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Veselits, M.

Publications and source records attributed to Veselits, M..

2 recordsLinked to original sources

In lupus nephritis, specific in situ inflammatory states are associated with refractory disease and progression to renal failure

In human lupus nephritis (LN), tubulointerstitial inflammation (TII) on biopsy predicts progression to end stage renal disease (ESRD). However, while approximately half of patients with moderate or severe TII develop ESRD, half do not. Therefore, we hypothesized that TII is heterogeneous, with distinct inflammatory states associated with different renal outcomes. We interrogated renal biopsies from LN longitudinal and cross-sectional cohorts using both conventional and highly multiplexed confocal microscopy. To accurately segment cells across whole biopsies, and to understand their spatial relationships, we developed unique computational pipelines by training and implementing several deep learning models and other computer vision techniques. Surprisingly, across biopsies, high B cell densities were strongly associated with protection from ESRD. In contrast, elevated CD4-T cell population densities, which included CD8, {gamma}{delta} and double negative (CD4-CD8-{delta}-, DN) T cells, were associated with both acute refractory renal failure and gradual progression to ESRD. Interestingly, lymphocytes and dendritic cells were organized into discrete clusters or neighborhoods that could be characterized by the enrichment for specific cell populations. B cells were often organized into large neighborhoods with CD4+ T cells including T follicular helper-like cells. In contrast, the CD4-T cell populations formed small cellular neighborhoods whose frequency predicted subsequent progression to ESRD. These data reveal that in LN, specific in situ inflammatory states are associated with refractory disease and progression to ESRD. One sentence summaryUsing deep machine learning to analyze confocal microscopy data, we demonstrate that in lupus nephritis, CD4-T cell populations, including CD8+ and {gamma}{delta} T cells, organize into specific spatial neighborhoods that predict progression to renal failure.

immunology

Intrarenal B cells integrate in situ innate and adaptive immunity in human renal allograft rejection

In human allograft rejection, intrarenal B cell infiltrates identify those with a poor prognosis. However, how intrarenal B cells contribute to rejection is not known. Single cell RNA-sequencing of intrarenal class-switched B cells revealed a unique innate cell transcriptional state resembling murine peritoneal B1 cells (Bin cells). Comparison to the transcriptome of whole renal allograft rejecting tissue revealed that Bin cells existed within a complex autocrine and paracrine network of signaling axes. The immunoglobulins expressed by Bin cells did not bind donor specific antigens nor were they enriched for reactivity to ubiquitously expressed self-antigens. Rather, Bin cells frequently expressed antibodies reactive with renal expressed antigens. Furthermore, local antigens could drive Bin cell proliferation and differentiation into plasma cells expressing self-reactive antibodies. By contributing to local innate immune networks, and expressing antibodies reactive with renal expressed antigens, Bin cells are predicted to amplify local inflammation and tissue destruction.

immunology