company.

[0140] In making such changes, the hydropathic index of amino acids may be considered. The importance of the hydropathic amino acid index in conferring interactive biologic function on a protein is generally understood in the art (Kyte and Doolittle, 1982, J. Mol. Biol. 157(1), 105-32). Each amino acid has been assigned a hydropathic index on the basis of its hydrophobicity and charge characteristics (Kyte and Doolittle, 1982). These values are: lie (+4.5); Val (+4.2); Leu (+3.8); Phe (+2.8); Cys (+2.5); Met (+1.9); Ala (+1.8); Gly (-0.4); Thr (-0.7); Ser (-0.8); Trp (-0.9); Tyr (-1.3); Pro (-1.6); His (-3.2); Glutamate (-3.5); Gin (-3.5); aspartate (-3.5); Asn (-3.5); Lys (-3.9); and Arg (-4.5).

[0141] It is known in the art that certain amino acids may be substituted by other amino acids having a similar hydropathic index or score and still result in a protein with similar biological activity, i.e. , still obtain a biological functionally equivalent protein. In making such changes, the substitution of amino acids whose hydropathic indices are within ±2 is preferred, those within ±1 are particularly preferred, and those within ±0.5 are even more particularly preferred. It is also understood in the art that the substitution of like amino acids can be made effectively on the basis of hydrophilicity.

[0142] As detailed in U.S. Pat. No. 4,554,101 , the following hydrophilicity values have been assigned to amino acid residues: Arg (+3.0); Lys (+3.0); aspartate (+3.0±1); glutamate (+3.0±1); Ser (+0.3); Asn (+0.2); Gin (+0.2); Gly (0); Thr (-0.4); Pro (-0.5±1); Ala (-0.5); His (-0.5); Cys (-1.0); Met (-1.3); Val (-1.5); Leu (-1.8); lie (-1.8); Tyr (-2.3); Phe (-2.5); Trp (-3.4). It is understood that an amino acid can be substituted for another having a similar hydrophilicity value and still obtain a biologically equivalent, and in particular, an immunologically equivalent protein. In such changes, the substitution of amino acids whose hydrophilicity values are within ±2 is preferred, those within ±1 are particularly preferred, and those within ±0.5 are even more particularly preferred.

[0143] As outlined above, amino acid substitutions may be based on the relative similarity of the amino acid side-chain substituents, for example, their hydrophobicity, hydrophilicity, charge, size, and the like.

[0144] Variants of gene sequences can include codon optimized variants, sequence polymorphisms, splice variants, and/or mutations that do not affect the function of an encoded product to a statisti cally-significant degree.

[0145] Variants of the protein, nucleic acid, and gene sequences disclosed herein also include sequences with at least 70% sequence identity, 80% sequence identity, 85% sequence, 90% sequence identity, 95% sequence identity, 96% sequence identity, 97% sequence identity, 98% sequence identity, or 99% sequence identity to the protein, nucleic acid, or gene sequences disclosed herein.

[0146]“% sequence identity” refers to a relationship between two or more sequences, as determined by comparing the sequences. In the art, "identity" also means the degree of sequence relatedness between protein, nucleic acid, or gene sequences as determined by the match between strings of such sequences. "Identity" (often referred to as "similarity") can be readily calculated by known methods, including (but not limited to) those described in: Computational Molecular Biology (Lesk, A. M., ed.) Oxford University Press, NY (1988); Biocomputing: Informatics and Genome Projects (Smith, D. W., ed.) Academic Press, NY (1994); Computer Analysis of Sequence Data, Part I (Griffin, A. M., and Griffin, H. G., eds.) Humana Press, NJ (1994); Sequence Analysis in Molecular Biology (Von Heijne, G., ed.) Academic Press (1987); and Sequence Analysis Primer (Gribskov, M. and Devereux, J., eds.) Oxford University Press, NY (1992). Preferred methods to determine identity are designed to give the best match between the sequences tested. Methods to determine identity and similarity are codified in publicly available computer programs. Sequence alignments and percent identity calculations may be performed using the Megalign program of the LASERGENE bioinformatics computing suite (DNASTAR, Inc., Madison, Wisconsin). Multiple alignment of the sequences can also be performed using the Clustal method of alignment (Higgins and Sharp CABIOS, 5, 151-153 (1989) with default parameters (GAP PENALTY=10, GAP LENGTH PENALTY=10). Relevant programs also include the GCG suite of programs (Wisconsin Package Version 9.0, Genetics Computer Group (GCG), Madison, Wisconsin); BLASTP, BLASTN, BLASTX (Altschul, et al., J. Mol. Biol. 215:403-410 (1990); DNASTAR (DNASTAR, Inc., Madison, Wisconsin); and the FASTA program incorporating the Smith-Waterman algorithm (Pearson, Comput. Methods Genome Res., [Proc. Int. Symp.] (1994), Meeting Date 1992, 111-20. Editor(s): Suhai, Sandor. Publisher: Plenum, New York, N.Y. Within the context of this disclosure it will be understood that where sequence analysis software is used for analysis, the results of the analysis are based on the "default values" of the program referenced. As used herein "default values" will mean any set of values or parameters, which originally load with the software when first initialized.

[0147] Variants also include nucleic acid molecules that hybridizes under stringent hybridization conditions to a sequence disclosed herein and provide the same function as the reference sequence. Exemplary stringent hybridization conditions include an overnight incubation at 42 °C in a solution including 50% formamide, 5XSSC (750 mM NaCI, 75 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6), 5XDenhardt's solution, 10% dextran sulfate, and 20 pg/ml denatured, sheared salmon sperm DNA, followed by washing the filters in 0.1XSSC at 50 °C. Changes in the stringency of hybridization and signal detection are primarily accomplished through the manipulation of formamide concentration (lower percentages of formamide result in lowered stringency); salt conditions, or temperature. For example, moderately high stringency conditions include an overnight incubation at 37°C in a solution including 6XSSPE (20XSSPE=3M NaCI; 0.2M NaH₂P0₄; 0.02M EDTA, pH 7.4), 0.5% SDS, 30% formamide, 100 pg/ml salmon sperm blocking DNA; followed by washes at 50 °C with 1XSSPE, 0.1% SDS. In addition, to achieve even lower stringency, washes performed following stringent hybridization can be done at higher salt concentrations (e.g. 5XSSC). Variations in the above conditions may be accomplished through the inclusion and/or substitution of alternate blocking reagents used to suppress background in hybridization experiments. Typical blocking reagents include Denhardt's reagent, BLOTTO, heparin, denatured salmon sperm DNA, and commercially available proprietary formulations. The inclusion of specific blocking reagents may require modification of the hybridization conditions described above, due to problems with compatibility.

