The prognostic significance of glomerular infiltrating leukocytes during acute renal allograft rejection

•During acute rejection, 96% of biopsies had at least some degree/form of glomerulitis.•Glomerulitis is mainly composed of T cells, (IL-17+) neutrophils and macrophages.•None of the quantified cell types appeared to be a good biomarker for the response to antirejection therapy.•Macrophage glomerulitis has a predictive value for graft failure until 500 days after rejection.

Transplant glomerulitis, observed in T cell-mediated and antibody-mediated rejection, is histologically characterized by intracapillary mononuclear cell infiltration. However, the prognostic value of counting various glomerular inflammatory cells during rejection has not been elucidated, which is a key step for the introduction of novel biomarkers in the clinics. We immunophenotyped glomerulitis during episodes of acute rejection in order to investigate their predictive value for transplant outcomes. To do so, we included 57 transplant biopsies of 57 renal transplant recipients with biopsy-proven acute rejection with a median follow-up of 4.2 years. We determined average glomerular cell counts for T cells, B cells, Tregs, IL-17+ cells, neutrophils and macrophages. Logistic and Cox regression models were used to investigate the association of glomerular inflammatory cells with response to therapy and graft failure on a population level. We used novel time-dependent ROC curve analyses to investigate the value of glomerular inflammatory cell infiltrates for the prediction of transplant outcomes, applicable to the individual patient. We identified three cell types that were responsible for glomerulitis during rejection: macrophages, T cells and neutrophils. By quantification of glomerular macrophages, an emerging cell type associated with antibody-mediated rejection, we were able to predict the progression towards death-censored graft failure within the first 500 days after the initial episode of rejection. With the use of novel time-dependent ROC analyses, we propose dynamic sensitivities, specificities, and positive and negative predictive values with their corresponding cut-off values for the average amount of glomerular macrophages, depending on what time after rejection death-censored graft failure needs prediction.