Functional mechanisms for type 2 diabetes-associated genetic variants

• Published in: Journal of diabetes and its complications 2015-05, Vol.29 (4), p.497-501
• Main Authors: Zhu, Xiao-Wei, Deng, Fei-Yan, Wu, Long-Fei, Tang, Zai-Xiang, Lei, Shu-Feng
• Format: Article
• Language: English
• Subjects: Alpha-Ketoglutarate-Dependent Dioxygenase FTO; Binding sites; Diabetes; Diabetes Mellitus, Type 2 - epidemiology; Diabetes Mellitus, Type 2 - genetics; DNA-Binding Proteins - genetics; Endocrinology & Metabolism; eQTL; Functional mechanism; Gene expression; Genetic Association Studies; Genetic Predisposition to Disease; Genomes; Genomics; Humans; Integrative analysis; Neuregulin-1 - genetics; Phenotype; Polymorphism, Single Nucleotide; Proteins - genetics; Quantitative Trait Loci - genetics; RNA-Binding Proteins - genetics; SNP; Statistical analysis; Studies; Type 2 diabetes
• ISSN: 1056-8727; 1873-460X
• DOI: 10.1016/j.jdiacomp.2015.02.007

Abstract Aims Type 2 diabetes (T2D) is a complex endocrine and metabolic disorder, characterized by hyperglycemia due to insulin resistance and relative lack of insulin. Several recent studies have identified a large number of genetic loci associated with T2D without exploring functional mechanisms underlying the associations. This study established integrative analyses to detect the functional mechanisms for T2D-related associations. Methods Based on the public available datasets and resources, this study performed integrative analyses (gene relationships among implicated loci (GRAIL), expression quantitative trait loci (eQTL) analysis, differential gene expression analysis and functional prediction analysis) to detect the molecular functional mechanisms underlying the associations. Results Two single nucleotide polymorphisms (SNPs) (rs7593730, rs2439312) have been found to act as cis-effect regulators of two corresponding eQTL genes (RBMS1, NRG1) among 252 selected (P < E-4) genetic associations that were archived in the public databases. These two non-HLA genes were also differentially expressed in T2D-related cell groups. The two SNPs were predicted as regulatory sites by utilizing online prediction tools. Conclusions This study detected potential regulatory mechanisms underlying the associations between T2D and two identified SNPs. Integrative analysis can be used to provide suggestive clues for the molecular functional mechanisms in T2D.