The high prevalence of common metabolic diseases such as type 2 diabetes, driven by bad nutritional habits and low physical activity, is a major worldwide health burden. During the last years, genome-wide association studies found numerous genetic risk loci associated with these diseases, but also with related risk factor traits such as increased lipid levels and obesity. Most identified genetic variants are located in non-coding regions, suggesting that regulatory variants modulating gene expression are major contributors to disease risk. However, the precise regulatory variants, regulated genes and particularly the exact molecular mechanisms modulated at risk loci, remain elusive in most cases. We are interested in identification of such mechanisms at type 2 diabetes risk loci. To find these variants we leverage public domain epigenetic data of regulatory regions and bioinformatics tools. By efficient proteomics, we identify allele- and tissue-specific transcription factors and co-factors. Using diverse molecular and cell biology approaches, such as reporter- and DNA-binding assays, genome-wide expression profiling and genome editing, we assess genotype how the identified factors modulate transcriptional activity, endogenous gene regulation and finally disease specific phenotypes.
For many diseases, genetic variation only partially explains heredity. Epigenetic mechanism such as DNA methylation at CpGs (dinucleotides containing cytosine and guanine) are considered to account for this missing heritability. Recent epigenome-wide association studies found several CpG sites at different gene loci associated with metabolic diseases or related traits such as altered lipid levels. Again, the modulated regulatory mechanisms remain elusive in most cases. In cooperation with the Helmholtz-Zentrum München we focus on recently found lipid level-associated DNA-methylation and want to unravel the precise modulated gene-regulatory mechanisms using similar approaches as for analysis of genetic variants.
Our in-depth analysis of selected type 2 diabetes and lipid metabolism associated genetic- and methylation loci, with the common focus to find precise regulatory mechanisms, may guide identification of previously unknown entry points for personalized intervention.
- Dr Stefanie Hauck (HMGU, Neuherberg, Germany)
- Dr Harald Grallert (HMGU, Neuherberg, Germany )
- Dr Melanie Waldenberger (HMGU, Neuherberg, Germany)
- Prof Ingrid Dahlman (Karolinska Institutet, Stockholm, Sweden)
- Prof Peter Arner (Karolinska Institutet, Stockholm, Sweden)
- Dr Martin Seifert (Genomatix, Munich)
- Prof Bernd Baumann (University of Ulm, Germany)
- Prof Cornelia Brunner (University of Ulm, Germany)
Lee H et al. Allele-specific quantitative proteomics unravels molecular mechanisms modulated by cis-regulatory PPARG locus variation. Nucleic Acids Res. 2017;45(6):3266-3279. doi: 10.1093/nar/gkx105. Pubmed (pdf file).
Claussnitzer M et al. Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms. Cell. 2014;156(1-2):343-58. doi: 10.1016/j.cell.2013.10.058. Pubmed (pdf file).