Compositions and methods for detection of transplant rejection status and treatment

Abstract

The present disclosure relates to compositions and methods for detecting rejection status of a transplant in a subject comprising detecting a B cell expression pattern in the subject and comparing the detected expression pattern to a control expression pattern, wherein a statistically significant difference in the two patterns indicates the transplant rejection. Also disclosed herein, is a method for treating a transplant rejection and a kit for detection of a transplant rejection status in a subject.

Description

COMPOSITIONS AND METHODS FOR DETECTION OF TRANSPLANT REJECTION STATUS AND TREATMENTCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to, and the benefit of, U.S. Provisional Patent Application No. 63 / 626,809, filed January 30, 2024, which is incorporated by reference herein in its entirety.REFERENCE TO SEQUENCE LISTING

[0002] The sequence listing submitted on January 30, 2025 as an .XML file entitled “10504- 100W01_ST26.xml” created on January 30, 2025 and having a file size of 38,824 bytes is hereby incorporated by reference pursuant to 37 C.F.R. § 1.52(e)(5).FIELD

[0003] Hie present disclosure relates to compositions and methods for the detection and treatment of transplant rejection.BACKGROUND OF THE INVENTION

[0004] Organ transplantation requires life-long immunosuppression to prevent acute rejection (AR). Despite improvements in immunosuppressive drugs, acute rejection occurs for example, in approximately~35% of all kidney transplant patients within the first year. Kidney biopsies are performed when there is clinical indication of decreased renal function, usually manifest by an increase in serum creatinine levels. Such biopsies are termed clinically indicated or "for cause" biopsies. However, amongst patients with an increase in creatinine, only 50-60% will prove to have rejection on biopsy. Thus, many patients are subjected to biopsies who would not need them if there was an accurate biomarker. Furthermore, it is well documented that patients can have AR with no clinical signs (termed "subclinical rejection"). This is only detected by performing surveillance biopsies.

[0005] Because of the risk of missing such subclinical AR episodes, at some institutions, surveillance biopsies are performed during the first-year post-transplant. It has been shown that approximately 50% of all AR in the first year is subclinical. Despite treatment, both clinical and subclinical AR are associated with decreased long-term allograft survival. Therefore, despite relatively low incidence of AR in patients with stable kidney function (approximately 15%), surveillance biopsies are performed so that subclinical rejection can be detected and treated. Moreover, recent data indicate that despite treatment, approximately 30% of AR either never reallyresolves or recurs after treatment. These patients with recurrent or persistent inflammation are at increased risk of allograft loss.

[0006] These data suggest that many patients should undergo post-treatment biopsies to prove that AR has resolved - which is not currently standard of practice if the renal function was never elevated in the first place (half of all rejections) or when renal function improves after treatment. Biopsies are invasive and carry some degree of risk including bleeding, blood transfusion and even allograft loss. They are also expensive, and inconvenient requiring patients to travel to the hospital and take a day off from work. For this reason, only 20% of transplant centers in the US routinely perform surveillance biopsies.

[0007] A number of biomarkers have been developed mostly based on transcript expression of various genes in peripheral blood or allograft-derived cell free DNA. Unfortunately, almost all have been tested in select groups of patients where confounding diagnoses like BK infection, that also lead to renal inflammation, have been excluded. Some biomarker studies have only examined patients retrospectively with clinical AR whereas, few have examined patients with subclinical rejection. In these select patient groups, the commercially available biomarkers uniformly have reasonably high negative predictive values of 80-86% with one study reporting 98%. This is expected given the relatively low prevalence of AR on biopsy. However, accuracy is relatively poor for the most common type of mild AR (Banff 1A) and improves for more severe rejection, which is unlikely to be clinically silent. None have good positive predictive values - especially for surveillance biopsies (13-48%). Thus, currently available biomarkers are not useful in identifying patients who have mild or subclinical AR.

[0008] Therefore, what is needed is one or more biomarkers of transplant rejection that can be used in methods for detection and / or treatment of such rejection, including mild and subclinical AR.SUMMARY

[0009] Disclosed herein are methods and kits for detection and treatment of transplant rejection in a subject in need thereof.

[0010] Accordingly, in one aspect disclosed herein, is a method of detecting rejection status of a transplant in a subject comprising obtaining a sample comprising B cells from the subject, detecting an expression pattern of the B cells, comparing the detected expression pattern to a control expression pattern; wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern and / or wherein a lack of transplant rejection is indicated by a statistically significant difference inthe detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern. In some embodiments, the B cells are identified by detecting an expression of a B cell identification marker. In some embodiments, the B cell identification marker is selected from a group consisting of CD19, CD20, CD79alpha, CD79beta, FcRL5, FcRL4, CD138, and B cell receptor or a component of the B cell receptor complex. In some embodiments, the B cell identification marker is CD 19.

[0011] In some embodiments, the expression pattern comprises expression data for two or more of thirteen polypeptides, or polynucleotides encoding the two or more of thirteen polypeptides, and wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the detected expression pattern consists of expression data for a B cell identification marker, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the detected expression pattern comprises expression data for two or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, and wherein the twenty -one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the detected expression pattern consists of expression data for a B cell identification marker, TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

[0012] In some embodiments, the detected expression pattern comprises expression data for CD19, CD38, and CD24. In some embodiments, the detected expression pattern comprises expression data for CD19, CD27, and CD21. In some embodiments, the detected expression pattern comprises expression data for CD19, CD38, and CD73. In some embodiments, the detected expression pattern comprises expression data for CD19, CD38, and CD23. In some embodiments, the detected expression pattern comprises expression data for CD19, CD24, and CD73. In some embodiments, the detected expression pattern comprises expression data for CD19, CD24, and CD21. In some embodiments, the detected expression pattern comprises expression data for CD19, CD25, and IgD. In some embodiments, the detected expression pattern comprises expression data for CD19, CD73, and IgM. In some embodiments, the detected expression pattern comprises expression data for CD 19, CD73, and IgD. In some embodiments, the detected expression pattern comprises expression data for CD19, CD39, and CD25. In some embodiments, the detected expression pattern comprises expression data for CD 19, CD39, and CD73. In some embodiments, the detected expression pattern comprises expression data for CD19, CD73, and LAG3. In some embodiments,the detected expression pattern comprises expression data for CD19, CD73, and CD10. In some embodiments, the detected expression pattern comprises expression data for CD19, CD23, and CD73. In some embodiments, the detected expression pattern comprises expression data for CD19, CD21, and CD9.

[0013] In some embodiments, the detection expression pattern comprises CD19bnght, CD39dim, CD80dim, CD23dim, CD73neg, IgMdim, CD21neg, CD27neg, CD24pos, IgDdimand CD38neg. In some embodiments, the detection expression pattern comprises CD19intennediate, CD39bngbt, CD80neg, HLA-IIbright, CD23bright, CD73bright, IgMdim, CD2intermedia,e, CD27neg, CD24dim, IgDintermedia,e, CD38dim, and CD9dim.

[0014] In some embodiments, the expression pattern is a surface expression pattern. In some embodiments, detecting the surface expression pattern comprises flow cytometry. In some embodiments, the detected expression pattern and the control expression pattern are obtained using a method comprising t-distributed stochastic neighbor embedding (t-SNE). In some embodiments, the statistically significant difference in the detected expression pattern and the control expression pattern is at least 0.05%. In some embodiments, the statistically significant difference in the detected expression pattern and the control expression pattern is at least 0.1%.

[0015] In some embodiments, the transplant is a kidney, a liver, a lung, a heart, a pancreas, an intestine, multi-visceral, a uterus, a vascularized composite allograft, a pancreatic islet, a stem cell, or a neuronal cell. In some embodiments, the transplant is an organ. In some embodiments, the organ is a kidney. In some embodiments, the transplant rejection is indicated. In some embodiments, the method further comprises obtaining a biopsy of the transplant. In some embodiments, the transplant rejection is an acute transplant rejection. In some embodiments, the transplant rejection is a subclinical transplant rejection. In some embodiments, the transplant rejection is a clinical transplant rejection. In some embodiments, the subject is a human. In some embodiments, the sample is a blood sample.

[0016] In some embodiments, the method further comprising administering to the subject a treatment for the transplant rejection. In some embodiments, the treatment is an immunosuppressive therapy.

[0017] In one aspect, disclosed herein is a kit for detection of rejection status of a transplant in a subject, wherein the kit is used, to obtain a sample comprising B cells from the subject; and to detect an expression pattern of the B cells; and comparing the detected expression pattern to a control expression pattern; wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejectionexpression pattern and / or wherein a lack of transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern.

[0018] In some embodiments, the B cells are identified by detecting expression of a B cell identification marker. In some embodiments, the B cell identification marker is selected from a group consisting of CD19, CD20, CD79alpha, CD79beta, FcRL5, FcRL4, CD138, and B cell receptor or a fragment thereof. In some embodiments, the B cell identification marker is CD 19. In some embodiments, the detected expression pattern comprises expression data for two or more of thirteen polypeptides, or polynucleotides encoding the two or more of thirteen polypeptides, and wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the detected expression pattern comprises expression data for two or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, and wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the kit comprises an antibody or ligand specific for a B cell identification marker, TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and / or CD80. In some embodiments, the kit comprises an antibody or ligand specific for B cell identification marker, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10 and / or LAG3.BRIEF DESCRIPTION OF FIGURES

[0019] Figure 1 shows representative flow cytometry plots of human peripheral blood mononuclear cells (PBMC), identifying B cells for subsequent t-SNE analysis. In this figure, CD19 is used as a “pan-B cell” marker to identify all B cells. CD3 is a T cells marker used to exclude T cells helping to distinguish B cells for the analysis.

[0020] Figure 2 shows concatenated t-distributed stochastic neighbor embedding (t-SNE) analysis of B cells data from 28 renal transplant patients undergoing surveillance biopsies based on simultaneous analysis of B cells using a pan-B cell marker such as CD 19, plus the following 21 additional markers expressed on the surface of subpopulations of B cells: TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In the t-SNE plot, individual B cells fall into regions based on similarities in their relative distribution of these markers. The subpopulation regions labeled G1-G7 were determined empirically. The Left panel shows the t-SNE analysis for all patients. The centerpanel shows the t-SNE analysis from the 14 patients whose biopsies showed no rejection (NR). The Right panel shows the t-SNE analysis from the 14 patients whose biopsies showed revealed subclinical acute rejection (AR).

[0021] Figure 3A is a bar graph showing the percentage of B cells in the G7 region identified in Figure 2, divided into patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in G7 between NR and AR patients is highly significant. Figure 3B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in G7 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.89 with a confidence interval (CI) of 0.75-1.0. From this curve an optimal cut-off for differentiating between AR and NR can be set at 15.5% (shown in Fig 3A). At this cut-off, the percent of cells in G7 in any given patient predicts acute rejection with a sensitivity (Sens) of 93%, a specificity (Spec) of 86%, and with a positive predictive value (PPV) of 87% and a negative predictive value (NPV) of 92%.

[0022] Figure 4A is a bar graph showing the percentage of B cells in the G5 region identified in Figure 2, in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / triangles. The differences in percent of cells in G5 between NR and AR patients is highly significant. Figure 4B shows a ROC curve for the percentage of cells in G5 predicting the lack of acute rejection on biopsy. The AUC for G5 for predicting no rejection is 0.85 with a Sensitivity of 86%, Specificity of 79%, PPV 80% and NPV 85% at an optimized cut-off of 0.7% of B cells in G5 (Fig 3A).

[0023] Figure 5 shows relative expressions of various surface markers in each of the B cell subpopulations (G1-G7) identified in Figure 2, left panel (total patient population), as visualized on a Heatmap map.

[0024] Figure 6 shows t-SNE analysis of CD19 plus the 21 B cell surface markers for 28 patients as discussed in relation to Figure 2 but having different subpopulation regions assigned than in Figure 2. The NR is no rejection. AR is subclinical acute rejection. The percentages refer to the average percent of B cells in each region in AR and NR patients.

[0025] Figure 7 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD19 plus one additional marker from the panel of 21 B cell surface markers (CD19 + CD24). NR is no rejection. AR is subclinical acute rejection.

[0026] Figure 8(A-O) shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD19 + two B cell surface markers CD19 + CD38 + CD24 as shown in Figure 8A, CD19 + CD27 + CD21 as shown in Figure 8B, CD19 + CD38 + CD73 as shown in Figure 8C, CD19 + CD38 + CD23 as shown in Figure 8D, CD 19 + CD24 + CD73 as shown in Figure 8E, CD 19 + CD24 + CD21 as shown in Figure 8F, CD19 + CD25 + IgD as shown in Figure 8G, CD19 + CD73 + IgM as shown in Figure 8H, CD19 + CD73 + IgD as shown in Figure 81, CD19 + CD39 + CD25 as shown in Figure 8J, CD19 + CD39 + CD73 as shown in Figure 8K, CD19 + CD73 + LAG3 as shown in Figure 8L, CD19 + CD73 + CD10 as shown in Figure 8M, CD19 + CD23 + CD73 as shown in Figure 8N and CD19 + CD21 + CD9 as shown in Figure 80. NR is no rejection. AR is subclinical acute rejection.

[0027] Figure 9 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + three B cell surface markers (CD19 + CD24 + CD38 + CD27). NR is no rejection. AR is subclinical acute rejection.

[0028] Figure 10 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + four B cell surface markers (CD19 + CD24 + CD38 +CD27 + CD21). NR is no rejection. AR is subclinical acute rejection.

[0029] Figure 11 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + five B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39). NR is no rejection. AR is subclinical acute rejection.

[0030] Figure 12 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + six B cell surface markers (CD19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23). NR is no rejection. AR is subclinical acute rejection.

