ECEESPE2025 Poster Presentations Diabetes and Insulin (143 abstracts)
Partitioning the genetic risk of obesity and type 2 diabetes using single-cell multi-omics of the gastrointestinal tract
Malte Thodberg 1 , Kata Krizic 1 , Jacob Antonsen 2 , Shanshan He 1 , Laura Pikkupeura 1 , Thomas Koefoed 1 , Rikard Fred 1 , Charlotte Kruse 1 , Benedicte Kapel 1 , Marina Kanellou 1 , Lars Nannestad 2 & Torben Hansen 1
1University of Copenhagen, Novo Nordisk Foundation Center for Basic Metabolic Research, Copenhagen, Denmark; 2Bispebjerg & Frederiksberg Hospital, 2Digestive Disease Centre, Copenhagen, Denmark
JOINT1307
The worldwide increase in the prevalence of Type 2 Diabetes (T2D) and obesity constitutes a major threat to global health; however, the complex nature of these diseases is severely hampering the development of prognostic tools and clinical interventions. Both T2D and obesity have a strong genetic component; yet, the functional impact of the identified genetic variants in terms of causal genes, cell types, and organs remains largely unknown. The gastrointestinal (GI) tract is located at the junction between the gut microbiome and the gut-brain axis, which links intestinal function to the central nervous system, resulting in changes in appetite and behavior. Due to the complex regionality and cellular composition of the GI tract, it is largely unknown to what extent genetics play a role in metabolic diseases mediated by the GI tract, in particular, T2D and obesity. We are performing single-cell sequencing on human biopsies from multiple locations in the colon using the 10x Multiome assay for gene expression and chromatin accessibility. This allows us to map the location, activity, and interaction of promoters and enhancers in individual cell types and integrate these with genome-wide association studies (GWASs) of T2D and obesity. Using the resulting multi-omic and cell type-specific map of gene regulation, we can i) partition the genetic risk of T2D and obesity across cell types of the GI tract, ii) prioritize causal genetic variants and genes, and iii) perform data-driven stratification of T2D and obesity patients based on their cell type-specific polygenic risks. Ultimately, this will lead to novel molecular clinical targets and non-invasive prognostic tools for T2D and obesity.
Volume 110
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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