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A pathway-based network analysis of hypertension-related genes

Author

Listed:
  • Wang, Huan
  • Hu, Jing-Bo
  • Xu, Chuan-Yun
  • Zhang, De-Hai
  • Yan, Qian
  • Xu, Ming
  • Cao, Ke-Fei
  • Zhang, Xu-Sheng

Abstract

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.

Suggested Citation

  • Wang, Huan & Hu, Jing-Bo & Xu, Chuan-Yun & Zhang, De-Hai & Yan, Qian & Xu, Ming & Cao, Ke-Fei & Zhang, Xu-Sheng, 2016. "A pathway-based network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 928-939.
    • Handle: RePEc:eee:phsmap:v:444:y:2016:i:c:p:928-939
    DOI: 10.1016/j.physa.2015.10.048
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    References listed on IDEAS

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    1. Wang, Huan & Xu, Chuan-Yun & Hu, Jing-Bo & Cao, Ke-Fei, 2014. "A complex network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 166-176.
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    Cited by:

    1. Xue-Yan Zhang & Tian-Yuan He & Chuan-Yun Xu & Ke-Fei Cao & Xu-Sheng Zhang, 2023. "Theoretical investigation of the pathway-based network of type 2 diabetes mellitus-related genes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-13, June.

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