Dataset Information

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

ABSTRACT: OBJECTIVE:Obesity and type 2 diabetes (T2D) arise from the interplay between genetic, epigenetic, and environmental factors. The aim of this study was to combine bioinformatics and functional studies to identify miRNAs that contribute to obesity and T2D. METHODS:A computational framework (miR-QTL-Scan) was applied by combining QTL, miRNA prediction, and transcriptomics in order to enhance the power for the discovery of miRNAs as regulative elements. Expression of several miRNAs was analyzed in human adipose tissue and blood cells and miR-31 was manipulated in a human fat cell line. RESULTS:In 17 partially overlapping QTL for obesity and T2D 170 miRNAs were identified. Four miRNAs (miR-15b, miR-30b, miR-31, miR-744) were recognized in gWAT (gonadal white adipose tissue) and six (miR-491, miR-455, miR-423-5p, miR-132-3p, miR-365-3p, miR-30b) in BAT (brown adipose tissue). To provide direct functional evidence for the achievement of the miR-QTL-Scan, miR-31 located in the obesity QTL Nob6 was experimentally analyzed. Its expression was higher in gWAT of obese and diabetic mice and humans than of lean controls. Accordingly, 10 potential target genes involved in insulin signaling and adipogenesis were suppressed. Manipulation of miR-31 in human SGBS adipocytes affected the expression of GLUT4, PPAR?, IRS1, and ACACA. In human peripheral blood mononuclear cells (PBMC) miR-15b levels were correlated to baseline blood glucose concentrations and might be an indicator for diabetes. CONCLUSION:Thus, miR-QTL-Scan allowed the identification of novel miRNAs relevant for obesity and T2D.

SUBMITTER: Gottmann P

PROVIDER: S-EPMC6001404 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

Gottmann Pascal P Ouni Meriem M Saussenthaler Sophie S Roos Julian J Stirm Laura L Jähnert Markus M Kamitz Anne A Hallahan Nicole N Jonas Wenke W Fritsche Andreas A Häring Hans-Ulrich HU Staiger Harald H Blüher Matthias M Fischer-Posovszky Pamela P Vogel Heike H Schürmann Annette A

Molecular metabolism 20180315

<h4>Objective</h4>Obesity and type 2 diabetes (T2D) arise from the interplay between genetic, epigenetic, and environmental factors. The aim of this study was to combine bioinformatics and functional studies to identify miRNAs that contribute to obesity and T2D.<h4>Methods</h4>A computational framework (miR-QTL-Scan) was applied by combining QTL, miRNA prediction, and transcriptomics in order to enhance the power for the discovery of miRNAs as regulative elements. Expression of several miRNAs wa ...[more]

PMID: 29605715

Similar Datasets

Project description:Genome-wide association studies (GWASs) have discovered association of several loci with Type 2 diabetes (T2D), a common complex disease characterized by impaired insulin secretion by pancreatic β cells and insulin signaling in target tissues. However, effect of genetic risk variants on continuous glycemic measures in nondiabetic subjects mainly elucidates perturbation of insulin secretion. Also, the disease associated genes do not clearly converge on functional categories consistent with the known aspects of T2D pathophysiology. We used a systems biology approach to unravel genome to phenome correlation in T2D. We first examined enrichment of pathways in genes identified in T2D GWASs at genome-wide or lower levels of significance. Genes at lower significance threshold showed enrichment of insulin secretion related pathway. Notably, physical and genetic interaction network of these genes showed robust enrichment of insulin signaling and other T2D pathophysiology related pathways including insulin secretion. The network also overrepresented genes reported to interact with insulin secretion and insulin action targeting antidiabetic drugs. The drug interacting genes themselves showed overrepresentation of insulin signaling and other T2D relevant pathways. Next, we generated genome-wide expression profiles of multiple insulin responsive tissues from nondiabetic and diabetic patients. Remarkably, the differentially expressed genes showed significant overlap with the network genes, with the intersection showing enrichment of insulin signaling and other pathways consistent with T2D pathophysiology. Literature search led our genomic, interactomic, transcriptomic and toxicogenomic evidence to converge on TGF-beta signaling, a pathway known to play a crucial role in pancreatic islets development and function, and insulin signaling. Cumulatively, we find that GWAS genes relate directly to insulin secretion and indirectly, through collaborating with other genes, to insulin resistance. This seems to support the epidemiological evidence that environmentally triggered insulin resistance interacts with genetically programmed β cell dysfunction to precipitate diabetes.

Dataset Information

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

Publications

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets