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

Autor:	O'Connor MJ; Department of Medicine, Massachusetts General Hospital, Boston, MA.; Endocrine Division, Massachusetts General Hospital, Boston, MA.; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA., Schroeder P; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA., Huerta-Chagoya A; Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico., Cortés-Sánchez P; Barcelona Supercomputing Center (BSC), Barcelona, Spain., Bonàs-Guarch S; Barcelona Supercomputing Center (BSC), Barcelona, Spain., Guindo-Martínez M; Barcelona Supercomputing Center (BSC), Barcelona, Spain., Cole JB; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Department of Medicine, Harvard Medical School, Boston, MA.; Center for Basic and Translations Obesity Research, Boston Children's Hospital, Boston, MA., Kaur V; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA., Torrents D; Barcelona Supercomputing Center (BSC), Barcelona, Spain.; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain., Veerapen K; Department of Medicine, Harvard Medical School, Boston, MA.; Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA., Grarup N; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Kurki M; Department of Medicine, Harvard Medical School, Boston, MA.; Stanley Center for Psychiatric Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA., Rundsten CF; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Pedersen O; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Brandslund I; Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark.; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark., Linneberg A; Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Hansen T; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Leong A; Department of Medicine, Massachusetts General Hospital, Boston, MA.; Endocrine Division, Massachusetts General Hospital, Boston, MA.; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Department of Medicine, Harvard Medical School, Boston, MA.; Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA., Florez JC; Department of Medicine, Massachusetts General Hospital, Boston, MA.; Endocrine Division, Massachusetts General Hospital, Boston, MA.; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Department of Medicine, Harvard Medical School, Boston, MA., Mercader JM; Diabetes Unit, Massachusetts General Hospital, Boston, MA.; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA.; Department of Medicine, Harvard Medical School, Boston, MA.
Jazyk:	angličtina
Zdroj:	Diabetes [Diabetes] 2022 Mar 01; Vol. 71 (3), pp. 554-565.
DOI:	10.2337/db21-0545
Abstrakt:	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 case subjects and 279,507 control subjects from 7 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 variants had minor allele frequency of <5% and were each associated with more than a 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 (for interaction, P = 7 × 10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL cholesterol and a 20% increase in triglycerides; colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared with GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes. (© 2022 by the American Diabetes Association.)
Databáze:	MEDLINE
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