Polymorphisms in miRNA binding sites involved in metabolic diseases in mice and humans

Abstract

Type 2 diabetes and obesity are well-studied metabolic diseases, which are based on genetic and epigenetic alterations in combination with an obesogenic lifestyle. The aim of this study was to test whether SNPs in miRNA-mRNA binding sites that potentially disrupt binding, elevate the expression of miRNA targets, which participate in the development of metabolic diseases. A computational approach was developed that integrates transcriptomics, linkage analysis, miRNA-target prediction data, and sequence information of a mouse model of obesity and diabetes. A statistical analysis demonstrated a significant enrichment of 566 genes for a location in obesity-and diabetes-related QTL. They are expressed at higher levels in metabolically relevant tissues presumably due to altered miRNA-mRNA binding sites. Of these, 51 genes harbor conserved and impaired miRNA-mRNA-interactions in human. Among these, 38 genes have been associated to metabolic diseases according to the phenotypes of corresponding knockout mice or other results described in the literature. The remaining 13 genes (e.g. Jrk, Megf9, Slfn8 and Tmem132e) could be interesting candidates and will be investigated in the future. Obesity, the excessive accumulation of body fat, is a lifestyle-driven as well as genetically heritable disorder, and a major risk factor for secondary diseases like type 2 diabetes (T2D) 1. In the past, several studies identified candidate disease genes by human genome-wide association studies (GWAS) or linkage analysis of inbreed mouse strains 2. Most studies identified different types of variants, which lead to an impaired protein function or different regulatory effects. However, investigations with respect to genomic binding sites of other translational regulators, such as non-coding RNAs, are still in an early state for obesity and type 2 diabetes. miRNAs are small non-coding RNAs of a length of 19-24 nucleotides that alter the expression or translation of the corresponding target genes 3. The target prediction of miRNAs is still inaccurate, resulting in a high false-positive rate. The combination of different prediction tools 4 , transcriptomics 5,6 , pathway analysis and the examination of a biologically meaningful context is important to lower the false-positive rate 7. In our previous study, the validity of an integrative approach was confirmed and led to the identification of miR-31 and the elucidation of its role in adipogenesis, also showing that results obtained for mice were successfully translated to human 8. We have also demonstrated that the combination of a computational framework and a linkage analysis of several mouse strains, that differ in their diabetes susceptibility, is indeed sufficient to narrow down the critical genomic region and identify genes, which are relevant for the metabolic syndrome 9. The aim of this study was to investigate to which extent genetic variants localized in quantitative trait loci (QTL) result in a loss of miRNA-mRNA binding, thereby affecting the expression of target genes in metabolically...

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