Non-HLA Markers of Transplant Rejection

Abstract

The present invention relates generally to transplant rejection. In particular, the present invention provides compositions, kits, assays, and methods for determining whether a subject has allograft rejection or is at high risk for developing rejection after transplantation, as well as methods for treating the same.

Description

[Technical field]

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 844,027, filed May 6, 2019, the entire contents of which are incorporated herein by reference. Acknowledgements for Government Support

[0002] This invention was made with Government support under Grant Nos. AI042819, AI135201, and DK104687 awarded by the National Institutes of Health. The Government has certain rights in this invention. Technical Field

[0003] The present invention generally relates to organ transplant rejection.In particular, the present invention provides compositions, kits, assays and methods for determining whether a subject has allograft rejection or is at high risk of developing rejection after transplantation, as well as treatment methods.In addition, the present invention provides biomarkers such as non-HLA antibodies associated with transplant rejection. [Background technology]

[0004] Organ transplantation from a donor to a host recipient is the hallmark of certain medical procedures and treatment regimens. After transplantation, immunosuppressive therapy is typically provided to the organ recipient to maintain the viability of the donor organ and avoid graft rejection. When organ transplant rejection occurs, the reaction is typically classified as hyperacute rejection, acute rejection, or chronic rejection. Hyperacute rejection occurs within minutes to hours after organ transplantation. This is typically due to antibodies in the recipient's bloodstream reacting with the new organ and is usually characterized by extensive glomerular capillary thrombosis and necrosis. Acute rejection (AR) typically occurs in the first 6-12 months after organ transplantation and is a complex immune response involving T cell recognition of alloantigens within the graft and an inflammatory response within the graft itself. Chronic rejection is not as clearly defined as either hyperacute or acute rejection and may be due to both antibodies and lymphocytes.

[0005] Despite advances in immunosuppressive therapy and transplant procedures, graft rejection remains a common risk for organ transplant recipients. For example, despite improvements in immunosuppressive therapy over the years, approximately 30-40% of heart transplant recipients require treatment for AR in the first year after transplant (see Taylor et al., J Heart Transplant., 2009, 28(10):1007-22). Furthermore, AR remains a risk factor for the development of cardiac allograft vasculopathy (CAV), the leading cause of graft dysfunction, mortality, and late graft failure (see Raichlin et al., J Heart Lung Transplant, 2009, 28(4):320-7).

[0006] Short-term allograft survival has increased over the past decade due to advances in human leukocyte antigen (HLA) antibody detection and improved immunosuppression, but long-term outcomes remain largely unchanged, and graft loss due to chronic rejection remains a significant problem.

[0007] HLA antibodies, especially donor-specific antibodies (DSA), contribute to antibody-mediated rejection (AMR) and acute cellular rejection (ACR) after transplantation. However, a significant proportion of heart transplant patients have been found to have AMR in the absence of HLA or DSA, suggesting that antibodies directed against non-HLA antigens are associated with an increased risk of AMR. Antibodies against non-HLA antigens, such as vimentin, MHC class I polypeptide-related sequence A (MICA), angiotensin II receptor type 1 (AT1R), and antibodies targeting endothelial cells, are associated with AMR and chronic allograft vasculopathy after heart transplantation. Furthermore, antibodies against non-HLA antigens have been identified and are associated with poor outcomes after transplantation of other organs.

[0008] Endothelial cells (ECs) are the first point of contact between the allograft and the transplant recipient's immune system and are therefore a potential source of non-HLA antigens that can stimulate humoral immune responses. Both the endothelial cell crossmatch (ECXM) using primary human aortic ECs (HAECs) and the XM-ONE® assay (Olerup SSP AB, Stockholm, Sweden) using EC precursors have proven clinically relevant to identify patient sera containing antibodies against ECs. However, cell-based assays are of limited utility because they do not identify antigens that bind to non-HLA antibodies present in the patient's serum. As a result, understanding the breadth of non-HLA antigens that induce humoral responses that result in poor allograft outcomes is limited by the inability to detect and characterize non-HLA antibodies.

[0009] Early detection of AR is one of the major clinical concerns in healing of transplant recipients, such as recipients of solid organs such as the heart, liver, lung, kidney, and intestine. Detecting AR before the onset of organ dysfunction allows for successful treatment of AR with aggressive immunosuppression. It is equally important to reduce immunosuppression in patients without AR to minimize drug toxicity. However, in most organs, rejection can only be clearly established by performing a biopsy of the organ.

[0010] For example, current definitive diagnosis of cardiac allograft rejection relies on endomyocardial biopsy (EMB), an invasive, inconvenient, and expensive procedure. Most heart transplant recipients undergo regular EMB procedures up to 15 times during the first year, and more frequently if rejection is detected. However, this procedure is limited by sampling error and interobserver variability (see Den et al., A. Transplant. 2006.6(1):150-60; Won et al., Cardiovas. Pathol. 2005.14(4):176-80). Potential complications include arterial puncture, vasovagal reactions and prolonged bleeding during catheter insertion, arrhythmias and conduction abnormalities, pneumothorax, tricuspid regurgitation on biopsy, and even cardiac perforation (see Baraldi-Junkin et al., Hear Lun Transplant 1993.12(1 Pt 1):63-7; Decker et al., A. Col. Cardiol. 1992.19(1):43-7; Navi et al., Hear Valv. Dis. 2005.14(2):264-7).

[0011] Although the diagnosis of acute rejection can be difficult, timely detection of immune-related damage is important to ensure graft health and long-term survival. A non-invasive biomarker panel for acute rejection that would allow frequent immunological monitoring of the graft would be of considerable value (see Evan et al., A. Transplant. 2005.5(6):1553-8; Mehr et al., Na. Cli. Prac. Cardiovas. Med. 2006.3(3):136-43). Recently, sensitive and specific gene-based biomarker panels have been developed for the diagnosis and prediction of biopsy confirming acute kidney transplant rejection (see L. et al., A. Transplant. 2012.12(10):2710-8; Bromber et al., A. Transplant. 2012.12(10):2573-4). This has been independently validated in randomized multicenter trials (see Chaudhur et al., Pediatri. Transplantation. 2012.16(5):E183-7; Naesen et al., A. Transplant. 2012.12(10):2730-43). Diagnosing acute rejection before the development of histopathological changes may allow optimization of immunosuppressive therapy to prevent progression to chronic allograft dysfunction (see Kienz et al., Transplantation. 2009.88(4):553-60).

[0012] A non-invasive assay that allows for the detection of acute graft rejection in different organs with high specificity (to reduce invasive protocol biopsies in patients at low risk for AR) and high sensitivity (to increase clinical surveillance in patients at high risk for AR) would lead to timely clinical intervention to mitigate AR and reduce immunosuppression protocols in quiescent and stable patients earlier than currently possible. Many assays may depend on the recipient's age, comorbidities, use of immunosuppression, and / or cause of end-stage renal disease. Thus, there remains a need for systems and methods for predicting, diagnosing, and monitoring AR responses in subjects who have received organ transplants.

[0013] Moreover, the rejection phenomenon is not limited to cardiac allografts. All organ transplants, such as kidney transplants, are subject to rejection (e.g., graft-versus-host disease). Furthermore, rejection-like events accompany graft-versus-host disease (e.g., transplanted leukocytes and lymphocytes attack host tissues) and autoimmune diseases (e.g., rheumatic fever, in which the heart is the target of autoantibodies and autoreactive lymphocytes). In all cases, aggressive immunosuppression has been shown to reverse or modify the immune response, but the associated risk of promoting opportunistic infections limits its use.

[0014] Thus, there is a need in the art for highly accurate prognostic indicators of the likelihood of developing allograft rejection, and non-invasive assays thereof. There is a further need in the art to identify markers that contribute to pathology or that are exclusively prognostic indicators of rejection.

[0015] The present invention is the first to develop and validate a large-scale, high-throughput, multiplexed bead array to test for the presence of novel and known non-HLA antibodies associated with rejection.

[0016] All patents, patent applications, publications, documents, and articles cited herein are incorporated by reference in their entirety unless otherwise noted. Summary of the Invention [Problem to be solved by the invention]

[0017] The present invention provides compositions, assays, kits, or methods for determining whether a subject has allograft rejection or asymptomatic allograft rejection, or an increased risk for post-transplant rejection.

[0018] In some embodiments, the invention provides a composition comprising a collection of solid substrates coated with one or more homogenous populations of binding agents, wherein each homogenous population of binding agents is selected from the group consisting of dexamethasone-induced transcript (DEXI), C-X-C motif chemokine ligand 11 (CXCL11), cytokeratin 18 (KRT18), cytokeratin 8 (KRT8), tubulin, e.g., tubulin alpha 1b (also called TUBα1b or TUBA1B), latrophilin 1 (LPHN1), colony-stimulating factor 2 (CSF2), signal transducer and activator of transcription 6 (STAT6), lectin galactoside-binding soluble 3 (LGALS3), SHC adaptor protein 3 (SHC3), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glutathione S-transferase (STT), and / or phospholipase A (GPA). and specific binding to an antibody directed against a single antigen selected from the group consisting of phospholipase theta-1 (GSTT1), phospholipase A2 receptor 1 (PLA2R1), interleukin 8 (IL-8), lectin galactoside-binding soluble 8 (LGALS8), small nuclear ribonucleoprotein polypeptide N (SNPRN), myosin, peroxisomal trans-2-enoyl-CoA reductase (PECR), vimentin (VIM), ATP synthase H+ transporting mitochondrial F1 complex beta polypeptide (ATP5B), collagen II, prelamin-A / C (LMNA), small nuclear ribonucleoprotein polypeptide B (SNRPB2), fibronectin 1 (FN1), vinculin (VCL), thioglobulin (TG), and nephrosis 1 (NPHS1). In some embodiments, the collection of solid phase substrates further comprises one or more additional homogenous populations of binding agents, each additional homogenous population of binding agents specifically binding to an antibody directed against a single additional antigen selected from the group consisting of alpha enolase (ENO1), agrin (AGRN), endomucin (EMCN), Sjogren's syndrome antigen B (SSB), actin, fms-related tyrosine kinase 3 ligand (FLT3LG), protein kinase C eta (PRKCH), and interleukin 21 (IL-21).

[0019] In another embodiment, a composition of the invention comprises a collection of one or more distinct homogenous populations of binding agents, each distinct homogenous population of binding agents being capable of specifically binding only to antibodies directed against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, GAPDH, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, TG, IL-8, and SHC3.

[0020] In another embodiment, a composition of the invention comprises a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents capable of specifically binding only to antibodies directed against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, and STAT6.

[0021] In another embodiment, a composition of the invention comprises a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents being capable of specifically binding only to antibodies directed against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, IL-8, and SHC3.

[0022] In another embodiment, a composition of the invention comprises a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents being capable of specifically binding only to antibodies directed against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1 and GSTT1.

[0023] In another embodiment, the composition of the invention comprises a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents being capable of specifically binding only to antibodies directed against tubulin, LPHN1, TG, GAPDH, FN1, NPHS1, VIM, myosin, VCL and PECR.

[0024] In some embodiments, the compositions of the invention comprise a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents capable of specifically binding only to antibodies directed against DEXI, LGALS3, SNPRN, CSF2, IL-8, STAT6, LGALS8, KRT18, KRT8, GSTT1, LMNA, collagen II, ATP5B, SNRPB2, and PLA2R1.

[0025] In some embodiments, the compositions of the invention comprise a collection of distinct homogenous populations of binding agents, each distinct homogenous population of binding agents being capable of specifically binding only to antibodies directed against tubulin, SHC3 and CXCL11.

[0026] In some embodiments, the solid substrate is porous or non-porous. In some embodiments, the solid substrate comprises particles, nanoparticles, beads, nanobeads, or microspheres. In some embodiments, the beads are polystyrene beads. In some embodiments, the collection of solid substrates comprises plate or membrane bound, or microarray. In some embodiments, the solid substrate is fluorescently, magnetically, chemiluminescently, or radioactively labeled. In some embodiments, the solid substrate is labeled with a small molecule. In some embodiments, one or more homogenous populations of binding agents are conjugated to the surface of the solid substrate. In some embodiments, the conjugation is covalent. In some embodiments, the homogenous populations of binding agents are attached to the surface of the solid substrate by affinity. In some embodiments, the binding agents are proteins, peptides, or polypeptides. In some embodiments, the solid substrate is coated with one or more different homogenous populations of binding agents that bind to one or more different antigens, each of the solid substrates being detectably distinguishable from the other solid substrates.

[0027] In some embodiments, the present invention provides a method for determining the presence of one or more antibodies in a biological sample obtained from a subject. In some embodiments, the method includes contacting the biological sample with a composition disclosed herein and detecting binding of one or more homogenous populations of binding agents to one or more antibodies. In some embodiments, the subject is a mammal. In some embodiments, the subject is a human. In some embodiments, the subject has received or will receive an organ transplant, such as a heart transplant or a kidney transplant. In some embodiments, the heart transplant or the kidney transplant is an allogeneic heart transplant or an allogeneic kidney transplant, respectively. In some embodiments, the biological sample is blood, plasma, serum, urine, spinal fluid, lymphatic fluid, synovial fluid, cerebrospinal fluid, tears, saliva, milk, mucosal secretions, exudates, sweat, biopsy aspirate, peritoneal fluid, or a body fluid extract. In some embodiments, the detecting is by measuring fluorescence intensity or by immunological analysis.