[0031] Figure 13 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + seven B cell surface markers (CD19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73). NR is no rejection. AR is subclinical acute rejection.

[0032] Figure 14 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + eight B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25). NR is no rejection. AR is subclinical acute rejection.

[0033] Figure 15 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + nine B cell surface markers (CD19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9). NR is no rejection. AR is subclinical acute rejection.

[0034] Figure 16 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + ten B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9 + IgD). NR is no rejection. AR is subclinical acute rejection.

[0035] Figure 17 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + eleven B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9 + IgD + IgM). NR is no rejection. AR is subclinical acute rejection.

[0036] Figure 18 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + twelve B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9 + IgD + IgM + CD10). NR is no rejection. AR is subclinical acute rejection.

[0037] Figure 19 shows t-SNE analysis of B cell data from the 28 renal transplant patients discussed in relation to Figure 2 based on simultaneous analysis of CD 19 + thirteen B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9 + IgD + IgM + CD10 + EAG3). There are five subpopulation groups P1-P5. NR is no rejection. AR is subclinical acute rejection.

[0038] Figure 20A is a bar graph showing the percentage of B cells in the Pl region of Figure 19 in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in Pl between NR and AR patients is highly significant. Figure 20B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in Pl predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.89 with a confidence interval (CI) of 0.76-1.0. From this curve an optimal cut-off for differentiating between AR and NR can be set at 2.01% (shown in Fig 20A). At this cut-off, the percent of cells in Pl in any given patient predicts acute rejection with a sensitivity (Sens) of 86%, a specificity (Spec) of 86%, and with a positive predictive value (PPV) of 86% and a negative predictive value (NPV) of 86%.

[0039] Figure 21 A is a bar graph showing the percentage of B cells in the P3 region of Figure 19 in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in P3 between NR and AR patients is highly significant. Figure 21B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in P3 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.94 with a confidence interval (CI) of 0.87-1.0. From this curve an optimal cut-off for differentiating between AR and NR can be set at 31.34% (shown in Fig 21 A). At this cut-off, the percent of cells in Pl in any given patient predicts acute rejection with a sensitivity (Sens) of 86%, a specificity (Spec) of 93%, and with a positive predictive value (PPV) of 92% and a negative predictive value (NPV) of 87%.

[0040] Figure 22A is a bar graph showing the percentage of B cells in the P4 region of Figure 19 in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in P4 between NR and AR patients is highly significant. Figure 22B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in P4 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.88 with a confidence interval (CI) of 0.74-1.0. From this curve an optimal cut-off for differentiating between AR and NR can be set at 17.74% (shown in Fig 22A). At this cut-off, the percent of cells in P4 in any given patient predicts acute rejection with a sensitivity (Sens) of 93%, a specificity (Spec) of 86%, and with a positive predictive value (PPV) of 87% and a negative predictive value (NPV) of 92%.

[0041] Figure 23 shows relative expressions of various surface markers in each of the B cell subpopulations (P1-P5) shown in Figure 19 as visualized on a Heatmap map.

[0042] Figure 24(A-B) shows individual t-SNE analyses of B cell data from each of the individual 28 renal transplant patients discussed in relation to Figure 19 based on simultaneous analysis of fourteen B cell surface markers (CD 19 + CD24 + CD38 +CD27 + CD21 + CD39 + CD23 + CD73 + CD25 + CD9 + IgD + IgM + CD10 + LAG3). (A) 14 patients with no rejection (NR). (B) 14 patients with acute rejection (AR).

[0043] Figure 25A is a bar graph showing the percentage of B cells in the P2 region of Figure 19 in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cellsin P2 between NR and AR patients is highly significant. Figure 25B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in P2 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.82 with a confidence interval (CI) of 0.65-0.98. From this curve an optimal cut-off for differentiating between AR and NR can be set at 2.59% (shown in Fig 25A). At this cut-off, the percent of cells in P2 in any given patient predicts acute rejection with a sensitivity (Sens) of 71%, a specificity (Spec) of 86%, and with a positive predictive value (PPV) of 83% and a negative predictive value (NPV) of 75%.

[0044] Figure 26A is a bar graph showing the percentage of B cells in the P5 region of Figure 19 in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in P5 between NR and AR patients is highly significant. Figure 26B shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in P5 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.90 with a confidence interval (CI) of 0.78-1.0. From this curve an optimal cut-off for differentiating between AR and NR can be set at 12.6% (shown in Fig 26A). At this cut-off, the percent of cells in P5 in any given patient predicts acute rejection with a sensitivity (Sens) of 79%, a specificity (Spec) of 86%, and with a positive predictive value (PPV) of 85% and a negative predictive value (NPV) of 80%.

[0045] Figure 27A shows t-SNE analysis of B cell data from the 28 renal transplant patients based on simultaneous analysis of CD19 + two B cell surface markers (CD19 + CD24 + CD27). There is one subpopulation group KI. NR is no rejection. AR is subclinical acute rejection. Figure 27B is a bar graph showing the percentage of B cells in the KI region of Figure 27 A in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in KI between NR and AR patients is highly significant. Figure 27C shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in KI predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.73 with a confidence interval (CI) of 0.54- 0.92. From this curve an optimal cut-off for differentiating between AR and NR can be set at 8.54% (shown in Fig 27B). At this cut-off, the percent of cells in KI in any given patient predicts acuterejection with a sensitivity (Sens) of 71%, a specificity (Spec) of 64%, and with a positive predictive value (PPV) of 57% and a negative predictive value (NPV) of 71%.

[0046] Figure 28A shows t-SNE analysis of B cell data from the 28 renal transplant patients based on simultaneous analysis of CD19 + two B cell surface markers (CD19 + CD24 + CD73). There are two subpopulation groups A1-A2. NR is no rejection. AR is subclinical acute rejection. Figure 28B is a bar graph showing the percentage of B cells in the A2 region of Figure 28A in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in A2 between NR and AR patients is significant (at a cut-off of p <0.1 for statistical significance). Figure 28C shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in A2 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.70 with a confidence interval (CI) of 0.51-0.9. From this curve an optimal cut-off for differentiating between AR and NR can be set at 20.84% (shown in Fig 28B). At this cut-off, the percent of cells in A2 in any given patient predicts acute rejection with a sensitivity (Sens) of 86%, a specificity (Spec) of 57%, and with a positive predictive value (PPV) of 73% and a negative predictive value (NPV) of 65%.

[0047] Figure 29A shows t-SNE analysis of B cell data from the 28 renal transplant patients based on simultaneous analysis of CD19 + two B cell surface markers (CD19 + CD21 + CD39). There are two subpopulation groups H1-H2. NR is no rejection. AR is subclinical acute rejection. Figure 29B is a bar graph showing the percentage of B cells in the H2 region of Figure 29A in patients who have no rejection (NR) vs. those with acute rejection (AR). Each individual patient is represented by small black square / rhombus. The differences in percent of cells in H2 between NR and AR patients is significant (at a cut-off of p <0. 1 for statistical significance). Figure 29C shows a Receiver Operator Characteristic (ROC) curve plotting sensitivity vs. specificity for the percentage of cells in H2 predicting the presence of acute rejection on biopsy. The area under the curve (AUC) is a measure of predictive value of the marker (with 1.0 being 100% sensitive and specific). Here the AUC is 0.68 with a confidence interval (CI) of 0.48-0.89. From this curve an optimal cut-off for differentiating between AR and NR can be set at 6.5% (shown in Fig 29B). At this cut-off, the percent of cells in H2 in any given patient predicts acute rejection with a sensitivity (Sens) of 71%, a specificity (Spec) of 71%, and with a positive predictive value (PPV) of 71% and a negative predictive value (NPV) of 71%.DETAILED DESCRIPTION

[0048] Provided herein is a method of detecting rejection status of a transplant in a subject that includes obtaining a sample comprising B cells from the subject, detecting an expression pattern of the B cells, and comparing the detected expression pattern to a control no rejection expression pattern and / or a control rejection expression pattern, wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern. Alternatively, lack of rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern. Also provided are compositions such as kits for detecting rejection status of a transplant in a subject.

[0049] DEFINITIONS

[0050] Terms used throughout this application are to be construed with ordinary and typical meaning to those of ordinary skill in the art. However, Applicant desires that the following terms be given the particular definition as provided below.

[0051] As used in the specification and claims, the singular form "a," "an," and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a cell" includes a plurality of cells, including mixtures thereof.

[0052] The terms "about" and "approximately" are defined as being “close to” as understood by one of ordinary skill in the art. In one non-limiting embodiment the terms are defined to be within 10%. In another non-limiting embodiment, the terms are defined to be within 5%. In still another non- limiting embodiment, the terms are defined to be within 1%.

[0053] The term “administering” refers to an administration that is oral, topical, intravenous, subcutaneous, transcutaneous, transdermal, intramuscular, intra-joint, parenteral, intra-arteriole, intradermal, intraventricular, intracranial, intraperitoneal, intralesional, intranasal, rectal, vaginal, by inhalation or via an implanted reservoir. The term “parenteral” includes subcutaneous, intravenous, intramuscular, intra- articular, intra- synovial, intrasternal, intrathecal, intrahepatic, intralesional, and intracranial injections or infusion techniques.

[0054] The term "antibody" is used in the broadest sense, and specifically covers monoclonal antibodies (including full length monoclonal antibodies), polyclonal antibodies, and multispecific antibodies (e.g., bispecific antibodies). Antibodies (Abs) and immunoglobulins (Igs) are glycoproteins having the same structural characteristics. While antibodies exhibit binding specificity to a specific target, immunoglobulins include both antibodies and other antibody-like moleculeswhich lack target specificity. Native antibodies and immunoglobulins are usually heterotetrameric glycoproteins of about 150,000 Daltons, composed of two identical light (L) chains and two identical heavy (H) chains. Each heavy chain has at one end a variable domain (VH) followed by a number of constant domains. Each light chain has a variable domain at one end (VL) and a constant domain at its other end. As used herein, the term “antibody” or “antibodies” can also refer to a human antibody and / or a humanized antibody. Many non-human antibodies (e.g., those derived from mice, rats, or rabbits) are naturally antigenic in humans, and thus can give rise to undesirable immune responses when administered to humans. Therefore, the use of human or humanized antibodies in the methods serves to lessen the chance that an antibody administered to a human will evoke an undesirable immune response. Antibodies may also be derived from mammals in the Camelidae family, such as camels, llamas, and alpacas. They are also known as single-domain antibodies (sdAbs) or nanobodies. Camelid antibodies are made up of two identical heavy chains, and lack light chains and the CHI region and are smaller than other antibodies.

[0055] The term "antibody fragment" refers to a portion of a full-length antibody, that includes the target, or antigen, binding or variable region. Examples of antibody fragments include Fab, Fab', F(ab')2 and Fv fragments. The “antibody fragment” is a compound having qualitative biological activity in common with a full-length antibody. As used herein, "antibody fragment" with respect to antibodies, includes Fv, F(ab) and F(ab’)2 fragments. An "Fv" fragment is the minimum antibody fragment which contains a complete target recognition and binding site. This region consists of a dimer of one heavy and one light chain variable domain in a tight, non-covalent association (VH-VL dimer). It is in this configuration that the three CDRs of each variable domain interact to define a target binding site on the surface of the VH-VL dimer. Collectively, the six CDRs confer target binding specificity to the antibody. However, even a single variable domain (or half of an Fv comprising only three CDRs specific for a target) has the ability to recognize and bind target, although at a lower affinity than the entire binding site. "Single-chain Fv" or "sFv" antibody fragments comprise the VH and VL domains of an antibody, wherein these domains are present in a single polypeptide chain. Generally, the Fv polypeptide further comprises a polypeptide linker between the VH and VL domains which enables the sFv to form the desired structure for target binding. The Fab fragment contains the constant domain of the light chain and the first constant domain (CHI) of the heavy chain. Fab' fragments differ from Fab fragments by the addition of a few residues at the carboxyl terminus of the heavy chain CHI domain including one or more cysteines from the antibody hinge region. F(ab') fragments are produced by cleavage of the disulfide bond at the hinge cysteines of the F(ab')2 pepsin digestion product. Additional chemical couplings of antibody fragments are known to those of ordinary skill in the art.

[0056] The term “monoclonal antibody” as used herein refers to an antibody obtained from a substantially homogeneous population of antibodies, i.e., the individual antibodies within the population are identical except for possible naturally occurring mutations that may be present in a small subset of the antibody molecules.

[0057] The term “B cell” refers to what is known in the art as a “B lymphocyte” and is a type of white blood cell. In some embodiments, the B cell is a plasma cell. In some embodiments, the B cell is a memory B cell. In some embodiments, the B cell is a regulatory B cell. In some embodiments, the B cell is identified as a B cell based on its expression of CD19. In other embodiments the B cell is identified as a B cell based on other markers including, but not limited to: CD20; CD79alpha, CD79beta, the B cell receptor, FcRL5, FcRL4, CD138, signaling molecules specific for B cells amongst lymphocytes (e.g. Syk), or other marker molecules, transcription factors, or expression patterns that identify B cells within the sample being tested. It would also be possible to identify B cells by excluding other cells types like T cells, macrophages / monocytes, neutrophils, and / or NK cells. It should be understood that the B cell can be identified prior to, simultaneously with, or after detecting the B cell expression pattern. In some embodiments, the B cell is identified as a B cell prior to detecting the B cell expression pattern

[0058] As used herein, the term "comprising" is intended to mean that the compositions and methods include the recited elements, but not excluding others. "Consisting essentially of" when used to define compositions and methods, shall mean excluding other elements of any essential significance to the combination. Thus, a composition consisting essentially of the elements as defined herein would not exclude trace contaminants from the isolation and purification method and pharmaceutically acceptable carriers, such as phosphate buffered saline, preservatives, and the like.

