Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

The genetic architecture of type 2 diabetes

Fuchsberger, Christian ; V. Varga, Tibor LU ; Ladenvall, Claes LU ; Kravic, Jasmina LU ; Franks, Paul LU ; Lyssenko, Valeriya LU ; Rosengren, Anders LU ; Groop, Leif LU ; Melander, Olle LU orcid and Nilsson, Peter LU , et al. (2016) In Nature 536(7614). p.41-47
Abstract
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a... (More)
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes. © 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; and (Less)
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
allele, ancestry, diabetes, genetic analysis, genetic structure, genome, health risk, pathology, physiology, Article, controlled study, European, exome, gene sequence, genetic code, genetic variation, genome-wide association study, genotype, human, major clinical study, non insulin dependent diabetes mellitus, priority journal, dna mutational analysis, ethnology, Europe, genetic predisposition, genetics, genotyping technique, sample size, Alleles, Diabetes Mellitus, Type 2, DNA Mutational Analysis, Exome, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotyping Techniques, Humans, Sample Size
in
Nature
volume
536
issue
7614
pages
41 - 47
publisher
Nature Publishing Group
external identifiers
  • scopus:84978128486
ISSN
0028-0836
DOI
10.1038/nature18642
language
English
LU publication?
yes
additional info
Cited By :306 Export Date: 15 February 2019
id
2eea818c-4b7e-449f-bfa2-d37414f7406e
date added to LUP
2019-02-15 15:13:57
date last changed
2024-04-01 22:01:30
@article{2eea818c-4b7e-449f-bfa2-d37414f7406e,
  abstract     = {{The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes. © 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.}},
  author       = {{Fuchsberger, Christian and V. Varga, Tibor and Ladenvall, Claes and Kravic, Jasmina and Franks, Paul and Lyssenko, Valeriya and Rosengren, Anders and Groop, Leif and Melander, Olle and Nilsson, Peter and McCarthy, Mark I.}},
  issn         = {{0028-0836}},
  keywords     = {{allele; ancestry; diabetes; genetic analysis; genetic structure; genome; health risk; pathology; physiology; Article; controlled study; European; exome; gene sequence; genetic code; genetic variation; genome-wide association study; genotype; human; major clinical study; non insulin dependent diabetes mellitus; priority journal; dna mutational analysis; ethnology; Europe; genetic predisposition; genetics; genotyping technique; sample size; Alleles; Diabetes Mellitus, Type 2; DNA Mutational Analysis; Exome; Genetic Predisposition to Disease; Genetic Variation; Genome-Wide Association Study; Genotyping Techniques; Humans; Sample Size}},
  language     = {{eng}},
  number       = {{7614}},
  pages        = {{41--47}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature}},
  title        = {{The genetic architecture of type 2 diabetes}},
  url          = {{http://dx.doi.org/10.1038/nature18642}},
  doi          = {{10.1038/nature18642}},
  volume       = {{536}},
  year         = {{2016}},
}