[0028] In some embodiments, the present invention provides a method for diagnosing transplant rejection in a subject who has received a heart or kidney transplant.In some embodiments, the method includes contacting a biological sample obtained from the subject with the composition disclosed herein and measuring the level of one or more antibodies in the sample.In some embodiments, an increase in the level of one or more antibodies compared to the reference level indicates that the subject has developed transplant rejection in response to the heart or kidney transplant.

[0029] In some embodiments, the present invention provides a method for predicting the likelihood of transplant rejection in a subject who needs a heart or kidney transplant.In some embodiments, the method comprises contacting a biological sample from a subject with the composition disclosed herein and measuring the level of one or more antibodies in the sample.In some embodiments, an increase in the level of one or more antibodies compared to the reference level indicates that the subject is more likely to develop transplant rejection after heart or kidney transplantation.

[0030] In some embodiments, the present invention provides a method of treating a subject in need of treatment for transplant rejection after receiving a heart or kidney transplant. In some embodiments, the method includes contacting a biological sample obtained from the subject with a composition disclosed herein, measuring the level of one or more antibodies in the sample, and administering a treatment for transplant rejection to the subject if the level of the one or more antibodies is increased compared to a reference level of the one or more antibodies.

[0031] In some embodiments, the present invention provides a kit.In some embodiments, the kit comprises the composition disclosed herein and a reagent for detecting the binding of one or more homogenous populations of binding agents to antibody.In other embodiments, the kit further comprises one or more reference samples. [Brief description of the drawings]

[0032] [Figure 1]Figure 1. Non-HLA antibodies significantly associated with (A) pediatric and (B) adult renal allograft rejection. A. High-throughput multiplex bead analysis was used to identify non-HLA antibodies in the sera of pediatric kidney transplant recipients (n=34 rejecting sera, n=95 non-rejecting sera). Antibodies to 15 non-HLA antigens (y-axis) were identified to be significantly associated with time to first rejection with odds ratios >1 (x-axis). Seven of these, DEXI, CSF2, IL-8, LGALS3, SNPRN, STAT6, and LGALS8, have been newly described in relation to kidney transplant rejection. Bars represent 95% confidence intervals (CI). (B) Antibodies to three non-HLA antigens (tubulin, CXCL11, SHC3) were significantly associated with renal allograft rejection in adult kidney transplant recipients (n=70 rejecting sera, n=90 non-rejecting sera). Risk ratios for antibodies binding to the remaining non-HLA antigens on the multiplex panel, which were not significantly different, are not shown. * indicates p<0.05, all other non-HLAAbs shown are p<0.1. [Diagram 2]Figure 1 shows the results of correlation matrix analysis showing hierarchical clustering of non-HLA antibodies in independent studies of (A) adult heart, (B) pediatric kidney, and (C) adult kidney allograft rejection sera. (A) Non-HLA antibodies associated with cardiac allograft rejection selectively cluster into four groups. This study newly identifies two non-HLA antibodies (TG and LPHN1) associated with cardiac allograft rejection. (B) The matrix shows the correlation of non-HLA antibodies found in pediatric kidney transplant patients with rejection. Non-HLA antibodies associated with renal allograft rejection selectively cluster into six groups. This study newly identifies seven non-HLA antibodies (DEXI, CSF2, IL-8, LGALS3, SNPRN, STAT6, and LGALS8) associated with renal allograft rejection. Four non-HLA antibodies (PLA2R1, CSF2, GSTT1, and LGALS8) independently cluster. (C) Targets found to be significant in the pediatric kidney cohort were used to generate a correlation matrix within the adult kidney cohort. Antigens independently correlated with rejection are similar in pediatric and adult kidney transplant recipients with rejection. [Diagram 3] Figure 1 shows the results of a correlation matrix analysis showing hierarchical clustering of non-HLA antibodies in a combined analysis of pediatric and adult renal allograft rejection sera. The matrix shows the correlation of non-HLA antibodies found in sera of rejection patients in a combined analysis of pediatric and adult renal sera. Non-HLA antibodies associated with renal allograft rejection selectively cluster into nine groups. Antibodies against eight non-HLA antigens (LGALS8, SHC3, STAT6, DEXI, IL-8, LGALS3, SNPRN, and CSF2) were newly identified to be associated with renal allograft rejection, and four non-HLA antigens (PLA2R1, STAT6, GSTT1, and CSF2) cluster independently. [Figure 4]Classification algorithm to identify non-HLA antibodies predictive of renal allograft rejection. Classification and Regression Tree (CART) analysis, showing a binary decision tree assessing rejection classification based on non-HLA antibody intensity (MFI). A. CART analysis of sera isolated from adult cardiac allograft recipients (n=67 sera). The analysis used a cut point of 1,000 MFI. The root node LPHN1, which contains all 67 sera, of which 49% are rejection samples, is split into child nodes with MFI<1000. As the algorithm progresses to the terminal nodes, 65% of the rejection samples are correctly identified (far right, darker boxes). The scale bar indicates the association with rejection, with lighter boxes in the terminal nodes correlating with non-rejection. B. CART analysis of sera isolated from pediatric renal allograft recipients (n=129 sera). The analysis used a cut point of 1,000 MFI. The root node SNPRN, which contains all 129 sera, of which 26% are rejection samples, is split into child nodes with MFI<1000. As the algorithm progresses to the terminal nodes, 56% of non-rejection samples are correctly identified (far left, lighter boxes). The scale bar indicates association with rejection, with lighter boxes in the terminal nodes correlating with non-rejection. [Diagram 5] Non-HLA antibodies classified into four groups. Group 1 are non-HLA antibodies found in multiple transplant cohorts (core:tubulin), all of which are predictive of rejection in the CART analysis (Figure 4). Group 2 are all newly identified non-HLA antibodies that were sorted independently in the correlation matrix (highlighted with shading and includes all such targets in all groups). Two non-HLA antibodies, PLA2R and GSTT1, are found in groups 1 and 2. Group 3 includes non-HLA antibodies that were found together in the correlation matrix analysis and are independent from groups 1 and 2. Group 4 includes all non-HLA antibodies found to be associated with rejection (Table 4). [Figure 6]Non-HLA antibodies sorted into four groups after extended analysis with cardiac allografts. Group 1 are non-HLA antibodies found in multiple transplant cohorts (core:tubulin), all of which are predictive of rejection in the CART analysis (Figure 4). Group 2 are all newly identified non-HLA antibodies that were sorted independently in the correlation matrix (highlighted with shading and includes all such targets in all groups). Group 3 includes non-HLA antibodies that were found together in the correlation matrix analysis and are independent from groups 1 and 2. Group 4 includes all non-HLA antibodies found to be associated with rejection (Table 4). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0033] The present invention relates to the diagnosis, prognosis, and / or treatment of acute, chronic, or delayed rejection of heart or kidney transplants.In some embodiments, the present invention relates to a method for determining whether a subject has a high risk of developing rejection after transplantation.In some embodiments, the rejection is acute rejection.

[0034] Additionally, the present invention provides transplant-related biomarkers, such as protein markers. The biomarkers, such as protein markers, described herein can be used to predict, diagnose, prognose, or treat heart or kidney transplant rejection.

[0035] The invention further encompasses devices for analyzing one or more protein or antibody markers from a subject to determine the presence or absence, or level, of the one or more markers, which indicates that the subject may be at increased or decreased risk of developing a rejection response to an organ transplant, as compared to a control (e.g., a healthy subject that does not express the one or more markers).

[0036] The term "collection of solid substrates" refers to a group of substrates that are solid in nature or can be formed on a solid surface. The term collection refers to a plurality of solid substrates, the number of substrates being determined by the number of separate markers, such as antibodies, that are assayed by the methods of the invention.

[0037] The term "homogeneous population" refers to a population of molecules that are identical with respect to their molecular structure. In one embodiment, a homogeneous population is a collection of single binding agents that specifically bind to antibodies in a sample, where the binding agents have the same amino acid sequence. In another embodiment, a homogeneous population is a collection of single binding agents that specifically bind to antibodies in a sample, where the binding agents all have the same protein structure.

[0038] The terms "transplantation" or "transplant" refer to the procedure of joining donor tissue, such as the heart or kidney, with the body of a graft recipient.

[0039] The terms "allogeneic" or "allograft" refer to the transplantation of an organ from an animal of the same species. However, "xenogeneic" transplants, i.e., the transplantation of organs from animals of other species into humans, for example, transplants using hearts or kidneys harvested from transgenic pigs, are also contemplated by the present invention.

[0040] The term "rejection" or "transplant rejection" is used herein to refer to rejection by the immune system of a tissue transplant recipient when the transplanted tissue is immunologically foreign. In certain embodiments, tissue rejection includes, but is not limited to, autoimmune organ rejection, e.g., pericarditis, and graft-versus-host associated rejection. Most frequently, organ rejection occurs after allograft or xenograft transplantation. In some instances, the rejection is an acute rejection. In some instances, the rejection is a chronic rejection.

[0041] As used in the art, "acute rejection" is a form of rejection that occurs within the first six months of transplantation and is often mediated by mononuclear cells that infiltrate the graft, causing acute damage to graft parenchymal cells.

[0042] As used in the art, "chronic rejection" is a form of rejection that develops within months to years after transplantation. Chronic rejection is the leading cause of long-term graft loss.

[0043] The terms "marker" or "biomarker" are used interchangeably herein to refer to proteins, such as antibodies, that exhibit altered expression levels compared to normal levels prior to or during heart or kidney transplant rejection. In some embodiments, such proteins are antibodies directed against non-HLA proteins associated with immune or inflammatory responses, "non-HLA antibodies." In other embodiments, the markers are proteins found in tissues of rejected organs prior to the onset of a rejection episode. For example, the markers used herein are non-HLA antibodies disclosed herein, e.g., in Table 4. In certain instances, the markers of the present invention are proteinaceous molecules and thus may be modified by the cells that express them. In some cases, partial sequence data confirms that spots with only minor variations in molecular weight, isoelectric point, or both represent various modified forms of the same protein. Such modifications include, but are not limited to, differential glycosylation, phosphorylation, N-terminal acetylation, C-terminal amidation, alterations in mRNA splicing, and the like.

[0044] The term "binding agent" refers to a molecule that specifically recognizes and binds to a target molecule of interest. Non-limiting examples of binding agents include any molecule that can form an immune complex with a target molecule. For example, in one particular embodiment, the target molecule can be an antibody or an antibody fragment, and the binding agent in this particular embodiment is an antigen molecule, such as, but not limited to, a polypeptide that the antibody or fragment specifically binds to.

[0045] The term "antibody" refers to an immunoglobulin molecule or fragment thereof that recognizes and specifically binds to a target, such as a protein, polypeptide, peptide, carbohydrate, polynucleotide, lipid, or a combination thereof, through at least one antigen recognition site within the variable region of the immunoglobulin molecule.

[0046] The terms "polypeptide", "peptide" and "protein" are used interchangeably herein to refer to polymers of amino acids of any length. As used herein, the term polypeptide may refer to a natural or synthetic molecule that includes two or more amino acids linked by the carboxyl group of one amino acid to the alpha amino group of another amino acid. In selected embodiments, a polypeptide is a binding agent used in the methods and compositions of the invention. The polypeptides used as binding agents in the methods and compositions of the invention may be of various animal origins, including, but not limited to, human, monkey, mouse, pig, cow, dog, horse, sheep, goat, and cunicular. In certain embodiments, the polypeptides used as binding agents are recombinant peptides. Polypeptides may be linear or branched, may contain modified amino acids, and may be interrupted by non-amino acids. The term also encompasses amino acid polymers that have been modified, naturally or by intervention, for example, by disulfide bond formation, glycosylation, lipidation, acetylation, phosphorylation, or other manipulations or modifications, such as conjugation with a labeling component. Also included within the definition are, for example, polypeptides containing one or more analogs of an amino acid, or one or more conservative substitutions, as well as other modifications known in the art.

[0047] The definition of the polypeptide of the present invention encompasses antigens or antibodies. For example, the polypeptide can be an antigenic binding agent that specifically binds to a non-HLA antibody disclosed herein. In some embodiments, the antigenic binding agent comprises a full-length protein or a protein fragment thereof. In some embodiments, the antigenic binding agent comprises or consists of an antigenic determinant thereof. In some embodiments, the antigenic binding agent is of human origin. In other embodiments, the antigenic binding agent is of non-human origin, including, but not limited to, monkey, mouse, pig, cow, dog, horse, sheep, goat, and rabbit.

[0048] The term "labeled" as used herein means that the entity comprises a member of a signal producing system and is therefore detectable directly or through the combined action of one or more additional members of the signal producing system. Examples of directly detectable labels include isotopic and fluorescent moieties, and are often covalently bound to solid phase substrates, binding agents, and / or biological samples. Labels can include, but are not limited to, fluorescent labels, immunolabels, magnetic labels, DNA labels, small molecule labels, or radioactive labels.

