Allogeneic CD4 T Cells Sustain Effective BK Polyomavirus-Specific CD8 T Cell Response in Kidney Transplant Recipients.

Introduction: BK polyomavirus-associated nephropathy (BKPyVAN) is a significant complication in kidney transplant recipients (KTRs), associated with a higher level of plasmatic BK polyomavirus (BKPyV) replication and leading to poor graft survival. Methods: We prospectively followed-up with 100 KTRs with various degrees of BKPyV reactivation (no BKPyV reactivation, BKPyV-DNAuria, BKPyV-DNAemia, and biopsy-proven BKPyVAN [bp-BKPyVAN], 25 patients per group) and evaluated BKPyV-specific T cell functionality and phenotype. Results: We demonstrate that bp-BKPyVAN is associated with a loss of BKPyV-specific T cell proliferation, cytokine secretion, and cytotoxic capacities. This severe functional impairment is associated with an overexpression of lymphocyte inhibitory receptors (programmed cell death 1 [PD1], cytotoxic T lymphocyte-associated protein 4, T cell immunoreceptor with Ig and ITIM domains, and T cell immunoglobulin and mucin domain-containing-3), highlighting an exhausted-like phenotype of BKPyV-specific CD4 and CD8 T cells in bp-BKPyVAN. This T cell dysfunction is associated with low class II donor-recipient human leukocyte antigen (HLA) divergence. In contrast, in the context of higher class II donor-recipient HLA (D/R-HLA) divergence, allogeneic CD4 T cells can provide help that sustains BKPyV-specific CD8 T cell responses. In vitro, allogeneic HLA-mismatched CD4 T cells rescue BKPyV-specific CD8 T cell responses. Conclusion: Our findings suggest that in KTRs, allogeneic CD4 T cells can help to maintain an effective BKPyV-specific CD8 T cell response that better controls BKPyV replication in the kidney allograft and may protect against BKPyVAN.

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients.

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.