[0059] As used herein, the term “expression” refers to either or both “gene expression” and “protein expression.” “Gene expression” refers to the process by which polynucleotides are transcribed into mRNA and “protein expression” refers to the process by which mRNA is translated into peptides, polypeptides, or proteins. If the polynucleotide is derived from genomic DNA, expression may include splicing of the mRNA in a eukaryotic cell. “Gene overexpression” refers to the overproduction of the mRNA transcribed from the gene, at a level that is at least about 2.5 times higher, at least about 5 times higher, or at least about 10 times higher than the expression level detected in a control sample. “Protein overexpression” includes the overproduction of the protein product encoded by a gene at a level that is at least about 1.5 times higher, at lease about 2.5 times higher, at least about 5 times higher, or at least about 10 times higher than the expression level detected in a control sample.

[0060] As used herein “surface expression” refers to the process by which polypeptides are translocated to the surface of a cell such that at least a portion of the polypeptide is located at the exterior of the cell surface. “Surface overexpression” includes an increase in the amount of a particular polypeptide at the exterior surface of a cell, at a level that is at least 5% higher, 10% higher, 20% higher, 30% higher, 40% higher, 50% higher, 60% higher, 70% higher, 80% higher, 90% higher, 100% higher, 1.5 times higher, 2.0 times higher, 2.5 times higher, 5 times higher, or 10 times higher than the surface expression level detected in a control sample.

[0061] The term “expression pattern” refers to the levels of expression of more than one, or a group, of polypeptides or polynucleotides. A “detected expression pattern” is the expression pattern of the subject’s B cells. A “control expression pattern” is either a B cell expression pattern associated with transplant rejection (“control rejection expression pattern”) or a B cell expression pattern associated with no rejection (“control no rejection expression pattern”). In some embodiments, the association with rejection and / or no-rejection is determined through analysis of B cell expression data from an appropriate cohort (a cohort presenting with rejection or a cohort presenting with no rejection) using t-distributed stochastic neighbor embedding (t-SNE). In some embodiments, the t-SNE control expression pattern data is represented in a two- or three- dimensional plot. In some embodiments, the compared expression patterns are limited to correlating subpopulation groups identified on t-SNE plots. In some embodiments, the control rejection expression pattern predicts acute rejection vs. no rejection with a sensitivity (Sens) of at least 71%, a specificity (Spec) of at least 79%, and with a positive predictive value (PPV) of at least 80% and / or a negative predictive value (NPV) of at least 75%. In some embodiments, the control no rejection expression pattern predicts acute rejection vs. no rejection with a sensitivity (Sens) of at least 93%, a specificity (Spec) of at least 86%, and with a positive predictive value (PPV) of at least 92% and / or a negative predictive value (NPV) of at least 92%.

[0062] A “protein”, "polypeptide", or “peptide” each refer to a polymer of amino acids and does not imply a specific length of a polymer of amino acids. Thus, for example, the terms peptide, oligopeptide, protein, antibody, and enzyme are included within the definition of polypeptide. This term also includes polypeptides with post-expression modification, such as glycosylation (e.g., the addition of a saccharide), acetylation, phosphorylation, and the like. Reference also is made herein to peptides, polypeptides, proteins, and compositions comprising peptides, polypeptides, and proteins. As used herein, a polypeptide and / or protein is defined as a polymer of amino acids, typically of length >100 amino acids (Garrett & Grisham, Biochemistry, 2nd edition, 1999, Brooks / Cole, 110). A polypeptide containing 20-100 amino acids is generally considered a peptide or a short polypeptide. A peptide is defined as a short polymer of amino acids,of a length typically of 20 or less amino acids, and more typically of a length of 12 or less amino acids (Garrett & Grisham, Biochemistry, 2nd edition, 1999, Brooks / Cole, 110).

[0063] The peptides, polypeptides, and proteins disclosed herein may be modified to include non-amino acid moieties. Modifications may include but are not limited to carboxylation (e.g., N- terminal carboxylation via addition of a di-carboxylic acid having 4-7 straight-chain or branched carbon atoms, such as glutaric acid, succinic acid, adipic acid, and 4,4-dimethylglutaric acid), amidation (e.g., C-terminal amidation via addition of an amide or substituted amide such as alkylamide or dialkylamide), PEGylation (e.g., N-terminal or C-terminal PEGylation via additional of polyethylene glycol), acylation (e.g., O-acylation (esters), N-acylation (amides), S-acylation (thioesters)), acetylation (e.g., the addition of an acetyl group, either at the N-terminus of the protein or at lysine residues), formylation lipoylation (e.g., attachment of a lipoate, a C8 functional group), myristoylation (e.g., attachment of myristate, a C14 saturated acid), palmitoylation (e.g., attachment of palmitate, a C16 saturated acid), alkylation (e.g., the addition of an alkyl group, such as an methyl at a lysine or arginine residue), isoprenylation or prenylation (e.g., the addition of an isoprenoid group such as famesol or geranylgeraniol), amidation at C-terminus, glycosylation (e.g., the addition of a glycosyl group to either asparagine, hydroxylysine, serine, or threonine, resulting in a glycoprotein). Distinct from glycation, which is regarded as a nonenzymatic attachment of sugars, polysialylation (e.g., the addition of polysialic acid), glypiation (e.g., glycosylphosphatidylinositol (GPI) anchor formation, hydroxylation, iodination (e.g., of thyroid hormones), and phosphorylation (e.g., the addition of a phosphate group, usually to serine, tyrosine, threonine, or histidine).

[0064] The phrase “percent identity” as applied to polypeptide sequences, refers to the percentage of residue matches between at least two polypeptide sequences aligned using a standardized algorithm. Methods of polypeptide sequence alignment are well-known. Some alignment methods consider conservative amino acid substitutions. Such conservative substitutions, generally preserve the charge and hydrophobicity at the site of substitution, thus preserving the structure (and therefore function) of the polypeptide. Percent identity for amino acid sequences may be determined as understood in the art. (See, e.g., U.S. Pat. No. 7,396,664, which is incorporated herein by reference in its entirety). A suite of commonly used and freely available sequence comparison algorithms is provided by the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST) (Altschul, S. F. et al. (1990) J. Mol. Biol. 215:403 410), which is available from several sources, including the NCBI, Bethesda, Md., at its website. The BLAST software suite includes various sequence analysis programs including “blastp,” that isused to align a known amino acid sequence with other amino acids sequences from a variety of databases.

[0065] Percent identity may be measured over the length of an entire defined polypeptide sequence or may be measured over a shorter length, for example, over the length of a fragment taken from a larger, defined polypeptide sequence, for instance, a fragment of at least 15, at least 20, at least 30, at least 40, at least 50, at least 70 or at least 150 contiguous residues. Such lengths are exemplary only, and it is understood that any fragment length may be used to describe a length over which percentage identity may be measured.

[0066] The terms “pharmaceutically effective amount”, “therapeutically effective amount” or “therapeutically effective dose” refer to the amount of a compound or compounds such as an immunosuppressive therapy that will elicit the biological or medical response of a tissue, system, animal, or human that is being sought by the researcher, veterinarian, medical doctor or other clinician. In some embodiments, a desired response is treatment of a patient who is having transplant rejection. In some embodiments, a desired response is pre-emptive treatment, and / or more close surveillance of a patient who is likely to have future transplant rejection. In some embodiments, a desired response is reduction or prevention of a future transplant rejection. In some instances, a desired biological or medical response is achieved following administration of multiple dosages of the composition to the subject over a period of days, weeks, or years. The terms “pharmaceutically effective amount”, “therapeutically effective amount” or “therapeutically effective dose” include that amount of a compound or compounds such as an immunosuppressive therapy that, when administered, is sufficient to prevent development of, or alleviate to some extent, one or more of the symptoms of the condition or disorder being treated. The therapeutically effective amount will vary depending on the immunosuppressive compound or compounds, the disorder or conditions and its severity, the route of administration, time of administration, rate of excretion, drug combination, judgment of the treating physician, dosage form, and the age, weight, general health, sex and / or diet of the subject to be treated.

[0067] The term “statistically significant difference” refers to p < 0.1, and more preferably, p <0.05. The term “statistically significant sameness” refers to p < 0.1, and more preferably, p <_0.05.

[0068] The term “subject” is defined herein to include animals such as mammals, including, but not limited to, primates (e.g., humans), cows, sheep, goats, horses, dogs, cats, rabbits, rats, mice and the like. In some embodiments, the subject is a human.

[0069] As used herein “surface expression” refers to the process by which polypeptides are translocated to the surface of a cell such that at least a portion of the polypeptide is located at the exterior of the cell surface. It should be understood that “surface expression” does not includesecretion of a polypeptide by a B cell as in, for example, a B cell’s secretion of a cytokine or antibody.

[0070] The term “t-distributed stochastic neighbor embedding” or “t-SNE” refers herein to a nonlinear dimensionality reduction algorithm. In some embodiments, the t-SNE analytical parameters include iterations: 2000. In some embodiments, the t-SNE parameters include perplexity: 50. In some embodiments, the t-SNE parameters include learning rate 48787.

[0071] As used herein, the term “transplant” can refer to vascularized composite allografts, organs, bodily tissues, or cells. Examples of vascularized composite allografts are face, fingers, hands, arms, toes, feet, and legs. Examples of organs are kidney, lung, liver, heart, pancreas, intestines, and uterus. Examples of bodily tissues are multi- visceral transplant tissue, and uterine tissue. Examples of cells are pancreatic islets, stem cells, neuronal cells, and genetically modified cells.

[0072] The terms “treat,” “treating,” “treatment,” and grammatical variations thereof as used herein, include partially or completely alleviating, mitigating or reducing the intensity of one or more attendant signs or symptoms of a disorder or condition and / or alleviating, mitigating or impeding one or more causes of a disorder or condition. Treatments according to the invention may be applied palliatively or remedially. Treatments are administered to a subject prior to onset (e.g., before obvious signs of a transplant rejection), during early onset (e.g., upon initial signs and symptoms of a transplant rejection), or after an established development of a transplant rejection. Prophylactic administration can occur for several days to years intending to reduce future rejection episodes.

[0073] Methods of Detection

[0074] Provided herein is a method of detecting rejection status of a transplant in a subject that includes obtaining a sample comprising B cells from the subject, detecting an expression pattern of the B cells, and comparing the detected expression pattern to a control rejection expression pattern and / or a control no rejection expression pattern, wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern and / or wherein a lack of transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern.

[0075] In some embodiments, B cells are identified as B cells prior to, simultaneously with, or after detecting the expression pattern of the B cell. In some embodiments, the B cells areidentified as B cells by detecting a pan B cell marker. In some embodiments, the B cell identification marker selected from a group consisting of CD19, CD20, CD79alpha, CD79beta, FcRL5, FcRL4, CD 138, and B cell receptor or a fragment thereof. In some embodiments, the pan B cell marker is CD19.

[0076] In some embodiments, the expression pattern comprises expression data for two or more of thirteen polypeptides, or polynucleotides encoding the two or more of thirteen polypeptides, and wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the detected expression pattern consists of expression data for CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the detected expression pattern comprises expression data for two or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, and wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the detected expression pattern consists of expression data for TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the detected expression pattern comprises expression data for CD38 and CD24. In some embodiments, the detected expression pattern consists of expression data for CD27 and CD21. In some embodiments, the detected expression pattern comprises expression data for CD38 and CD73. In some embodiments, the detected expression pattern consists of expression data for CD38 and CD23. In some embodiments, the detected expression pattern comprises expression data for CD24 and CD73. In some embodiments, the detected expression pattern consists of expression data for CD24 and CD21. In some embodiments, the detected expression pattern comprises expression data for CD25 and IgD. In some embodiments, the detected expression pattern consists of expression data for CD73 and IgM. In some embodiments, the detected expression pattern comprises expression data for CD73 and IgD. In some embodiments, the detected expression pattern consists of expression data for CD39 and CD25. In some embodiments, the detected expression pattern comprises expression data for CD39 and CD73. In some embodiments, the detected expression pattern consists of expression data for CD73 and LAG3. In some embodiments, the detected expression pattern comprises expression data for CD73 and CD10. In some embodiments, the detected expression pattern consists of expression data for CD23 and CD73. In some embodiments, the detected expression pattern comprises expression data for CD21 and CD9.

[0077] In some embodiments, the expression pattern of the B cells comprises expression data one or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3,CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for two or two or more of twenty-one polypeptides, wherein the twenty - one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for five or five or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for six or six or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for seven or seven or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for eight or eight or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for nine or nine or more of twenty-one polypeptides, wherein the twenty- one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for ten or ten or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for eleven or eleven or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for twelve or twelve or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD 10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for thirteen or thirteen or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2,LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells comprises expression data for fourteen or fourteen or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern of the B cells consists of expression data for TNFR2, CD19, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. As discussed above, in any embodiment disclosed herein, the method can further comprises detecting CD 19 or another B cell identification marker.

[0078] In some embodiments, the method comprises detecting expression data for one or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for two or two or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for three or three or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for four or four or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data five or five or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for six or six or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for seven or seven or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for eight or eight or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for nine or nine or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21,CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for ten or ten or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for eleven or eleven or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for twelve or twelve or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. As discussed above, in any embodiment disclosed herein, the method can further comprises detecting CD 19 or another B cell identification marker. In some embodiments, the expression pattern of the B cells consists of expression data for CD 19, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

[0079] It should be understood that detecting the expression pattern of CD 19 can occur prior to or concurrently with detection of the expression pattern of the remaining B cell polypeptides described herein. In some embodiments, CD 19 is detected before the expression pattern of one or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80 is detected. In some embodiments, the expression pattern is a surface expression pattern.