[0049] The term "affinity" as used herein means to bind or attach non-covalently. Non-covalent binding refers to an interaction that does not involve the formation of a covalent chemical bond. Non-covalent attachment involves binding between molecules and may include one or more of a variety of non-covalent forces, such as, but not limited to, hydrogen bonds, van der Waals forces, and electrostatic forces. When a ligand has affinity for a particular target, it means that the ligand has a favorable tendency to specifically and non-covalently associate with the target to form a complex(es). The affinity of a ligand for its target depends on multiple factors, including, but not limited to, the conformation of the ligand, the conformation of the target, and local environmental parameters such as temperature and ionic conditions, which can strongly affect binding without significant conformational changes. Non-limiting examples of affinity attachment include the binding between biotin and streptavidin, histidine and nickel, or an antibody and an antigen.

[0050] As used herein, the term "detect" refers to the qualitative or quantitative measurement of undetectable, low, normal, or high concentrations of one or more biomarkers in a biological sample, such as, for example, an antigen, antibody, or other biomolecule.

[0051] The term "likelihood of organ rejection" refers to the probability of a rejection episode, which can be predicted based on the expression levels of the marker(s) disclosed herein.

[0052] The term "increased expression" of a marker(s) in a test sample refers to an elevated expression level of the marker(s) compared to the level of the corresponding marker(s) in a reference sample, or the presence of the corresponding marker(s) in a test sample that is not expressed in the reference sample. In some embodiments, the level of a marker as used herein refers to the circulating level of the marker. The term "circulating level" is intended to refer to the amount or concentration of the marker present in the circulation. The circulating level can be expressed, for example, in absolute amount, concentration, amount per unit mass of the subject, and can be expressed in relative amount. The level of a marker can also be expressed, without limitation, as a relative amount when compared to an internal standard or baseline level, or as a range of amounts, minimum and / or maximum amounts, average amounts, medians, or the presence or absence of a marker. In one example, the increased expression is measured by median fluorescence intensity (MFI). In other examples, the increased expression is measured, for example, by immunohistochemistry (IHC), enzyme-linked immunosorbent assay (ELISA), or electrochemiluminescence ELISA. In one example, increased expression refers to an elevated level of or the presence of one marker disclosed herein. In one example, increased expression refers to the level or presence of a collection of markers disclosed herein.

[0053] A "sample", "test sample" or "biological sample", as used interchangeably herein, is of biological origin in certain embodiments, such as a mammal. In certain examples, the sample is a tissue or bodily fluid obtained from a subject. In other specific examples, the sample is a human sample or an animal sample. Non-limiting sources of the sample are blood, plasma, serum, urine, spinal fluid, lymphatic fluid, synovial fluid, cerebrospinal fluid, tears, saliva, milk, mucosal secretions, exudates, sweat, biopsy aspirate, peritoneal fluid or bodily fluid extracts. In certain examples, the sample is a fluid sample. In some embodiments, the sample is derived from a subject (e.g., a human), including the different sample sources described herein.

[0054] The term "subject" refers to any animal, e.g., mammal, including, but not limited to, humans and non-human primates, that will be the recipient of a particular treatment. Typically, as used herein, the terms "individual," "patient," "subject," and "study subject" are used interchangeably to refer to a mammal, particularly a human or a non-human primate. In some embodiments, the subject is an adult. In one embodiment, the adult subject is a post-pubertal human. In another embodiment, the subject is an adolescent human. The term "adult" does not include pre-pubertal children. Subjects of interest include subjects who will be or have been tested for the evaluation (e.g., prediction, diagnosis, identification, etc.) of allograft rejection. Subjects may have been previously evaluated or diagnosed using other methods, such as those described in current clinical practice. In some embodiments, subjects of interest belong to a subpopulation of patients. For example, any of the methods described herein may be used in assessing acute rejection in a patient subpopulation with a cardiac or renal allograft rejection (e.g., acute rejection) score of grade 0, grade 1A, grade 1B, grade 2, grade 3A, grade 3B, or grade 4. In some embodiments, the subject has an allograft rejection score of grade 1B or higher. In some embodiments, the subject has at least one histologically proven rejection episode. In some embodiments, acute cellular rejection (ACR) and antibody-mediated rejection (AMR) are assessed by endomyocardial biopsy (EMB) according to the International Society for Heart and Lung Transplantation (ISHLT) criteria. In some embodiments, the subject has an ACR 1R. In some embodiments, the subject has an ACR 2R. In some embodiments, the subject has an ACR 3R. In some embodiments, the subject has an AMR. In some embodiments, the subject has a mixed ACR and AMR. In some embodiments, the subject may or may not have undergone a biopsy, such as a kidney or cardiac biopsy.Any of the methods, compositions, or kits described herein can be used to non-invasively assess rejection in a subject at risk of having cardiac or renal allograft rejection.

[0055] A "reference sample" is used to correlate and compare results obtained from a test sample. A reference sample can be any biological sample used herein. The method of the present invention includes comparing the level of one or more markers, such as non-HLA antibodies disclosed herein, in a test sample with a "reference level". Reference samples can be obtained from various subgroups, including, but not limited to, healthy individuals, individuals who have not previously undergone an organ transplant, individuals who have undergone an organ transplant but have not experienced severe rejection of the transplant, and individuals of any age group. A reference sample may also be obtained from a subject before the subject undergoes a transplant or before the subject develops rejection of the transplant. The level of a marker in a "reference sample" is referred to as a "reference level". Non-limiting examples of reference samples or reference levels are provided in the Examples section below.

[0056] The term "immunological analysis" refers to characterizing the markers disclosed herein based on immunospecific binding, i.e., reactivity of the marker with a specific binding partner. When the marker is an antibody, the specific binding partner paradigm is an antigen. Thus, any technique applicable to antigen-antibody binding is extended to the binding of any specific binding partner of the marker. Examples of immunological analysis techniques include, but are not limited to, immunoblotting, ELISA, radioimmunoassay (RIA), agglutination, immunofluorescence, immunochemiluminescence, immunochromatography, IHC, biosensors, optical sensors, and immunoprecipitation.

[0057] Reference to a value or parameter of "about" herein includes (and describes) an embodiment directed to that value or parameter itself. For example, a description referring to "about X" includes a description of "X". The term "about" is used to provide flexibility to numerical range endpoints by providing that a particular value may be "a little above" or "a little below" the endpoint without affecting the desired result, but also includes a range of + / - 10% of the indicated value. Concentrations, amounts, and other numerical data may be expressed or presented in a range format herein. It is to be understood that such range formats are used merely for convenience and brevity, and thus should be interpreted flexibly to include not only the numerical values ​​explicitly stated as the limits of the range, but also all individual numerical values ​​or subranges contained within the range as if each numerical value and subrange were explicitly stated.

[0058] As used herein, the singular forms "a," "an," and "the" include the plural forms unless the context clearly dictates otherwise.

[0059] Unless otherwise defined, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0060] The practice of the present invention employs, unless otherwise indicated, conventional techniques of protein biology, protein chemistry, molecular biology (including recombinant techniques), microbiology, cell biology, biochemistry, and immunology that are within the skill of the art. Such techniques are fully explained in such references as "Molecular Cloning: A Laboratory Manual," 2nd Edition (Sambrook et al., 1989); "Current Protocols in Molecular Biology" (Ausubel et al., eds., 1987, periodically revised); "PCR: The Polymerase Chain Reaction" (Mullis et al., eds., 1994); and Singleton et al., Dictionary of Microbiology and Molecular Biology, 2nd Edition, J. Wiley & Sons (New York, NY 1994).

[0061] The biomarkers of the present invention include proteins, such as antibodies, expressed by cells in subjects undergoing or having undergone heart or kidney transplant rejection.Marker proteins are typically expressed at very low levels or not expressed in reference samples.In some embodiments, the level of expression of marker proteins increases in association with organ rejection, for example, when acute rejection is imminent or initiation of acute rejection.

[0062] The present invention provides a homogenous population of biomarkers, eg, binders to non-HLA antibodies, associated with allograft rejection.

[0063] In another embodiment, the present invention provides non-HLA antibodies predictive of allograft rejection, including, but not limited to, tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB. In some embodiments, any combination of one or more of the aforementioned non-HLA antibodies is informative as a marker of allograft rejection. In some embodiments, non-HLA antibody combinations informative of allograft rejection based on additional organ-specific analysis include tubulin, LPHN1, SNRPN, KRT18, KRT8, DEXI, and GAPDH. In some embodiments, allograft rejection is predicted by assessing the levels of any one or any combination of two or more of the following non-HLA antibodies: tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB. In some embodiments, for example, combinations of non-HLA antibodies that are informative of allograft rejection based on additional organ-specific analysis include tubulin, LPHN1, SNRPN, KRT18, KRT8, DEXI, and GAPDH.

[0064] In some embodiments, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, or fifteen of the following non-HLA antibodies are informative as independent markers of allograft rejection: tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, and STAT6. In some embodiments, any one, two, three, four, five, six, or seven additional non-HLA antibodies of GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB are informative as independent markers of allograft rejection. In some embodiments, allograft rejection is predicted by assessing the levels of any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, or fifteen of the following non-HLA antibodies: tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, and STAT6. In some embodiments, allograft rejection is predicted by assessing the levels of any one, two, three, four, five, six, or seven of the following non-HLA antibodies: GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB.

[0065] In some embodiments, cardiac allograft rejection is predicted by assessing the levels of any one, two, three, four, five, six, seven, eight, nine, or ten of tubulin, LPHN1, TG, GAPDH, FN1, NPHS1, VIM, myosin, VCL, and PECR non-HLA antibodies. For example, cardiac allograft rejection is predicted by assessing the levels of TG and LPHN1 non-HLA antibodies. In another example, cardiac allograft rejection is predicted by assessing the levels of tubulin, LPHN1, TG, and VCL non-HLA antibodies. In another example, cardiac allograft rejection is predicted by assessing the levels of tubulin, LPHN1, and TG non-HLA antibodies. In another example, cardiac allograft rejection is predicted by assessing the levels of DEXI, EMCN, SNRPN, LPHN1, and SSB non-HLA antibodies. In another example, non-rejection is predicted by assessing the levels of KRT18, GAPDH, AGRN, ENO1, and EMCN non-HLA antibodies. In some embodiments, cardiac allograft rejection is predicted by assessing the levels of any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, or eighteen of ENO1, AGRN, EMCN, SSB, actin, FLT3LG, PRKCH, IL-21, tubulin, LPHN1, TG, GAPDH, FN1, NPHS1, VIM, myosin, VCL, and PECR non-HLA antibodies.

[0066] In some embodiments, evaluating the levels of any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen or fifteen of DEXI, LGALS3, SNPRN, CSF2, IL-8, STAT6, LGALS8, KRT18, KRT8, GSTT1, LMNA, collagen II, ATP5B, SNRPB2 and PLA2R1 non-HLA antibodies is predictive of pediatric renal allograft rejection.

[0067] For example, renal allograft rejection is predicted by assessing the levels of DEXI, LGALS3, SNPRN, CSF2, IL-8, STAT6, and LGALS8 non-HLA antibodies. In another example, renal allograft rejection is predicted by assessing the levels of DEXI, LGALS3, SNPRN, CSF2, STAT6, LGALS8, KRT18, KRT8, GSTT1, collagen II, SNRPB2, and PLA2R1 non-HLA antibodies. In another example, renal allograft rejection is predicted by assessing the levels of tubulin, DEXI, LGALS3, SNPRN, KRT18, KRT8, GSTT1, collagen II, SNRPB2, and PLA2R1 non-HLA antibodies.

[0068] In some embodiments, assessing the levels of any one, two, or three of tubulin, SHC3, and CXCL11 non-HLA antibodies is predictive of adult renal allograft rejection.

[0069] In one embodiment, the present invention provides a composition for determining the presence of one or more antibodies in a biological sample.In one embodiment, the composition comprises a collection of solid substrates coated with one or more homogenous populations of binding agents.In one embodiment, each of the homogenous populations of binding agents specifically binds to the non-HLA antibodies disclosed herein.

[0070] In some embodiments, the coating is by conjugation. That is, one or more homogenous populations of binding agents are conjugated to the surface of the solid phase substrate. In some embodiments, the conjugation is covalent. In some embodiments, the coating is by covalent attachment. Examples of covalent attachment include, but are not limited to, glutaraldehyde. In some embodiments, the coating is by covalent cross-linking. Examples of covalent attachment include, but are not limited to, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC), H-benzotriazol-1-yloxytris(dimethylamino)phosphonium hexafluorophosphate (BOP), N-ethoxycarbonyl-2-ethoxy-1,2-dihydroquinoline (EEDQ), (1-[3-(dimethylamino)propyl]-3-ethylcarbodiimide hydrochloride) (EDAC), and N-hydroxysuccinimide (NHS). In some embodiments, the coating is by physical adsorption. In some embodiments, the coating is by encapsulation. Examples of encapsulation include, but are not limited to, polymers. In some embodiments, the coating is by affinity attachment. Examples of physical adsorption include, but are not limited to, biotin / streptavidin, histidine / nickel, and antibody / antigen. Methods of covalent attachment, covalent cross-linking, physical adsorption, encapsulation, and affinity attachment are generally known in the art and are encompassed by the present invention.

[0071] In some embodiments, the solid substrate comprises particles, nanoparticles, beads, nanobeads or microspheres. In some embodiments, the solid substrate can be porous or non-porous. In some embodiments, the substrate can be array-based. In another embodiment, the solid substrate of the present invention comprises magnetic-based protein assay components. In other embodiments, the substrate can be organic or inorganic; metallic (e.g., copper or silver) or non-metallic; polymeric or non-polymeric; conductive, semiconductive, or non-conductive (insulating); reflective or non-reflective. For example, the substrate can comprise polyethylene, polytetrafluoroethylene, polystyrene, polyethylene terephthalate, polycarbonate, gold, silicon, silicon oxide, silicon oxynitride, indium, tantalum oxide, niobium oxide, titanium, titanium oxide, platinum, iridium, indium tin oxide, diamond or diamond-like films, and the like.

