Identification of Potential Biomarkers for Hypertensive Nephropathy by Bioinformatics Analysis
DOI:
https://doi.org/10.24036/eksakta/vol25-iss04/537Keywords:
hypertensive nephropathy, biomarkers, bioinformatics, genesAbstract
Hypertensive nephropathy (HN) is a common complication of chronic hypertension that leads to kidney damage. This study aimed to identify potential biomarkers and key pathways associated with HN using bioinformatics tools. Gene data related to HN were retrieved from GeneCards and the Comparative Toxicogenomics Database (CTD), resulting in 89 genes from GeneCards and 10,898 genes from CTD. A Venn diagram revealed 58 overlapping genes, which were then analyzed using Protein-Protein Interaction (PPI) networks and the CytoHubba plugin in Cytoscape. The Maximal Clique Centrality (MCC) algorithm identified 10 hub genes, including ACE, AGT, ACE2, AGTR1, and AGTR2, integral to the renin- angiotensin-aldosterone system (RAAS). Functional enrichment analysis using Gene Ontology (GO) and KEGG pathways revealed that the most significant biological process was regulating systemic arterial blood pressure by the Renin-Angiotensin system, with the renin-angiotensin system pathway being the most highly enriched. Further visualization using ShinyGo highlighted the involvement of key genes in the RAAS pathway. These findings provide valuable insights into the molecular mechanisms underlying HN and suggest that bioinformatics approaches can aid in the identification of specific biomarkers for early diagnosis, non-invasive monitoring, and targeted treatments for HN in the future.
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Copyright (c) 2024 Ariski Fajarido, Fadilah Fadilah, Wawaimuli Arozal
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