[0080] As used herein, the term “transplant rejection” refers to acute rejection and chronic rejection. In some embodiments, the transplant rejection is acute. In other embodiments, the transplant rejection is chronic. The acute transplant rejection can be severe, moderate, mild, clinical or subclinical. The transplant rejection can be mediated by antibodies, or by T cells, or other immune cells. In some embodiments, the transplant rejection is an acute organ transplant rejection. Acute transplant rejection commonly occurs days to over one year after a transplant. In some embodiments, the transplant rejection is a chronic transplant rejection. Chronic transplant rejection commonly occurs or continues after about six months following a transplant. In certain aspects, the chronic transplant rejection is mild. In certain aspects, the chronic transplant rejection is subclinical

[0081] As discussed above, the “transplant” can be a transplant of vascularized composite allografts, organs, bodily tissues, or cells. Accordingly, in some embodiments, the transplant rejection is an acute organ transplant rejection. In some embodiments, the transplant rejection is a subclinical organ transplant rejection. In some embodiments, the transplant rejection is a mild organ transplant rejection. In some embodiments, the transplant rejection is a chronic organ transplant rejection. The organ can be any organ, and in some embodiments is a kidney, liver, lung, heart, smallbowel, multi- visceral, pancreas, limb or face (composite tissue allografts). In some embodiments, the organ is a kidney, liver or lung. In some embodiments, the organ is a kidney. In other embodiments, the organ is a liver. In other embodiments, the organ is a lung. In other embodiments the transplant may be cellular comprised of pancreatic islets, neuronal cells, stem cells or genetically modified cells.

[0082] Classification as “acute,” “chronic,” “subclinical,” “clinical,” “antibody-mediated” or “T cell mediated” of kidney transplants can be achieved using the Banff Classification of Allograft Pathology, a classification system known to those of ordinary skill in the art (Appendix 1). In some aspects, “acute” rejection of kidney transplants is characterized by tubulitis, interstitial inflammation, glomerulitis, peritubular capillaritis and arteritis as defined in the Banff Classification. In some aspects, “chronic” rejection of kidney transplants is characterized by tubular atrophy, interstitial fibrosis, transplant glomerulopathy, multilayering of peritubular capillary (PCT) basement membranes and transplant arteriopathy as defined in the Banff Classification. In some aspects, a subclinical rejection is scored as less than a Banff grade 1A. In some embodiments, the subject has no or a minor increase in creatine levels.

[0083] In organs other than kidney transplants, different pathology and grading for rejection have been defined by the Banff Classification of Allograft Pathology. Although attribution of antibody-mediated or T cell mediated rejection may be less clear, rejection is still defined and graded based on tissue histology and may also include functional deterioration of the transplanted organ. For example, Chronic lung allograft dysfunction (CLAD) encompasses a range of pathologies that cause a transplanted lung to not achieve or maintain normal function. CLAD manifests as airflow restriction and / or obstruction and is predominantly a result of chronic rejection. In other organs and cell transplants identification of rejection is based on loss of function or measurement of other markers in the blood or urine. For example, in pancreas or islet transplants, a loss of glycemic control, decreased serum c-peptide or insulin levels or increased serum or urine amylase levels may be used.

[0084] With regard to the step of obtaining a sample comprising B cells from the subject, in some embodiments, the sample is a blood sample. In other embodiments the B cells may be obtained from allograft biopsies, bronchial washings (bronchioalveloar lavage), urine or other excretions or secretions. The B cells can be naive B cells, memory B cells, plasma B cells, and any combination thereof. In some aspects, the subject is a human. The methods of the present disclosure include detecting a B cell expression pattern on B cells in the sample. The B cells may be live, fixed, or cryopreserved. In some embodiments, the B cell expression pattern is a B cell surface expression pattern. In some embodiments, the B cell expression pattern is a pattern of relative expression of agroup of B cell polypeptides such as CD 19 or another B cell specific marker plus two or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the B cell expression pattern is a pattern of relative expression of a group of B cell polypeptides such as CD 19 or another B cell identification marker plus five or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

[0085] As noted above, the term “expression pattern” refers to the levels of expression of more than one, or a group, of polypeptides or polynucleotides. A “detected expression pattern” is the expression pattern of the subject’s B cells. A “control expression pattern” is either a B cell expression pattern associated with transplant rejection (“control rejection expression pattern”) or a B cell expression pattern associated with a lack of rejection (“control no rejection expression pattern”). In some embodiments, the development of a control rejection expression pattern or a control no rejection expression pattern is determined through analysis of B cell expression data from an appropriate cohort (a cohort presenting with rejection or a cohort presenting with no rejection) using t-distributed stochastic neighbor embedding (t-SNE). In some embodiments data is analyzed using other dimensionality reduction algorithms (such as, for example, Principal component analysis (PCA), Independent component analysis (ICA), Low variance filter, High correlation filter, Isomap, or Singular value decomposition). In some embodiments, the t-SNE control expression pattern data is represented in a two- or three-dimensional plot. Non-limiting examples of t-SNE plots are shown in Figures 2 and 6-19. In some embodiments, the compared expression patterns are limited to correlating subpopulation groups identified on t-SNE plots. Accordingly, a control rejection expression pattern can be as shown in a t-SNE plot in its entirety or a portion of a t-SNE plot. A portion of a t-SNE plot is referred to herein as a “subpopulation.” Non-limiting examples of subpopulations are shown in Figure 2 as Gl, G2, G3, G4, G5, G6 and G7 and in Figure 19 as Pl, P2, P3, P4 and P5. Therefore, in some embodiments, the control expression pattern is a subpopulation of a t-SNE plot and the detected expression pattern to which it is compared is a correlating subpopulation of a t-SNE plot, wherein “correlating” refers to having the same spatial location and boundaries in a t-SNE plot wherein the t-SNE plots were generated using the same t-SNE parameters. For example, the G7 subpopulation in each panel of Figure 2 correlates with the other G7 subpopulations in the other panels of Figure 2. Similarly, the P2 subpopulation in each panel of Figure 19 correlates with the other P2 subpopulations in the other panels of Figure 19.

[0086] In some embodiments, the control rejection expression pattern is that shown in the right panel of Figure 2 or one or more the Gl, G2, G3, G4, G5, G6 or G7 subpopulations in the rightpanel of Figure 2. In some embodiments, the control rejection expression pattern is or comprises that shown in the G7 subpopulation in the right panel of Figure 2. In some embodiments, the control no rejection expression pattern is that shown in the G7 subpopulation of the center panel of Figure 2. In some embodiments, the control rejection expression pattern is that shown in the right panel of Figure 19. In some embodiments, the control no rejection expression pattern is that shown in the center panel of Figure 19. In some embodiments, the control rejection expression pattern is that shown in one or more of the Pl, P3 and P4 subpopulations shown in the right panel of Figure 19. In some embodiments, the control no rejection expression pattern is that shown in one or more of the Pl, P3 and P4 subpopulations shown in the center panel of Figure 19.

[0087] It should be understood that, in some embodiments, an “expression pattern” refers to the expression levels of a group of polypeptides or polynucleotides and can include values for expression, no expression, and any level of expression. In some embodiments, expression values are obtained using flow cytometry methods. In some aspects, the expression values are obtained using a t-distributed stochastic neighbor embedding (t-SNE) analysis of flow cytometry data. The t-SNE surface expression values can range broadly but the algorithm places cells in a given region according to their relative brightness of each marker. For example, surface marker fluorescence may range from -3,000 to 600,000, wherein ranges below the background fluorescence of isotype and fluorochrome controls are referred to as “negative” or “neg,” ranges above the background fluorescence of isotype and fluorochrome controls are referred to as “positive” or “pos,” ranges between about 40% and 70% compared to the brightest population are referred to as “dim,” and ranges between about greater than 70% of the brightest population are referred to as “bright.” In some embodiments, “neg,” “dim,” “pos” and “bright” correspond with the results shown in Figure 5.

[0088] In some embodiments, the expression pattern comprises the expression level of 20 or less of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern comprises the expression level of 15 or less of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern comprises the expression level of 12 or less of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern comprises the expression level of 10 or less of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some embodiments, the expression pattern comprises the expression level of 5 or less of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10,CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

[0089] In some embodiments, the method comprises detecting expression data for one of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for two or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for three or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for four or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data five or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for six or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for seven or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for eight or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for nine or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for ten or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for eleven or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3. In some embodiments, the expression pattern of the B cells comprises expression data for twelve or less of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. Insome aspects, the B cell expression pattern comprises the expression level of CD 19, CD39, CD80, CD23, CD73, IgM, CD21, CD27, CD24, IgD and CD38.

[0090] It should be understood that detecting the expression pattern of CD19 can occur prior to or concurrently with detection of the expression pattern of the remaining B cell markers described herein. In some embodiments, CD19 expression is detected before the expression pattern of any combination of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

[0091] In some aspects, the expression pattern corresponds to the G7 group shown in Figure 2. In other embodiments, the expression level correlates with the Gl, G2, G3, G4, G5 or G6 group shown in Figure 2. In some embodiments, the expression pattern comprises CD19bngbt, CD39d,ra, CD80dim, CD23dim, CD73ncg, IgMdim, CD21ncg, CD27ncg, CD24pos, IgDdimand CD38ncgas determined by t-SNE. In some embodiments, the surface expression pattern corresponds to group G5 and in some embodiments comprises CD19bright, CD39dim, CD80dim, CD23dim, CD73neg, IgMdim, CD21neg, CD27neg, CD24pos, IgDdimand CD38negand correlates with the results shown in Figure 5. In some embodiments, the expression pattern comprises CD19udermediate, CD39bngbt, CD80neg, HLA-IIbnght, CD23bright, CD73bright, IgMdim, CD2intermediate, CD27neg, CD24dim, igDinte™ediate, CD38dim, and CD9dimas determined by t-SNE.

[0092] In some aspects, the B cell expression pattern comprises the expression level of two to twelve of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to eleven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to ten of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to nine of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to eight of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to seven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of two to six of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39.

[0093] In some aspects, the B cell expression pattern comprises the expression level of three to twelve of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of three toeleven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of three to ten of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of three to nine of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level three to eight of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of three to seven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of three to six of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39.

[0094] In some aspects, the B cell expression pattern comprises the expression level of five to twelve of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five to eleven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five to ten of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five to nine of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five to eight of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five to seven of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some aspects, the B cell expression pattern comprises the expression level of five or six of CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39.

[0095] It should be understood that detecting the expression pattern of CD19 can occur prior to or concurrently with detection of the expression pattern of the remaining B cell markers described herein. In some embodiments, the expression pattern of CD 19 is detected before the expression pattern of one or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80 is detected.

[0096] In some embodiments, the B cell expression pattern is a B cell surface expression pattern. In some embodiments, the B cell expression pattern is a relative B cell expression pattern. In some embodiments, the B cells are live.

[0097] In some embodiments, the CD 19 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 1633, Entrez Gene: 930, Ensembl:ENS G00000177455, OMIM: 107265, and UniProtKB: P15391. In some embodiments, the CD19 polypeptide comprises SEQ ID NO: 1. In some embodiments, the CD19 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 1, or a polypeptide comprising a portion of SEQ ID NO: 1.

[0098] In some embodiments, the CD39 polypeptide is also known as NTPDase-1 encoded by the ENTPD1 gene. In some embodiments, the CD39 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 3363, NCBI Gene: 953, Ensembl: ENSG00000138185, OMIM: 601752, and UniProtKB: P49961. In some embodiments, the CD39 polypeptide comprises SEQ ID NO:2. In some embodiments, the CD39 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:2, or a polypeptide comprising a portion of SEQ ID NO:2.

[0099] In some embodiments, the CD80 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 1700, NCBI Gene: 941, Ensembl: ENSG00000121594, OMIM: 112203, and UniProtKB: P33681. In some embodiments, the CD80 polypeptide comprises SEQ ID NOG. In some embodiments, the CD80 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NOG, or a polypeptide comprising a portion of SEQ ID NOG.

[0100] In some embodiments, the CD23 polypeptide is also known as the FC Epsilon Receptor II encoded by the FCER2 gene. In some embodiments, the CD23 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 3612, NCBI Gene: 2208, Ensembl: ENS G00000104921, OMIM: 151445, and UniProtKB: P06734. In some embodiments, the CD23 polypeptide comprises SEQ ID NOG. In some embodiments, the CD23 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NOG, or a polypeptide comprising a portion of SEQ ID NOG.

[0101] In some embodiments, the CD73 polypeptide is also known as 5 '-Nucleotidase Ecto and encoded by the NT5E gene. In some embodiments, the CD73 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 8021, NCBI Gene: 4907, Ensembl: ENSG00000135318, OMIM: 129190, and UniProtKB: P21589. In some embodiments, the CD73 polypeptide comprises SEQ ID NOG. In some embodiments, the CD73 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NOG, or a polypeptide comprising a portion of SEQ ID NOG.

[0102] In some embodiments, the CD21 polypeptide is also referred to as the Complement C3d Receptor 2 encoded by the CR2 gene. In some embodiments, the CD21 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 2336, NCBI Gene: 1380, Ensembl: ENSG00000117322, OMIM: 1120650, and UniProtKB: P20023. In some embodiments, the CD21 polypeptide comprises SEQ ID NO:6. In some embodiments, the CD21 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:6, or a polypeptide comprising a portion of SEQ ID NO:6.

[0103] In some embodiments, the CD27 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 11922, NCBIGene: 939, Ensembl: ENSG00000139193, OMIM: 186711, and UniProtKB: P26842. In some embodiments, the CD27 polypeptide comprises SEQ ID NO:7. In some embodiments, the CD27 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:7, or a polypeptide comprising a portion of SEQ ID NO:7.

