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Background No validated system currently exists to realistically characterize the chronic pathology of kidney transplants that represents the dynamic disease process and spectrum of disease severity. We sought to develop and validate a tool to describe chronicity and severity of renal allograft disease and integrate it with the evaluation of disease activity. Methods The training cohort included 3549 kidney transplant biopsies from an observational cohort of 937 recipients. We reweighted the chronic histologic lesions according to their time-dependent association with graft failure, and performed consensus k-means clustering analysis. Total chronicity was calculated as the sum of the weighted chronic lesions scores, scaled to the unit interval. Results We identified four chronic clusters associated with graft outcome, based on the proportion of ambiguous clustering. The two clusters with the worst survival outcome were determined by interstitial fibrosis/tubular atrophy (IFTA) and by transplant glomerulopathy. The chronic clusters partially overlapped with the existing Banff IFTA classification (adjusted Rand index, 0.35) and were distributed independently of the acute lesions. Total chronicity strongly associated with graft failure (hazard ratio [HR], 8.33; 95% confidence interval [95% CI], 5.94 to 10.88; P value <0.0001), independent of the total activity scores (HR, 5.01; 95% CI 2.83 to 7.00; P value <0.0001). These results were validated on an external cohort of 4031 biopsies from 2054 kidney transplant recipients. Conclusions The evaluation of total chronicity provides information on kidney transplant pathology that complements the estimation of disease activity from acute lesion scores. Use of the data-driven algorithm used in this study, called RejectClass, may provide a holistic and quantitative assessment of kidney transplant injury phenotypes and severity.

Despite the critical role of cytokines in allograft rejection, the relation of peripheral blood cytokine profiles to clinical kidney transplant rejection has not been fully elucidated. We assessed 28 cytokines through multiplex assay in 293 blood samples from kidney transplant recipients at time of graft dysfunction. Unsupervised hierarchical clustering identified a subset of patients with increased pro-inflammatory cytokine levels. This patient subset was hallmarked by a high prevalence (75%) of donor-specific anti-human leukocyte antigen antibodies (HLA-DSA) and histological rejection (70%) and had worse graft survival compared to the group with low cytokine levels (HLA-DSA in 1.7% and rejection in 33.7%). Thirty percent of patients with high pro-inflammatory cytokine levels and HLA-DSA did not have histological rejection. Exploring the cellular origin of these cytokines, we found a corresponding expression in endothelial cells, monocytes, and natural killer cells in single-cell RNASeq data from kidney transplant biopsies. Finally, we confirmed secretion of these cytokines in HLA-DSA-mediated cross talk between endothelial cells, NK cells, and monocytes. In conclusion, blood pro-inflammatory cytokines are increased in kidney transplant patients with HLA-DSA, even in the absence of histology of rejection. These observations challenge the concept that histology is the gold standard for identification of ongoing allo-immune activation after transplantation.

Interpretation of kidney graft biopsies using the Banff classification is still heterogeneous. In this study, extreme gradient boosting classifiers learned from two large training datasets (n = 631 and 304 cases) where the “reference diagnoses” were not strictly defined following the Banff rules but from central reading by expert pathologists and further interpreted consensually by experienced transplant nephrologists, in light of the clinical context. In three external validation datasets (n = 3744, 589, and 360), the classifiers yielded a mean ROC curve AUC (95%CI) of: 0.97 (0.92–1.00), 0.97 (0.96–0.97), and 0.95 (0.93–0.97) for antibody‐mediated rejection (ABMR); 0.94 (0.91–0.96), 0.94 (0.92–0.95), and 0.91 (0.88–0.95) for T cell–mediated rejection; >0.96 (0.90–1.00) with all three for interstitial fibrosis–tubular atrophy. We also developed a classifier to discriminate active and chronic active ABMR with 95% accuracy. In conclusion, we built highly sensitive and specific artificial intelligence classifiers able to interpret kidney graft scoring together with a few clinical data and automatically diagnose rejection, with excellent concordance with the Banff rules and reference diagnoses made by a group of experts. Some discrepancies may point toward possible improvements that could be made to the Banff classification.

Background The Flemish Collaborative Glomerulonephritis Group (FCGG) registry is the first population-based native kidney biopsy registry in Flanders, Belgium. In this first analysis, we report on patient demographics, frequency distribution and incidence rate of biopsied kidney disease in adults in Flanders. Methods From January 2017 until December 2019, a total of 2,054 adult first native kidney biopsies were included. A ‘double diagnostic coding’ strategy was used, in which every biopsy sample received a histopathological and final clinical diagnosis. Frequency distribution and incidence rate of both diagnoses are reported and compared with other European registries. Results The median age at biopsy was 61.1 years (IQR, 46.1-71.7), male patients were more prevalent (62.1%) and biopsy incidence rate was 129.3 per million persons per year. IgA nephropathy was the most frequently diagnosed kidney disease (355 biopsies, 17.3% of total) with a similar frequency as in previously published European registries. The frequency of tubulointerstitial nephritis (220 biopsies, 10.7%) and diabetic kidney disease (154 biopsies, 7.5%) was remarkably higher, which may be attributed to changes in disease incidence as well as biopsy practices. Discordances between histopathological and final clinical diagnoses were noted and indicate areas for improvement in diagnostic coding systems. Conclusions The FCGG registry, with its ‘double diagnostic coding’ strategy, provides useful population-based epidemiological data on a large Western-European population and allows subgroup selection for future research.