Understanding the Correlation Between DSA, Complement Activation, and Antibody-Mediated Rejection in Heart Transplant Recipients.

BackgroundDonor-specific HLA antibodies (DSA) are associated with increased rates of rejection and of graft failure in cardiac transplantation. The goal of this study was to determine the association of preformed and posttransplant development of newly detected DSA (ndDSA) with antibody-mediated rejection (AMR) and characterize the clinical relevance of complement-activating DSA in heart allograft recipients.MethodsThe study included 128 adult and 48 pediatric heart transplant patients transplanted between 2010 and 2013. Routine posttransplant HLA antibody testing was performed by IgG single-antigen bead test. The C3d single-antigen bead assay was used to identify complement-activating antibodies. Rejection was diagnosed using International Society for Heart and Lung Transplantation criteria.ResultsIn this study, 22 patients were transplanted with preexisting DSA, and 43 patients developed ndDSA posttransplant. Pretransplant (P < 0.05) and posttransplant (P < 0.001) ndDSA were associated with higher incidence of AMR. Patients with C3d + DSA had significantly higher incidence of AMR compared with patients with no DSA (P < 0.001) or patients with C3d-DSA (P = 0.02). Nine (36%) of 25 patients with AMR developed transplant coronary artery disease compared with 17 (15.9%) of 107 patients without AMR (P < 0.05). Among the 47 patients who received ventricular assistant device (VAD), 7 of 9 VAD+ patients with preformed DSA experienced AMR compared with 7 of 38 VAD+ patients without preformed DSA, indicating presensitization to donor HLA significantly increased the risk of AMR (P < 0.01).ConclusionsPreformed and posttransplant ndDSA were associated with AMR. C3d + DSA correlates with complement deposition on the graft and higher risk of AMR which may permit the application of personalized immunotherapy targeting the complement pathway

Clinical Phenomapping and Outcomes after Heart Transplantation

BackgroundSurvival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and side effects of pharmacological therapies. We hypothesize that time-dependent phenomapping of clinical and molecular datasets is a valuable approach to clinical assessments and guiding medical management to improve outcomes.MethodsWe analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were employed to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical endpoint of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (k=2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, HLA antibody titers, peripheral blood mononuclear cell gene expression of the AlloMap test genes, and an intragraft, heart tissue gene co-expression network analysis was performed.ResultsUnsupervised cluster analysis of immunosuppressive therapies identified two groups, one characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined endpoint, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the higher event rate group had increased HLA class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the March8 and WDNR40A AlloMap genes. Intramyocardial biomarker-related co-expression network analysis of the FLT3 showed an immune system-related network underlying this biomarker.ConclusionTime-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes

Clinical Phenomapping and Outcomes after Heart Transplantation

BackgroundSurvival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and side effects of pharmacological therapies. We hypothesize that time-dependent phenomapping of clinical and molecular datasets is a valuable approach to clinical assessments and guiding medical management to improve outcomes.MethodsWe analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were employed to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical endpoint of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (k=2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, HLA antibody titers, peripheral blood mononuclear cell gene expression of the AlloMap test genes, and an intragraft, heart tissue gene co-expression network analysis was performed.ResultsUnsupervised cluster analysis of immunosuppressive therapies identified two groups, one characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined endpoint, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the higher event rate group had increased HLA class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the March8 and WDNR40A AlloMap genes. Intramyocardial biomarker-related co-expression network analysis of the FLT3 showed an immune system-related network underlying this biomarker.ConclusionTime-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes

