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The trans-ancestral genomic architecture of glycemic traits

Chen, J. ; Lyssenko, Valeriya LU ; Franks, Paul LU ; Elmståhl, Sölve LU ; Groop, Leif LU and van Duijn, C. (2021) In Nature Genetics 53(6). p.840-860
Abstract
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new... (More)
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc. (Less)
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Contribution to journal
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published
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keywords
glycosylated hemoglobin, allele, Caucasian, chromosomal mapping, gene expression profiling, genetic epigenesis, genetics, genome-wide association study, glucose blood level, human, human genome, metabolism, multifactorial inheritance, quantitative trait, quantitative trait locus, Alleles, Blood Glucose, Epigenesis, Genetic, European Continental Ancestry Group, Gene Expression Profiling, Genome, Human, Genome-Wide Association Study, Glycated Hemoglobin A, Humans, Multifactorial Inheritance, Physical Chromosome Mapping, Quantitative Trait Loci, Quantitative Trait, Heritable
in
Nature Genetics
volume
53
issue
6
pages
21 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85108020584
  • pmid:34059833
ISSN
1546-1718
DOI
10.1038/s41588-021-00852-9
language
English
LU publication?
yes
id
c245cd5b-81e9-43a1-bdc6-4daf3398393a
date added to LUP
2021-12-28 14:22:18
date last changed
2025-04-04 14:02:37
@article{c245cd5b-81e9-43a1-bdc6-4daf3398393a,
  abstract     = {{Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P &lt; 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.}},
  author       = {{Chen, J. and Lyssenko, Valeriya and Franks, Paul and Elmståhl, Sölve and Groop, Leif and van Duijn, C.}},
  issn         = {{1546-1718}},
  keywords     = {{glycosylated hemoglobin; allele; Caucasian; chromosomal mapping; gene expression profiling; genetic epigenesis; genetics; genome-wide association study; glucose blood level; human; human genome; metabolism; multifactorial inheritance; quantitative trait; quantitative trait locus; Alleles; Blood Glucose; Epigenesis, Genetic; European Continental Ancestry Group; Gene Expression Profiling; Genome, Human; Genome-Wide Association Study; Glycated Hemoglobin A; Humans; Multifactorial Inheritance; Physical Chromosome Mapping; Quantitative Trait Loci; Quantitative Trait, Heritable}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{840--860}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Genetics}},
  title        = {{The trans-ancestral genomic architecture of glycemic traits}},
  url          = {{http://dx.doi.org/10.1038/s41588-021-00852-9}},
  doi          = {{10.1038/s41588-021-00852-9}},
  volume       = {{53}},
  year         = {{2021}},
}