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Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy.
Yan, Qianqian; Zhao, Zihao; Liu, Dongwei; Li, Jia; Pan, Shaokang; Duan, Jiayu; Liu, Zhangsuo.
Affiliation
  • Yan Q; Department of Integrated Traditional and Western Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China.
  • Zhao Z; Research Institute of Nephrology, Zhengzhou University, Zhengzhou, P. R. China.
  • Liu D; Department of Integrated Traditional and Western Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China.
  • Li J; Research Institute of Nephrology, Zhengzhou University, Zhengzhou, P. R. China.
  • Pan S; Department of Integrated Traditional and Western Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China.
  • Duan J; Research Institute of Nephrology, Zhengzhou University, Zhengzhou, P. R. China.
  • Liu Z; Henan Province Research Center for Kidney Disease, Zhengzhou, P. R. China.
Ren Fail ; 46(1): 2337288, 2024 Dec.
Article in En | MEDLINE | ID: mdl-38628140
ABSTRACT
The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Inflammatory Bowel Diseases / Glomerulonephritis, IGA Limits: Animals / Humans Language: En Journal: Ren Fail Journal subject: NEFROLOGIA Year: 2024 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Inflammatory Bowel Diseases / Glomerulonephritis, IGA Limits: Animals / Humans Language: En Journal: Ren Fail Journal subject: NEFROLOGIA Year: 2024 Type: Article