A bioinformatics approach to the identification of type 2 diabetes susceptibility gene variants in Africans

Type 2 diabetes (T2D) is a metabolic disease that results from complex interactions between the environment, the genetic variation and epigenetic regulation of gene expression in individuals. Beta-cell dysfunction and insulin resistance are regarded as the hallmarks of the disease as the common presentation of T2D is the inability of beta-cells to adequately respond to the insulin demands of the body. The prevalence of T2D in Africa, and particularly South Africa, is on the rise. This is very likely the result of the combination of genetic susceptibility with increasing availability and accessibility of relatively cheap, highly palatable, calorie-dense meals with no corresponding lifestyle adjustment. This study aims to utilize available data from GWAS and gene expression arrays to identify potential variants that likely influence T2D susceptibility in African populations. Two public data repositories were mined – the National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) and the National Human Genome Research Institute’s (NHGRI) GWAS Catalog. The criteria for selecting the studies for inclusion were based on ten descriptive T2D-related terms taken from the GWAS catalog’s pre-defined search categories. These terms were also applied to the selection of gene expression studies in GEO. These terms are: “fasting glucose-related traits”, “fasting insulin-related traits”, “fasting plasma glucose”, “insulin resistance/response”, “insulin traits”, “diabetes-related insulin traits”, “pro insulin levels” “Type 2 diabetes”, “type 2 diabetes and 6 quantitative traits” and “type 2 diabetes and other traits”. Ten Affymetrix platform-based studies in human tissues were chosen from GEO using these criteria. A Benjamin-Hochberg adjusted p-value of 0.05 was set as a cut-off for significant differentially expressed genes (7,887 genes) with 497 genes occurring in two or more studies, based on tissue- or array-type, considered candidates for downstream analysis. The GWAS catalogue presented 175 “reported” genes and 218 SNPs from 51 studies matching the set T2D-related criteria. Functional analyses done with the Database for Annotation, Visualization and Integrated Discovery (DAVID) on both the GWAS and expression studies genes lists