<b>Functional Characterization of Non-Synonymous SNPs in the Hypertension-Associated AGT Gene Using Bioinformatic Tools</b>

Background: Hypertension, the “silent killer,” is a multifactorial disorder driven by genetic and environmental factors. Approximately 90% of cases are essential hypertension. Despite effective pharmacotherapy, there is no permanent cure; lifestyle modification remains foundational. Within the renin–angiotensin–aldosterone system (RAAS), the angiotensinogen (AGT) gene has been widely investigated and linked to essential hypertension across populations. Objective: To identify potentially pathogenic non-synonymous variants (nsSNPs) in AGT and evaluate their effects on protein structure, stability, and function using comprehensive in-silico analyses. Methods: Functional impact was predicted with SIFT, PolyPhen-2, PhD-SNP, SNP&GO, and PANTHER. Protein stability was assessed with I-Mutant 3.0 and MUpro. Evolutionary conservation was analyzed using ConSurf; functional consequences were explored with MutPred2. Post-translational modifications (PTMs) were screened. Three-dimensional structures were modeled with I-TASSER; wild-type vs mutant conformations were examined in Chimera 1.11 and compared using TM-align. Gene–gene and protein–protein interaction networks were explored using GeneMANIA and STRING, respectively. Results: Among 475 missense variants retrieved, 21 nsSNPs were consistently predicted as deleterious by all five functional tools. Most of these variants decreased predicted protein stability (I-Mutant: 18/21; MUpro: 20/21). Several mapped to highly conserved and functionally exposed positions. Structural modeling indicated measurable deviations between wild-type and mutant models (TM-scores ~0.97–0.99; RMSD ~0.87–1.76 Å). Network analyses highlighted the centrality of AGT within RAAS-related interactions. Conclusion: The study prioritizes 21 AGT nsSNPs with strong in-silico evidence for structural/functional impact. These candidates merit targeted association studies and experimental validation to clarify their roles in hypertension pathophysiology and to inform precision therapeutics.

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Journal
Journal of Health Wellness and Community Research
Published
2025-09-20
DOI
https://doi.org/10.61919/4jj1yk96
Primary Topic
Nutrition, Genetics, and Disease
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article
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article

Functional Characterization of Non-Synonymous SNPs in the Hypertension-Associated AGT Gene Using Bioinformatic Tools

Fazal Jalil, Fahd Baig, Naveed Khan, Aina Sibghat et al.
Journal of Health Wellness and Community Research
Nutrition, Genetics, and Disease
article

Functional Characterization of Non-Synonymous SNPs in the Hypertension-Associated AGT Gene Using Bioinformatic Tools

Fazal Jalil, Fahd Baig, Naveed Khan, Aina Sibghat, Huma Israr, Wagma Gul
article en

Abstract

Background: Hypertension, the “silent killer,” is a multifactorial disorder driven by genetic and environmental factors. Approximately 90% of cases are essential hypertension. Despite effective pharmacotherapy, there is no permanent cure; lifestyle modification remains foundational. Within the renin–angiotensin–aldosterone system (RAAS), the angiotensinogen (AGT) gene has been widely investigated and linked to essential hypertension across populations. Objective: To identify potentially pathogenic non-synonymous variants (nsSNPs) in AGT and evaluate their effects on protein structure, stability, and function using comprehensive in-silico analyses. Methods: Functional impact was predicted with SIFT, PolyPhen-2, PhD-SNP, SNP&GO, and PANTHER. Protein stability was assessed with I-Mutant 3.0 and MUpro. Evolutionary conservation was analyzed using ConSurf; functional consequences were explored with MutPred2. Post-translational modifications (PTMs) were screened. Three-dimensional structures were modeled with I-TASSER; wild-type vs mutant conformations were examined in Chimera 1.11 and compared using TM-align. Gene–gene and protein–protein interaction networks were explored using GeneMANIA and STRING, respectively. Results: Among 475 missense variants retrieved, 21 nsSNPs were consistently predicted as deleterious by all five functional tools. Most of these variants decreased predicted protein stability (I-Mutant: 18/21; MUpro: 20/21). Several mapped to highly conserved and functionally exposed positions. Structural modeling indicated measurable deviations between wild-type and mutant models (TM-scores ~0.97–0.99; RMSD ~0.87–1.76 Å). Network analyses highlighted the centrality of AGT within RAAS-related interactions. Conclusion: The study prioritizes 21 AGT nsSNPs with strong in-silico evidence for structural/functional impact. These candidates merit targeted association studies and experimental validation to clarify their roles in hypertension pathophysiology and to inform precision therapeutics.

Journal of Health Wellness and Community Research
Abdul Wali Khan University Mardan (PK)
Openalex Percentile: Top 72%
Nutrition, Genetics, and Disease
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