[0148] The Exemplary Embodiments and Example below are included to demonstrate particular embodiments of the disclosure. Those of ordinary skill in the art should recognize in light of the present disclosure that many changes can be made to the specific embodiments disclosed herein and still obtain a like or similar result without departing from the spirit and scope of the disclosure.

[0149] Exemplary Embodiments.

1. A method of identifying a subject infected with human immunodeficiency virus (HIV) as having an increased risk of an adverse cardiovascular event (CVE) or not having an increased risk of an adverse CVE, including:

obtaining a biological sample derived from the subject;

measuring a level of each of one or more primary biomarkers selected from the group consisting of glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); and plasma kallikrein (KLKB1);

measuring levels of nine or more secondary biomarkers wherein at least one of the secondary biomarkers is lysophosphatidylserine 18:1 (lysoPS 18:1) or lysophosphatidylserine 20:4 (lysoPS 20:4) and the remaining secondary biomarkers are selected from the group consisting of serotonin; factor V; protein C (PROC); protein C inhibitor (PCI); C-reactive protein (CRP); linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysoPS 18:1 ; lysoPS 20:4; Cysteine (Cys); and protein bound Cysteine (P-ss-Cys);

comparing the level of each measured primary biomarker to a corresponding first reference level of the same biomarker;

comparing the level of each measured secondary biomarker to a corresponding second reference level of the same biomarker;

identifying the subject as having an increased risk of an adverse CVE if:

the level of each of one or more of GPX-3 and KLKB1 is decreased compared to the corresponding first reference level; and/or

the level of each of one or more of PF4, PBP, and TSP-1 is increased compared to the corresponding first reference level;

and

the level of each of at least one of lysoPS 18:1 or lysoPS 20:4 is increased compared to the corresponding second reference level; and

the level of each of at least one of serotonin, factor V, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and P-ss-Cys is increased compared to the corresponding reference level; and/or

the level of each of at least one of PROC, PCI, and Cys is decreased compared to the corresponding reference level;

or

identifying the subject as not having an increased risk of an adverse CVE if:

the level of each of one or more of GPX-3 and KLKB1 is increased or unchanged as compared to the corresponding first reference level; and/or

the level of each of one or more of PF4, PBP, and TSP-1 is decreased or unchanged as compared to the corresponding first reference level;

and

the level of each of at least one of serotonin, factor V, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and P-ss-Cys is increased compared to the corresponding second reference level; and/or

the level of each of at least one of PROC, PCI, and Cys is decreased compared to the corresponding second reference level.

2. The method of embodiment 1 , wherein the first reference level is derived from a control sample including one or more individuals who have HIV and who have had or who have an adverse CVE.

3. The method of embodiment 1 or 2, wherein the second reference level is derived from a control sample including one or more individuals who are not infected with HIV.

4. The method of embodiment 2 or 3, wherein the control sample includes two or more individuals.

5. The method of any one of embodiments 1-4, wherein the first and/or second reference level includes an average of levels of biomarkers measured in the individuals. 6. The method of any one of embodiments 1-5, wherein the biological sample is plasma.

7. The method of embodiment 6, wherein the plasma is depleted of one or more of albumin, IgG, a1 -antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein A1 , apolipoprotein All, complement C3, and transthyretin before the measuring.

8. The method of any one of embodiments 1-7, wherein the measuring includes measuring the levels of PF4, PBP, TSP-1 , and KLKB1.

9. The method of any one of embodiments 1-8, wherein the measuring includes measuring the levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys.

10. The method of any one of embodiments 1-9, wherein the measuring includes using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

11. A kit for diagnosing an HIV-infected subject with an increased risk of an adverse cardiovascular event (CVE) including one or more binding agents, each binding agent able to bind a biomarker selected from glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); plasma kallikrein (KLKB1); serotonin; factor V; protein C; protein C inhibitor; C-reactive protein (CRP); Cysteine (Cys); and protein bound Cysteine (P-ss-Cys).

12. The kit of embodiment 11 , wherein the binding agents are proteins, antibodies, aptamers, mimotopes, or oligonucleotides.

13. The kit of embodiment 11 or 12, further including a detectable label.

14. The kit of embodiment 13, wherein the detectable label is a radioactive isotope, enzyme reporter, colorimetric label, fluorescent label, chemiluminescent label, colored particles, gold nanoparticles, colloids, magnetic bead, or biotin.

15. The kit of any one of embodiments 11-14, wherein the kit includes reagents to perform amplification of nucleic acids, an immunoassay, an immunohistochemical staining, flow cytometry, an enzyme-based colorimetric assay, and/or a protein activity assay.

16. The kit of embodiment 15, wherein the protein activity assay includes an assay selected from an oxidation/reduction assay, a platelet aggregation assay, a platelet activation assay, an endothelial cell activation assay, and/or a cell-matrix interaction assay.

17. The kit of any one of embodiments 11-16, further including reagents to detect a biomarker selected from linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12- HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysophosphatidylserine 18:1 (lysoPS 18:1); lysophosphatidylserine 20:4 (lysoPS 20:4); Cys; and P-ss-Cys.

18. The kit of embodiment 17, wherein the reagents are used in liquid chromatography, gas chromatography, thin layer chromatography, UV spectroscopy, capillary electrophoresis, and/or mass spectrometry.

19. A method of treating or not treating an HIV-infected subject for an adverse cardiovascular event (CVE) including:

obtaining a biological sample derived from the subject;

identifying the subject as having an increased risk of an adverse CVE if:

and

the level of each of at least one of PROC, PCI, and Cys is decreased compared to the corresponding reference level; or

identifying the subject as not having an increased risk of an adverse CVE if:

and

the level of each of at least one of PROC, PCI, and Cys is decreased compared to the corresponding second reference level;

and

treating the subject for an adverse CVE if the subject is identified as having an increased risk of an adverse CVE,

or

not treating the subject for an adverse CVE if the subject is identified as not having an increased risk of an adverse CVE.