[0104] In some embodiments, the CD24 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 1645, NCBI Gene: 100133941, Ensembl: ENSG00000272398, OMIM: 600074, and UniProtKB: P25063. In some embodiments, the CD24 polypeptide comprises SEQ ID NO:8. In some embodiments, the CD24 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:8, or a polypeptide comprising a portion of SEQ ID NO:8.

[0105] In some embodiments, the CD38 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 1667, NCBI Gene: 952, Ensembl: ENSG00000004468, OMIM: 107270, and UniProtKB: P28907. In some embodiments, the CD38 polypeptide comprises SEQ ID NO:9. In some embodiments, the CD38 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:9, or a polypeptide comprising a portion of SEQ ID NO:9.

[0106] In some embodiments, the TNFR2 polypeptide is also referred to as the TNF Receptor Superfamily Member IB encoded by the TNFRSF1B gene. In some embodiments, the TNFR2 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 11917, NCBI Gene: 7133, Ensembl: ENSG00000028137, OMIM®: 191191, UniProtKB / Swiss-Prot: P20333. In some embodiments, the TNFR2 polypeptide comprises SEQ ID NO: 10. In some embodiments, the TNFR2 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 10, or a polypeptide comprising a portion of SEQ ID NO: 10.

[0107] In some embodiments, the LAG3 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 6476, NCBI Gene: 3902, Ensembl: ENSG00000089692, OMIM®: 153337, UniProtKB / Swiss-Prot: P18627. In some embodiments, the LAG3 polypeptide comprises SEQ ID NO:11. In some embodiments, the LAG3 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 11, or a polypeptide comprising a portion of SEQ ID NO:11.

[0108] In some embodiments, the IgM polypeptide is also referred to as the Immunoglobulin Heavy Constant Mu encoded by the IGHM gene. In some embodiments, the IgM polypeptide is that identified in one or more publicly available databases as follows: HGNC: 5541, NCBI Gene: 3507, Ensembl: ENS G00000211899, OMIM®: 147020, UniProtKB / Swiss-Prot: P01871. In some embodiments, the IgM polypeptide comprises SEQ ID NO: 12. In some embodiments, the IgM polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 12, or a polypeptide comprising a portion of SEQ ID NO: 12.

[0109] In some embodiments, the CD9 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 1709, NCBI Gene: 928, Ensembl: ENS G00000010278, OMIM®: 143030, UniProtKB / Swiss-Prot: P21926. In some embodiments, the CD9 polypeptide comprises SEQ ID NO: 13. In some embodiments, the CD9 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 13, or a polypeptide comprising a portion of SEQ ID NO: 13.

[0110] In some embodiments, the CD10 polypeptide is also referred to as the Membrane Metalloendopeptidase encoded by the MME gene. In some embodiments, the CD10 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 7154, NCBI Gene: 4311, Ensembl: ENS G00000196549, OMIM®: 120520, UniProtKB / Swiss-Prot: P08473. In some embodiments, the CD10 polypeptide comprises SEQ ID NO: 14. In some embodiments, the CD10 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 14, or a polypeptide comprising a portion of SEQ ID NO: 14.

[0111] In some embodiments, the IgD polypeptide is also referred to as the Immunoglobulin Heavy Constant Delta encoded by the IGHD gene. In some embodiments, the IgD polypeptide is that identified in one or more publicly available databases as follows: HGNC: 5480, NCBI Gene: 3495, Ensembl: ENSG000002U898, OMIM®: 147170, UniProtKB / Swiss-Prot: P01880. In some embodiments, the IgD polypeptide comprises SEQ ID NO: 15. In some embodiments, the IgDpolypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 15, or a polypeptide comprising a portion of SEQ ID NO: 15.

[0112] In some embodiments, the PDL1 polypeptide is also referred to as the CD274 Molecule encoded by the CD274 gene. In some embodiments, the PDL1 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 17635, NCBI Gene: 29126, Ensembl: ENSG00000120217, OMIM®: 605402, UniProtKB / Swiss-Prot: Q9NZQ7. In some embodiments, the PDL1 polypeptide comprises SEQ ID NO: 16. In some embodiments, the PDL1 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 16, or a polypeptide comprising a portion of SEQ ID NO: 16.

[0113] In some embodiments, the TIGIT polypeptide is that identified in one or more publicly available databases as follows: HGNC: 26838, NCBI Gene: 201633, Ensembl: ENSG00000181847, OMIM®: 612859, UniProtKB / Swiss-Prot: Q495A1. In some embodiments, the TIGIT polypeptide comprises SEQ ID NO: 17. In some embodiments, the TIGIT polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 17, or a polypeptide comprising a portion of SEQ ID NO: 17.

[0114] In some embodiments, the HLA Class II polypeptide is that identified in one or more publicly available databases as follows: HGNC: 4948, NCBI Gene: 3123, Ensembl: ENSG00000196126, OMIM®: 142857, UniProtKB / Swiss-Prot: P01911. In some embodiments, the HLA Class II polypeptide comprises SEQ ID NO: 18. In some embodiments, the HLA Class II polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 18, or a polypeptide comprising a portion of SEQ ID NO: 18.

[0115] In some embodiments, the TIM-1 polypeptide is also referred to as the Hepatitis A Virus Cellular Receptor 1 encoded by the HAVCR1 gene. In some embodiments, the TIM-1 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 17866, NCBI Gene: 26762, Ensembl: ENSG00000113249, OMIM®: 606518, UniProtKB / Swiss- Prot: Q96D42. In some embodiments, the TIM-1 polypeptide comprises SEQ ID NO: 19. In some embodiments, the TIM-1 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO: 19, or a polypeptide comprising a portion of SEQ ID NO: 19.

[0116] In some embodiments, the TIM-4 polypeptide is also referred to as the T Cell Immunoglobulin And Mucin Domain Containing 4 encoded by the TIMD4 gene. In some embodiments, the TIM-4 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 25132, NCBI Gene: 91937, Ensembl: ENSG00000145850, OMIM®: 610096, UniProtKB / Swiss-Prot: Q96H15. In some embodiments, the TIM-4 polypeptide comprises SEQ ID NO:20. In some embodiments, the TIM-4 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:20, or a polypeptide comprising a portion of SEQ ID NQ:20.

[0117] In some embodiments, the PD1 polypeptide is also referred to as the Programmed Cell Death 1 encoded by the PDCD1 gene. In some embodiments, the PD1 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 8760, NCBI Gene: 5133, Ensembl: ENSG00000188389, OMIM®: 600244, UniProtKB / Swiss-Prot: Q15116. In some embodiments, the PD1 polypeptide comprises SEQ ID NO:21. In some embodiments, the PD1 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:21, or a polypeptide comprising a portion of SEQ ID NO:21.

[0118] In some embodiments, the CD25 polypeptide is also referred to as the Interleukin 2 Receptor Subunit Alpha encoded by the IL2RA gene. In some embodiments, the CD25 polypeptide is that identified in one or more publicly available databases as follows: HGNC: 6008, NCBI Gene: 3559, Ensembl: ENS G00000134460, OMIM®: 147730, UniProtKB / Swiss-Prot: P01589. In some embodiments, the CD25 polypeptide comprises SEQ ID NO:22. In some embodiments, the CD25 polypeptide comprises a polypeptide sequence having at or greater than about 80%, about 85%, about 90%, about 95%, or about 98% identity with SEQ ID NO:22, or a polypeptide comprising a portion of SEQ ID NO:22.

[0119] The methods of detection can allow a determination of who to biopsy (or obtain other diagnostic tissue or fluid sample from the patient) or who needs or does not need a biopsy. Therefore, in some embodiments of the method of detection, no rejection is detected and no biopsy or diagnostic sample is needed from the subject. The methods herein can therefore prevent unnecessary biopsy or sampling from the subject.

[0120] Accordingly, in some embodiments, detection of the expression pattern may be used to rule out transplant rejection and avoid biopsy or treatment. In some embodiments this might comprise a decrease in B cells in subpopulation G7 as shown in Figure 3, or an increase in cells in G5 as shown in Figure 4 when the polypeptides are TNFR2, CD 19, LAG3, CD27, CD21, IgM, CD9,CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD8O.

[0121] In other embodiments, rejection is detected and the method further comprises obtaining a biopsy or diagnostic sample from the subject. In some embodiments, the biopsy is a transplant biopsy. In some detection embodiments, the transplant is an organ. In some embodiments of the method of detection the organ is a kidney. In some embodiments, the diagnostic sample is a blood sample. In some embodiments, the diagnostic sample is a bronchoalveloar lavage. In some embodiments, rejection is detected and the method further comprises one or more of a functional test, bronchioalveolar lavage, cardiac catheterization and blood measurement after detection of the transplant rejection.

[0122] Methods of Treatment

[0123] Also included herein are methods of treating a transplant rejection in a subject that is detected using the methods described above and below. In some embodiments, the method of treating a transplant rejection in a subject comprises obtaining a sample comprising B cells from the subject, detecting an expression pattern of the B cells, and comparing the detected expression pattern to a control rejection expression pattern and / or a control no rejection expression pattern, wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern, and administering to the subject a treatment for the detected transplant rejection. In some embodiments, the methods of treatment include obtaining a biopsy or diagnostic sample from the subject prior to treatment and after detection of the transplant rejection. Accordingly, in some embodiments of the method of treatment, the method further comprises obtaining a biopsy or diagnostic sample from the subject. In some embodiments, the biopsy is a transplant biopsy. In some embodiments, the diagnostic sample is a blood sample. In some embodiments, the diagnostic sample is a bronchoalveloar lavage or cardiac catheterization.

[0124] In these treatment methods, the detected B cell expression pattern can comprise any combination of B cell polypeptides or polynucleotides described herein and can be any as described herein as indicating a rejection. In some embodiments, the method of treating a transplant rejection in a subject comprises a) obtaining a sample comprising B cells from the subject, and b) detecting a B cell expression pattern comprising identification marker plus one or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80, comparing thedetected expression pattern to a control rejection expression pattern and / or a control no rejection expression pattern and identifying an indication of transplant rejection, and c) administering to the subject a treatment for detected transplant rejection. In some embodiments, the method of treating a transplant rejection in a subject comprises a) obtaining a sample comprising B cells from the subject, and b) detecting a B cell expression pattern comprising CD 19 or another B cell identification marker plus two or more of thirteen polypeptides, or polynucleotides encoding the one or more of thirteen polypeptides, wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3, wherein detection of the expression pattern is a detection of transplant rejection, and c) administering to the subject a treatment for the detected transplant rejection. It should be understood that detecting the expression pattern of CD 19 can occur prior to or concurrently with detection of the expression pattern of the remaining B cell markers described herein. In some embodiments, the expression pattern of CD19 is detected before the expression pattern of one or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80 is detected.

[0125] In some embodiments of the method of treatment, the expression pattern is a surface expression pattern. In some embodiments of the method of treatment, the transplant is an organ. In some embodiments of the method of treatment, the organ is a kidney.

[0126] In certain aspects of the method of treatment, the two or more of twenty-two polypeptides are CD39, CD80, CD23, CD73, IgM, CD21, CD27, CD24, IgD and CD38. In some embodiments of the method of treatment, the expression pattern comprises CD39dim, CD80dim, CD23dim, CD73neg, IgMdim, CD21neg, CD27neg, CD24POS, IgDdimand CD38neg. In other or further aspects of the method of treatment, the expression pattern comprises CD39bnght, CD80neg, HLA- IIbright, CD23bright, CD73bright, IgMdim, CD2in,eraiediate, CD27neg, CD24dira, igDin,e™ediate, CD38dim, and CD9dim. In some embodiments, the two or more of thirteen polypeptides are CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39. In some embodiments, the B cell identification marker is CD19 and its expression is CD19bnghtor CD19m,ermedia,e.

[0127] In some embodiments of the method of treatment, the polypeptides are TNFR2, CD19, LAG3, CD27, CD21, IgM, CD9, CD 10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80, and the detected expression pattern has a statistically significant sameness to the expression pattern depicted in Figure 2, right panel, using the t-SNE parameters described herein. In some embodiments of the method of treatment, the polypeptides are TNFR2, CD19, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80, and the detectedexpression pattern has a statistically significant difference to the expression pattern depicted in Figure 2, center panel, using the t-SNE parameters described herein. In some embodiments of the method of treatment, the polypeptides are CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39 and the detected expression pattern has a statistically significant sameness to the expression pattern depicted in Figure 19, right panel, using the t-SNE parameters described herein. In some embodiments of the method of treatment, the polypeptides are CD38, IgD, CD27, CD21, IgM, LAG3, CD9, CD10, CD24, CD73, CD25, CD23, and CD39 and the detected expression pattern has a statistically significant difference to the expression pattern depicted in Figure 19, center panel, using the t-SNE parameters described herein.

[0128] As discussed above, included herein are methods of treatment wherein the subject is a human and / or where the sample is a blood sample. The treatment administered to the subject can be any known to those of skill in the art. In some embodiments, the treatment is an immunosuppressive therapy. In some embodiments, the treatment comprises administration of a therapeutically effective composition that is an immunosuppressive therapy. In some embodiments the treatment is intended to reduce the likelihood of future transplant rejection or reduce the severity of future transplant rejection.

[0129] Kits

[0130] Provided herein is a kit for detecting rejection status of a transplant in a subject, wherein the kit is used to obtain a sample comprising B cells from the subject and to identify an expression pattern of the B cells and comparing the detected expression pattern to a control rejection expression pattern and / or a control no rejection expression pattern, wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern and / or wherein a lack of transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern.

