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Molecular crosstalk between AHR, CYP1B1, and ITGAM in diabetic nephropathy: Integrated insights from bioinformatics
Seyed Amirhossein Hosseini1,2, Parisa Ajorlou1,2, Pegah Mousavi1
1Endocrinology and Metabolism Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
Abstract:
Chronic inflammation and a progressive loss of kidney function are hallmarks of diabetic nephropathy (DN). Th22 cells are mainly regulated by the transcription factor AHR, which is essential for their differentiation and inflammatory responses. This study aims to investigate the regulatory role of Th22 cells in the progression of DN. The GEO database was used to retrieve the GSE142025 (DN) and GSE135390 (Th22) datasets, which provided transcriptomic profiles for gene expression analysis. WGCNA was employed to identify gene co-expression modules strongly correlated with DN progression. Gene expression levels were validated by real-time PCR in 90 PBMC samples (30 per group: T2DM, DN, and healthy controls). Gene-drug interactions were subsequently predicted using the DGIdb database. In DN, 4006 differentially expressed genes (DEGs) were identified, while 831 DEGs were detected in Th22 cells. After intersecting these DEGs using a Venn diagram tool, 106 common genes were found. Following the construction of a protein-protein interaction network using the STRING database and subsequent analysis in Cytoscape, ITGAM was identified as the central hub gene. Real-time PCR analysis demonstrated significantly elevated expression levels of AHR (a major transcription factor of Th22 cells), ITGAM, and CYP1B1 (a downstream target gene of AHR) in DN patients compared to those with T2DM and healthy controls. Changes in the transcript levels of ITGAM, CYP1B1, and AHR were associated with renal biochemical parameters. Additionally, 60 drugs were predicted to regulate AHR, 12 targeted ITGAM, and 33 targeted CYP1B1. This study highlights the potential role of AHR, ITGAM, and CYP1B1 in the pathogenesis of DN. Their altered expression patterns suggest they could serve as useful biomarkers for monitoring disease progression.
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