20. The method of embodiment 19, wherein the treating includes administering drugs selected from aspirin, anti-hypertensive drugs, angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blockers, calcium-channel blockers, thiazide-like diuretics, alpha-blockers, central alpha-agonists, peripheral alpha-agonists, and lipid lowering drugs.

21. The method of embodiment 19 or 20, wherein the treating includes ceasing smoking, reducing alcohol consumption, reducing weight, improving diet, and/or increasing physical activity.

22. The method of any one of embodiments 19-21 , wherein the first reference level is derived from a control sample including one or more individuals who have HIV and who have had or who have an adverse CVE.

23. The method of any one of embodiments 19-22, wherein the second reference level is derived from a control sample including one or more individuals who are not infected with HIV.

24. The method of embodiment 22 or 23, wherein the control sample includes two or more individuals. 25. The method of any one of embodiments 19-24, wherein the first and/or second reference level includes an average of levels of biomarkers measured in the individuals.

26. The method of any one of embodiments 19-25, wherein the biological sample is plasma.

27. The method of any one of embodiments 19-26, wherein the measuring includes using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

28. A method of monitoring an HIV-infected subject for risk of an adverse cardiovascular event (CVE) including:

obtaining a biological sample derived from the subject;

identifying the subject as having an increased risk of an adverse CVE if:

and

the level of each of at least one of serotonin, factor V, CRP, LA, AA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and P-ss-Cys is increased compared to the corresponding reference level; and/or the level of each of at least one of PROC, PCI, and Cys is decreased compared to the corresponding reference level;

or

identifying the subject as not having an increased risk of an adverse CVE if:

and

repeating the measuring through the identifying, thereby monitoring an HIV-infected subject for risk of an adverse CVE.

29. A method, including:

obtaining a biological sample derived from an HIV-infected subject;

testing the biological sample for a level of each of one or more primary biomarkers selected from the group consisting of glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); and plasma kallikrein (KLKB1); and testing the biological sample for levels of nine or more secondary biomarkers wherein at least one of the secondary biomarkers is lysophosphatidylserine 18:1 (lysoPS 18:1) or lysophosphatidylserine 20:4 (lysoPS 20:4) and the remaining secondary biomarkers are selected from the group consisting of serotonin; factor V; protein C (PROC); protein C inhibitor (PCI); C-reactive protein (CRP); linoleic acid (LA); arachidonic acid (AA); 12- hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysoPS 18:1 ; lysoPS 20:4; Cysteine (Cys); and protein bound Cysteine (P-ss-Cys).

30. The method of embodiment 29, wherein the testing includes measuring the level of the one or more primary biomarkers and measuring the levels of the nine or more secondary biomarkers. 31. The method of embodiment 30, wherein the measuring includes measuring the levels of PF4, PPBP, TSP-1 , and KLKB1.

32. The method of embodiment 30 or 31 , wherein the measuring includes measuring the levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys.

33. The method of any one of embodiments 30-32, wherein the measuring includes using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

34. The method of any one of embodiments 30-33, wherein the biological sample is plasma.

35. The method of embodiment 34, wherein the plasma is depleted of one or more of albumin, IgG, a1 -antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein A1 , apolipoprotein All, complement C3, and transthyretin.

36. An array including a biomarker selected from glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); plasma kallikrein (KLKB1); serotonin; factor V; protein C; protein C inhibitor; C-reactive protein (CRP); and/or protein bound Cys.

37. The array of embodiment 36, wherein the array is a protein array.

38. The array of embodiment 36, wherein the array is a nucleic acid array.

39. The array of any one of embodiments 36-38, wherein the array is a microarray.

40. An array including a biomarker selected from serotonin; linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysophosphatidylserine 18:1 (lysoPS 18:1); lysophosphatidylserine 20:4 (lysoPS 20:4); and/or Cys.

[0150] Example 1. This Example describes targeted metabolomic and proteomic profiles of two subsets of HIV patients with myocardial infarction (Ml) or ischemic stroke compared to corresponding matched controls.

[0151] Study cohort. The study cohort included subjects from a national network of 8 HIV clinical care sites. The population is large and diverse with regard to sex, race/ethnicity, age, and transmission risk factor. The subset for metabolomic analyses included normal control subjects (n=6), HIV patients without cardiovascular events (CVE, n=4), and HIV patients who have suffered either Ml or stroke (n=7). For HIV infected subjects, two plasma samples from each subject collected at two time points were studied. In proteomic analyses, the subset included 4 normal individuals, two HIV patients without CVE, and 3 HIV patients with CVE; two samples from each HIV patient were also analyzed. In targeted metabolomic studies, a panel of 47 lipid and oxylipin targets, as well as a panel of 68 targets representing metabolites from arginine and tryptophan metabolic pathways, phosphatidylcholine-related metabolites, and carnitine-related metabolites were analyzed. In targeted proteomic studies, a panel of 32 plasma proteins indicative of oxidative stress, platelet activation, endothelial activation, inflammation, and thrombosis was analyzed. Additional protein targets were also quantified by ELISA.

[0152] Materials and Methods. In proteomics studies, 10 pL of human plasma was depleted of the 14 highest abundance proteins with the Human 14 Multiple Affinity Removal Spin Cartridge (Human-14, Agilent, Santa Clara, CA). This cartridge removed 94% of albumin, IgG, a1- antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein Al, apolipoprotein All, complement C3 and transthyretin. Ten pg of depleted plasma proteins were reduced with dithiothreitol, alkylated with iodoacetamide, and digested with trypsin (Chen et al. Blood. 2010;115(3):706-712). Tryptic peptides were analyzed by LC- MS/MS with a Thermo Scientific LTQ OrbitrapVelos mass spectrometer coupled to a Waters nanoAcquity Ultra Performance LC system using an HSS T3 nanoACQUITY column. MS/MS spectra were searched against the human protein database from UniProt using Proteome Discoverer software (Thermo Fisher Scientific, Waltham, MA). All protein identifications required detection of two unique peptides from each protein. Protein abundance was determined by peak area of unique peptides detected or spectral counts. For comparison, peak area was normalized to the mean. Reproducibility was monitored with isotopically labeled peptides (<5%). For polyunsaturated fatty acids, oxylipins, and lysophospholipids, methods as described in previous publications were used (Fu et al. Transfusion. 2016;56(10):2560-2570; Fu et al. Transfusion. 2017;57(S3)). Briefly, metabolites in plasma containing isotopically labeled internal standards were extracted with 80% methanol. Extracted metabolites were analyzed by LC-MS/MS with multiple reaction monitoring (MRM) using a AB Sciex 6500 QTRAP mass spectrometer coupled with a Waters Acquity l-class UPLC system in negative mode. Same extractions were used for the analysis of other 68 metabolites using LC-MS/MS-MRM in either positive or negative ion mode.