[0072] Such substrates may be formed of any suitable material, including, but not limited to, materials selected from the group consisting of metals, metal oxides, alloys, semiconductors, polymers (including organic polymers in any suitable form, such as woven, non-woven, molded, extruded, cast, etc.), silicon, silicon oxides, ceramics, glasses, and composites thereof.

[0073] In some embodiments, the solid phase substrate is labeled. In some embodiments, the binding agent is labeled. In some embodiments, the biological sample is labeled. In some embodiments, any one or two of the above components are labeled. In some embodiments, all of the above are labeled.

[0074] In one embodiment, the label is a fluorescent moiety.Fluorescent moieties or labels of interest include, but are not limited to, coumarin and its derivatives, such as 7-amino-4-methylcoumarin, aminocoumarin, Bodipy dyes, such as Bodipy FL, Cascade Blue, fluorescein and its derivatives, such as fluorescein isothiocyanate, Oregon Green, rhodamine dyes, such as Texas Red, tetramethylrhodamine, eosin and erythrosine, cyanine dyes, such as Cy3 and Cy5, macrocyclic chelates of lanthanide ions, such as quantum Dye™, fluorescent energy transfer dyes, such as thiazole orange-ethidium heterodimer TOTAB, etc. In one embodiment, the fluorescent label is phycoerythrin (e.g., R-phycoerythrin (R-PE). R-PE exhibits very bright red-orange fluorescence and has a high quantum yield. It is excited with laser lines from 488 to 561 nm, with absorbance maxima at 496 nm, 546 nm, and 565 nm, and a fluorescence emission peak at 578 nm. R-PE is a large molecule used in fluorescence-based detection, such as flow cytometry, microarray assays, ELISA, and other applications requiring high sensitivity but not photostability.

[0075] Fluorescent dyes can be detected in droplets with high resolution and in real time, and many fluorescent dyes with different excitation and emission wavelengths are available, allowing many labels to be monitored in one experiment. A set of fluorescent dyes can be selected, allowing multiple dyes to be detected simultaneously in the same reaction. A set of dyes that can be detected simultaneously can include, but is not limited to, Cy3, Cy5, FAM, JOE, TAMRA, ROX, dR110, dR6G, dTAMRA, dROX, or any mixture thereof. Any of these dyes can be used individually or in any combination to practice the embodiments herein. The dyes allow for single molecule detection. Many fluorescent dyes have been synthesized and are commercially available in various formats.

[0076] In some embodiments, the label is an affinity tag. Common choices of affinity tags are known in the art, such as biotin, histidine, glutathione S-transferase (GST) and maltose binding protein (MBP). Antibodies and antigens can also be used as affinity tags. In one particular embodiment, the binding agent is labeled with an affinity tag, and this label is used to coat the binding agent on a solid substrate.

[0077] In some embodiments, the label is an isotopic moiety. For example, the isotopic moiety is 32 P, 33 P, 35 S, 125 I, etc. In some embodiments, the solid substrate is magnetically labeled. In some embodiments, the solid substrate is labeled with one or more small molecules.

[0078] In some embodiments, each solid substrate is detectably distinguishable from other solid substrates in the composition, hi some embodiments, detectably distinguishable solid substrates are distinguishable by labels.

[0079] Described herein, in one embodiment, is a method for detecting biomarkers of solid organ transplant rejection in a patient sample. In some embodiments, the method comprises: (a) detecting a first graft rejection biomarker and one or more additional graft rejection biomarkers in a sample obtained from the patient, where the first graft rejection biomarker is an antibody directed against tubulin and the one or more additional graft rejection biomarkers are antibodies directed against an antigen selected from the group consisting of LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB; (b) determining whether the amount of the graft rejection biomarker is significantly different from the amount in a control sample; and (c) detecting the biomarker of graft rejection if the determination in (b) indicates a significant difference in the patient sample compared to the control sample. In other embodiments, the first graft rejection biomarker is an antibody directed against tubulin and the additional graft rejection biomarker is an antibody directed against an antigen selected from the group consisting of LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, and SSB. In some embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against TG, PECR, NPHS1, FN1, myosin, VIM, ATP5B, LMNA, CXCL11, actin, FLT3LG, PRKCH, and IL-21.

[0080] Described herein, in another embodiment, is a method for detecting a biomarker of solid organ transplant rejection in a patient sample. In some embodiments, the method includes: (a) detecting a first transplant rejection biomarker and one or more additional transplant rejection biomarkers in a patient sample, where the first transplant rejection biomarker is an antibody directed against dexamethasone-induced transcript (DEXI), and the one or more additional transplant rejection biomarkers are an antibody directed against an antigen selected from the group consisting of C-X-C motif chemokine ligand 11 (CXCL11), cytokeratin 18 (KRT18), cytokeratin 8 (KRT8), TUBα1b:tubulin alpha 1 b (TUBA1B), and tubulin; (b) determining whether the amount of the transplant rejection biomarker is significantly different from the amount in a control sample; and (c) detecting the biomarker of transplant rejection if the determination in (b) indicates a significant difference in the patient sample compared to the control sample. In other embodiments, the first graft rejection biomarker is an antibody directed against tubulin and the additional graft rejection biomarker is an antibody directed against an antigen selected from the group consisting of CXCL11, DEXI, KRT18, and KRT8.

[0081] In some embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, and PLA2R1.In other embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, PLA2R1, IL-8, LGALS3, SNPRN, myosin, PECR, VIM, ATP5B, collagen II, LMNA, and SNRPB2.

[0082] In some embodiments, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, or nineteen of the non-HLA antigen targets disclosed herein are informative as independent markers of cardiac allograft rejection. In some embodiments, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, or nineteen of the non-HLA antigen targets disclosed herein are predictive of cardiac allograft rejection.

[0083] In some embodiments, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, or twelve of the non-HLA antigenic targets disclosed herein are informative as independent markers of renal allograft rejection. In some embodiments, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, or twelve of the non-HLA antigenic targets disclosed herein are predictive of renal allograft rejection.

[0084] In one embodiment, the method is performed with 8 or less graft rejection markers. Optionally, the detecting can be performed with up to 5, 10, 15, 20, 25, 30, or up to 35 graft rejection markers. In some embodiments, the graft rejection markers are exclusively selected from the group consisting of DEXI, CXCL11, KRT18, KRT8, TUBA1B, tubulin, LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, PLA2R1, IL-8, LGALS3, SNPRN, myosin, PECR, VIM, ATP5B, collagen II, LMNA, SNRPB2, VCL, TG, FN1, ENO1, AGRN, EMCN, SSB, actin, FLT3LG, PRKCH, and IL-21, and antibodies directed against combinations of two or more of these markers. In some embodiments, the graft rejection marker is exclusively selected from the group consisting of antibodies directed against DEXI, CXCL11, KRT18, KRT8, TUBA1B, tubulin, LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, PLA2R1, IL-8, LGALS3, SNPRN, myosin, PECR, VIM, ATP5B, collagen II, LMNA, SNRPB2, and combinations of two or more of these markers. In other embodiments, the graft rejection marker further comprises one or more additional markers other than those listed herein, e.g., additional markers of interest to the user.

[0085] Further provided is a method for assaying a combination of markers in a sample of a biological fluid obtained from a human subject, the method comprising performing an immunoassay by contacting the sample with a solid support of a kit or composition described herein. Examples of immunoassays include, but are not limited to, enzyme-linked immunosorbent assays (ELISAs), and bead-based, particle-based, or other multiplex assays.

[0086] In some embodiments, the sample is plasma or serum. In some embodiments, the method further comprises contacting the sample with a conjugate of the kit and assaying the reaction of the conjugate with the sample. In some embodiments, the method further comprises contacting an antigen standard with the solid support and the conjugate and assaying the relative level of the transplant rejection biomarker in the sample to the antigen standard.

[0087] Further provided is a method for assaying a graft rejection biomarker in a serum or plasma sample. In some embodiments, the method includes: (a) providing a binding agent that specifically binds to an antibody directed against DEXI and one or more binding agents that specifically bind to an antibody directed against a single antigen selected from the group consisting of CXCL11, KRT18, KRT8, TUBA1B, and tubulin; (b) providing a microtiter plate coated with the binding agent; (c) adding serum or plasma to the microtiter plate; (d) providing an alkaline phosphatase-antibody conjugate that reacts with a graft rejection biomarker to the microtiter plate; (e) providing p-nitrophenyl phosphate to the microtiter plate; and (f) assaying the reaction resulting from steps (a)-(e) against a standard curve to determine the level of the graft rejection biomarker in the sample.

[0088] In some embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, PLA2R1, IL-8, LGALS3, SNPRN, myosin, PECR, VIM, ATP5B, collagen II, LMNA, SNRPB2, VCL, TG, FN1, ENO1, AGRN, EMCN, SSB, actin, FLT3LG, PRKCH, and IL-21. In some embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, and PLA2R1. In some embodiments, the detecting further comprises detecting in the patient sample one or more additional graft rejection biomarkers selected from the group consisting of antibodies directed against LPHN1, CSF2, STAT6, LGALS8, SHC3, GAPDH, GSTT1, PLA2R1, IL-8, LGALS3, SNPRN, myosin, PECR, VIM, ATP5B, collagen II, LMNA, and SNRPB2.

[0089] Other groups of transplant rejection biomarkers can be identified by reference to the figures and tables herein. For example, the selection of biomarkers for use together includes grouping one or more members of the groups identified in Figure 5 or Figure 6 as "Group I," "Group II," and / or "Group III," and / or identified in Table 4. In another example, the selection includes one or more representatives of different groups of those identified in Figure 5 or Figure 6 and Table 4. A representative group of biomarkers for use together may include one or more members of one of the columns shown in Table 3 and / or Table 5, thereby tailoring the grouping to detection of cardiac transplant rejection, or adult renal transplant rejection, or pediatric renal transplant rejection. In another example, a "core" biomarker (e.g., tubulin) associated with rejection in different organ systems and populations is selected and combined with one or more biomarkers associated with each of the columns identified in Table 3 and / or Table 5. Other bases for selecting biomarkers to use together include, but are not limited to, whether the biomarkers are predictive in a CART analysis (classification and regression tree analysis), whether the biomarkers are sorted independently in an analysis showing them to be independent predictors of rejection, whether the markers cluster together (or independently as in VCL) in a correlation matrix (see Figures 2 and 3), whether the biomarkers were significantly associated with time to first rejection (see Figure 1), whether the biomarkers are newly described herein (Table 1 or Table 6) or have previously been associated with graft rejection. Various other combinations of groupings of biomarkers are also contemplated.Some representative examples include selected individual biomarkers such as, but not limited to, antibodies directed against tubulin or DEXI or EMCN or LGALS3 or SNPRN or LPHN1 or SSB or TG or CXCL11 or KRT8 or KRT18 in combination with one, two, three, four, five or more additional biomarkers, as proposed individual examples, selected subsets of markers grouped together herein (e.g., those grouped in groups I, II, III or IV, or in one of the tables or figures herein); selected combinations including one or more representative markers within such subsets.

[0090] In some embodiments, the above steps are performed for 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 30, or all 31 of the markers listed in Table 1. In one embodiment, the set of markers consists of 8 or fewer markers listed in Table 1. In another embodiment, the set of markers consists of 6 or fewer markers listed in Table 1. In yet another embodiment, the set of markers consists of 4 or fewer markers listed in Table 1. Representative groups of biomarkers of transplant rejection include, but are not limited to, antibodies directed against DEXI, KRT8, and KRT18; CXC11 and tubulin / TUBA1B; DEXI, KRT8, KRT18, CXC11, and tubulin / TUBA1B; DEXI, SNPRN, Smith Antigen, LGALS3, ANXA2R, Jo-1, CCP, and TG; DEXI, LPHN1, CSF2, LGALS8, STAT6, and SHC3. Other groups include tubulin, LPHN1, SNRPN, KRT18, KRT8, DEXI, and GAPDH, as well as various groups identified in Figures 5 and 6 and various exemplary embodiments listed herein.

[0091] In one embodiment, the present invention describes a method for determining the presence of one or more non-HLA antibodies disclosed herein in a biological sample obtained from a subject, such as a subject who has undergone or is about to undergo an organ transplant. Such methods provided herein can be used to screen or monitor antibodies against non-HLA antigens in heart and / or kidney allograft patients, and thus assess the risk of developing rejection.

[0092] The first step of the method generally involves contacting a biological sample obtained from a subject with a composition disclosed herein.

[0093] Contacting a biological sample with a composition generally involves adding the composition to the sample, or vice versa, and incubating the mixture for a time sufficient for the composition to specifically bind to any target antibody present in the sample. Effective or optimal conditions can be determined using methods known in the art.

