A pathway-based network analysis of hypertension-related genes

• Published in: Physica A 2016-02, Vol.444, p.928-939
• Main Authors: Wang, Huan, Hu, Jing-Bo, Xu, Chuan-Yun, Zhang, De-Hai, Yan, Qian, Xu, Ming, Cao, Ke-Fei, Zhang, Xu-Sheng
• Format: Article
• Language: English
• Subjects: Complex network; Hub gene; Hypertension; Modular structure; Pathway
• ISSN: 0378-4371; 1873-2119
• DOI: 10.1016/j.physa.2015.10.048

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes. •A network of hypertension-related genes is proposed based on biological pathways.•Statistical and topological characteristics of the gene network are analyzed.•Seven key hub genes of hypertension are determined through integrated centrality.•The modular structure analysis can facilitate the exploration of drug targets.•The network approach provides another perspective to explore disease pathogenesis.