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Title:
Identification of novel high-impact recessively inherited type 2 diabetes risk variants in the Greenlandic population | Diabetologia
Description:
Aims/hypothesis In a recent study using a standard additive genetic model, we identified a TBC1D4 loss-of-function variant with a large recessive impact on risk of type 2 diabetes in Greenlanders. The aim of the current study was to identify additional genetic variation underlying type 2 diabetes using a recessive genetic model, thereby increasing the power to detect variants with recessive effects. Methods We investigated three cohorts of Greenlanders (B99, nโ=โ1401; IHIT, nโ=โ3115; and BBH, nโ=โ547), which were genotyped using Illumina MetaboChip. Of the 4674 genotyped individuals passing quality control, 4648 had phenotype data available, and type 2 diabetes association analyses were performed for 317 individuals with type 2 diabetes and 2631 participants with normal glucose tolerance. Statistical association analyses were performed using a linear mixed model. Results Using a recessive genetic model, we identified two novel loci associated with type 2 diabetes in Greenlanders, namely rs870992 in ITGA1 on chromosome 5 (OR 2.79, pโ=โ1.8โรโ10โ8), and rs16993330 upstream of LARGE1 on chromosome 22 (OR 3.52, pโ=โ1.3โรโ10โ7). The LARGE1 variant did not reach the conventional threshold for genome-wide significance (pโ<โ5โรโ10โ8) but did withstand a study-wide Bonferroni-corrected significance threshold. Both variants were common in Greenlanders, with minor allele frequencies of 23% and 16%, respectively, and were estimated to have large recessive effects on risk of type 2 diabetes in Greenlanders, compared with additively inherited variants previously observed in European populations. Conclusions/interpretation We demonstrate the value of using a recessive genetic model in a historically small and isolated population to identify genetic risk variants. Our findings give new insights into the genetic architecture of type 2 diabetes, and further support the existence of high-effect genetic risk factors of potential clinical relevance, particularly in isolated populations. Data availability The Greenlandic MetaboChip-genotype data are available at European Genome-Phenome Archive (EGA; https://ega-archive.org/ ) under the accession EGAS00001002641.
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Keywords {๐}
diabetes, type, pubmed, genetic, article, association, google, scholar, variants, model, cas, itga, study, recessive, large, risk, variant, insulin, individuals, health, greenlandic, central, data, glucose, samples, population, effect, studies, research, analyses, traits, allele, loci, table, genet, greenlanders, effects, performed, european, estimated, yupik, additive, identified, power, statistical, results, nat, gwas, denmark, esm,
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oluf pedersenย &ย torben hansen genome-wide trans-ancestry meta-analysis emil jรธrsboe cohort profile oluf pedersen uk/resources/downloads/human/hapmap3 genome-wide association study genome-wide association studies anti-human insulin-specific antibody study-wide significance threshold transcriptomic profiles genome-wide significant variant original author genome-wide significance bonferroni-corrected significance threshold institutional review boards cross-sectional pooled study european genome-phenome archive human beta-cell adhesion article download pdf islet-specific epigenome maps 125i-iodinated insulin tracer large-scale association analysis trans-ethnic meta-analysis uk/genetics_software/snptest/snptest canhr yupโik samples chronic disease-related protective left y-axis shows diabetes-related mechanisms underlying article grarup present-day greenlandic population rare sequence variants quantitative diabetes-related traits diabetes-related quantitative traits transethnic gwas meta-analysis population-based association studies recessive model-based test exome sequencing-driven discovery fast model-based estimation yupโik people yup'ik people recessive model-based tests recessive genetic model analysed diabetes-related traits org/mammals/haploreg/haploreg org/collaboration/giant/index correct genetic model additive genetic model yupโik studies ฮฑ1-integrin subunit
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headline:Identification of novel high-impact recessively inherited type 2 diabetes risk variants in the Greenlandic population
description:In a recent study using a standard additive genetic model, we identified a TBC1D4 loss-of-function variant with a large recessive impact on risk of type 2 diabetes in Greenlanders. The aim of the current study was to identify additional genetic variation underlying type 2 diabetes using a recessive genetic model, thereby increasing the power to detect variants with recessive effects. We investigated three cohorts of Greenlanders (B99, nโ=โ1401; IHIT, nโ=โ3115; and BBH, nโ=โ547), which were genotyped using Illumina MetaboChip. Of the 4674 genotyped individuals passing quality control, 4648 had phenotype data available, and type 2 diabetes association analyses were performed for 317 individuals with type 2 diabetes and 2631 participants with normal glucose tolerance. Statistical association analyses were performed using a linear mixed model. Using a recessive genetic model, we identified two novel loci associated with type 2 diabetes in Greenlanders, namely rs870992 in ITGA1 on chromosome 5 (OR 2.79, pโ=โ1.8โรโ10โ8), and rs16993330 upstream of LARGE1 on chromosome 22 (OR 3.52, pโ=โ1.3โรโ10โ7). The LARGE1 variant did not reach the conventional threshold for genome-wide significance (pโ<โ5โรโ10โ8) but did withstand a study-wide Bonferroni-corrected significance threshold. Both variants were common in Greenlanders, with minor allele frequencies of 23% and 16%, respectively, and were estimated to have large recessive effects on risk of type 2 diabetes in Greenlanders, compared with additively inherited variants previously observed in European populations. We demonstrate the value of using a recessive genetic model in a historically small and isolated population to identify genetic risk variants. Our findings give new insights into the genetic architecture of type 2 diabetes, and further support the existence of high-effect genetic risk factors of potential clinical relevance, particularly in isolated populations. The Greenlandic MetaboChip-genotype data are available at European Genome-Phenome Archive (EGA;
https://ega-archive.org/
) under the accession EGAS00001002641.