[0094] Any convenient protocol for obtaining such biological samples can be used, provided that suitable protocols are well known in the art. When obtaining a sample (e.g., a blood sample) from a subject, the amount can vary depending on the size of the subject and the condition being screened. In some embodiments, up to about 1 mL, 2 mL, 3 mL, 4 mL, 5 mL, 6 mL, 7 mL, 8 mL, 9 mL, 10 mL, 20 mL, 30 mL, 40 mL, or 50 mL of sample is obtained. In some embodiments, about 1-50 mL, 2-40 mL, 3-30 mL, or 4-20 mL of sample is obtained. In some embodiments, more than about 5 mL, 10 mL, 15 mL, 20 mL, 25 mL, 30 mL, 35 mL, 40 mL, 45 mL, 50 mL, 55 mL, 60 mL, 65 mL, 70 mL, 75 mL, 80 mL, 85 mL, 90 mL, 95, or 100 mL of sample is obtained. In some embodiments, up to about 1 μL, 2 μL, 3 μL, 4 μL, 5 μL, 6 μL, 7 μL, 8 μL, 9 μL, 10 μL, 20 μL, 30 μL, 40 μL, or 50 μL of sample is obtained. In some embodiments, about 1-50 μL, 2-40 μL, 3-30 μL, or 4-20 μL of sample is obtained. In some embodiments, more than about 5 μL, 10 μL, 15 μL, 20 μL, 25 μL, 30 μL, 35 μL, 40 μL, 45 μL, 50 μL, 55 μL, 60 μL, 65 μL, 70 μL, 75 μL, 80 μL, 85 μL, 90 μL, 95, or 100 μL of sample is obtained. In some embodiments, the sample for analysis will yield 1 pg, 5 pg, 10 pg, 20 pg, 30 pg, 40 pg, 50 pg, 100 pg, 200 pg, 500 pg, 1 ng, 5 ng, 10 ng, 20 ng, 30 ng, 40 ng, 50 ng, 100 ng, 200 ng, 500 ng, 1 μg, 5 μg, 10 μg, 20 μg, 30 μg, 40 μg, 50 μg, 100 μg, 200 μg, 500 μg, 1 mg, 5 mg, 10 mg, 50 mg, 100 mg, 200 mg, 500 mg, 1 gram, 5 grams, 10 grams, 20 grams, 50 grams, 100 grams or more of sample.In some embodiments, the sample for analysis provides about 1-5 pg, 5-10 pg, 10-100 pg, 100 pg-1 ng, 1-5 ng, 5-10 ng, 10-100 ng, or 100 ng-1 μg of sample. In some embodiments, the sample for analysis provides about 1 mg of sample.

[0095] Multiple biological samples may be collected at one time. The biological sample(s) may be taken from the subject at any time, such as before, at the time of transplant, or after transplant.

[0096] After contacting biological sample with the composition described herein, a signal is generated from the contact step, which can be detected using any suitable method known in the art.Exemplary methods can include, but are not limited to, visual detection, fluorescence detection (e.g., fluorescence microscopy), scintillation counting, surface plasmon resonance, ellipsometry, atomic force microscopy, surface acoustic wave device detection, autoradiography, and chemiluminescence.As those skilled in the art will understand, the selection of detection method will depend on the specific labeling agent used.

[0097] In some embodiments, detecting is performed by measuring fluorescence intensity. Such methods are generally known in the art. For example, the xMAP technology of Luminex (Luminex Corp., Austin, TX) allows up to 500 immunoassays in various combinations to be performed in a single reaction in a standard 96-well microplate. In some embodiments, detecting is performed by immunological analysis. In the exemplary section, exemplary embodiments of effective or optimal conditions of the methods described herein are provided.

[0098] In some embodiments, the detecting is performed by a labeled secondary anti-human antibody. Labeled secondary anti-human antibodies are commonly used in the art and are available from a variety of vendors. In some embodiments, the secondary anti-human antibody is labeled by an enzyme conjugate. Non-limiting examples include alkaline phosphatase (AP) or horseradish peroxidase (HRP). In some embodiments, the secondary anti-human antibody is labeled by a fluorescent conjugate. Non-limiting examples include fluorescein (FITC), tetramethylrhodamine (TRITC), Alexa Fluor, phycoerythrin, and the like. In some embodiments, the secondary anti-human antibody is labeled by biotin. Specific embodiments of labeled secondary anti-human antibodies are provided in the Examples section.

[0099] In one embodiment, the present invention provides a method for diagnosing transplant rejection in a subject who has received a heart or kidney transplant. In yet another embodiment, the present invention describes a method for predicting the likelihood of transplant rejection in a subject in need of a heart or kidney transplant.

[0100] In certain embodiments, the method provided herein comprises measuring the binding of one or more homogenous populations of binding agents to one or more antibodies that may be present in a sample.In some embodiments, the method comprises measuring the level of one or more antibodies in a sample.In some embodiments, the increase in the level of one or more antibodies compared to the reference level indicates that the subject has a possibility of developing transplant rejection after heart transplantation or kidney transplantation.

[0101] In some embodiments, whether a subject has a rejection (e.g., acute rejection) is determined based on the presence of one or more biomarkers disclosed herein. In some embodiments, the presence of one or more biomarkers at a level above a reference level, any one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, or eighteen of the non-HLA antibodies disclosed herein, is informative as an independent marker of allograft rejection.

[0102] The accuracy of a diagnostic and / or prognostic method can be measured by how close a measured or calculated value is to an actual measured value. For example, the accuracy of the methods provided herein can be measured by the percentage of rejection or non-rejection that is correctly predicted. In some embodiments of the invention, the accuracy of the methods described herein is the number of subjects without rejection predicted by the methods described herein to have no rejection divided by the total number of subjects that actually have no rejection. In other embodiments, the accuracy of the methods described herein is the number of subjects predicted by the methods described herein to have rejection divided by the total number of subjects that actually have rejection. In some embodiments, the methods described herein include assessing (e.g., predicting, diagnosing, identifying, etc.) rejection with about 60-100% accuracy. In some embodiments, the accuracy is about 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%, but less than 100%. In some embodiments, the accuracy is about 60-65%, 65-70%, 70-75%, 75-80%, 80-85%, 85-90%, 90-95%, or 95-100%, but not greater than 100%. In some embodiments, the accuracy is about 90%. In some embodiments, the accuracy is about 87%. In some embodiments, the accuracy is about 86%. In some embodiments, the accuracy is about 80%. In some embodiments, the accuracy is about 70%. In some embodiments, the accuracy is about 60%.

[0103] The specificity of a diagnostic and / or prognostic method may be a measure of the proportion of subjects who are actually negative for a condition who are correctly identified as negative for the condition by the model. The specificity of a model may be equal to the number of true negatives divided by the number of true negatives plus the number of false positives. In other words, the specificity of a model may be the probability of a negative test result if the subject is actually negative for the condition. In some embodiments, the specificity of a method described herein is the number of subjects without rejection predicted to have no rejection by a method described herein divided by the total number of subjects predicted to have no rejection using a method described herein. In some embodiments, the step of comparing a method described herein includes assessing (e.g., predicting, diagnosing, identifying, etc.) rejection with a specificity of about 60-100%. In some embodiments, the specificity is about 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%, but less than 100%. In some embodiments, the specificity is about 60-65%, 65-70%, 70-75%, 75-80%, 80-85%, 85-90%, 90-95%, or 95-100%, but not greater than 100%. In some embodiments, the specificity is about 90%. In some embodiments, the specificity is about 80%. In some embodiments, the specificity is about 70%. In some embodiments, the specificity is about 66.67%. In some embodiments, the specificity is about 60%.

[0104] The sensitivity of a diagnostic and / or prognostic method may be a measure of the proportion of subjects who are actually positive for a condition who are correctly identified as positive for the condition by the model. The sensitivity of a model may be equal to the number of true positives divided by the number of true positives plus the number of false negatives. In other words, the sensitivity of a model may be the probability of a positive test result if the subject is actually positive for the condition. In some embodiments, the sensitivity of a method described herein is the number of subjects who have rejection predicted to have rejection by a method described herein divided by the total number of subjects who are predicted to have rejection using a method described herein. In some embodiments, the step of comparing a method described herein includes assessing (e.g., predicting, diagnosing, identifying, etc.) rejection with a sensitivity of about 70-100%. In some embodiments, the sensitivity is about 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%, but not greater than 100%. In some embodiments, the sensitivity is about 70-75%, 75-80%, 80-85%, 85-90%, 90-95%, or 95-100%, but not greater than 100%. In some embodiments, the sensitivity is about 70%. In some embodiments, the sensitivity is about 92%. In some embodiments, the sensitivity is about 99%.

[0105] The present invention further encompasses a method for treating a subject in need of treatment for transplant rejection after receiving a heart or kidney transplant. In some embodiments, the number of non-HLA antibodies disclosed herein whose levels are altered (e.g., increased or present compared to a reference level) in a sample obtained from a subject can inform treatment methods. In some embodiments, detecting an increase in the level of one or more non-HLA antibodies described herein compared to a reference level indicates that the subject needs treatment.

[0106] In an embodiment, if one or more non-HLA antibodies disclosed herein are detected in a biological sample, standard treatment methods for removing the antibodies can be used. For example, the attending physician administers, performs, or requests that the subject undergo plasmapheresis. Plasmapheresis is a well-known procedure that can selectively remove harmful antibodies from the circulation of a subject. In an embodiment, the method includes contacting a biological sample obtained from the subject with a composition disclosed herein, measuring the level of one or more antibodies in the sample, and administering a treatment for transplant rejection to the subject if the level of one or more antibodies disclosed herein is increased compared to a reference level of one or more antibodies.

[0107] In an embodiment, the treatment protocol for AMR uses a permutation of a multifaceted approach, including but not limited to: (1) suppressing T cell-dependent antibody responses, (2) removing reactive antibodies, (3) blocking residual alloantibodies, and (4) depleting naive and memory B cells. In an embodiment, the treatment regimen applies plasma exchange. In an embodiment, the treatment regimen is administering rituximab. In an embodiment, the treatment regimen includes administering at least one proteasome inhibitor (such as but not limited to bortezomib)-based therapy. In an embodiment, the treatment regimen is administering mycophenolate mofetil. Additional treatment methods are known in the art. See, for example, Levine MH et al., Treatment options and strategies for antibody mediated rejection after renal transplantation.Semin Immunol. 2012 April;24(2):136-42, which are incorporated by reference.

[0108] In certain embodiments, the therapeutic agent is selected from tacrolimus, mycophenolate mofetil, and everolimus, with or without a corticosteroid. In certain embodiments, the therapeutic agent is tacrolimus, mycophenolate mofetil, and a corticosteroid. In certain embodiments, the therapeutic agent is tacrolimus, everolimus, and a corticosteroid.

[0109] In some embodiments, the treatment further comprises a steroid. In some embodiments, the steroid includes, but is not limited to, a corticosteroid (e.g., glucocorticoid and mineralocorticoid). In some embodiments, the corticosteroid is selected from prednisone (Deltasone, Orasone), budesonide (Entocort EC), and prednisolone (Millipred). In some embodiments, the steroid is used to reduce inflammation and reduce immune system activity. In some embodiments, the treatment does not comprise a steroid.

[0110] In certain embodiments, the method includes administering to the subject a therapeutically effective amount of one or more therapeutic agents. In some embodiments, the therapeutic agent is a Janus kinase inhibitor (e.g., tofacitinib (Xeljanz)). In some embodiments, the therapeutic agent is a calcineurin inhibitor (e.g., cyclosporine (Neoral, Sandimmune, SangCya), or tacrolimus (Astagraf XL, Envarsus XR, Prograf). In some embodiments, the therapeutic agent is an mTOR inhibitor (e.g., sirolimus (Rapamune), or everolimus (Afinitor, Zortress)). In some embodiments, the therapeutic agent is an IMDH inhibitor (e.g., azathioprine (Azasan, Imuran), leflunomide (Arava), or mycophenolate (CellCept, mycophenolic acid)). In some embodiments, the therapeutic agent is a biologic (e.g., abata sept (Orencia), adalimumab (Humira), anakinra (Kineret), certolizumab (Cimzia), etanercept (Enbrel), golimumab (Simpony), infliximab (Remicade), ixekizumab (Taltz), natalizumab (Tysabri), rituximab (Rituxan), secukinumab (Cosentyx), tocilizumab (Actemra), ustekinumab (Stelara), vedolizumab (Entyvio) or belatacept (Nulojix). In some embodiments, the therapeutic agent is a monoclonal antibody (e.g., basiliximab (Simulect) or daclizumab (Zinbryta)). In certain embodiments, the treatment comprises one or more therapeutic agents selected from the above.

[0111] In some embodiments, the treatment further comprises a steroid. In some embodiments, the steroid includes, but is not limited to, a corticosteroid (e.g., glucocorticoid and mineralocorticoid). In some embodiments, the corticosteroid is selected from prednisone (Deltasone, Orasone), budesonide (Entocort EC), and prednisolone (Millipred). In some embodiments, the steroid is used to reduce inflammation and reduce immune system activity. In some embodiments, the treatment does not comprise a steroid.

[0112] In certain embodiments, the therapeutic agent is selected from tacrolimus, mycophenolate mofetil, and everolimus, with or without a corticosteroid. In certain embodiments, the therapeutic agent is tacrolimus, mycophenolate mofetil, and a corticosteroid. In certain embodiments, the therapeutic agent is tacrolimus, everolimus, and a corticosteroid.

