American Diabetes Association
2 files

Recessive Genome-wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes

posted on 2021-12-03, 21:10 authored by Mark J. O’Connor, Philip Schroeder, Alicia Huerta-Chagoya, Paula Cortés-Sánchez, Silvía Bonàs-Guarch, Marta Guindo-Martínez, Joanne B. Cole, Varinderpal Kaur, David Torrents, Kumar Veerapen, Niels Grarup, Mitja Kurki, Carsten F. Rundsten, Oluf Pedersen, Ivan Brandslund, Allan Linneberg, Torben Hansen, Aaron Leong, Jose C. Florez, Josep M. Mercader
Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 cases and 279,507 controls from seven European-ancestry cohorts including the UK Biobank. We identified 51 loci associated with type 2 diabetes, including five variants undetected by prior additive analyses. Two of the five had minor allele frequency less than 5% and were each associated with more than doubled risk in homozygous carriers. Using two additional cohorts, FinnGen and a Danish cohort, we replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19, P=1´10-16) and a stronger effect in men than in women (interaction P=7´10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL and a 20% increase in triglycerides, and colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared to GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.


American Diabetes Association 1-19-ICTS-068 MINECO x FJCI-2017-32090 U.S. Department of Health and Human Services > National Institutes of Health > National Human Genome Research Institute U01HG011723 NIDDK x K24 DK110550 T32 DK110919