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Journal of Diabetes Research
Volume 2013, Article ID 970435, 9 pages
http://dx.doi.org/10.1155/2013/970435
Research Article

Identifying Candidate Genes for Type 2 Diabetes Mellitus and Obesity through Gene Expression Profiling in Multiple Tissues or Cells

1School of Bioscience and Bioengineering, Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, South China University of Technology, Guangzhou 510006, China
2Chinese PLA General Hospital, Beijing 100853, China
3Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510555, China

Received 16 July 2013; Revised 30 September 2013; Accepted 25 October 2013

Academic Editor: Mark A. Yorek

Copyright © 2013 Junhui Chen 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

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.