[0113] In another embodiment, the present invention provides a kit. Such a kit is a packaged combination comprising (a) a composition comprising a collection of solid-phase substrates coated with one or more homogenous populations of binding agents, and (b) a reagent for detecting binding of the one or more homogenous populations of binding agents to an antibody, wherein each homogenous population of binding agents is selected from the group consisting of (DEXI), C-X-C motif chemokine ligand 11 (CXCL11), cytokeratin 18 (KRT18), cytokeratin 8 (KRT8), tubulin, e.g., tubulin alpha 1b (also called TUBα1b or TUBA1B), latrophilin 1 (LPHN1), colony stimulating factor 2 (CSF2), signal transducer and activator of transcription 6 (STAT6), lectin galactoside-binding soluble 3 (LGALS3), SHC adaptor protein 3 (SHC3), glyceraldehyde-3 -phosphate dehydrogenase (GAPDH), glutathione S-transferase theta-1 (GSTT1), phospholipase A2 receptor 1 (PLA2R1), interleukin 8 (IL-8), lectin galactoside-binding soluble 8 (LGALS8), small nuclear ribonucleoprotein polypeptide N (SNPRN), myosin, peroxisomal trans-2-enoyl-CoA reductase (PECR), vimentin (VIM), ATP synthase H+ transport mitochondrial F1 complex beta polypeptide (ATP5B), collagen II, prelamin-A / C (LMNA), small nuclear ribonucleoprotein polypeptide B (SNRPB2), fibronectin 1 (FN1), and vinculin (VCL).

[0114] In another embodiment, each homogenous population of binding agents specifically binds to an antibody directed against a single antigen selected from the group consisting of tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, GAPDH, IL-8, SHC3, ENO1, AGRN, EMCN, SSB, TG, PECR, NPHS1, FN1, myosin, VIM, ATP5B, LMNA, CXCL11, actin, FLT3LG, PRKCH, and IL-21. In an embodiment, the kit also includes instructions for its use.

[0115] In a further embodiment, the kit can include one or more reference samples. The reference sample can be any biological sample used herein. In another embodiment, the kit can include one or more reference levels of non-HLA antibodies disclosed herein.

[0116] All patents and publications mentioned in this specification are indicative of the level of those skilled in the art to which this invention pertains. All patents and publications cited in this specification are incorporated by reference to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference in its entirety. Exemplary embodiments

[0117] The following are examples of embodiments described herein.

[0118] Embodiment 1: A composition comprising a collection of solid-phase substrates coated with one or more homogenous populations of binding agents, wherein each homogenous population of binding agents is selected from the group consisting of dexamethasone-induced transcript (DEXI), C-X-C motif chemokine ligand 11 (CXCL11), cytokeratin 18 (KRT18), cytokeratin 8 (KRT8), tubulin, e.g., tubulin alpha 1b (also called TUBα1b or TUBA1B), latrophilin 1 (LPHN1), colony-stimulating factor 2 (CSF2), signal transducer and activator of transcription 6 (STAT6), lectin galactoside-binding soluble 3 (LGALS3), SHC adaptor protein 3 (SHC3), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glutathione S-transferase theta-1 (G A composition that specifically binds to an antibody directed against a single antigen selected from the group consisting of: phospholipase A2 receptor 1 (PLA2R1), interleukin 8 (IL-8), lectin galactoside-binding soluble 8 (LGALS8), small nuclear ribonucleoprotein polypeptide N (SNPRN), myosin, peroxisomal trans-2-enoyl-CoA reductase (PECR), vimentin (VIM), ATP synthase H+ transporting mitochondrial F1 complex beta polypeptide (ATP5B), collagen II, prelamin-A / C (LMNA), small nuclear ribonucleoprotein polypeptide B (SNRPB2), fibronectin 1 (FN1), nephrosis 1, congenital, Finnish type (NPHS1), thyroglobulin (TG), and vinculin (VCL).

[0119] Embodiment 2: The composition of embodiment 1, wherein the collection of solid phase substrates further comprises one or more additional homogenous populations of binding agents, each additional homogenous population of binding agents specifically binds to an antibody directed against a single additional antigen selected from the group consisting of alpha enolase (ENO1), agrin (AGRN), endomucin (EMCN), Sjogren's syndrome antigen B (SSB), actin, fms-related tyrosine kinase 3 ligand (FLT3LG), protein kinase C eta (PRKCH), and interleukin 21 (IL-21).

[0120] Embodiment 3: The composition of embodiment 1 or 2, wherein the solid phase substrate is porous or non-porous.

[0121] Embodiment 4: The composition of embodiment 2 or 3, wherein the solid phase substrate comprises a particle, nanoparticle, bead, nanobead or microsphere.

[0122] Embodiment 5: The composition of embodiment 4, wherein the beads are polystyrene beads.

[0123] Embodiment 6: The composition of any one of embodiments 1 to 5, wherein the collection of solid substrates comprises a microarray.

[0124] Embodiment 7: The composition of any one of embodiments 1 to 6, wherein the solid phase substrate is fluorescently labeled, magnetically labeled, chemiluminescently labeled, or radioactively labeled.

[0125] Embodiment 8: The composition of any one of embodiments 1 to 7, wherein the solid phase substrate is labeled with a small molecule.

[0126] Embodiment 9: The composition of any one of embodiments 1 to 8, wherein the one or more homogenous populations of binding agents are conjugated to the surface of a solid substrate.

[0127] Embodiment 10: The composition of embodiment 9, wherein the conjugation is a covalent bond.

[0128] Embodiment 11: The composition of any one of embodiments 1 to 10, wherein one or more homogenous populations of binding agents are attached to the surface of the solid substrate by affinity.

[0129] Embodiment 12: The composition of any one of embodiments 1 to 11, wherein the binding agent is a polypeptide.

[0130] Embodiment 13: The composition of any one of embodiments 1 to 13, wherein the solid substrate is coated with at least three different homogenous populations of binding agents that bind to at least three different antigens.

[0131] Embodiment 14: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, PLA2R1, GSTT1, VCL, CSF2, LGALS8, and STAT6.

[0132] Embodiment 15: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against tubulin, LPHN1, TG, GAPDH, FN1, NPHS1, VIM, myosin, VCL and PECR.

[0133] Embodiment 16: The composition of embodiment 15, wherein the substrate is further coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against ENO1, AGRN, EMCN, SSB, actin, FLT3LG, PRKCH, and IL-21.

[0134] Embodiment 17: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against DEXI, LGALS3, SNPRN, CSF2, IL-8, STAT6, LGALS8, KRT18, KRT8, GSTT1, LMNA, Collagen II, ATP5B, SNRPB2, and PLA2R1.

[0135] Embodiment 18: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against tubulin, SHC3 and CXCL11.

[0136] Embodiment 19: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against DEXI, EMCN, SNRPN, LPHN1 and SSB.

[0137] Embodiment 20: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against KRT18, GAPDH, AGRN, ENO1 and EMCN.

[0138] Embodiment 21: The composition of embodiment 13, wherein the substrate is coated with a plurality of distinct homogenous populations of binding agents that bind to antibodies consisting of antibodies against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, GAPDH, ENO1, AGRN, EMCN, SSB, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, IL-8, and SHC3.

[0139] Embodiment 22: The composition of embodiment 1, wherein the single antigen is selected from the group consisting of LPHN1, TG, DEXI, CSF2, IL-8, LGALS3, SNPRN, STAT6, SHC3, and LGALS8.

[0140] Embodiment 23: The composition of embodiment 2, wherein the single additional antigen is selected from the group consisting of EMCN and SSB.

[0141] Embodiment 24: The composition of any one of embodiments 1 to 23, wherein at least one solid phase substrate is detectably distinguishable from at least one other solid phase substrate.

[0142] Embodiment 25: A method for determining the presence of one or more antibodies in a biological sample obtained from a subject, the method comprising contacting the biological sample with a composition of any one of embodiments 1 to 24 and detecting binding of one or more homogenous populations of binding agents to the one or more antibodies.

[0143] Embodiment 26: The method of embodiment 25, wherein the subject is a mammal.

[0144] Embodiment 27: The method of embodiment 26, wherein the subject is a human.

[0145] Embodiment 28: The method of any one of embodiments 25 to 27, wherein the subject has undergone or is going to undergo a heart or kidney transplant.

[0146] Embodiment 29: The method of embodiment 28, wherein the heart transplant is an allograft heart transplant or a kidney transplant.

[0147] Embodiment 30: The method of any one of embodiments 25 to 29, wherein the biological sample is blood, plasma, serum, urine, spinal fluid, lymphatic fluid, synovial fluid, cerebrospinal fluid, tears, saliva, milk, mucosal secretions, exudates, sweat, biopsy aspirate, peritoneal fluid or a body fluid extract.

[0148] Embodiment 31: The method of any one of embodiments 25 to 30, wherein detecting is by measuring fluorescence intensity or by immunological analysis.

[0149] Embodiment 32: A method for diagnosing transplant rejection in a subject who has received a heart or kidney transplant, the method comprising contacting a biological sample obtained from the subject with a composition of any one of embodiments 1 to 24 and measuring the level of one or more antibodies in the sample, wherein an increase in the level of the one or more antibodies compared to a reference level indicates that the subject has developed transplant rejection in response to the heart or kidney transplant.

[0150] Embodiment 33: A method for predicting the likelihood of transplant rejection in a subject in need of a heart or kidney transplant, the method comprising contacting a biological sample from the subject with a composition of any one of embodiments 1 to 24 and measuring the level of one or more antibodies in the sample, wherein an increased level of the one or more antibodies compared to a reference level indicates an increased likelihood that the subject will develop transplant rejection after a heart or kidney transplant.

[0151] Embodiment 34: A method of treating a subject in need of treatment for transplant rejection after receiving a heart or kidney transplant, comprising contacting a biological sample obtained from the subject with a composition of any one of embodiments 1 to 24, measuring the level of one or more antibodies in the sample, and administering to the subject treatment for transplant rejection if the level of the one or more antibodies is increased compared to a reference level of the one or more antibodies.

[0152] Embodiment 35: A kit comprising a composition according to any one of embodiments 1 to 24 and a reagent for detecting binding of one or more homogenous populations of binding agents to an antibody.

[0153] Embodiment 36: The kit of embodiment 35, further comprising one or more reference samples. Working Example

[0154] The following examples are provided for illustrative purposes and are intended to illustrate certain aspects and embodiments of the present invention, but are not intended to limit the invention in any manner. Example 1. Non-HLA antibodies associated with cardiac and renal allograft rejection

[0155] There is accumulating evidence that the development of post-transplant antibodies against non-HLA antigens is associated with rejection and reduced long-term graft survival. This example describes the use of sera from kidney and heart transplant recipients obtained before and after transplantation to generate a panel of non-HLA antigen targets that can be used to identify transplant recipients with circulating non-HLA antibodies that may portend risk of graft injury and loss.

[0156] Non-HLA antibodies reactive with endothelial cells were identified by testing sera from heart and kidney transplant recipients diagnosed with acute rejection in the absence of detectable circulating donor-specific HLA antibodies for binding in flow crossmatches to human primary arterial endothelial cells (Zhang and Reed, Transplantation 2005). Sera positive in endothelial cell crossmatches were tested without solvent and / or after absorption and elution from aortic endothelial cells on protoarrays containing over 9000 full-length human protein antigens. Non-HLA antibody targets associated with EC plasma membrane and self-antigens were classified using bioinformatics and gene ontological approaches. These studies identified 31 non-HLA antigen targets (Table 1). These and other non-HLA antigens were conjugated to polystyrene beads to develop multiplex bead arrays for further high-throughput testing in heart, and pediatric and adult kidney transplant recipients (Table 1). [Table 1]

[0157] Heart Transplant Rejection Discovery Cohort. The heart transplant discovery cohort was identified from 12 cardiac allograft recipients who were transplanted at UCLA between 2001 and 2005 and were positive for endothelial cell (EC) antibodies by EC flow crossmatch (ECXM) and negative for HLA DSA and MICA antibodies (Zhang Transplantation 2005). Six ECXM-, HLA DSA- patients without rejection were included as controls. Patients were typed for HLA by LABType SSO DNA typing (One Lambda, Canoga Park, CA) according to the manufacturer's specifications. MICA antibodies and HLA class I and class II antibodies were identified using the Single Antigen Luminex assay (One Lambda, Canoga Park, CAA). Acute cellular rejection (ACR) and AMR were diagnosed by endomyocardial biopsy (EMB) according to the International Society for Heart and Lung Transplantation (ISHLT) criteria as previously reported (Zhang Transplantation 2005, Stewart J Heart and Lung Transplant, 005). The mean time to collection of serum samples from the date of transplantation was 67 days, and the mean time from the date of rejection + biopsy was 14 days.

[0158] Kidney Transplant Rejection Discovery Cohort. The kidney transplant discovery cohort (n=16) was identified from renal allograft recipients transplanted at UCLA between 2010 and 2015 who were diagnosed with rejection and had positive endothelial cell antibodies by ECXM (Zhang Transplantation 2005). Pre-transplant sera from 3 of the 16 patients served as negative controls. Patient sera were solvent-free and tested after adsorption and elution from endothelial cells. The mean time of serum sample collection from the date of transplant was 21 days, and the mean time from the date of rejection+biopsy was 23 days.