[0153] Results. Biomarkers of oxidative stress. Proteomic analysis showed a significant decrease in the level of plasma glutathione peroxidase-3 (GPX-3) in HIV patients without CVE, and the level of GPX-3 further decreased in HIV patients with CVE (FIG. 1). GPX-3 is a selenium-containing enzyme, which scavenges reactive oxygen species in plasma. It has been reported that a deficiency in GPX-3 results in a prothrombotic state that promotes platelet- dependent arterial thrombosis (Jin et al. Circulation. 2011 ;123(18): 1963-1973). Therefore, reduced levels of GPX-3 in HIV patients correlate with a reduced capacity to mitigate oxidative stress. Elevated levels of cystine and protein bound Cys indicated the patients were under oxidative stress (FIGs. 9A, 9B). Cystine (Cys-ss-Cys) is an oxidized form of cysteine, in which two cysteine molecules are linked by a disulfide bond. Protein bound Cys (P-ss-Cys) is another oxidized form of cysteine, in which the cysteine is bound by a disulfide bond to another cysteine molecule that is in a protein. Elevation of both forms of oxidized cysteine is consistent with a state of oxidative stress in HIV-infected patients.

[0154] Targeted metabolomic analyses by mass spectrometry showed that two omega-6 polyunsaturated fatty acids, linoleic acid (LA) and arachidonic acid (AA), were elevated in HIV patients (FIGs. 7A, 7B), while the levels of two other polyunsaturated fatty acids EPA and DHA remained essentially unchanged (not shown). Elevated levels of omega-6 fatty acids including LA and AA correlate with proinflam matory conditions (Simopoulos, World Rev Nutr Diet. 2003;92:1-22) and elevated AA, an agonist for platelets, is prothrombotic. Analysis for oxidized derivatives of AA also showed significant elevations in 12-hydroxyeicosatetraenoic acid (12- HETE) levels in HIV patients (FIG. 7C). 12-HETE is derived from AA by oxidation by platelet arachidonic lipoxygenase 12 (12-LOX). High 12-HETE levels correlate with an inflammatory state and pro-aggregation state, characterized by activation of neutrophils, monocytes, eosinophils and platelets. Thus, levels of key oxidized polyunsaturated fatty acids may serve as biomarkers of oxidative stress in HIV patients.

[0155] Biomarkers of inflammation. Proteomic studies showed that the level of C-reactive protein (CRP), an acute phase protein, increased in HIV patients (FIG. 6), consistent with the presence of an inflammatory state in HIV patients. The levels of plasma kallikrein (KLKB1) were reduced in HIV-infected patients (FIG. 3). This reduction might be attributed to its activation and subsequent turnover in plasma. Activation of KLKB1 is consistent with generation of bradykinin and association with pain and inflammation.

[0156] Biomarkers of platelet activation. Proteomic analysis of plasma depleted of the 14 most abundant proteins showed significantly increased levels of platelet factor 4 (PF4), platelet basic protein (PBP), and thrombospondin-1 (TSP-1) in HIV patients with CVE (FIGs. 2A-2C). These three proteins are normally stored in the a-granules of platelets and their increased levels in plasma indicate platelet activation and a-granule release in HIV patients with CVE. Consistent with platelet activation, metabolomic analysis showed increased levels of serotonin in HIV patients (FIG. 4). Since the plasma samples were collected from HIV patients prior to CVE, the elevated levels of serotonin correlate with HIV infection. Serotonin is stored in dense granules of platelets and elevated serotonin levels in plasma are consistent with platelet activation and dense granule release. [0157] Levels of lysoPS. The levels of three lysoPS species were elevated in HIV patients (FIGs. 8A-8C). Increased plasma lysoPS levels are highly unusual as lysoPS is normally surface-bound and localized on activated platelet surfaces or apoptotic neutrophil surfaces. Increased lysoPS in plasma may reflect platelet activation (Frasch et al. Prog Lipid Res. 2012;51 (3):199-207), consistent with elevation of other markers of platelet activation described above. Elevated lysoPS levels in plasma may also correlate with the unusual and persistent accumulation of activated neutrophils in the mucosal lining of the gut in HIV patients. This accumulation is suggestive of a clearance defect of apoptotic neutrophils by macrophages, which use lysoPS on apoptotic neutrophil surfaces as targets for efferocytosis (Frasch et al. infra).

[0158] Changes in levels of coagulation factors. Of all the coagulation factors monitored by proteomic analysis, the levels of factor V were elevated in HIV patients (FIG. 5A). This is consistent with platelet activation and a-granule secretion since factor V is stored in platelet a- granules and released into the circulation together with other a-granule proteins such as VWF, PF4, TSP-1 , and fibrinogen upon platelet activation. The levels of protein C decreased in HIV patients, accompanied with similar decreases in protein C inhibitor in HIV patients (FIGs. 5B, 5C). Parallel decreases in protein C and protein C inhibitor suggest that a small amount of protein C has been activated, and the activated protein C has been inactivated by forming covalent complexes with protein C inhibitor.

[0159] The data suggests that HIV infection is often accompanied by a state of inflammation and oxidative stress, producing a highly prothrombotic state that may predict who will progress to develop cardiovascular events.

[0160] Example 2. This Example describes how the biomarkers associated with CVE identified in Example 1 will be confirmed or how additional biomarkers associated with CVE will be identified.

