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Single-cell transcriptomic analysis of PBMCs from IgAN patients

GSE285335 Homo sapiens Expression profiling by high throughput sequencing 26 samples 2026/01/21 GPL24676
Summary
IgA nephropathy (IgAN), the most common primary glomerulonephritis, is a significant cause of chronic kidney disease. While previous studies have highlighted the role of immune cells in IgAN development, the disease’s heterogeneous clinical presentation and prognosis have hindered a comprehensive understanding of its specific pathogenesis. This study aimed to identify circulating immune cell subsets linked to the progression of IgAN. Peripheral blood samples were obtained from 9 healthy controls and 17 biopsy-proven IgAN patients, and stratified into early- and late-stage groups based on their estimated glomerular filtration rate (eGFR) at the time of blood sampling. To characterize IgAN-specific immune cell profiles and underlying regulatory mechanisms, single-cell RNA sequencing was conducted to observe distinct immune cell profiles and transcriptomic differences between the IgAN groups. Notably, CD8+ T cells, particularly IL-7Rαlow effector memory, exhibited a significant correlation with the disease progression. Trajectory analysis highlighted distinct CD8+ T-cell developmental patterns, with the early-stage group showing unique enrichment of memory CD8+ T cells. Gene expression profiling of CD8+ T-cell clusters indicated differences in activation and differentiation, emphasizing the critical role of CD8+ T cells in IgAN progression. In contrast, CD4+ T cells and B cells exhibited limited correlation with disease progression. The present transcriptome profiling underscores the prognostic significance of CD8+ T-cell subpopulations in IgAN progression. The findings highlight their potential as therapeutic targets and offers novel insights into the role of circulating immune cells in the progression of IgAN.
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NCBI GEO page ↗ Paper (PMID 41466033) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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