[0131] The kit comprises compositions for the detection of expression of any detected expression pattern described herein. For example, in some embodiments, the kit comprises compositions for detection of expression of two or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80 in or on B cells in a sample obtained from the subject. In other embodiments, the kit comprises compositions for detection of expression of CD19 or another B cellspecific marker plus two or more of CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD 10, and LAG3 in or on B cells in a sample obtained from the subject.

[0132] In some kit embodiments, the compositions for detection comprise antibodies specific for the two or more B cell polypeptides described herein. In some kit embodiments, the antibodies are labeled. In some embodiments, the labels are fluorescent. More specifically, in some kit embodiments, the kit comprises labeled antibodies specific for two or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIG1T, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some kit embodiments, the kit comprises labeled antibodies specific for two or more of CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some kit embodiments, the kit comprises labeled antibodies specific for CD19, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

[0133] In some kit embodiments, the compositions for detection comprise polynucleotide sequences specific for two or more B cell polynucleotides described herein. More specifically, in some kit embodiments, the kit comprises polynucleotides specific for polynucleotides that encode two or more of TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80. In some kit embodiments, the kit comprises polynucleotides specific for polynucleotides that encode two or more of CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3. In some kit embodiments, the kit comprises polynucleotides specific for CD 19, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

[0134] In some embodiments, the kit further comprises a visual representation of a control no rejection expression pattern and / or a control rejection expression pattern as described herein. In some embodiments, the kit further comprises data representing a control no rejection expression pattern and / or a control rejection expression pattern as described herein. In some embodiments, the kit comprises information regarding statistically significant differences and / or statistically significant sameness as described herein.

[0135] The term “kit” describes a wide variety of bags, containers, carrying cases, and other portable enclosures which may be used to carry and store solid substances, liquid substances, and other accessories necessary to detect transplant rejection. Such kits and their contents along with any applicable procedures may be used to provide access to detection of transplant rejection in accordance with the teachings of the present disclosure.

[0136] In some embodiments, the kit comprises a sample collection device, a centrifuge tube, one or more fluorescently conjugated antibody(s), one or more control sample(s), a nucleic aciddetection probe, a staining buffer and a flow-cytometer, single cell isolation reagents, or a combination thereof. In some embodiments, the sample collection device is selected from a group comprising of a tourniquet, an alcohol swab, a needle, a syringe, a blood collection tube, a dissection tool, a biopsy punch device, a biopsy needle, a biopsy syringe, a specimen container, or a combination thereof.

[0137] The transplant of the kit embodiments can be any as described herein. In some kit embodiments, the transplant is a kidney, liver, lung, heart, pancreas, intestines, multi-visceral, uterus, vascularized composite allograft, pancreatic islet, stem cell, or neuronal cell. In some kit embodiments, the transplant is an organ. In some kit embodiments, the organ is a kidney. In some embodiments, the transplant rejection is an acute transplant rejection. In some kit embodiments, the transplant rejection is a subclinical transplant rejection. In some kit embodiments, the transplant rejection is a clinical transplant rejection. In some kit embodiments, the subject is a human. In some kit embodiments, the sample is a blood sample.

[0138] It should be understood that the foregoing relates to preferred embodiments of the present invention and that numerous changes may be made therein without departing from the scope of the invention. The invention is further illustrated by the following examples, which are not to be construed in any way as imposing limitations upon the scope thereof. On the contrary, it is to be clearly understood that resort may be had to various other embodiments, modifications, and equivalents thereof, which, after reading the description herein, may suggest themselves to those skilled in the art without departing from the spirit of the present invention and / or the scope of the appended claims. All patents, patent applications, and publications referenced herein are incorporated by reference in their entirety for all purposes.

[0139] EXAMPLES

[0140] Example 1

[0141] B Cell Phenotyping by Spectral Flow Cytometry for Predicting Rejection After Renal Transplantation

[0142] B Cell Surface Marker Staining: Human PBMCs were rapidly thawed in a 37°C water bath. Thereafter, 10 mL of pre-warmed PBS-0.5% BSA is added to 1 mL of the thawed PBMCs (~5- 10 X 106 cells / ml). The cells were then centrifuged at 350g (1350 rpm) for 10 minutes with high brake at room temperature. The pellet obtained was then resuspended in 10 mL of PBS-0.5% BSA, then centrifuged at 350g for 10 min at 4°C. The cell pellet was then resuspended in PBS-0.5% BSA at a final concentration of 2.5million cells / ml in a BD falcon tube and centrifuged for 5 min at 350g and high brake. These 2.5million cells (1ml) were used for subsequent staining. A viability stain was performed using LIVE / DEAD™ Fixable Aqua Dead Cell Stain Kit, for 405 nm excitation(ThermoFisher Scientific, #L34966). For each sample, 1 pL of LIVE / DEAD reagent was used in 1 mL of PBS to re-suspend cell pellet and then the samples were incubated on ice and covered in darkness (with aluminum foil) for 20 minutes. Each sample was then washed in 2 mis of PBS-0.5% BSA at 350g (1350 rpm) for 5 minutes with high brake at 4°C. Prior to centrifugation, an aliquot of cells was removed to create a single color ‘LIVE / DEAD’ control. The antibody cocktail was prepared as shown in Table 2. The cell pellet was resuspended in 200 pl of the antibody cocktail and incubated on ice and covered in darkness for 45 minutes. Thereafter, each sample was washed twice in 1ml of PBS-0.5% BSA at 350g (1350 rpm) for 5 minutes with high brake at 4°C. A fixation step was performed for each sample by resuspending the cell pellet of each sample using 250 pl of Fixation / Permeabilization Solution on ice and covered by aluminum foil for 10 min. After fixation, each sample was washed in 2 mis of PBS-0.5% BSA at 350g (1350 rpm) for 5 minutes with high brake at 4°C. The final cell pellet was then resuspended in 100 pl of PBS and flow cytometry was performed immediately for analysis using Cytek Aurora spectral flow cytometer.

