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BioMed Research International
Volume 2015 (2015), Article ID 619730, 9 pages
http://dx.doi.org/10.1155/2015/619730
Research Article

Network-Based Association Study of Obesity and Type 2 Diabetes with Gene Expression Profiles

1Department of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
2National Clinical Research Center of Kidney Disease, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210016, China
3Shanghai Center for Bioinformation Technology, Shanghai 201203, China

Received 29 December 2014; Accepted 5 February 2015

Academic Editor: Xiao Chang

Copyright © 2015 Siyi Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The increased prevalence of obesity and type 2 diabetes (T2D) has become an important factor affecting the health of the human. Obesity is commonly considered as a major risk factor for the development of T2D. However, the molecular mechanisms of the disease relations are not well discovered yet. In this study, the combination of multiple differential expression profiles and a comprehensive biological network of obesity and T2D allowed us to identify and compare the disease-responsive active modules and subclusters. The results demonstrated that the connection between obesity and T2D mainly relied on several pathways involved in the digestive metabolism, immunization, and signal transduction, such as adipocytokine, chemokine signaling pathway, T cell receptor signaling pathway, and MAPK signaling pathways. The relationships of almost all of these pathways with obesity and T2D have been verified by the previous reports individually. We also found that the different parts in the same pathway are activated in obesity and T2D. The association of cancer, obesity, and T2D was identified too here. As a conclusion, our network-based method not only gives better support for the close connection between obesity and T2D, but also provides a systemic view in understanding the molecular functions underneath the links. It should be helpful in the development of new therapies for obesity, T2D, and the associated diseases.