Immune cell quantification of in situ inflammation partitions human lupus nephritis into mechanistic subtypes

狼疮性肾炎 炎症 免疫系统 免疫学 肾炎 系统性红斑狼疮 医学 生物 计算生物学 病理 疾病
作者
Gabriel Casella,Madeleine S. Durkee,Junting Ai,Thao Cao,Satoshi Hara,Michael S. Andrade,Deepjyoti Ghosh,Daming Shao,Anthony Chang,Kichul Ko,Anita S. Chong,Maryellen L. Giger,Marcus R. Clark
出处
期刊:Journal of Clinical Investigation [American Society for Clinical Investigation]
卷期号:135 (21) 被引量:2
标识
DOI:10.1172/jci192669
摘要

BACKGROUNDIn human lupus nephritis (LuN), tubulointerstitial inflammation (TII) is prognostically more important than glomerular inflammation. However, a comprehensive understanding of both TII complexity and heterogeneity is lacking.METHODSHerein, we used high-dimensional confocal microscopy, spatial transcriptomics, and specialized computer vision techniques to quantify immune cell populations and localize these within normal and diseased renal cortex structures. With these tools, we compared LuN to renal allograft rejection (RAR) and normal kidney tissues on 54 deidentified biopsies.RESULTSIn both LuN and RAR, the 33 characterized immune cell populations formed discrete subgroups whose constituents covaried in prevalence across biopsies. In both diseases, these covariant immune cell subgroups organized into the same unique niches. Therefore, inflammation could be resolved into trajectories representing the relative prevalence and density of cardinal immune cell members of each covariant subgroup. Indeed, in any one biopsy, the inflammatory state could be characterized by quantifying constituent immune cell trajectories. Remarkably, LuN heterogeneity could be captured by quantifying a few myeloid immune cell trajectories, while RAR was more complex with additional T cell trajectories.CONCLUSIONSOur studies identify rules governing renal inflammation and thus provide an approach for resolving LuN into discrete mechanistic categories.FUNDINGNIH (U19 AI 082724 [MRC], R01 AI148705 [MRC and ASC]), Chan Zuckerberg Biohub (MRC), and Lupus Research Alliance (MRC).
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