[0161] Evaluation of a molecular cardiovascular profile in a cohort of HIV-infected patients will be used to confirm biomarkers and/or identify additional biomarkers associated with the occurrence of either myocardial infarction or ischemic stroke. Molecular profiling will include unbiased plasma proteomics after removal of the 14 most abundant plasma proteins (listed above in Example 1), which may confound the molecular profiling studies. Molecular profiling will also include quantitative proteomics of proteins involved in blood coagulation, platelet activation, and endothelial activation. Molecular profiling will also include assessments of redox status through the measurement of reduced and oxidized forms of small molecule thiols in plasma, assessment of protein methionine oxidation, and plasma lipid oxidation. 64 cases and 128 controls will be analyzed at minimum.

[0162] Characteristics of study cohort. Study subjects will be drawn from a large and diverse population of HIV-infected subjects from several clinical treatment centers in the United States with a repository of samples and data from >30,000 HIV-infected patients. This cohort includes both men and women from a broad range of racial and ethnic groups, and individuals who are 18 years of age and older; over 25% of current participants are aged 50 years or older. The majority of the cohort includes male patients who have sex with males, heterosexuals, and injection drug users, with life styles known to be associated with major routes of HIV transmission in the United States. Overall, 19% of the cohort from which participants will be drawn are women and over 50% are minorities. The majority of the cohort (over 85%) have undertaken or are currently undertaking antiretroviral therapy (ART).

[0163] Patient sample testing. Analyses will focus on participants who meet the inclusion and exclusion criteria described below and have stored specimens available for testing. Biomarker levels in cases who have experienced a Ml or stroke will be compared to biomarkers levels from controls matched for time since initiation of antiretroviral therapy (ART) and ART regimen. Each existing specimen in the HIV cohort is linked to de-identified clinical data with an identification (ID) number, without any personal identifiers. No additional specimens or data beyond what is already part of the population data and specimen repository will be collected from participants.

[0164] Data is collected and maintained on 10 unique domains in the population: (1) diagnoses, (2) laboratory data, (3) medication data, (4) demographics, (5) health care utilization, (6) vital status, (7) patient- re ported outcomes (PROs), (8) genotypic resistance, (9) biologic specimens and (10) census block data. Diagnoses include AIDS-defining diagnoses, non-AIDS malignancies, cardiovascular disease, kidney disease, diabetes, dyslipidemia, liver disease, hypertension, mental illness, and substance use. Laboratory Data include plasma HIV-1 RNA levels, CD4 counts, and viral hepatitis, hematologic, and metabolic markers. Medication Data include ART, anti-microbial, anti-hypertensive, diabetes, lipid lowering, psychiatric medications and transfusion. Demographic Data include sex, race/ethnicity, age, and HIV transmission risk factors. Utilization Data include primary care and specialty care visits and hospitalizations. Vital Status Data include cause of death, death date, and information source. Antiretroviral Resistance Data include full viral genotype, phenotype, and tropism assay results. Patient- reported outcomes (PROs) are collected at the time of routine clinic appointments using web- based software. Domains obtained include substance use, tobacco, medication adherence, physical activity and others.

[0165] Cases: The study will include participants who initiate potent ART after enrollment, attain viral suppression, experience a primary Ml or stroke >6 months after ART initiation, and have stored plasma samples available in the 12 months prior to the event. The study will exclude participants who experienced a primary Ml prior to or within 6 months of ART initiation.

[0166] Controls: The study will include participants who initiate potent ART after enrollment, attain viral suppression, and have stored plasma samples available for testing, and who have not experienced a primary Ml or stroke. Two controls will be selected for each case, matched to the case based on time since ART initiation (within 12 months) and on current ART regimen.

[0167] The study will exclude participants with an adjudicated secondary Ml or stroke from both patient groups. Stored plasma specimens from cases and controls meeting the above criteria will be identified. A 400-microliter aliquot of plasma will be shipped from participating sites to the study site on dry ice and stored at -80°C prior to testing.

[0168] Plasma proteomics. Unbiased proteomics of the samples will be performed as described in Example 1 to determine whether certain plasma proteins are over- or under represented in the patients with events. This analysis may also help to identify alterations produced by ART. Briefly, a very small volume of plasma (10 pi) is first depleted of the 14 most abundant proteins (as listed above in Example 1) using a well characterized affinity spin column (for example, Human 14 Multiple Affinity Removal Spin Cartridge from Agilent, Santa Clara, CA) so as to avoid interference of the high abundance proteins with the much more numerous but less abundant remaining proteins. The proteins remaining in the small plasma volume are then reduced, alkylated, and digested with trypsin. The tryptic peptides thus produced are then analyzed by liquid chromatography/tandem MS. Proteins are then identified, for instance by searching the MS/MS spectra against the human protein database (UniProt) using Proteome Discoverer software. Relative protein abundance is determined by either peak area or spectral counting.

[0169] Quantitative plasma proteomics. The proteins to be quantified by MS are listed in Table 4. Included in this list are proteins involved in modulating plasma oxidative stress, acute phase proteins, proteins secreted from activated platelets, proteins known to be involved in platelet adhesion and thrombotic microangiopathies, coagulation and anticoagulation proteins, and serpins, which regulate the activity of the coagulation proteases. The Quantification concatamers strategy (QconCATs) (Simpson and Beynon, Anal Bioanal Chem. 404(4):977-989, 2012) will be used to quantify the concentrations of proteins of interest. Briefly, three isotopically labeled proteins will be expressed in Escherichia coli, which will serve as internal standards for quantification. The three co-expressed internal standards, each representative of a protein expressed at low, medium, and high levels in plasma, would be used at concentrations representative of their physiological concentrations. Three unique peptides from each protein will be expressed. To ensure accurate quantification, these three isotopically labeled proteins will be mixed in proportion to their concentrations in plasma to create an isotopically labeled internal standard (IS) mixture. This IS mixture will be added to plasma prior to depletion of either the 14 highest abundance proteins (Human-14, Agilent, Santa Clara, CA) or the six highest abundance proteins (Human-6, Agilent, Santa Clara, CA), including albumin, IgG, IgA, transferrin, haptoglobin, and a1 -antitrypsin. Flow through fractions will be digested by proteases and analyzed by targeted LC-MS/MS for quantification of protein and oxidant modifications. Three unique peptides from each isotopically labeled protein will be used as internal standards.

