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Updated: May 20, 2026

Detection of MicroRNA Expression in the Kidneys of Immunoglobulin A Nephropathic Mice
Published on: July 8, 2020
Combination scRNA-seq with GWAS identifies genetic risk factors in IgA nephropathy: An observational study
Jinhua Zhang1,2, Shuo Lu1, Guancan Liang3
1Department of Kidney Transplantation, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Abstract:
IgA nephropathy (IgAN) is a common autoimmune kidney disease and a leading cause of chronic kidney disease (CKD), yet the immune cell-specific mechanisms underlying disease progression remain incompletely understood, particularly with respect to macrophage heterogeneity. We analyzed single-cell RNA sequencing (scRNA-seq) data from IgAN and CKD kidney samples to characterize macrophage subpopulations and identify differentially expressed genes. Mendelian randomization analyses using publicly available genome-wide association study data were performed as an exploratory approach to prioritize macrophage-associated genes potentially linked to IgAN risk. Bulk RNA-seq datasets were used for transcriptomic validation. In silico molecular docking was conducted to explore potential small-molecule interactions with prioritized targets. Alternatively activated macrophages were the predominant macrophage subpopulation in both IgAN and CKD samples compared with controls. Exploratory Mendelian randomization analyses highlighted several macrophage-associated genes, including RGS1 and HLA-DPA1, as candidates potentially linked to IgAN susceptibility. Bulk RNA-seq analyses showed downregulation of RGS1 and upregulation of HLA-DPA1 in IgAN, supporting their transcriptional relevance. Molecular docking suggested isotretinoin as a potential small-molecule interactor with RGS1, although this finding is based solely on computational prediction. This integrative, hypothesis-generating study highlights the expansion of alternatively activated macrophage in IgAN and prioritizes macrophage-associated genes that may contribute to disease susceptibility. These findings provide a computational framework for future experimental validation and mechanistic studies, rather than definitive evidence of causality or therapeutic efficacy.
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