Discover the network mechanisms underlying the connections between aging and age-related diseases

Jialiang Yang, Tao Huang, Won Min Song, Francesca Petralia, Charles V. Mobbs, Bin Zhang, Yong Zhao, Eric E. Schadt, Jun Zhu, Zhidong Tu

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Although our knowledge of aging has greatly expanded in the past decades, it remains elusive why and how aging contributes to the development of age-related diseases (ARDs). In particular, a global mechanistic understanding of the connections between aging and ARDs is yet to be established. We rely on a network modelling named "GeroNet" to study the connections between aging and more than a hundred diseases. By evaluating topological connections between aging genes and disease genes in over three thousand subnetworks corresponding to various biological processes, we show that aging has stronger connections with ARD genes compared to non-ARD genes in subnetworks corresponding to "response to decreased oxygen levels", "insulin signalling pathway", "cell cycle", etc. Based on subnetwork connectivity, we can correctly "predict" if a disease is age-related and prioritize the biological processes that are involved in connecting to multiple ARDs. Using Alzheimer's disease (AD) as an example, GeroNet identifies meaningful genes that may play key roles in connecting aging and ARDs. The top modules identified by GeroNet in AD significantly overlap with modules identified from a large scale AD brain gene expression experiment, supporting that GeroNet indeed reveals the underlying biological processes involved in the disease.

Original languageEnglish
Article number32566
JournalScientific Reports
Volume6
DOIs
StatePublished - 1 Sep 2016

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