[0143] Analysis of Flow Cytometric Data: The voltage for each fluorochrome was adjusted using unstained cells along with each of the isotype-matched single-color controls. The instrument settings such as voltage and gain for each detector were adjusted to optimize signal detection and the instrument configures for spectral unmixing (computationally separate signals from different fluorochromes). A total of 500,000 to 1 million events were acquired to ensure adequate cell numbers for analysis of B cell subsets. Flow cytometry standard (FCS) files were generated for single color controls and actual experimental samples were labeled and stored for data analysis by Cytobank. The FCS files were then uploaded onto the Cytobank platform. Following QC, lymphocytes were identified based on forward and side scatter characteristics. Then dead cells were excluded based on staining by live-dead dye. Single lymphocytes were then defined (by excluding doublets), and B cells gated based on CD19 staining (Fig 1). CD19+ B cells from individual samples were concatenated and were subjected to t-SNE analysis based on the surface expression of the stained markers. T-SNE plots were then analyzed to identify clusters of B cell sub-populations (Fig 2). Relative expression of various surface markers in each of the B cell subpopulations were visualized on a Heatmap map (Fig 5). Thus, the G7 subpopulation that was significantly increased in patients with acute rejection (AR) is characterized as: CD19bnght, CD39dim, CD80dmi, CD23dmi, CD73neg, IgMdim, CD21neg, CD27neg, CD24?OS, IgDdim, CD38neg. These markers can be used to distinguish G7 from other B subpopulations.Table 1: B cell PanelTable 2:Appendix 1CURRENT BANFF CLASSIFICATION OF KIDNEY TRANSPLANT REJECTIONCategory 1: Normal biopsy or nonspecific changesCategory 2: Antibody-mediated changesActive AB MR (All 3 criteria must be met for diagnosis):1. Histologic evidence of acute tissue injury, including 1 or more of the following:- At least moderate microvascular inflammation ([g + ptc] >2) in the absence of recurrent or de novo glomerulonephritis (in the presence of borderline or acute TCMR, or infection, ptc > 2 must accompany g>l)- Intimal or transmural arteritis (v > 0)- Acute thrombotic microangiopathy, in the absence of any other cause- Acute tubular injury, in the absence of any other apparent cause2. Evidence of current / recent antibody interaction with vascular endothelium, including 1 or more of the following:- Linear C4d staining in peritubular capillaries or medullary vasa recta (C4d2 or C4d3 by IF on frozen sections, or C4d > 0 by IHC on paraffin sections)- At least moderate microvascular inflammation ([g + ptc] >2) in the absence of recurrent or de novo glomerulonephritis (in the presence of borderline or acute TCMR, or infection, ptc > 2 must accompany g>l)- Increased expression of gene transcripts / classifiers in the biopsy tissue strongly associated with AB MR, if thoroughly validated3. Circulating donor-specific antibodies (DSA to HLA or other antigens). C4d staining or expression of validated transcripts / classifiers as noted above in criterion 2 may substitute for DSA.Chronic active AB MR (All 3 criteria must be met for diagnosis):1. Morphologic evidence of chronic tissue injury, including 1 or more of the following:- Transplant glomerulopathy (eg > 0) if no evidence of chronic TMA or chronic recurrent / de novo glomerulonephritis- Arterial intimal fibrosis of new onset, excluding other causes; leukocytes within the sclerotic intima favor chronic AB MR if there is no prior history of TCMR, but are not required2. Identical to criterion 2 for active ABMR, above3. Identical to criterion 3 for active ABMR, aboveChronic (inactive) ABMR1. eg > 0 and / or severe ptcml (ptcmll)2. Absence of criterion 2 of current / recent antibody interaction with the endothelium3. Prior documented diagnosis of active or chronic active ABMR and / or documented prior evidence ofDSACategory 3: Borderline (Suspicious) for acute TCMRFoci of tubulitis (tl , t2, or t3) with mild interstitial inflammation (il), or mild (tl) tubulitis with moderate-severe interstitial inflammation (i2 or i3). No intimal or transmural arteritis (v = 0)Category 4: TCMR (Acute TCMR)Grade IA: Interstitial inflammation involving >25% of non-sclerotic cortical parenchyma (i2 or i3) with moderate tubulitis (t2) involving 1 or more tubules, not including tubules that are severely atrophic.Grade IB: Interstitial inflammation involving >25% of non-sclerotic cortical parenchyma (i2 or i3) with severe tubulitis (t3) involving 1 or more tubules, not including tubules that are severely atrophic.Grade IIA: Mild to moderate intimal arteritis (vl), with or without interstitial inflammation and / or tubulitisGrade IIB : Severe intimal arteritis (v2), with or without interstitial inflammation and / or tubulitisGrade III: Transmural arteritis and / or arterial fibrinoid necrosis involving medial smooth muscle with accompanying mononuclear cell intimal arteritis (v3), with or without interstitial inflammation and / or tubulitisChronic active TCMRGrade I A: Interstitial inflammation involving >25% of sclerotic cortical parenchyma (i-IFTA2 or i- IFTA3) AND > 25% of total cortical parenchyma (ti2 or ti3) with moderate tubulitis (t2 or t-IFTA2) involving 1 or more tubules, not including severely atrophic tubules; other known causes of i-IFTA should be ruled outGrade IB: Interstitial inflammation involving >25% of sclerotic cortical parenchyma (i-IFTA2 or i- IFTA3) AND > 25% of total cortical parenchyma (ti2 or ti3) with severe tubulitis (t3 or 1-1FTA3) involving 1 or more tubules, not including severely atrophic tubules; other known causes of i-IFTA should be ruled outGrade II: Chronic allograft arteriopathy (arterial intimal fibrosis with mononuclear cell inflammation in fibrosis and formation of neointima). This may also be a manifestation of chronic active or chronic ABMR or mixed ABMR / TCMRSEQ ID NO: 1 (CD 19)MPPPRLLFFLLFLTPMEVRPEEPLVVKVEEGDNAVLQCLKGTSDGPTQQLTWSRESPLKPFLKLSLGLPGLGIHMRPLAIWLFIFNVSQQMGGFYLCQPGPPSEKAWQPGWTVNVEGSGELFRWNVSDLGGLGCGLKNRSSEGPSSPSGKLMSPKLYVWAKDRPEIWEGEPPCLPPRDSLNQSLSQDLTMAPGSTLWLSCGVPPDSVSRGPLSWTHVHPKGPKSLLSLELKDDRPARDMWVMETGLLLPRATAQDAGKYYCHRGNLTMSFHLEITARPVLWHWLLRTGGWKVSAVTLAYLIFCLCSLVGILHLQRALVLRRKRKRMTDPTRRFFKVTPPPGSGPQNQYGNVLSLPTPTSGLGRAQRWAAGLGGTAPSYGNPSSDVQADGALGSRSPPGVGPEEEEGEGYEEPDSEEDSEFYENDSNLGQDQLSQDGSGYENPEDEPLGPEDEDSFSNAESYENEDEELTQPVARTMDFLSPHGSAWDPSREATSLGSQSYEDMRGILYAAPQLRSIRGQPGPNHEEDADSYENMDNPDGPDPAWGGGGRMGTWSTRSEQ ID NO: 2 (CD39)MEDTKESNVKTFCSKNILAILGFSSIIAVIALLAVGLTQNKALPENVKYGIVLDAGSSHTSLYIYKWPAEKENDTGVVHQVEECRVKGPGISKFVQKVNEIGIYLTDCMERAREVIPRSQHQETPVYLGATAGMRLLRMESEELADRVLDVVERSLSNYPFDFQGARnTGQEEGAYGWrnNYLLGKFSQKTRWFSIVPYETNNQETFGALDLGGASTQVTFVPQNQTIESPDNALQFRLYGKDYNVYTHSFLCYGKDQALWQKLAKDIQVASNEILRDPCFHPGYKKVVNVSDLYKTPCTKRFEMTLPFQQFEIQGIGNYQQCHQSILELFNTSYCPYSQCAFNGIFLPPLQGDFGAFSAFYFVMKFLNLTSEKVSQEKVTEMMKKFCAQPWEEIKTSYAGVKEKYLSEYCFSGTYILSLLLQGYHFTADSWEHIHFIGKIQGSDAGWTLGYMLNLTNMIPAEQPLSTPLSHSTYVFLMVLFSLVLFTVAIIGLLIFHKPSYFWKDMVSEQ ID NO: 3 (CD80)MGHTRRQGTSPSKCPYLNFFQLLVLAGLSHFCSGVIHVTKEVKEVATLSCGHNVSVEELAQTRIYWQKEKKMVLTMMSGDMNIWPEYKNRTIFDITNNLSIVILALRPSDEGTYECVVLKYEKDAFKREHLAEVTLSVKADFPTPSISDFEIPTSNIRRIICSTSGGFPEPHLSWLENGEELNAINTTVSQDPETELYAVSSKLDFNMTTNHSFMCLIKYGHLRVNQTFNWNTTKQEHFPDNLLPSWAITLISVNGIFVICCLTYCFAPRCRERRRNERLRRESVRPVSEQ ID NO:4 (CD23)MEEGQYSEIEELPRRRCCRRGTQIVLLGLVTAALWAGLLTLLLLWHWDTTQSLKQLEERAARNVSQVSKNLESHHGDQMAQKSQSTQISQELEELRAEQQRLKSQDLELSWNLNGLQADLSSFKSQELNERNEASDLLERLREEVTKLRMELQVSSGFVCNTCPEKWINFQRKCYYFGKGTKQWVHARYACDDMEGQLVSIHSPEEQDFLTKHASHTGSWIGLRNLDLKGEFIWVDGSHVDYSNWAPGEPTSRSQGEDCVMMRGSGRWNDAFCDRKLGAWVCDRLATCTPPASEGSAESMGPDSRPDPDGRLPTPSAPLHSSEQ ID NO:5 (CD73)MCPRAARAPATLLLALGAVLWPAAGAWELTILHTNDVHSRLEQTSEDSSKCVNASRCMGGVARLFTKVQQIRRAEPNVLLLDAGDQYQGTIWFTVYKGAEVAHFMNALRYDAMALGNHEFDNGVEGLIEPLLKEAKFPILSANIKAKGPLASQISGLYLPYKVLPVGDEVVGIVGYTSKETPFLSNPGTNLVFEDEITALQPEVDKLKTLNVNKIIALGHSGFEMDKLIAQKVRGVDVVVGGHSNTFLYTGNPPSKEVPAGKYPFIVTSDDGRKVPVVQAYAFGKYLGYLKIEFDERGNVISSHGNPILLNSSIPEDPSIKADINKWRIKLDNYSTQELGKTIVYLDGSSQSCRFRECNMGNLICDAMINNNLRHTDEMFWNHVSMCILNGGGIRSPIDERNNGTITWENLAAVLPFGGTFDLVQLKGSTLKKAFEHSVHRYGQSTGEFLQVGGIHVVYDLSRKPGDRVVKLDVLCTKCRVPSYDPLKMDEVYKVILPNFLANGGDGFQMIKDELLRHDSGDQDINVVSTYISKMKVIYPAVEGRIKFSTGSHCHGSFSLIFLSLWAVIFVLYQSEQ ID NO:6 (CD21)MGAAGLLGVFLALVAPGVLGISCGSPPPILNGRISYYSTPIAVGTVIRYSCSGTFRLIGEKSLLCITKDKVDGTWDKPAPKCEYFNKYSSCPEPIVPGGYKIRGSTPYRHGDSVTFACKTNFSMNGNKSVWCQANNMWGPTRLPTCVSVFPLECPALPMIHNGHHTSENVGSIAPGLSVTYSCESGYLLVGEKIINCLSSGKWSAVPPTCEEARCKSLGRFPNGKVKEPPILRVGVTANFFCDEGYRLQGPPSSRCVIAGQGVAWTKMPVCEEIFCPSPPPILNGRHIGNSLANVSYGSIVTYTCDPDPEEGVNFILIGESTLRCTVDSQKTGTWSGPAPRCELSTSAVQCPHPQILRGRMVSGQKDRYTYNDTVIFACMFGFTLKGSKQIRCNAQGTWEPSAPVCEKECQAPPNILNGQKEDRHMVRFDPGTSIKYSCNPGYVLVGEESIQCTSEGVWTPPVPQCKVAACEATGRQLLTKPQHQFVRPDVNSSCGEGYKLSGSVYQECQGTIPWFMEIRLCKEITCPPPPVIYNGAHTGSSLEDFPYGTTVTYTCNPGPERGVEFSLIGESTIRCTSNDQERGTWSGPAPLCKLSLLAVQCSHVHIANGYKISGKEAPYFYNDTVTFKCYSGFTLKGSSQIRCKADNTWDPEIPVCEKETCQHVRQSLQELPAGSRVELVNTSCQDGYQLTGHAYQMCQDAENGIWFKKIPLCKVIHCHPPPVIVNGKHTGMMAENFLYGNEVSYECDQGFYLLGEKKLQCRSDSKGHGSWSGPSPQCLRSPPVTRCPNPEVKHGYKLNKTHSAYSHNDIVYVDCNPGFIMNGSRVIRCHTDNTWVPGVPTCIKKAFIGCPPPPKTPNGNHTGGNIARFSPGMSILYSCDQGYLLVGEALLLCTHEGTWSQPAPHCKEVNCSSPADMDGIQKGLEPRKMYQYGAVVTLECEDGYMLEGSPQSQCQSDHQWNPPLAVCRSRSLAPVLCGIAAGLILLTFLIVITLYVISKHRARNYYTDTSQKEAFHLEAREVYSVDPYNPASSEQ ID NO:7 (CD27)MARPHPWWLCVLGTLVGLSATPAPKSCPERHYWAQGKLCCQMCEPGTFLVKDCDQHRKAAQCDPCIPGVSFSPDHHTRPHCESCRHCNSGLLVRNCTITANAECACRNGWQCRDKECTECDPLPNPSLTARSSQALSPHPQPTHLPYVSEMLEARTAGHMQTLADFRQLPARTLSTHWPPQRSLCSSDFIRILVIFSGMFLVFTLAGALFLHQRRKYRSNKGESPVEPAEPCHYSCPREEEGSTIPIQEDYRKPEPACSPSEQ ID NO: 8 (CD24)MGRAMVARLGLGLLLLALLLPTQIYSSETTTGTSSNSSQSTSNSGLAPNPTNATrKAAGGALQSTASLFVVSLSLLHLYSSEQ ID NO:9 (CD38)MANCEFSPVSGDKPCCRLSRRAQLCLGVSILVLILVVVLAVVVPRWRQQWSGPGTTKRFPETVLARCVKYTEIHPEMRHVDCQSVWDAFKGAFISKHPCNITEEDYQPLMKLGTQTVPCNKILLWSRIKDLAHQFTQVQRDMFTLEDTLLGYLADDLTWCGEFNTSKINYQSCPDWRKDCSNNPVSVFWKTVSRRFAEAACDVVHVMLNGSRSKIFDKNSTFGSVEVHNLQPEKVQTLEAWVIHGGREDSRDLCQDPTIKELESIISKRNIQFSCKNIYRPDKFLQCVKNPEDSSCTSEISEQ ID NO: 10 (TNFR2)MAPVAVWAALAVGLELWAAAHALPAQVAFTPYAPEPGSTCRLREYYDQTAQMCCSKCSPGQHAKVFCTKTSDTVCDSCEDSTYTQLWNWVPECLSCGSRCSSDQVETQACTREQNRICTCRPGWYCALSKQEGCRLCAPLRKCRPGFGVARPGTETSDVVCKPCAPGTFSNTTSSTDICRPHQICNVVAIPGNASMDAVCTSTSPTRSMAPGAVHLPQPVSTRSQHTQPTPEPSTAPSTSFLLPMGPSPPAEGSTGDFALPVGLIVGVTALGLLIIGVVNCVIMTQVKKKPLCLQREAKVPHLPADKARGTQGPEQQHLLITAPSSSSSSLESSASALDRRAPTRNQPQAPGVEASGAGEARASTGSSDSSPGGHGTQVNVTCIVNVCSSSDHSSQCSSQASSTMGDTDSSPSESPKDEQVPFSKEECAFRSQLETPETLLGSTEEKPLPLGVPDAGMKPSSEQ ID NO: 11 (LAG3)MWEAQFLGLLFLQPLWVAPVKPLQPGAEVPVVWAQEGAPAQLPCSPTIPLQDLSLLRRAGVTWQHQPDSGPPAAAPGHPLAPGPHPAAPSSWGPRPRRYTVLSVGPGGLRSGRLPLQPRVQLDERGRQRGDFSLWLRPARRADAGEYRAAVHLRDRALSCRLRLRLGQASMTASPPGSLRASDWVILNCSFSRPDRPASVHWFRNRGQGRVPVRESPHHHLAESFLFLPQVSPMDSGPWGCILTYRDGFNVSIMYNLTVLGLEPPTPLTVYAGAGSRVGLPCRLPAGVGTRSFLTAKWTPPGGGPDLLVTGDNGDFTLRLEDVSQAQAGTYTCHIHLQEQQLNATVTLAIITVTPKSFGSPGSLGKLLCEVTPVSGQERFVWSSLDTPSQRSFSGPWLEAQEAQLLSQPWQCQLYQGERLLGAAVYFTELSSPGAQRSGRAPGALPAGHLLLFLILGVLSLLLLVTGAFGFHLWRRQWRPRRFSALEQGIHPPQAQSKIEELEQEPEPEPEPEPEPEPEPEPEQLSEQ ID NO: 12 (IgM)QVTLTESGPALVKPKQPLTLTCTFSGFSLSTSRMRVSWIRRPPGKALEWLARIDDDDKFYWSTSLRTRLSISKNDSKNQVVLIMINVNPVDTATYYCARVVNSVMAGYYYYYMDVWGKGTTVTVSSGSASAPTLFPLVSCENSNPSSTVAVGCLAQDFLPDSITFSWKYNQSQKISSTRGFPSVLRGGKYAATSQVLLPSKDVMQGTDEHVCKWVQHPNGNKQKNVPLPVIAELPPKVSVFVPPRDGFFGNPRKSKLICQATGFSPRQVWSLREGKQVGSGVTTDQVQAEAKESGPTTYKVTSTLTIKESDWLGESMFTCRVDHRGLTFQQNASSMCVPDQDTAIRVFAIPPSFASIFLTKSTKLTCLVTDLTTYDSVTISWTREENGAVKTHTNISESHPNATFSAVGEASICEDDDWSGERFTCTVTHTDLPSPLKQTISRPKGVALHRPDVYLLPPAREQLNLRESATI TCLVTGFSPADVFVQWMQRGEPLSPEKYVTSAPMPEPQAPGRYFAHSILTVSEEEWNTGQTYTCVV AHEALPNRVTERTVDKSTGKPTLYNVSLVMSDTAGTCYSEQ ID NO: 13 (CD9)MPVKGGTKCIKYLLFGFNFIFWLAGIAVLAIGLWLRFDSQTKSIFEQETNNNNSSFYTGVYILIGAGAL MMLVGFLGCCGAVQESQCMLGLFFGFLLVIFAIEIAAAIWGYSHKDEVIKEVQEFYKDTYNKLKTKD EPQRETLKAIHYALNCCGLAGGVEQFISDICPKKDVLETFTVKSCPDAIKEVFDNKFHIIGAVGIGIAV VMIFGMIFSMILCCAIRRNREMVSEQ ID NO: 14 (CD10)MGKSESQMDITDINTPKPKKKQRWTPLEISLSVLVLLLTIIAVTMIALYATYDDGICKSSDCIKSAARLI QNMDATTEPCTDFFKYACGGWLKRNVIPETSSRYGNFDILRDELEVVLKDVLQEPKTEDIVAVQKA KALYRSCINESAIDSRGGEPLLKLLPDIYGWPVATENWEQKYGASWTAEKAIAQLNSKYGKKVLINL FVGTDDKNSVNHVIHIDQPRLGLPSRDYYECTGIYKEACTAYVDFMISVARLIRQEERLPIDENQLAL EMNKVMELEKEIANATAKPEDRNDPMLLYNKMTLAQIQNNFSLEINGKPFSWLNFTNEIMSTVNISIT NEEDVVVYAPEYLTKLKPILTKYSARDLQNLMSWRFIMDLVSSLSRTYKESRNAFRKALYGTTSETATWRRCANYVNGNMENAVGRLYVEAAFAGESKHVVEDLIAQIREVFIQTLDDLTWMDAETKKRAEE KALAIKERIGYPDDIVSNDNKLNNEYLELNYKEDEYFENIIQNLKFSQSKQLKKLREKVDKDEWISGA AVVNAFYSSGRNQIVFPAGILQPPFFSAQQSNSLNYGGIGMVIGHEITHGFDDNGRNFNKDGDLVDW WTQQSASNFKEQSQCMVYQYGNFSWDLAGGQHLNGINTLGENIADNGGLGQAYRAYQNYIKKNG EEKLLPGLDLNHKQLFFLNFAQVWCGTYRPEYAVNSIKTDVHSPGNFRIIGTLQNSAEFSEAFHCRKN SYMNPEKKCRVWSEQ ID NO: 15 (IgD)RLQLQESGPGLVKPSETLSLTCIVSGGPIRRTGYYWGWIRQPPGKGLEWIGGVYYTGSIYYNPSLRGR VTISVDTSRNQFSLNLRSMSAADTAMYYCARGNPPPYYDIGTGSDDGIDVWGQGTTVHVSSAPTKA PDVFPIISGCRHPKDNSPVVLACLITGYHPTSVTVTWYMGTQSQPQRTFPEIQRRDSYYMTSSQLSTPL QQWRQGEYKCVVQHTASKSKKEIFRWPESPKAQASSVPTAQPQAEGSLAKATTAPATTRNTGRGGE EKKKEKEKEEQEERETKTPECPSHTQPLGVYLLTPAVQDLWLRDKATFTCFVVGSDLKDAHLTWEV AGKVPTGGVEEGLLERHSNGSQSQHSRLTLPRSLWNAGTSVTCTLNHPSLPPQRLMALREPAAQAPVKLSLNLLASSDPPEAASWLLCEVSGFSPPNILLMWLEDQREVNTSGFAPARPPPQPGSTTFWAWSVLR VPAPPSPQPATYTCVVSHEDSRTLLNASRSLEVSYVTDHGPMSEQ ID NO: 16 (PDL1MRIFAVFIFMTYWHLLNAFTVTVPKDLYVVEYGSNMTIECKFPVEKQLDLAALIVYWEMEDKNIIQF VHGEEDLKVQHSSYRQRARLLKDQLSLGNAALQITDVKLQDAGVYRCMISYGGADYKRITVKVNA PYNKINQRILVVDPVTSEHELTCQAEGYPKAEVIWTSSDHQVLSGKTTTTNSKREEKLFNVTSTLRIN TTTNEIFYCTFRRLDPEENHTAELVIPELPLAHPPNERTHLVILGAILLCLGVALTFIFRLRKGRMMDV KKCGIQDTNSKKQSDTHLEETSEQ ID NO: 17 (TIGIT)MRWCLLLIWAQGLRQAPLASGMMTGTIETTGNISAEKGGSIILQCHLSSTTAQVTQVNWEQQDQLL AICNADLGWHISPSFKDRVAPGPGLGLTLQSLTVNDTGEYFCIYHTYPDGTYTGRIFLEVLESSVAEH GARFQIPLLGAMAATLVVICTAVIVVVALTRKKKALRIHSVEGDLRRKSAGQEEWSPSAPSPPGSCV QAEAAPAGLCGEQRGEDCAELHDYFNVLSYRSLGNCSFFTETGSEQ ID NO: 18 (HLA Class II; HLA-II)MVCLKLPGGSCMTALTVTLMVLSSPLALSGDTRPRFLWQPKRECHFFNGTERVRFLDRYFYNQEES VRFDSDVGEFRAVTELGRPDAEYWNSQKDILEQARAAVDTYCRHNYGVVESFTVQRRVQPKVTVY PSKTQPLQHHNLLVCSVSGFYPGSIEVRWFLNGQEEKAGMVSTGLIQNGDWTFQTLVMLETVPRSGE VYTCQVEHPSVTSPLTVEWRARSESAQSKMLSGVGGFVLGLLFLGAGLFIYFRNQKGHSGLQPTGFL SSEQ ID NO: 19 (TIM-1)MDLHMMNCELLATCSALGYLEGDTYHKEPDCLESVKDLIRYLRHEDETRDVRQQLGAAQILQSDLLPILTQHHQDKPLFDAVIRLMVNLTQPALLCFGNLPKEPSFRHHFLQVLTYLQAYKEAFASEKAFGVLSETLYELLQLGWEERQEEDNLLIERILLLVRNILHVPADLDQEKKIDDDASAHDQLLWAIHLSGLDDLLLFLASSSAEEQWSLHVLEIVSLMFRDQNPEQLAGVGQGRLAQERSADFAELEVLRQREMAEKKTRALQRGNRHSRFGGSYIVQGLKSIGERDLIFHKGLHNLRNYSSDLGKQPKKVPKRRQAARELSIQRRSALNVRLFLRDFCSEFLENCYNRLMGSVKDHLLREKAQQHDETYYMWALAFFMAFNRAASFRPGLVSETLSVRTFHFIEQNLTNYYEMMLTDRKEAASWARRMHLALKAYQELLATVNEMDISPDEAVRESSRIIKNNIFYVMEYRELFLALFRKFDERCQPRSFLRDLVETTHLFLKMLERFCRSRGNLVVQNKQKKRRKKKKKVLDQAIVSGNVPSSPEEVEAVWPALAEQLQCCAQNSELSMDSVVPFDAASEVPVEEQRAEAMVRIQDCLLAGQAPQALTLLRSAREVWPEGDVFGSQDISPEEEIQLLKQILSAPLPRQQGPEERGAEEEEEEEEEEEEELQVVQVSEKEFNFLDYLKRFACSTVVRAYVLLLRSYQQNSAHTNHCIVKMLHRLAHDLKMEALLFQLSVFCLFNRLLSDPAAGAYKELVTFAKYILGKFFALAAVNQKAFVELLFWKNTAVVREMTEGYGSLDDRSSSRRAPTWSPEEEAHLRELYLANKDVEGQDVVEAILAHLNTVPRTRKQIIHHLVQMGLADSVKDFQRKGTHIVLWTGDQELELQRLFEEFRDSDDVLGHIMKNITAKRSRARIVDKLLALGLVAERRELYKKRQKKLASSILPNGAESLKDFCQEDLEEEENLPEEDSEEEEEGGSEAEQVQGSLVLSNENLGQSLHQEGFSIPLLWLQNCLIRAADDREEDGCSQAVPLVPLTEENEEAMENEQFQQLLRKLGVRPPASGQETFWRIPAKLSPTQLRRAAASLSQPEEEQKLQPELQPKVPGEQGSDEEHCKEHRAQALRALLLAHKKKAGLASPEEEDAVGKEPLKAAPKKRQLLDSDEEQEEDEGRNRAPELGAPGIQKKKRYQIEDDEDDSEQ ID NO: 20 (TIM-4)MSKEPLILWLMIEFWWLYLTPVTSETVVTEVLGHRVTLPCLYSSWSHNSNSMCWGKDQCPYSGCKEALIRTDGMRVTSRKSAKYRLQGTIPRGDVSLTILNPSESDSGVYCCRIEVPGWFNDVKINVRLNLQRASTTTHRTATTTTRRTTTTSPTTTRQMTTTPAALPTTVVTTPDLTTGTPLQMTTIAVFTTANTCLSLTPSTLPEEATGLLTPEPSKEGPILTAESETVLPSDSWSSVESTSADTVLLTSKESKVWDLPSTSHVSMWKTSDSVSSPQPGASDTAVPEQNKTTKTGQMDGIPMSMKNEMPISQLLMIIAPSLGFVLFALFVAFLLRGKLMETYCSQKHTRLDYIGDSKNVLNDVQHGREDEDGLFTLSEQ ID NO: 21 (PD1)MQIPQAPWPVVWAVLQLGWRPGWFLDSPDRPWNPPTFSPALLVVTEGDNATFTCSFSNTSESFVLNWYRMSPSNQTDKLAAFPEDRSQPGQDCRFRVTQLPNGRDFHMSVVRARRNDSGTYLCGAISLAPKAQIKESLRAELRVTERRAEVPTAHPSPSPRPAGQFQTLVVGVVGGLLGSLVLLVWVLAVICSRAARGTIGARRTGQPLKEDPSAVPVFSVDYGELDFQWREKTPEPPVPCVPEQTEYATIVFPSGMGTSSPARRGSADGPRSAQPLRPEDGHCSWPLSEQ ID NO: 22 (CD25)MDSYLLMWGLLTFIMVPGCQAELCDDDPPEIPHATFKAMAYKEGTMLNCECKRGFRRIKSGSLYMLCTGNSSHSSWDNQCQCTSSATRNTTKQVTPQPEEQKERKTTEMQSPMQPVDQASLPGHCREPPPWENEATERIYHFVVGQMVYYQCVQGYRALHRGPAESVCKMTHGKTRWTQPQLICTGEMETSQFPGEEKPQASPEGRPESETSCLVTTTDFQIQTEMAATMETSIFTTEYQVAVAGCVFLLISVLLLSGLTWQRRQRKSRRTI

