Value of Donor-Specific Anti-HLA Antibody Monitoring and Characterization for Risk Stratification of Kidney Allograft Loss
The diagnosis system for allograft loss lacks accurate individual risk stratification on the basis of donor-specific anti-HLA antibody (anti-HLA DSA) characterization. We investigated whether systematic monitoring of DSA with extensive characterization increases performance in predicting kidney allograft loss. This prospective study included 851 kidney recipients transplanted between 2008 and 2010 who were systematically screened for DSA at transplant, 1 and 2 years post-transplant, and the time of post-transplant clinical events. We assessed DSA characteristics and performed systematic allograft biopsies at the time of post-transplant serum evaluation. At transplant, 110 (12.9%) patients had DSAs; post-transplant screening identified 186 (21.9%) DSA-positive patients. Post-transplant DSA monitoring improved the prediction of allograft loss when added to a model that included traditional determinants of allograft loss (increase in c statistic from 0.67; 95% confidence interval [95% CI], 0.62 to 0.73 to 0.72; 95% CI, 0.67 to 0.77). Addition of DSA IgG3 positivity or C1q binding capacity increased discrimination performance of the traditional model at transplant and post-transplant. Compared with DSA mean fluorescence intensity, DSA IgG3 positivity and C1q binding capacity adequately reclassified patients at lower or higher risk for allograft loss at transplant (category-free net reclassification index, 1.30; 95% CI, 0.94 to 1.67; P<0.001 and 0.93; 95% CI, 0.49 to 1.36; P<0.001, respectively) and post-transplant (category-free net reclassification index, 1.33; 95% CI, 1.03 to 1.62; P<0.001 and 0.95; 95% CI, 0.62 to 1.28; P<0.001, respectively). Thus, pre- and post-transplant DSA monitoring and characterization may improve individual risk stratification for kidney allograft loss.
The purpose of the present review is to describe how we improve the model for risk stratification of transplant outcomes in kidney transplantation by incorporating the novel insights of donor-specific anti-HLA antibody (DSA) characteristics. The detection of anti-HLA DSA is widely used for the assessment of pre- and posttransplant risks of rejection and allograft loss; however, not all anti-HLA DSA carry the same risk for transplant outcomes. These antibodies have been shown to cause a wide spectrum of effects on allografts, ranging from the absence of injury to indolent or full-blown acute antibody-mediated rejection. Consequently, the presence of circulating anti-HLA DSA does not provide a sufficient level of accuracy for the risk stratification of allograft outcomes. Enhancing the predictive performance of anti-HLA DSA is currently one of the most pressing unmet needs for facilitating individualized treatment choices that may improve outcomes. Recent advancements in the assessment of anti-HLA DSA properties, including their strength, complement-binding capacity, and IgG subclass composition, significantly improved the risk stratification model to predict allograft injury and failure. Although risk stratification based on anti-HLA DSA properties appears promising, further specific studies that address immunological risk stratification in large and unselected populations are required to define the benefits and cost-effectiveness of such comprehensive assessment prior to clinical implementation.
Paris Transplant Group
Our global aim is to accelerate the translation of immunological and gene expression discoveries into the clinical field by filling the gap between basic science and applied biomedical researches.