[0159] Single-center heart transplant validation cohort. The single-center cohort consisted of 63 heart transplant recipients transplanted at UCLA between 2009 and 2016. Serum was collected at the time of EMB. Rejection (n=42, ACR>1R) was scored according to the ISHLT revision of the 1990 working formulation of heart transplant rejection. The median and interquartile range of days from serum collection to EMB was 0 for both rejection and no rejection samples (p<0.26). Post-transplant, patients were maintained on triple-drug immunosuppression (tacrolimus, mycophenolate mofetil, and corticosteroids).

[0160] Pediatric kidney transplant validation cohort. From August 2005 to November 2014, 83 pediatric kidney transplant patients transplanted at UCLA were enrolled in this study. Twenty-one patients were excluded from this analysis because more than one study sample was missing at the time of listing. The remaining 62 patients were included in this retrospective study. This study was approved by the UCLA Institutional Review Board (#11-002375) and complies with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or equivalent and the principles of the Declaration of Istanbul. Informed consent was obtained from legal guardians for all patients. Immunosuppressive therapy included induction with ATG when PRA was ≥30%, delayed graft function, or either a rapid steroid withdrawal protocol or anti-CD25 monoclonal antibody when PRA was <30%. Maintenance immunosuppression consisted of steroid-free or steroid-based immunosuppression, calcineurin inhibitors, and antimetabolites. Acute and chronic rejection were treated with a previously described protocol (Pearl, Pediatr Nephrol, 2016). Patients underwent protocol biopsy at 6, 12, and 24 months post-transplant or for clinical indications. Biopsy samples were evaluated based on the 2013 Banff criteria (Haas, Am J Transplant, 2014). Blood samples were obtained pre-transplant, 6, 12, and 24 months post-transplant, and during kidney transplant rejection episodes.

[0161] Adult Kidney Transplant Validation Cohort. The cohort consisted of 163 heart transplant recipients transplanted at UCLA between 2006 and 2012. Biopsy samples were evaluated based on the 2013 Banff criteria (Haas, Am J Transplant, 2014). Serum was collected at the time of biopsy (+ / - 6 weeks). Post-transplant, patients were maintained on triple immunosuppression (tacrolimus, mycophenolate mofetil, and corticosteroids). Induction was primarily solumedrol and basiliximab or antithymocyte globulin. IVIG is used to augment immunosuppression at the time of transplant in patients with DSA identified within 1 year (present) of transplant. For patients with historical DSA, use of IVIG at the time of transplant is at the discretion of the treating nephrologist. The study was approved by the UCLA Institutional Review Board (#16-000786).

[0162] HLA typing and HLA DSA testing. All patients were HLA typed by LABType SSO DNA typing (One Lambda, Canoga Park, CA) according to the manufacturer's specifications. MICA antibodies and HLA class I and class II antibodies were identified using the Single Antigen Luminex assay (One Lambda, Canoga Park, CA).

[0163] Kidney transplant rejection. ACR and AMR were diagnosed by kidney biopsy according to the Banff criteria (Haas M et al, AJT 2014).

[0164] Protoarray assay for discovering non-HLA antigens. Serum antibodies were profiled by human protein microarray as previously described. Briefly, InVitrogen Human ProtoArray v5.0 containing over 9,000 proteins from a baculovirus-based expression system was blocked with blocking buffer for 1 h and incubated with 5 μL of serum diluted in PBST buffer (1:150 dilution) for 90 min. Slides were washed four times with 5 mL of fresh PBST buffer for 10 min each and probed with goat anti-human Alexa fluor 647 IgG secondary antibody (Molecular Probes, Eugene, OR) for 90 min. After two washes with PBST buffer, slides were dried and scanned using a GenePix4100A fluorescent microarray scanner and GenePixPro 6.0 software (Molecular devices, Sunnyvale, CA). Protein arrays included 12 rejection+ECXM+ sera, and six rejection-ECXM- sera to serve as technical controls. Array normalization and analysis were performed using Prospector 2.0 software (Life Technologies, Grand Island, NY) as previously described. Gene ontology analysis of the 366 antigens was evaluated with DAVID gene ontology analysis software (available on the world wide web at david.ncifcrf.gov) to identify enriched biological themes as previously described.

[0165] Development of a multiplex non-HLA antigen panel for detecting non-HLA antibodies. The non-HLA antigen targets newly described herein were discovered using the selected discovery cohort described above and in Table 1. Gene ontology analysis and tissue expression data were used to select the most biologically relevant non-HLA targets for inclusion in the non-HLA panel. The non-HLA multiplex bead panel of single antigen beads was manufactured by Immucor, Inc. (Peachtree Corners, GA), which provided the reagents for use in screening sera from selected cohorts of heart transplant recipients, adult and pediatric kidney transplant recipients. Briefly, 40 μL of antigen-coated beads were incubated with 10 μL of patient serum for 30 minutes. Unbound serum was removed by washing. The beads were stained with 50 μL of conjugate containing phycoerythrin (PE)-conjugated goat anti-human IgG diluted 1:10 in wash buffer and incubated in the dark for 30 minutes on a shaking platform. Results were examined by reading the median fluorescence intensity (MFI) of IgG binding on a Luminex 100 analyzer (Luminex, Austin, TX). To determine the positive threshold for the non-HLA antibody luminex assay, non-HLA antibodies were evaluated in serum isolated from 44 healthy individuals. The median MFI of antibody reactivity against 18 antigens significantly associated with cardiac allograft rejection was 510 MFI (range: 67–8367 MFI, SD=900). A positive threshold of MFI>1000 was chosen according to previous experience with Luminex-based solid-phase antibody detection methods.

[0166] Statistics. Odds ratios associating non-HLA antibodies with allograft rejection were determined to be significantly greater than 1 by a two-tailed Fisher's exact test (p<0.1; StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP). The p<0.1 threshold for significance was set according to standard practice for discovery analysis (Fan, L. et al., Am J Transplant 2011) and a default alpha (p-value) of 0.1 in STATA to prevent the exclusion of antibodies that may interact with each other. Confidence intervals (95%) were constructed assuming that standard error estimates are asymptotically independent and normal.

[0167] In the cluster analysis, the order of the non-HLA markers, the size of the circles, and the diagram of the inner boxes identifying the clusters correspond to the numerical values ​​of the pairwise correlation coefficients. The analysis was performed using hierarchical clustering with complete linkage and Euclidean distance in the R Corrplot application (Simko, TwaV2017).

[0168] Classification and Regression Tree (CART) analysis was performed by applying the rpart function of the R library (R software package version 3.4.0, available on the world wide web www.r-project.org / ). To avoid overfitting and to select a concise set of predictor variables, maxdepth (maximum depth of any node in the final tree, counting the root node as depth 0) was set to 3 and minsplit (minimum number of observations that must be present in a node to attempt a split) was set to 5. All other computer software parameters were set to default values.

[0169] Development of a non-HLA panel for cardiac transplantation: We hypothesized that antibodies targeting non-HLA antigens expressed by allograft endothelium would be identified by protein microarray analysis using sera from cardiac allograft recipients with biopsy-proven rejection. Sera from 12 cardiac transplant recipients (median 117 MCS; range: 62-529 MCS) without HLA or MICA DSA but with biopsy-proven rejection and positive reactivity on ECXM were collected as a discovery cohort. Discovery serum samples were collected a mean of 14 days (range: 0-76 days) from the EMB. EMBs were obtained a mean of 67 days after transplantation (range: 20-222 days). An additional 6 sera not associated with rejection and that were ECXM-negative and MICADSA-negative were used as controls. Eighteen sera (12 rejection+ / ECXM+ and 6 rejection- / ECXM- controls) were hybridized to a protein microarray containing 9,000 full-length human proteins. Bioinformatics analysis of the protein microarray identified 366 rejection-associated antigens with significantly increased fluorescence intensity (>1.5-fold; p<0.05), indicating positive antibody reactivity in sera isolated from rejection+ / ECXM+ patients compared to rejection- / ECXM- controls. A gene ontological analysis of the 366 non-HLA antigens was then performed to identify the most biologically relevant antigens with respect to known functional characteristics. From this analysis, 22 plasma membrane antigens and 10v known autoantigens were selected as they were likely target antigens expressed on the endothelial cell surface and could contribute to ECXM positivity. Nineteen of these could be expressed and conjugated to luminex polystyrene beads for further downstream high-throughput testing (Table 1). Other non-HLA antigens (9 heart, 30 kidney, 8 lung, 1 liver) (Table 4) were selected to generate a multiplex panel of 67 non-HLA antigens.

[0170] Development of a kidney transplant non-HLA panel: We tested sera from 16 kidney transplant recipients with no HLA or MICA DSA but with biopsy-proven rejection and positive ECXM. Three additional sera collected pre-transplant from 3 / 16 recipients were used as negative controls. Sera were tested in parallel, solvent-free and after adsorption to endothelial cells and elution. Testing of non-adsorbed and eluted sera on protein microarrays identified 1252 antigen targets (>1.5-fold increase, p<0.05) compared to pre-transplant sera. Prospector analysis identified antibodies present in both solvent-free and eluted rejection sera reacting with 386 distinct proteins. Of these, 251 were present in pre-transplant sera and therefore excluded from the analysis. This yielded 135 unique proteins as potential candidates for constructing a non-HLA panel. After gene ontology and frequency analysis, 12 / 135 antigen targets were selected based on their expression profiles and functional properties and added to the 67 antigens used in the cardiac multiplex bead array to generate the renal multiplex bead array.

[0171] Identification of non-HLA antibodies associated with allograft rejection. Using multiplex bead arrays, serum samples from 34 non-rejected and 33 rejected heart transplant samples from patients transplanted at UCLA between 2009 and 2016 were screened to determine whether they expressed non-HLA antibodies. A higher proportion of rejected heart transplant recipient samples were observed for 10 non-HLA antibodies (tubulin, LPHN1, thyroglobulin (TG), GAPDH, FN1, NPHS1, VIM, myosin, VCL, PECR) compared to serum samples from non-rejected patients (Table 2). LPHN1 and thyroglobulin (TG) are newly described herein. [Table 2]

[0172] Identification of non-HLA antibodies associated with renal allograft rejection. Multiplex bead arrays were used to screen serum samples isolated from pediatric (samples: no rejection, n=95 and with rejection, n=34) and adult (samples: no rejection, n=90, and with rejection, n=70) kidney transplant recipients. Patients in the rejection group experienced at least one histologically proven rejection episode during the study period. Pediatric and adult kidney sample cohorts were analyzed separately (Figure 1A and Figure 1B). From these independent analyses, 15 and 3 antibodies against non-HLA antigens were identified as significantly associated with rejection, respectively (p<0.01, and risk ratio>1) (Figure 1). In the pediatric cohort, antibodies against 15 non-HLA antigens (y-axis) were identified as significantly associated with time to first kidney rejection with odds ratio>1 (x-axis) in pediatric kidney transplant recipients (Figure 1A). Seven of these, DEXI, CSF2, IL-8, LGALS3, SNPRN, STAT6, and LGALS8, have been newly described as significantly associated with renal transplant rejection. Bars represent 95% confidence intervals (CI). Antibodies against three non-HLA antigens (tubulin, CXCL11, SHC3) were significantly associated with renal allograft rejection in adult renal transplant recipients (Figure 1B). SHC3 is newly identified herein as significantly associated with renal transplant rejection.

[0173] Table 3 shows the list of non-HLA antibodies identified as associated with rejection after adult heart transplantation (column 1), pediatric kidney transplantation (column 2), and adult kidney transplantation (column 3). These same targets are shown in Figures 1-3, 5, and 6. These indicators were predicted in the CART analysis, sorted independently, de novo, and clustered together in a correlation matrix. [Table 3]

[0174] A correlation matrix analysis of non-HLA antibodies associated with rejection after adult cardiac transplantation was performed (Figure 2A). Non-HLA antibodies associated with adult cardiac allograft rejection selectively clustered into four groups, one of which clustered independently (VCL). (Non-HLA antibodies associated with pediatric renal allograft rejection selectively clustered into six groups (Figure 2B), four of which clustered independently (PLAR1, CSF2, GSTT1, and LGALS8). Seven non-HLA antibodies were newly identified in this study to be associated with renal allograft rejection (CSF2, SNPRN, LGALS8, STAT6, IL-8, DEXI, and LGALS3). The non-HLA antibodies found to be significantly associated with transplant rejection in the pediatric renal cohort were applied to the adult renal transplant cohort to similarly evaluate the correlation (Figure 2C). Antigens independently correlated during rejection episodes are similar between pediatric and adult renal transplant recipients with rejection (adult renal: CSF2, GSTT1).

[0175] We next combined the pediatric and adult cohorts into one analysis to determine how antibodies specific for a panel of 18 non-HLA targets independently sort rejection (Figure 3, n=104). In rejection samples, antibodies cluster into 9 groups, with 4 of the 18 groups independently clustering (PLA2R, STAT6, GSTT1, and CSF2). Three of these four (STAT6, GSTT1, and CSF2) are newly identified here via proteomics-based discovery.

