CALL FOR PAPERS Understanding the Mechanisms of Disease Using Biomarkers Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk

Vaquero AR, Ferreira NE, Omae SV, Rodrigues MV, Teixeira SK, Krieger JE, Pereira AC. Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk. Physiol Genomics 44: 903–914, 2012. First published August 7, 2012; doi:10.1152/physiolgenomics.00030.2012.—The single nucleotide polymorphism (SNP) within the TCF7L2 gene, rs7903146, is, to date, the most significant genetic marker associated with Type 2 diabetes mellitus (T2DM) risk. Nonetheless, its functional role in disease pathology is poorly understood. The aim of the present study was to investigate, in vascular smooth muscle cells from 92 patients undergoing aortocoronary bypass surgery, the contribution of this SNP in T2DM using expression levels and expression correlation comparison approaches, which were visually represented as gene interaction networks. Initially, the expression levels of 41 genes (seven TCF7L2 splice forms and 40 other T2DM relevant genes) were compared between rs7903146 wild-type (CC) and T2DM-risk (CT TT) genotype groups. Next, we compared the expression correlation patterns of these 41 genes between groups to observe if the relationships between genes were different. Five TCF7L2 splice forms and nine genes showed significant expression differences between groups. RXR gene was pinpointed as showing the most different expression correlation pattern with other genes. Therefore, T2DM risk alleles appear to be influencing TCF7L2 splice form’s expression in vascular smooth muscle cells, and RXR gene is pointed out as a treatment target candidate for risk reduction in individuals with high risk of developing T2DM, especially individuals harboring TCF7L2 risk genotypes.