[0170] Table 4. List of plasma proteins to be quantified by mass spectrometry

[0171] Plasma thiol/disulfide redox status to evaluate oxidative stress. A highly sensitive, specific, and quantitative assay has been developed by the inventors to measure all of the small molecule thiols present in the blood, in both their reduced and disulfide forms. These small molecule thiols include cysteine, reduced glutathione (GSH), homocysteine, Cys-Gly, yGlu-Cys, N-acetylcysteine (NAC), disulfides, and protein-bound Cys (Fu et al. Blood. 2015; 126: 1044; Cate et al. Blood. 2014; 124:2662; Fu et al., Scientific Reports, 9(1): 115, 2019). In vitro addition of the oxidants to plasma diminishes the free thiol forms of the small molecule thiols, increases their disulfide forms, and increases the concentration of protein-bound Cys in a concentration- dependent manner. Plasma from several disorders characterized by oxidative stress, including sickle cell disease, sepsis, and thrombotic thrombocytopenic purpura (Fu et al. infra ; Cate et al. infra) have also been analyzed; the level of protein-bound Cys correlates very well with disease severity, reflecting a state of oxidative stress. Examination of this parameter in HIV patients indicates a high level of oxidative stress associated with the infection and no apparent change in this parameter was observed after ART. Briefly, free thiols in plasma will be blocked by N- ethylmaleimide (NEM), which will also stop further disulfide exchange. NEM-blocked thiols and small-molecule disulfides and isotopically-labeled internal standards will be extracted by methanol and analyzed by LC-MS/MS with multiple reactive monitoring (LC-MS/MS-MRM). To determine total Cys including protein-bound Cys, a parallel aliquot of plasma will be evaluated by first reducing all disulfide-bound Cys with dithiothreitol (DTT) and then blocking the thiols with NEM before methanol extraction.

[0172] Plasma metabolomics. Plasma will be analyzed as described in Example 1 for small metabolites, including lipids, lyso-lipids, oxylipins, oxidized lipids, and metabolites derived from the amino acids tryptophan and arginine.

[0173] Quality control (QC) sample, internal standards, extraction of metabolites. Pooled plasma samples from controls, HIV patients with or without CVE will be used as quality control (QC), metabolite validation, and identification of new metabolites. A mixture of isotopically labeled standards will be added before extraction. Metabolites in plasma (100 pl_) will be extracted with 80% methanol (Fu et al. Transfusion. 2016;56(10):2560-2570, supra). Extractions will be analyzed by either targeted metabolomics or untargeted metabolomics (Fu et al. Transfusion. 2016;56(10):2560-2570, supra ; Zimring et al. Transfusion. 2016;56(8): 1974-1983; de Wolski et al. Haematologica. 2016;101(5):578-586).

[0174] Targeted metabolomics analysis. Extracted metabolites will be analyzed by liquid chromatography (LC)-tandem mass spectrometry (MS/MS) with multiple reaction monitoring (MRM) using a AB Sciex 6500 QTRAP mass spectrometer coupled with a Waters Acquity I- class UPLC system or a system with comparable capability. To cover all metabolites of interest, LC-MS conditions will be optimized, such as use of appropriate LC columns and MS positive/negative ion mode, MRM transitions and collision energy (CE) based on the characteristics of the metabolites to be analyzed. MRM data will be acquired using Analyst 1.6 and peak area of the metabolites will be integrated using MultiQuant 2.1 software and resulting data will be further analyzed with MetaboAnalyst (see below metabolomics data analysis).

[0175] Targeted metabolomic approaches have been developed to quantify over 100 metabolites involved in pathways related to oxidative stress, amino acids and their metabolites, carboxylic acids, fatty acids, oxylipins, lipids and microbiome-derived metabolites including trimethylamine N-oxide (TMAO) and indoxyl sulfate (Zhang and Davies, Genome Med. 2016;8(1):46). The study will focus on biomarkers for lipid oxidation and degradation and biomarkers of endothelial activation and VWF dysregulation. The latter biomarkers will be measured as described in Example 1.

[0176] Biomarkers for lipid oxidation and degradation. Lipid oxidation and degradation products (bioactive lipids) have been implicated in many biological processes. Polyunsaturated fatty acids are very sensitive to oxidation by either enzymatic or peroxidation pathway. For example, arachidonic acid (FA 20:4) can be oxidized enzymatically by 5-, 12-, or 15- lipoxygenases (LOX) to 5-, 12-, 15- hydroxyeicosatetraenoic acids (HETEs), whereas lipid peroxidation is non-specific and can produce 8-, 9-, 11-HETEs. A quantitative targeted metabolomics assay to quantify fatty acids, oxylipins (oxidized fatty acids) and lyso- phospholipids (product of phosphides by enzymatic action of phospholipids) has recently been developed (Fu et al. Transfusion. 2016;56(10):2560-2570, supra ; Fu et al. Transfusion. 2017;57(S3), supra). This assay will cover all common polyunsaturated fatty acids and their potential oxidation products, and lysophosphatidylcholines (LysoPCs), lysophosphatidylserines (LysoPSs), lysophosphatidylethanolamines(LysoPEs), lysophosphatidylinositols (LysoPI), and lyso platelet activating factor (lysoPAF).

[0177] Statistical analysis. For targeted proteomic analysis, the levels of potential biomarkers will be analyzed as continuous variables, maximizing the power to detect differences. Sample size calculations will conservatively be based on the power to detect a difference of ½ a standard deviation for each biomarker. With a = 0.05, power = 90%, and 2 controls per case, 64 cases are needed to detect a difference of ½ a standard deviation for each biomarker, assuming that cases and controls are independent. Therefore, 64 cases with HIV-related Ml and 128 matched controls, and 42 cases of HIV-related stroke and 83 matched controls, will be included in this study.

