Identification of hypertension-associated bacterial key genes as potential targets and therapeutic agents through integrated bioinformatics approach.

Abstract

Hypertension (HTN) is a major global health burden and a leading risk factor for cardiovascular morbidity and mortality. Although numerous studies have explored host genetic factors and molecular mechanisms underlying HTN, increasing evidence indicates that gut microbiota dysbiosis also contributes to disease development. However, the specific microbial genes involved in HTN pathogenesis and their potential therapeutic targeting remain largely unexplored. This study aimed to identify HTN-associated differentially abundant bacterial genes (DAGs), prioritize bacterial key genes (bKGs) from among them, and repurpose potential therapeutic agents targeting these bKGs using an integrated bioinformatics framework. A total of 167 stool (fecal) microbiome samples, comprising 72 samples from HTN patients and 95 samples from HCs, were analyzed using publicly available 16 S rRNA sequencing data. After quality processing and clustering at 97% similarity, 95,361 representative operational taxonomic units were obtained. Microbial diversity analysis revealed significant alterations in community composition between HTN and HC groups. Differential abundance analysis identified 24 significantly altered bacterial genera associated with HTN. Functional prediction analysis further revealed 28 differentially abundant metabolic pathways and 631 differentially abundant bacterial genes (DAGs) potentially involved in HTN pathogenesis. From these DAGs, protein-protein interaction network analysis prioritized ten hub genes as bKGs (alsB, ampC, gsiB, araC, coaA, dnaB, fruA, ssuA, minE and tsx) representing potential microbial therapeutic targets. Structure-based molecular docking identified five approved drugs, namely Azilsartan, Eplerenone, Candesartan, Conivaptan, and Telmisartan, as top-ranked compounds exhibiting strong binding affinities toward the proposed targets. ADMET evaluation suggested favorable pharmacokinetic and safety profiles for Azilsartan, Eplerenone, and Candesartan. Furthermore, molecular dynamics simulation analyses confirmed that Eplerenone and Candesartan exhibited greater structural stability and sustained binding interactions, suggesting their potential as promising therapeutic candidates for HTN management. Therefore, this study identifies microbial gene signatures potentially involved in HTN and proposes a microbiome-guided drug repurposing strategy targeting bacterial functional pathways. These findings provide novel insights into microbiota-host interactions in HTN and highlight promising therapeutic candidates that warrant further experimental and clinical validation.