Clinical phenomapping and outcomes after heart transplantation

BackgroundSurvival after heart transplantation (HTx) is limited by complications related to alloreactivity, immune suppression, and adverse effects of pharmacologic therapies. We hypothesize that time-dependent phenomapping of clinical and molecular data sets is a valuable approach to clinical assessments and guiding medical management to improve outcomes.MethodsWe analyzed clinical, therapeutic, biomarker, and outcome data from 94 adult HTx patients and 1,557 clinical encounters performed between January 2010 and April 2013. Multivariate analyses were used to evaluate the association between immunosuppression therapy, biomarkers, and the combined clinical end point of death, allograft loss, retransplantation, and rejection. Data were analyzed by K-means clustering (K = 2) to identify patterns of similar combined immunosuppression management, and percentile slopes were computed to examine the changes in dosages over time. Findings were correlated with clinical parameters, human leucocyte antigen antibody titers, and peripheral blood mononuclear cell gene expression of the AlloMap (CareDx, Inc., Brisbane, CA) test genes. An intragraft, heart tissue gene coexpression network analysis was performed.ResultsUnsupervised cluster analysis of immunosuppressive therapies identified 2 groups, 1 characterized by a steeper immunosuppression minimization, associated with a higher likelihood for the combined end point, and the other by a less pronounced change. A time-dependent phenomap suggested that patients in the group with higher event rates had increased human leukocyte antigen class I and II antibody titers, higher expression of the FLT3 AlloMap gene, and lower expression of the MARCH8 and WDR40A AlloMap genes. Intramyocardial biomarker-related coexpression network analysis of the FLT3 gene showed an immune system-related network underlying this biomarker.ConclusionsTime-dependent precision phenotyping is a mechanistically insightful, data-driven approach to characterize patterns of clinical care and identify ways to improve clinical management and outcomes

Discovery of non‐HLA antibodies associated with cardiac allograft rejection and development and validation of a non‐HLA antigen multiplex panel: From bench to bedside

We analyzed humoral immune responses to nonhuman leukocyte antigen (HLA) after cardiac transplantation to identify antibodies associated with allograft rejection. Protein microarray identified 366 non-HLA antibodies (>1.5 fold, P < .5) from a discovery cohort of HLA antibody-negative, endothelial cell crossmatch-positive sera obtained from 12 cardiac allograft recipients at the time of biopsy-proven rejection. From these, 19 plasma membrane proteins and 10 autoantigens identified from gene ontology analysis were combined with 48 proteins identified through literature search to generate a multiplex bead array. Longitudinal sera from a multicenter cohort of adult cardiac allograft recipients (samples: n = 477 no rejection; n = 69 rejection) identified 18 non-HLA antibodies associated with rejection (P < .1) including 4 newly identified non-HLA antigenic targets (DEXI, EMCN, LPHN1, and SSB). CART analysis showed 5/18 non-HLA antibodies distinguished rejection vs nonrejection. Antibodies to 4/18 non-HLA antigens synergize with HLA donor-specific antibodies and significantly increase the odds of rejection (P < .1). The non-HLA panel was validated using an independent adult cardiac transplant cohort (n = 21 no rejection; n = 42 rejection, >1R) with an area under the curve of 0.87 (P < .05) with 92.86% sensitivity and 66.67% specificity. We conclude that multiplex bead array assessment of non-HLA antibodies identifies cardiac transplant recipients at risk of rejection

The importance of non-HLA antibodies in transplantation

The development of post-transplantation antibodies against non-HLA autoantigens is associated with rejection and decreased long-term graft survival. Although our knowledge of non-HLA antibodies is incomplete, compelling experimental and clinical findings demonstrate that antibodies directed against autoantigens such as angiotensin type 1 receptor, perlecan and collagen, contribute to the process of antibody-mediated acute and chronic rejection. The mechanisms that underlie the production of autoantibodies in the setting of organ transplantation is an important area of ongoing investigation. Ischaemia-reperfusion injury, surgical trauma and/or alloimmune responses can result in the release of organ-derived autoantigens (such as soluble antigens, extracellular vesicles or apoptotic bodies) that are presented to B cells in the context of the transplant recipient's antigen presenting cells and stimulate autoantibody production. Type 17 T helper cells orchestrate autoantibody production by supporting the proliferation and maturation of autoreactive B cells within ectopic tertiary lymphoid tissue. Conversely, autoantibody-mediated graft damage can trigger alloimmunity and the development of donor-specific HLA antibodies that can act in synergy to promote allograft rejection. Identification of the immunologic phenotypes of transplant recipients at risk of non-HLA antibody-mediated rejection, and the development of targeted therapies to treat such rejection, are sorely needed to improve both graft and patient survival