ArticleScientific reports2025
Integrating bioinformatics and metabolomics to identify potential biomarkers of hypertensive nephropathy.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Metabolomics and Precision Medicine in Resistant Hypertension: Pathophysiological Insights, Biomarker Discovery, and Translational Strategies.International journal of hypertension · 2026Review
- Integrative Bioinformatics-Guided Analysis of Glomerular Transcriptome Implicates Potential Therapeutic Targets and Pathogenesis Mechanisms in IgA Nephropathy.Bioengineering (Basel, Switzerland) · 2025Article
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11 authors.
Funding
Abstract
Hypertensive nephropathy (HN), caused by long-term poorly controlled hypertension, is the second common cause of end-stage renal disease after diabetes mellitus, but the pathogenesis of HN is unclear. The purpose of this study was to identify the biological pathways involved in the progression of HN and bile acid (BA)-related biomarkers, and to analyze the role of bile acids in HN. Download gene microarray data from Gene Expression Omnibus. Differentially expressed genes (DEGs) associated with HN were identified, and then DEGs were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. A protein-protein interaction (PPI) network was established using DEGs to identify BA-related hub genes in combination with bile acid identical targets. An animal model of early hypertensive nephropathy was established using SHR and the concentrations of 39 bile acids were measured quantitatively in the renal cortex to screen for significantly different concentrations and to analyze the correlation between bile acid concentrations and blood pressure. A total of 398 DEGs were screened. The results of enrichment analysis identified multiple biological pathways associated with hypertension, nephropathy and bile acids. Combining PPI network and bile acid-related targets, three BA-related hub genes (APOE, ALB, SERPINA1) were identified. Quantitative analysis of bile acids revealed significant differences in the concentrations of seven bile acids (DCA, CDCA, UDCA, UCA, CA, TDCA, TCDCA). The concentrations of these bile acids showed a positive correlation with blood pressure values in SHR, with CA, DCA and TDCA showing a stronger correlation and specificity with blood pressure in SHR. Three BA-related hub genes (APOE, ALB, SERPINA1) may be involved in the early stages of HN. The concentrations of multiple bile acids were significantly elevated in the early stages of HN, with CA, DCA and TDCA being more correlated and specific with blood pressure and having higher diagnostic value. These BA-related hub genes and BAs may be involved in disease progression in the early stages of HN.
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