Claims

CLAIMSWhat is claimed is1. A method of detecting rejection status of a transplant in a subject comprising, a. obtaining a sample comprising B cells from the subject; b. detecting an expression pattern of the B cells; and c. comparing the detected expression pattern to a control expression pattern; wherein a transplant rejection is indicated by a statistically significant difference in the detected expression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern and / or wherein a lack of rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern.

2. The method of claim 1, wherein the B cells are identified by detecting a B cell identification marker.

3. The method of claim 2, wherein the B cell identification marker is selected from a group consisting of CD 19, CD20, CD79alpha, CD79beta, FcRL5, FcRL4, CD 138, and B cell receptor or a fragment thereof.

4. The method of claim 2 or claim 3, wherein the B cell identification marker is CD19.

5. The method of any one of claims 1-2, wherein the expression pattern comprises expression data for two or more of thirteen polypeptides, or polynucleotides encoding the two or more of thirteen polypeptides, and wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

6. The method of any one of claims 1-2, wherein the detected expression pattern consists of expression data for CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

7. The method of any one of claims 1-4, wherein the detected expression pattern comprises expression data for two or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, and wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

8. The method of any one of claims 1-4, and 7, wherein the detected expression pattern consists of expression data for TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and CD80.

9. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD38 and CD24.

10. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD27 and CD21.

11. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD38 and CD73.

12. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD38 and CD23.

13. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD24 and CD73.

14. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD24 and CD21.

15. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD25 and IgD.

16. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD73 and IgM.

17. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD73 and IgD.

18. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD39 and CD25.

19. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD39 and CD73.

20. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD73 and LAG3.

21. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD73 and CD 10.

22. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD23 and CD73.

23. The method of any one of claims 1-8, wherein the detected expression pattern comprises expression data for CD21 and CD9.

24. The method of any one of claims 1-8, wherein the detected expression pattern comprises CD19bright, CD39dim, CD80dim, CD23dim, CD73neg, IgMdim, CD21neg, CD27neg, CD24pos, IgDdimand CD38neg.

25. The method of any one of claims 1-8, wherein the detected expression pattern comprises26. The method of any of claims 1-25, wherein the expression pattern is a surface expression pattern.

27. The method of claim 26, wherein detecting the surface expression pattern comprises flow cytometry.

28. The method of any one of claims 1-27, wherein the detected expression pattern and the control expression pattern are obtained using a method comprising t-distributed stochastic neighbor embedding (t-SNE).

29. The method of claim 28, wherein the statistically significant difference in the detected expression pattern and the control expression pattern is at least p < 0.05.

30. The method of any one of claims 1-29, wherein the transplant is a kidney, a liver, a lung, a heart, a pancreas, an intestine, multi-visceral, a uterus, a vascularized composite allograft, a pancreatic islet, a stem cell, or a neuronal cell.

31. The method of any one of claims 1-30, wherein the transplant is an organ.

32. The method of claim 31, wherein the organ is a kidney.

33. The method of any of claims 1-32, wherein the transplant rejection is indicated.

34. The method of claim 33, further comprising obtaining a biopsy of the transplant or a diagnostic sample from the subject.

35. The method of claim 33 or claim 34, wherein the rejection is an acute transplant rejection.

36. The method of claim 33 or claim 34, wherein the rejection is a subclinical transplant rejection.

37. The method of claim 33 or claim 34, wherein the rejection is a clinical transplant rejection.

38. The method of any one of claims 1-37, wherein the subject is a human.

39. The method of any one of claims 1-38, wherein the sample is a blood sample.

40. The method of any of claims 33-39, further comprising administering to the subject a treatment for the transplant rejection.

41. The method of claim 40, wherein the treatment is an immunosuppressive therapy.

42. A kit for detection of rejection status of a transplant in a subject, wherein the kit is used, a. to obtain a sample comprising B cells from the subject; and b. to detect an expression pattern of the B cells; and comparing the detected expression pattern to a control expression pattern; wherein a transplant rejection is indicated by a statistically significant difference in the detectedexpression pattern and the control no rejection expression pattern or a statistically significant sameness of the detected expression pattern and the control rejection expression pattern and / or wherein a lack of rejection is indicated by a statistically significant difference in the detected expression pattern and the control rejection pattern or a statistically significant sameness of the detected expression pattern and the control no rejection expression pattern.

43. The kit of claim 42, wherein the B cells are identified by detecting an expression of a B cell identification marker.

44. The kit of claim 43, wherein the B cell identification marker is CD19.

45. The kit of any one of claims 42-44, wherein the B cells are identified by detecting an expression of a B cell identification marker; and The kit of claim 41, wherein the B cell identification marker is selected from a group consisting of CD 19, CD20, CD79alpha, CD79beta, FcRL5, FcRL4, CD138, and B cell receptor or a fragment thereof.

46. The kit of any one of claims 42-45, wherein the detected expression pattern comprises expression data for the B cell identification marker and two or more of thirteen polypeptides, or polynucleotides encoding the two or more of thirteen polypeptides, and wherein the thirteen polypeptides are CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10, and LAG3.

47. The kit of any one of claims 42-45, wherein the detected expression pattern comprises expression data for the B cell identification marker and two or more of twenty-one polypeptides, or polynucleotides encoding the two or more of twenty-one polypeptides, and wherein the twenty-one polypeptides are TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PDl, and CD80.

48. The kit of any one of claims 42-45 and 47, wherein the kit comprises an antibody or ligand specific for the B cell identification marker, TNFR2, LAG3, CD27, CD21, IgM, CD9, CD10, CD38, IgD, PDL1, CD39, TIGIT, CD24, CD73, CD25, CD23, HLA Class II, TIM-1, TIM-4, PD1, and / or CD80.

49. The kit of any of claims 42-46, wherein the kit comprises an antibody or ligand specific for the B cell identification marker, CD24, CD38, CD27, CD21, CD39, CD23, CD73, CD25, CD9, IgD, IgM, CD10 and / or LAG3.

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