Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes

Publication date: Available online 27 January 2020Source: Genes & DiseasesAuthor(s): Fengji Liang, Yuan Quan, Andong Wu, Ying Chen, Ruifeng Xu, Yuexing Zhu, Jianghui XiongAbstractInsulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0....
Source: Genes and Diseases - Category: Genetics & Stem Cells Source Type: research