TY - JOUR
T1 - Identification of novel high-impact recessively inherited type 2 diabetes risk variants in the Greenlandic population
AU - Grarup, Niels
AU - Moltke, Ida
AU - Andersen, Mette K.
AU - Bjerregaard, Peter
AU - Larsen, Christina V.L.
AU - Dahl-Petersen, Inger K.
AU - Jørsboe, Emil
AU - Tiwari, Hemant K.
AU - Hopkins, Scarlett E.
AU - Wiener, Howard W.
AU - Boyer, Bert B.
AU - Linneberg, Allan
AU - Pedersen, Oluf
AU - Jørgensen, Marit E.
AU - Albrechtsen, Anders
AU - Hansen, Torben
N1 - Funding Information:
Funding The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). This project was also funded by the Danish Council for Independent Research (DFF-4090-00244, Sapere Aude grant DFF-11-120909 and DFF-4181-00383), the Steno Diabetes Center Copenhagen (www.steno.dk), the Lundbeck Foundation (R215–2015-4174) and the Novo Nordisk Foundation (NNF15OC0017918, NNF16OC0019986 and NNF15CC0018486). The Greenlandic health surveys (IHIT and B99) were supported by Karen Elise Jensen’s Foundation, the Department of Health in Greenland, NunaFonden, Medical Research Council of Denmark, Medical Research Council of Greenland and Commission for Scientific Research in Greenland. The CANHR studies involving Alaska Native Yup’ik people were funded by the following National Institutes of Health grants: P30 GM103325, R01 DK104347 and R01 DK074842.
Funding Information:
Acknowledgements We gratefully acknowledge the participants in the Greenlandic health surveys. From Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark, we wish to thank A. Forman, T. H. Lorentzen and G. J. Klavsen for laboratory assistance, P. Sandbeck for data management, G. Lademann for secretarial support, and T. F. Toldsted for grant management.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/9/1
Y1 - 2018/9/1
N2 - 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, n = 1401; IHIT, n = 3115; and BBH, n = 547), 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, p = 1.8 × 10 −8 ), and rs16993330 upstream of LARGE1 on chromosome 22 (OR 3.52, p = 1.3 × 10 −7 ). The LARGE1 variant did not reach the conventional threshold for genome-wide significance (p < 5 × 10 −8 ) 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.
AB - 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, n = 1401; IHIT, n = 3115; and BBH, n = 547), 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, p = 1.8 × 10 −8 ), and rs16993330 upstream of LARGE1 on chromosome 22 (OR 3.52, p = 1.3 × 10 −7 ). The LARGE1 variant did not reach the conventional threshold for genome-wide significance (p < 5 × 10 −8 ) 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.
KW - Genetic association
KW - Genome-wide association study
KW - Greenlanders
KW - ITGA1
KW - Inuit
KW - LARGE1
KW - Recessive genetic model
KW - Type 2 diabetes
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U2 - 10.1007/s00125-018-4659-2
DO - 10.1007/s00125-018-4659-2
M3 - Article
C2 - 29926116
AN - SCOPUS:85048749142
SN - 0012-186X
VL - 61
SP - 2005
EP - 2015
JO - Diabetologia
JF - Diabetologia
IS - 9
ER -