[0176] Classification and regression tree (CART) analysis was used to identify non-HLA antibodies that could distinguish rejection from non-rejection. Figure 4 shows the CART analysis of sera from adult heart transplant patients (n = 67 sera, Figure 4A) and pediatric kidney allograft patients (n = 129 sera, Figure 4B). CART analysis of sera isolated from adult heart allograft patients (n = 67 sera) with a 1,000 MFI cut point was used for the analysis. The root node LPHN1, which contains all 67 sera, of which 49% are rejection samples, is split into child nodes with MFI < 1000. As the algorithm proceeds to the terminal nodes, 65% of the rejection samples are correctly identified (far right, darker boxes). The scale bar indicates the association with rejection, with lighter boxes in the terminal nodes correlating with non-rejection. Eight non-HLA antibodies (SNPRN, KRT18, LGALS3, KRT8, SNRPB2, DEXI, PLA2R1, collagen II, and GSTT1) were informative predictors of renal allograft rejection. The root node SNPRN, which contains all 129 sera, of which 26% were rejection samples, is split into child nodes with MFI <1000. As the algorithm proceeds to the terminal nodes, 56% of non-rejection samples are correctly identified (far left, darker squares). The scale bar indicates the association with rejection, with lighter squares in the terminal nodes correlating with non-rejection. Importantly, PLA2R1 and GSTT1 were also found to cluster independently among rejection samples, and three of the eight (SNPRN, LGALS3, and DEXI) are newly identified here.

[0177] Described above are non-HLA antibodies significantly associated with renal and cardiac allograft rejection. Using protein microarrays populated with 9000 full-length proteins, followed by gene ontology analysis and development of high-throughput multiplex bead arrays, 10 non-HLA antibodies were associated with cardiac allograft rejection (Table 2) and 18 non-HLA antibodies were significantly associated with renal (pediatric and adult) graft rejection (Figure 1, Table 3). Two of these non-HLA antigens are newly described herein as associated with transplant rejection (LPHN1 and TG). Nine of these renal targets (DEXI, SHC3, SNPRN, LGALS3, CSF2, LGALS8, and STAT6) are newly described herein as associated with transplant rejection (Figure 1, Table 3). Non-HLA antibodies are shown in Table 3 and Figure 5. Some markers are found in multiple organs and are predicted by CART analysis. Other markers are non-HLA antibodies that sort independently. Further markers include non-HLA antibodies that sort together in a correlation matrix and are independent of other markers. Correlation matrix analysis identified a panel of non-HLA antibodies that can be used independently to predict rejection. [Table 4] TIFF0007675441000005.tif242162TIFF0007675441000006.tif242162TIFF0007675441000007.t if237159TIFF0007675441000008.tif241162TIFF0007675441000009.tif237162TIFF00076754410 00010.tif237162TIFF0007675441000011.tif237162TIFF0007675441000012.tif237162TIFF000 7675441000013.tif241162TIFF0007675441000014.tif242162TIFF0007675441000015.tif237162 TIFF0007675441000016.tif237162TIFF0007675441000017.tif242162TIFF0007675441000018.t if237162TIFF0007675441000019.tif237162TIFF0007675441000020.tif241162TIFF00076754410 00021.tif241162TIFF0007675441000022.tif242162TIFF0007675441000023.tif241162TIFF000 7675441000024.tif242162TIFF0007675441000025.tif237162TIFF0007675441000026.tif155162 Example 2. Identification of non-HLA antibodies associated with cardiac allograft rejection

[0178] Additional analysis of the above non-HLA antigens was performed as described by CL Butler et al., Am J Transplant. 2020;00:1-13. In a study of adult cardiac allograft recipients (samples: non-rejected n=477; rejected n=69), we identified 18 non-HLA antibodies associated with rejection (P<.1), including 4 newly identified non-HLA antigen targets (DEXI, EMCN, LPHN1, and SSB). CART analysis showed that 5 / 18 non-HLA antibodies differentiated between rejection and non-rejection. Antibodies against 4 / 18 non-HLA antigens synergized with HLA donor-specific antibodies to significantly increase the probability of rejection (P<.1). The non-HLA panel was validated using an independent adult heart transplant cohort (n=21 without rejection, n=42 with rejection, >1R) with an area under the curve of 0.87 (P<.05), sensitivity of 92.86%, and specificity of 66.67%. Results confirm that multiplex bead array assessment of non-HLA antibodies identifies heart transplant recipients at risk for rejection.

[0179] Table 5 lists targets identified through additional analysis and confirms the value of those targets previously identified in Table 4. Table 6 summarizes the various targets identified through both kidney and heart transplant studies. Figure 6 provides an expanded summary of what is shown in Figure 5, reflecting the results of additional analysis. [Table 5] Group 1 = Core + CART analysis prediction Group 2 = Independently sorted + newly described by UCLA Group 3 = clustered together in correlation matrix [Table 6] Italics indicate newly identified items. Bold indicates the core (whole organ). *Indicates prediction from CART analysis. **Independently sorted. ***Indicates clustered together in the correlation matrix. References Fan, L. et al. Neutralizing IL-17 prevents obliterative bronchiolitis in murine orthotopic lung transplantation. Am J Transplant 11, 911-22 (2011). Haas, M., et al. Banff meeting report writing (2014). "Banff 2013 meeting report: inclusion of c4d-negative antibody-mediated rejection and antibody-associated arterial lesions." Am J Transplant 14(2): 272-283. Huang da, W., BT Sherman and RA Lempicki (2009). "Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists." Nucleic Acids Res 37(1): 1-13. Michaels, PJ, et al. (2003). "Humoral rejection in cardiac transplantation: risk factors, hemodynamic consequences and relationship to transplant artery coronary disease." J Heart Lung Transplant 22(1): 58-69. Pearl, M. H., et al. (2016). "Bortezomib may stabilize pediatric renal transplant recipients with antibody-mediated rejection." Pediatr Nephrol 31(8): 1341-1348. Simko, T. w. a. V. (2017). "R package “corrplot”: Visualization of a Correlation Matrix (Version 0.84)." Smith, N. R. D. a. H. (1998). "Applied Regression Analysis." Stewart, S., et al. (2005). "Revision of the 1990 working formulation for the standardization of nomenclature in the diagnosis of heart rejection." J Heart Lung Transplant 24(11): 1710-1720. Zhang, Q., et al. (2005). "Development of posttransplant antidonor HLA antibodies is associated with acute humoral rejection and early graft dysfunction." Transplantation 79(5): 591-598. Zhang, Q. and E. F. Reed (2016). "The importance of non-HLA antibodies in transplantation." Nat Rev Nephrol 12(8): 484-495.

Claims

1. 1. A method for determining the presence of one or more antibodies in a biological sample from a subject, the method comprising: a) contacting the biological sample with a composition; b) detecting binding of a homogenous population of binding agents to said one or more antibodies in said biological sample; The composition comprises a collection of solid substrates coated with a homogenous population of the binding agent, the binding agent specifically binding to an antibody against dexamethasone-induced transcript (DEXI); The method, wherein the subject has undergone or will undergo a heart or kidney transplant.

2. 2. The method of claim 1, wherein the collection of solid phase substrates further comprises a homogenous population of one or more additional binding agents, each of the homogenous populations of additional binding agents specifically binding to an antibody against a single antigen, the antigen being selected from the group consisting of alpha enolase (ENO1), agrin (AGRN), endomucin (EMCN), Sjogren's syndrome antigen B (SSB), actin, fms-related tyrosine kinase 3 ligand (FLT3LG), protein kinase C eta (PRKCH), and interleukin 21 (IL-21).

3. The method of claim 1 or 2, wherein the solid phase substrate is porous or non-porous.

4. The method of claim 2 or 3, wherein the solid substrate comprises a particle, nanoparticle, bead, nanobead or microsphere.

5. The method of claim 4 , wherein the beads are polystyrene beads.

6. The method of any one of claims 1 to 5, wherein the collection of solid substrates comprises a microarray.

7. The method of any one of claims 1 to 6, wherein the solid phase substrate is fluorescently, magnetically or radioactively labeled.

8. The method of any one of claims 1 to 7, wherein the solid phase substrate is labeled with a small molecule.

9. The method of any one of claims 1 to 8, wherein the homogenous population of binding agents is conjugated to the surface of the solid substrate.

10. The method of any one of claims 1 to 8, wherein the homogenous population of binding agents is covalently conjugated to the surface of the solid substrate.

11. The method of claim 9 , wherein the homogenous population of binding agents is attached to the surface of the solid substrate by affinity.

12. The method of any one of claims 1 to 11, wherein the binding agent is a polypeptide.

13. The method of any one of claims 1 to 12, wherein the solid substrate is coated with a homogenous population of at least three different binding agents, each of the homogenous populations of different binding agents binding to a different antibody.

14. 14. The method of claim 13, wherein the solid substrate is coated with a homogenous population of multiple different binding agents that bind to the antibodies consisting of antibodies against tubulin, latrophilin 1 (LPHN1), small nuclear ribonucleoprotein polypeptide N (SNRPN), cytokeratin 18 (KRT18), cytokeratin 8 (KRT8), lectin galactoside-binding soluble 3 (LGALS3), small nuclear ribonucleoprotein polypeptide B (SNRPB2), DEXI, collagen II, phospholipase A2 receptor 1 (PLA2R1), glutathione S-transferase theta-1 (GSTT1), vinculin (VCL), colony stimulating factor 2 (CSF2), lectin galactoside-binding soluble 8 (LGALS8), and signal transducer and activator of transcription 6 (STAT6).

15. 14. The method of claim 13, wherein the solid substrate is coated with a homogenous population of multiple different binding agents that bind to the antibodies consisting of antibodies against DEXI, LGALS3, SNPRN, CSF2, interleukin 8 (IL-8), STAT6, LGALS8, KRT18, KRT8, GSTT1, prelamin-A / C (LMNA), collagen II, ATP synthase H+ transporting mitochondrial F1 complex beta polypeptide (ATP5B), SNRPB2, and PLA2R1.

16. 14. The method of claim 13, wherein the solid substrate is coated with a homogenous population of multiple different binding agents that bind to the antibody consisting of antibodies against DEXI, EMCN, SNRPN, LPHN1 and SSB.

17. 14. The method of claim 13, wherein the solid substrate is coated with a homogenous population of multiple different binding agents that bind to the antibodies consisting of antibodies against tubulin, LPHN1, SNRPN, KRT18, KRT8, LGALS3, SNRPB2, DEXI, collagen II, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ENO1, AGRN, EMCN, SSB, PLA2R1, GSTT1, VCL, CSF2, LGALS8, STAT6, IL-8, and SHC adaptor protein 3 (SHC3).

18. 2. The method of claim 1, wherein the collection of solid substrates further comprises a homogenous population of one or more additional binding agents, each of the homogenous populations of additional binding agents specifically binding to an antibody against a single antigen selected from the group consisting of LPHN1, thyroglobulin (TG), CSF2, IL-8, LGALS3, SNPRN, STAT6, SHC3, and LGALS8.

19. 3. The method of claim 2, wherein the single antigen is selected from the group consisting of EMCN and SSB.

20. The method of any one of claims 1 to 19, wherein at least one solid phase substrate is detectably distinguishable from at least one other solid phase substrate.

21. The method of claim 1 , wherein the subject is a mammal.

22. The method of claim 1 , wherein the subject is a human.

23. 2. The method of claim 1, wherein the heart transplant is a heart allograft transplant or a kidney allograft transplant.

24. 24. The method of any one of claims 1 to 23, wherein the biological sample is blood, plasma, serum, urine, spinal fluid, lymphatic fluid, synovial fluid, cerebrospinal fluid, tears, saliva, milk, mucosal secretions, exudates, sweat, biopsy aspirate, peritoneal fluid or a body fluid extract.

25. The method of any one of claims 1 to 24, wherein said detecting is by measuring fluorescence intensity or by immunological analysis.

26. 1. A method for providing an indicator for detecting transplant rejection in a subject who has received a heart or kidney transplant, the method comprising: a) contacting a biological sample from said subject with a composition comprising a collection of solid substrates coated with a homogenous population of binding agents that specifically bind to one or more antibodies against dexamethasone-induced transcript (DEXI); b) measuring the level of said one or more antibodies in said biological sample; An increase in the level of the one or more antibodies measured in step b) compared to a reference level is an indication that the subject has developed transplant rejection in response to the heart transplant or the kidney transplant.

27. 1. A method for providing an index for predicting the likelihood of transplant rejection in a subject in need of a heart or kidney transplant, comprising: a) contacting a biological sample from said subject with a composition comprising a collection of solid substrates coated with a homogenous population of binding agents that specifically bind to one or more antibodies against dexamethasone-induced transcript (DEXI); b) measuring the level of said one or more antibodies in said biological sample; wherein an increase in the level of the one or more antibodies measured in step b) compared to a reference level is an indication that the subject is more likely to develop transplant rejection after heart or kidney transplantation.

28. 1. A composition comprising a collection of solid substrates coated with a homogenous population of binding agents that specifically bind to one or more antibodies against dexamethasone-induced transcript (DEXI) for use in a method of treating a subject in need of treatment for transplant rejection after receiving a heart or kidney transplant, the method comprising: a) contacting a biological sample from said subject with said composition; b) determining the level of said one or more antibodies in said biological sample; and and c) administering to the subject a treatment for transplant rejection if the level of the one or more antibodies measured in step b) is increased compared to the reference level of the one or more antibodies.

29. a) a composition comprising a collection of solid substrates coated with a homogenous population of binding agents that specifically bind to one or more antibodies against dexamethasone-induced transcript (DEXI); b) a reagent for detecting binding of said homogenous population of one or more binding agents to said antibody.

30. 30. The kit of claim 29, further comprising one or more reference samples.

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