[0178] Analysis Plans. The biomarker levels will be logio-transformed to approximate normality as needed. Characteristics between cases and controls will be compared using the Mann- Whitney U test for continuous variables, and Fisher’s exact tests will be used for categorical variables. Conditional logistic regression accounting for each risk set (defined as a case and its 2 controls) will be used to analyze the risk of Ml or stroke associated with biomarkers. Potential confounders include sex, age, race/ethnicity, body mass index, smoking, alcohol and recreational drug use, diabetes, hyperlipidemia, hypertension, CRP, CD4 count, and plasma viral load. For biomarkers associated with Ml or stroke, a receiver operating characteristic (ROC) curve (i.e. , one for each significant predictor) will be created and optimal cut-points for the prediction of Ml will be identified, calculating the sensitivity, specificity, and positive and neg ative predictive values for each biomarker above or below its optimal cut-point. Logistic regression analysis will be used to determine the effects of sex, age, comorbid medical conditions (e.g., diabetes), and other predictors on the performance of each test (i.e., area under the ROC curve), by the methods of Coughlin et al. (J Clin Epidemiol. 1992;45(1):1-7). The relative sensitivity, or true positive fraction (rTPF = TPFA/TPFB), and false positive fraction (rFPF = FPFA/FPFB) will be assessed as described by Pepe (Pepe MS. The statistical evaluation of medical tests for classification and prediction. New York, NY: Oxford University Press. 2003).

[0179] Computational analysis of unbiased proteomic and metabolomic data.

[0180] Differential protein expression by MS. To assess differences in relative protein abundance between subject populations, individual protein spectral counts are normalized using the spectral index (SI) metric (Fu et al. J Proteome Res. 2008;7(3):845-854). SI compares relative protein abundance between groups of samples by normalizing their values to a range of [-1 , +1]. For a given protein, an SI close to +1 implies abundance in one group whereas a value close to -1 signifies abundance in the other group. A value close to 0 indicates that a protein is about equally abundant in both groups. Statistical significance is determined through random permutation analysis (n = 10,000 permutations), with a 95% confidence threshold for significant differential expression. The nonparametric approach adjusts for multiple hypothesis testing. This statistical approach has been used and validated in multiple proteomic studies (Gharib et al. J Proteome Res. 2009;8(6):3020-3028; Nguyen et al. PLoS One. 2013;8(3):e58782; Becker et al. Cell Metab. 2010; 11 (2): 125-135; Chang et al. Am J Respir Crit Care Med. 2008; 178(7):701-709; Vaisar et al. J Clin Invest. 2007; 1 17(3) :746-756).

[0181] The study will confirm the biomarkers disclosed herein and/or identify additional biomarkers that correlate with risk of cardiovascular disease in patients infected with HIV. These biomarkers will not only serve to identify those at risk but also point to physiologic and metabolic pathways involved.

[0182] As will be understood by one of ordinary skill in the art, each embodiment disclosed herein can comprise, consist essentially of or consist of its particular stated element, step, ingredient or component. Thus, the terms“include” or“including” should be interpreted to recite: “comprise, consist of, or consist essentially of.” The transition term“comprise” or“comprises” means includes, but is not limited to, and allows for the inclusion of unspecified elements, steps, ingredients, or components, even in major amounts. The transitional phrase “consisting of’ excludes any element, step, ingredient or component not specified. The transition phrase “consisting essentially of” limits the scope of the embodiment to the specified elements, steps, ingredients or components and to those that do not materially affect the embodiment. A material effect would cause a significant decrease in the ability to use one or more of glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); plasma kallikrein (KLKB1); serotonin; Factor V; Protein C; Protein C inhibitor; C- Reactive Protein (CRP); linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine (lysoPS) 18:0; lysoPS 18:1 ; lysoPS 20:4; Cys; and/or protein bound Cys (P-ss-Cys) to predict the occurrence of adverse CVE in patients infected with human immunodeficiency virus (HIV).

[0183] Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as molecular weight, reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term“about.” Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by the present invention. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. When further clarity is required, the term“about” has the meaning reasonably ascribed to it by a person skilled in the art when used in conjunction with a stated numerical value or range, i.e. denoting somewhat more or somewhat less than the stated value or range, to within a range of ±20% of the stated value; ±19% of the stated value; ±18% of the stated value; ±17% of the stated value; ±16% of the stated value; ±15% of the stated value; ±14% of the stated value; ±13% of the stated value; ±12% of the stated value; ±11% of the stated value; ±10% of the stated value; ±9% of the stated value; ±8% of the stated value; ±7% of the stated value; ±6% of the stated value; ±5% of the stated value; ±4% of the stated value; ±3% of the stated value; ±2% of the stated value; or ±1% of the stated value.

[0184] Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements.

[0185] The terms“a,”“an,”“the” and similar referents used in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. Recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g.,“such as”) provided herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.

[0186] Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member may be referred to and claimed individually or in any combination with other members of the group or other elements found herein. It is anticipated that one or more members of a group may be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.

[0187] Certain embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Of course, variations on these described embodiments will become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventor expects skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.

[0188] Furthermore, numerous references have been made to patents, printed publications, journal articles and other written text throughout this specification (referenced materials herein). Each of the referenced materials are individually incorporated herein by reference in their entirety for their referenced teaching.

[0189] In closing, it is to be understood that the embodiments of the invention disclosed herein are illustrative of the principles of the present invention. Other modifications that may be employed are within the scope of the invention. Thus, by way of example, but not of limitation, alternative configurations of the present invention may be utilized in accordance with the teachings herein. Accordingly, the present invention is not limited to that precisely as shown and described.

[0190] The particulars shown herein are by way of example and for purposes of illustrative discussion of the preferred embodiments of the present invention only and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of various embodiments of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the invention, the description taken with the drawings and/or examples making apparent to those skilled in the art how the several forms of the invention may be embodied in practice.

[0191] Definitions and explanations used in the present disclosure are meant and intended to be controlling in any future construction unless clearly and unambiguously modified in the preceding examples or when application of the meaning renders any construction meaningless or essentially meaningless. In cases where the construction of the term would render it meaningless or essentially meaningless, the definition should be taken from Webster's Dictionary, 3rd Edition or a dictionary known to those of ordinary skill in the art, such as the Oxford Dictionary of Biochemistry and Molecular Biology (Eds. Attwood T et al., Oxford University Press, Oxford, 2006).

Claims

1. A method of identifying a subject infected with human immunodeficiency virus (HIV) as having an increased risk of an adverse cardiovascular event (CVE) or not having an increased risk of an adverse CVE, comprising:

obtaining a biological sample derived from the subject;

identifying the subject as having an increased risk of an adverse CVE if:

and

or

identifying the subject as not having an increased risk of an adverse CVE if: the level of each of one or more of GPX-3 and KLKB1 is increased or unchanged as compared to the corresponding first reference level; and/or

and

2. The method of claim 1 , wherein the first reference level is derived from a control sample comprised of one or more individuals who have HIV and who have had or who have an adverse CVE.

