Year: 2020
Type: review
Study design: Observational Study
Abstract: CONTEXT: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity. OBJECTIVE: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies. DESIGN: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models. RESULTS: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity. CONCLUSION: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.
Authors: Harshal A Deshmukh, Anne Lundager Madsen, Ana Viñuela, Christian Theil Have, Niels Grarup, Andrea Tura, Anubha Mahajan, Alison J Heggie, Robert W Koivula, Federico De Masi, Konstantinos K Tsirigos, Allan Linneberg, Thomas Drivsholm, Oluf Pedersen, Thorkild I A Sørensen, Arne Astrup, Anette A P Gjesing, Imre Pavo, Andrew R Wood, Hartmut Ruetten, Angus G Jones, Anitra D M Koopman, Henna Cederberg, Femke Rutters, Martin Ridderstrale, Markku Laakso, Mark I McCarthy, Tim M Frayling, Ele Ferrannini, Paul W Franks, Ewan R Pearson, Andrea Mari, Torben Hansen, Mark Walker
Institutions: Newcastle University, University of Copenhagen, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Geneva, National Research Council, Centre for Human Genetics, University of Oxford, Oxford Centre for Diabetes, Endocrinology and Metabolism, Lund University, Skåne University Hospital, Technical University of Denmark, Frederiksberg Hospital, Bispebjerg Hospital, Novo Nordisk Foundation, University of Exeter, Sanofi (Germany), NIHR Exeter Clinical Research Facility, Amsterdam UMC Location Vrije Universiteit Amsterdam, Helsinki University Hospital, University of Eastern Finland, Istituto di Fisiologia Clinica, Harvard University, Umeå University, University of Dundee
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,750
Funders: Hjerteforeningen, Sundhed og Sygdom, Det Frie Forskningsråd, Velux Fonden, Wellcome Trust, European Federation of Pharmaceutical Industries and Associations, National Institute for Health and Care Research, European Commission, University of Bristol, National Research Foundation, European Foundation for the Study of Diabetes, Danmarks Grundforskningsfond, Københavns Universitet, Lundbeckfonden, Novo Nordisk, Copenhagen Graduate School for Nanoscience and Nanotechnology, Novo Nordisk Fonden, Novo Nordisk Foundation Center for Basic Metabolic Research, H. Lundbeck A/S, Diabetesforeningen, Medical Research Council
Awards: G1073258374, G1093531541, G119964413, DIabetes REsearCh on patient sTratification, G1876651919, G2885439837, G3207356259, Development of a systems biomedicine approach for risk identification, prevention and treatment of type 2 diabetes, G342286053, G393177772, G4504918650, G5476537510, G553931797, G5702163051, G5893854107, G6153457846, G6394858868, G7350470161, Stratified medicine in Type 2 diabetes: Insights from the study of drug response., Stratified medicine in Type 2 diabetes: Insights from the study of drug response., G8351935874, Integrating clinical features and biomarkers to improve diabetes classification and treatment in young adults, NIHR Senior Investigator Award
OpenAlex ID: W3087077297