Central regulation of metabolism in the Pers Group
The Pers Group investigates molecular processes that regulate energy balance and glucose control and develops computational tools to prioritize cell type specific risk pathways for complex traits.
The brain receives perpetual information flow from internal metabolic cues including endocrine factors, metabolites, nutrients, and neuronal signals. This biological information integrates with environmental input and is processed into a concerted appropriate physiological or behavioural response. The Pers Group’s primary focus is to identify molecular processes regulating energy balance and glucose control.
To achieve this, we use in vivo rodent models, single cell transcriptomics profiling, large scale genetic association data for various metabolic risk phenotypes and computational data integration techniques. We also develop computational tools to predict complications in patients with chronic diseases such as type 2 diabetes based on Danish population-wide electronic health registry data.
“Gene set analysis for interpreting genetic studies”
Published in Human Molecular Genetics in 2016 this review examines different types of gene sets, discusses how inconsistencies in gene set definitions impact on gene set analysis, describes how gene set analysis has helped to elucidate biology and outlines potential future directions.
“Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes”
Published in Human Molecular Genetics in 2016 this study uses a data-driven approach to show that genes in associated loci are highly expressed in cortical brain areas, that they are enriched for ion channel pathways and contain 62 genes that are functionally related to each other and hence represent promising candidates for experimental follow up.
“Biological interpretation of genome-wide association studies using predicted gene functions”
Published in Nature Communications in 2015 this article presents DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed.
Staff of the Pers Group
Group leader: Associate Professor Tune Pers