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HTSNPedia:一个关于高血压相关基因的分子视角与风险评估数据库。

HTSNPedia: A Molecular Perspective and Risk Estimator Database for Hypertension-Associated Genes.

作者信息

Sankar Jeyanthi, Arumugam Agnal, Prakash A Antony, Wong Ling Shing, Muthusamy Karthikeyan

机构信息

Pharmacogenomics and CADD Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630 003, India.

Asx Technologies, 53, Metha Nagar, Velachery Main Road, Selaiyur, Chennai, Tamil Nadu, 600 073, India.

出版信息

Biochem Genet. 2025 Aug 25. doi: 10.1007/s10528-025-11232-x.

Abstract

Hypertension is a major public health concern, affecting more than one billion adults worldwide. The etiology of hypertension is associated with various genetic and epigenetic interactions. The candidate genes from various signaling pathways, such as RAAS, KKS and endothelin system, play a significant role in the progression of hypertension. The research aimed to develop a comprehensive knowledge base pertaining to hypertension, which would facilitate the integration of information related to SNPs associated with hypertension, pertinent biological pathways, risk assessment factors, molecular mechanisms, pharmacogenomic aspects of hypertension, a blood pressure calculator, and the existing literature on hypertension. This database has been implemented using HTML and Java programming languages. The deployment of the HTSNPedia database is expected to enhance the efficiency of identifying novel pharmacological drug candidates for the treatment of hypertension. A comprehensive understanding of the interrelationships among signaling pathways, molecular mechanisms, and risk-associated SNPs related to hypertension may significantly contribute to advancements in human health, particularly for individuals affected by this condition. The HTSNPedia is an openly accessible database, available at the following URL: https://www.generisk.in/HTSNPedia/main.html.

摘要

高血压是一个主要的公共卫生问题,全球有超过10亿成年人受其影响。高血压的病因与多种遗传和表观遗传相互作用有关。来自各种信号通路(如肾素-血管紧张素-醛固酮系统、激肽释放酶-激肽系统和内皮素系统)的候选基因在高血压的进展中起重要作用。该研究旨在建立一个关于高血压的综合知识库,这将有助于整合与高血压相关的单核苷酸多态性(SNP)、相关生物途径、风险评估因素、分子机制、高血压的药物基因组学方面、血压计算器以及现有高血压文献的信息。该数据库已使用HTML和Java编程语言实现。HTSNPedia数据库的部署有望提高识别治疗高血压新候选药物的效率。全面了解与高血压相关的信号通路、分子机制和风险相关SNP之间的相互关系,可能会对人类健康的进步做出重大贡献,特别是对于受这种疾病影响的个体。HTSNPedia是一个可公开访问的数据库,可通过以下网址获取:https://www.generisk.in/HTSNPedia/main.html。

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