datePublished:2018-06-20T00:00:00Z
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Genetic association
Genome-wide association study
Greenlanders
Inuit
ITGA1
LARGE1
Recessive genetic model
Type 2 diabetes
Internal Medicine
Metabolic Diseases
Human Physiology
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headline:Identification of novel high-impact recessively inherited type 2 diabetes risk variants in the Greenlandic population
description:In a recent study using a standard additive genetic model, we identified a TBC1D4 loss-of-function variant with a large recessive impact on risk of type 2 diabetes in Greenlanders. The aim of the current study was to identify additional genetic variation underlying type 2 diabetes using a recessive genetic model, thereby increasing the power to detect variants with recessive effects. We investigated three cohorts of Greenlanders (B99, nโ=โ1401; IHIT, nโ=โ3115; and BBH, nโ=โ547), which were genotyped using Illumina MetaboChip. Of the 4674 genotyped individuals passing quality control, 4648 had phenotype data available, and type 2 diabetes association analyses were performed for 317 individuals with type 2 diabetes and 2631 participants with normal glucose tolerance. Statistical association analyses were performed using a linear mixed model. Using a recessive genetic model, we identified two novel loci associated with type 2 diabetes in Greenlanders, namely rs870992 in ITGA1 on chromosome 5 (OR 2.79, pโ=โ1.8โรโ10โ8), and rs16993330 upstream of LARGE1 on chromosome 22 (OR 3.52, pโ=โ1.3โรโ10โ7). The LARGE1 variant did not reach the conventional threshold for genome-wide significance (pโ<โ5โรโ10โ8) but did withstand a study-wide Bonferroni-corrected significance threshold. Both variants were common in Greenlanders, with minor allele frequencies of 23% and 16%, respectively, and were estimated to have large recessive effects on risk of type 2 diabetes in Greenlanders, compared with additively inherited variants previously observed in European populations. We demonstrate the value of using a recessive genetic model in a historically small and isolated population to identify genetic risk variants. Our findings give new insights into the genetic architecture of type 2 diabetes, and further support the existence of high-effect genetic risk factors of potential clinical relevance, particularly in isolated populations. The Greenlandic MetaboChip-genotype data are available at European Genome-Phenome Archive (EGA;
https://ega-archive.org/
) under the accession EGAS00001002641.
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Genetic association
Genome-wide association study
Greenlanders
Inuit
ITGA1
LARGE1
Recessive genetic model
Type 2 diabetes
Internal Medicine
Metabolic Diseases
Human Physiology
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name:University of Copenhagen
address:
name:The Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
type:PostalAddress
type:Organization
email:[email protected]
name:Torben Hansen
affiliation:
name:University of Copenhagen
address:
name:Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
type:PostalAddress
type:Organization
name:University of Southern Denmark
address:
name:Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
type:PostalAddress
type:Organization
email:[email protected]
PostalAddress:
name:Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
name:The Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
name:Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
name:National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
name:Greenland Centre for Health Research, University of Greenland, Nuuk, Greenland
name:National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
name:Greenland Centre for Health Research, University of Greenland, Nuuk, Greenland
name:National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
name:The Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
name:Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, USA
name:Center for Alaska Native Health Research, University of Alaska Fairbanks, Fairbanks, USA
name:Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, USA
name:Center for Alaska Native Health Research, University of Alaska Fairbanks, Fairbanks, USA
name:Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
name:Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
name:Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
name:National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
name:Greenland Centre for Health Research, University of Greenland, Nuuk, Greenland
name:Steno Diabetes Center Copenhagen, Gentofte, Denmark
name:The Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
name:Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
name:Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
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