3. The method of claim 1 , wherein the second reference level is derived from a control sample comprised of one or more individuals who are not infected with HIV.

4. The method of claim 2 or 3, wherein the control sample comprises two or more individuals and the first or second reference level is an average of levels of biomarkers measured in the individuals.

5. The method of claim 1 , wherein the biological sample is plasma.

6. The method of claim 5, wherein the plasma is depleted of one or more of albumin, IgG, a1- antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein A1 , apolipoprotein All, complement C3, and transthyretin before the measuring.

7. The method of claim 1 , wherein the measuring comprises measuring the levels of PF4, PBP, TSP-1 , and KLKB1.

8. The method of claim 1 , wherein the measuring comprises measuring the levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys.

9. The method of claim 1 , wherein the measuring comprises using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

10. A kit for diagnosing an HIV-infected subject with an increased risk of an adverse cardiovascular event (CVE) comprising one or more binding agents, each binding agent able to bind a biomarker selected from glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); plasma kallikrein (KLKB1); serotonin; factor V; protein C; protein C inhibitor; C-reactive protein (CRP); Cysteine (Cys); and protein bound Cysteine (P-ss-Cys).

11. The kit of claim 10, wherein the binding agents are proteins, antibodies, aptamers, mimotopes, or oligonucleotides.

12. The kit of claim 10, further comprising a detectable label.

13. The kit of claim 12, wherein the detectable label is a radioactive isotope, enzyme reporter, colorimetric label, fluorescent label, chemiluminescent label, colored particles, gold nanoparticles, colloids, magnetic bead, or biotin.

14. The kit of claim 10, wherein the kit comprises reagents to perform amplification of nucleic acids, an immunoassay, an immunohistochemical staining, flow cytometry, an enzyme-based colorimetric assay, and/or a protein activity assay.

15. The kit of claim 14, wherein the protein activity assay comprises an assay selected from an oxidation/reduction assay, a platelet aggregation assay, a platelet activation assay, an endothelial cell activation assay, and/or a cell-matrix interaction assay.

16. The kit of claim 10, further comprising reagents to detect a biomarker selected from linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysophosphatidylserine 18:1 (lysoPS 18:1); lysophosphatidylserine 20:4 (lysoPS 20:4); Cys; and P-ss-Cys.

17. The kit of claim 16, wherein the reagents are used in liquid chromatography, gas chromatography, thin layer chromatography, UV spectroscopy, capillary electrophoresis, and/or mass spectrometry.

18. A method of treating or not treating an HIV-infected subject for an adverse cardiovascular event (CVE) comprising:

obtaining a biological sample derived from the subject;

identifying the subject as having an increased risk of an adverse CVE if:

and

or

identifying the subject as not having an increased risk of an adverse CVE if:

and

or

19. The method of claim 18, wherein the treating comprises administering drugs selected from aspirin, anti-hypertensive drugs, angiotensin converting enzyme inhibitors (ACEI), angiotensin receptor blockers, calcium-channel blockers, thiazide-like diuretics, alpha-blockers, central alpha-agonists, peripheral alpha-agonists, and lipid lowering drugs.

20. The method of claim 18, wherein the treating comprises ceasing smoking, reducing alcohol consumption, reducing weight, improving diet, and/or increasing physical activity.

21. The method of claim 18, wherein the first reference level is derived from a control sample comprised of one or more individuals who have HIV and who have had or who have an adverse CVE.

22. The method of claim 21 , wherein the second reference level is derived from a control sample comprised of one or more individuals who are not infected with HIV.

23. The method of claim 21 , wherein the control sample comprises two or more individuals and the first or second reference level is an average of levels of biomarkers measured in the individuals.

24. The method of claim 18, wherein the biological sample is plasma.

25. The method of claim 18, wherein the measuring comprises using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

26. A method of monitoring an HIV-infected subject for risk of an adverse cardiovascular event (CVE) comprising:

obtaining a biological sample derived from the subject;

identifying the subject as having an increased risk of an adverse CVE if:

the level of each of one or more of GPX-3 and KLKB1 is decreased compared to the corresponding first reference level; and/or the level of each of one or more of PF4, PBP, and TSP-1 is increased compared to the corresponding first reference level;

and

or

identifying the subject as not having an increased risk of an adverse CVE if:

and

27. A method, comprising:

obtaining a biological sample derived from an HIV-infected subject;

28. The method of claim 27, wherein the testing comprises measuring the level of the one or more primary biomarkers and measuring the levels of the nine or more secondary biomarkers.

29. The method of claim 28, wherein the measuring comprises measuring the levels of PF4, PPBP, TSP-1 , and KLKB1.

30. The method of claim 28, wherein the measuring comprises measuring the levels of serotonin, PROC, PCI, CRP, LA, 12-HETE, lysoPS 18:0, lysoPS 18:1 , lysoPS 20:4, and Cys.

31. The method of claim 28, wherein the measuring comprises using one or more of mass spectrometry, immunoassay, chromatography, spectroscopy, electrophoresis, or a combination thereof.

32. The method of claim 27, wherein the biological sample is plasma.

33. The method of claim 32, wherein the plasma is depleted of one or more of albumin, IgG, a1-antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, a2-macroglobulin, a1-acid glycoprotein, IgM, apolipoprotein A1 , apolipoprotein All, complement C3, and transthyretin.

34. An array comprising a biomarker selected from glutathione peroxidase-3 (GPX-3); platelet factor 4 (PF4); platelet basic protein (PBP); thrombospondin-1 (TSP-1); plasma kallikrein (KLKB1); serotonin; factor V; protein C; protein C inhibitor; C-reactive protein (CRP); and/or protein bound Cys.

35. The array of claim 34, wherein the array is a protein array.

36. The array of claim 34, wherein the array is a nucleic acid array.

37. The array of claim 34, wherein the array is a microarray.

38. An array comprising a biomarker selected from serotonin; linoleic acid (LA); arachidonic acid (AA); 12-hydroxyeicosatetraenoic acid (12-HETE); lysophosphatidylserine 18:0 (lysoPS 18:0); lysophosphatidylserine 18:1 (lysoPS 18:1); lysophosphatidylserine 20:4 (lysoPS 20:4); and/or Cys.