The Potential Role of the Leucocyte Immunoglobulin-Like Receptors in Kidney Transplant Rejection: A Mini Review.

Antibody-mediated rejection (ABMR) remains one of the main causes of long-term graft failure after kidney transplantation, despite the development of powerful immunosuppressive therapy. A detailed understanding of the complex interaction between recipient-derived immune cells and the allograft is therefore essential. Until recently, ABMR mechanisms were thought to be solely caused by adaptive immunity, namely, by anti-human leucocyte antigen (HLA) donor-specific antibody. However recent reports support other and/or additive mechanisms, designating monocytes/macrophages as innate immune contributors of ABMR histological lesions. In particular, in mouse models of experimental allograft rejection, monocytes/macrophages are readily able to discriminate non-self via paired immunoglobulin receptors (PIRs) and thus accelerate rejection. The human orthologs of PIRs are leukocyte immunoglobulin-like receptors (LILRs). Among those, LILRB3 has recently been reported as a potential binder of HLA class I molecules, shedding new light on LILRB3 potential as a myeloid mediator of allograft rejection. In this issue, we review the current data on the role of LILRB3 and discuss the potential mechanisms of its biological functions.

Recognition of intraglomerular histological features with deep learning in protocol transplant biopsies and their association with kidney function and prognosis.

Background: The Banff Classification may not adequately address protocol transplant biopsies categorized as normal in patients experiencing unexplained graft function deterioration. This study seeks to employ convolutional neural networks to automate the segmentation of glomerular cells and capillaries and assess their correlation with transplant function. Methods: A total of 215 patients were categorized into three groups. In the Training cohort, glomerular cells and capillaries from 37 patients were manually annotated to train the networks. The Test cohort (24 patients) compared manual annotations vs automated predictions, while the Application cohort (154 protocol transplant biopsies) examined predicted factors in relation to kidney function and prognosis. Results: In the Test cohort, the networks recognized histological structures with Precision, Recall, F-score and Intersection Over Union exceeding 0.92, 0.85, 0.89 and 0.74, respectively. Univariate analysis revealed associations between the estimated glomerular filtration rate (eGFR) at biopsy and relative endothelial area (r = 0.19, P = .027), endothelial cell density (r = 0.20, P = .017), mean parietal epithelial cell area (r = -0.38, P < .001), parietal epithelial cell density (r = 0.29, P < .001) and mesangial cell density (r = 0.22, P = .010). Multivariate analysis retained only endothelial cell density as associated with eGFR (Beta = 0.13, P = .040). Endothelial cell density (r = -0.22, P = .010) and mean podocyte area (r = 0.21, P = .016) were linked to proteinuria at biopsy. Over 44 ± 29 months, 25 patients (16%) reached the primary composite endpoint (dialysis initiation, or 30% eGFR sustained decline), with relative endothelial area, mean endothelial cell area and parietal epithelial cell density below medians linked to this endpoint [hazard ratios, respectively, of 2.63 (P = .048), 2.60 (P = .039) and 3.23 (P = .019)]. Conclusion: This study automated the measurement of intraglomerular cells and capillaries. Our results suggest that the precise segmentation of endothelial and epithelial cells may serve as a potential future marker for the risk of graft loss.