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Wei, W.B. |
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dc.contributor.author |
Wickremasinghe, A.R. |
|
dc.contributor.author |
Willemsen, G. |
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dc.contributor.author |
Wilson, J.F. |
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dc.contributor.author |
Wong, T.Y. |
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dc.contributor.author |
Wu, J.Y. |
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dc.contributor.author |
Xiang, A.H. |
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dc.contributor.author |
Yanek, L.R. |
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dc.contributor.author |
Yengo, L. |
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dc.contributor.author |
Yokota, M. |
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dc.contributor.author |
Zeggini, E. |
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dc.contributor.author |
Zheng, W. |
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dc.contributor.author |
Zonderman, A.B. |
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dc.contributor.author |
Rotter, J.I. |
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dc.contributor.author |
Gloyn, A.L. |
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dc.contributor.author |
McCarthy, M.I. |
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dc.contributor.author |
Dupuis, J. |
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dc.contributor.author |
Meigs, J.B. |
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dc.contributor.author |
Scott, R.A. |
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dc.contributor.author |
Prokopenko, I. |
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dc.contributor.author |
Leong, A. |
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dc.contributor.author |
Liu, C.T. |
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dc.contributor.author |
Parker, S.C.J. |
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dc.contributor.author |
Mohlke, K.L. |
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dc.contributor.author |
Langenberg, C. |
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dc.contributor.author |
Wheeler, E. |
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dc.contributor.author |
Morris, A.P. |
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dc.contributor.author |
Barroso, I. |
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dc.contributor.author |
Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) Collaborators. |
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dc.date.accessioned |
2021-06-30T08:02:00Z |
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dc.date.available |
2021-06-30T08:02:00Z |
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dc.date.issued |
2021 |
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dc.identifier.citation |
Nature Genetics. 2021; 53(6):840-860. |
en_US |
dc.identifier.issn |
1061-4036 (Print) |
|
dc.identifier.issn |
1546-1718 (Electronic) |
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dc.identifier.issn |
1061-4036 (Linking) |
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dc.identifier.uri |
http://repository.kln.ac.lk/handle/123456789/23045 |
|
dc.description |
Indexed in MEDLINE |
en_US |
dc.description.abstract |
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 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. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Nature Pub. Co. |
en_US |
dc.subject |
glycemic traits |
en_US |
dc.title |
The Trans-ancestral genomic architecture of glycemic traits |
en_US |
dc.type |
Article |
en_US |