Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Paul R. Burton, David G. Clayton, Lon R. Cardon, Nick Craddock, Panos Deloukas, Audrey Duncanson, Dominic P. Kwiatkowski, Mark I. McCarthy, Willem H. Ouwehand, Nilesh J. Samani, John A. Todd, Peter Donnelly, Jeffrey C. Barrett, Dan Davison, Doug Easton, David Evans, Hin-Tak Leung, Jonathan L. Marchini, Andrew P. Morris, Chris C. A. SpencerMartin D. Tobin, Antony P. Attwood, James P. Boorman, Barbara Cant, Ursula Everson, Judith M. Hussey, Jennifer D. Jolley, Alexandra S. Knight, Kerstin Koch, Elizabeth Meech, Sarah Nutland, Christopher V. Prowse, Helen E. Stevens, Niall C. Taylor, Graham R. Walters, Neil M. Walker, Nicholas A. Watkins, Thilo Winzer, Richard W. Jones, Wendy L. McArdle, Susan M. Ring, David P. Strachan, Marcus Pembrey, Gerome Breen, David St Clair, Sian Caesar, Katherine Gordon-Smith, Lisa Jones, Christine Fraser, Elain K. Green, Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat

Research output: Contribution to journalLiterature review

6897 Citations (Scopus)

Abstract

There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

Original languageEnglish
Pages (from-to)661-678
Number of pages18
JournalNature
Volume447
Issue number7145
DOIs
Publication statusPublished - 7 Jun 2007

Keywords

  • single-nucleotide polymorphisms
  • coronary-artery-disease
  • mitochondrial c-1-tetrahydrofolate synthase
  • lymphoid tyrosine phosphatase
  • rheumatoid-arthritis families
  • inflammatory-bowel-disease
  • multilocus genotype data
  • affected sibling pairs
  • type-1 diabetes locus
  • bipolar disorder

Cite this

Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., ... Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661-678. https://doi.org/10.1038/nature05911

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. / Burton, Paul R.; Clayton, David G.; Cardon, Lon R.; Craddock, Nick; Deloukas, Panos; Duncanson, Audrey; Kwiatkowski, Dominic P.; McCarthy, Mark I.; Ouwehand, Willem H.; Samani, Nilesh J.; Todd, John A.; Donnelly, Peter; Barrett, Jeffrey C.; Davison, Dan; Easton, Doug; Evans, David; Leung, Hin-Tak; Marchini, Jonathan L.; Morris, Andrew P.; Spencer, Chris C. A.; Tobin, Martin D.; Attwood, Antony P.; Boorman, James P.; Cant, Barbara; Everson, Ursula; Hussey, Judith M.; Jolley, Jennifer D.; Knight, Alexandra S.; Koch, Kerstin; Meech, Elizabeth; Nutland, Sarah; Prowse, Christopher V.; Stevens, Helen E.; Taylor, Niall C.; Walters, Graham R.; Walker, Neil M.; Watkins, Nicholas A.; Winzer, Thilo; Jones, Richard W.; McArdle, Wendy L.; Ring, Susan M.; Strachan, David P.; Pembrey, Marcus; Breen, Gerome; St Clair, David; Caesar, Sian; Gordon-Smith, Katherine; Jones, Lisa; Fraser, Christine; Green, Elain K.; Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat.

In: Nature, Vol. 447, No. 7145, 07.06.2007, p. 661-678.

Research output: Contribution to journalLiterature review

Burton, PR, Clayton, DG, Cardon, LR, Craddock, N, Deloukas, P, Duncanson, A, Kwiatkowski, DP, McCarthy, MI, Ouwehand, WH, Samani, NJ, Todd, JA, Donnelly, P, Barrett, JC, Davison, D, Easton, D, Evans, D, Leung, H-T, Marchini, JL, Morris, AP, Spencer, CCA, Tobin, MD, Attwood, AP, Boorman, JP, Cant, B, Everson, U, Hussey, JM, Jolley, JD, Knight, AS, Koch, K, Meech, E, Nutland, S, Prowse, CV, Stevens, HE, Taylor, NC, Walters, GR, Walker, NM, Watkins, NA, Winzer, T, Jones, RW, McArdle, WL, Ring, SM, Strachan, DP, Pembrey, M, Breen, G, St Clair, D, Caesar, S, Gordon-Smith, K, Jones, L, Fraser, C, Green, EK & Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat 2007, 'Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls', Nature, vol. 447, no. 7145, pp. 661-678. https://doi.org/10.1038/nature05911
Burton PR, Clayton DG, Cardon LR, Craddock N, Deloukas P, Duncanson A et al. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007 Jun 7;447(7145):661-678. https://doi.org/10.1038/nature05911
Burton, Paul R. ; Clayton, David G. ; Cardon, Lon R. ; Craddock, Nick ; Deloukas, Panos ; Duncanson, Audrey ; Kwiatkowski, Dominic P. ; McCarthy, Mark I. ; Ouwehand, Willem H. ; Samani, Nilesh J. ; Todd, John A. ; Donnelly, Peter ; Barrett, Jeffrey C. ; Davison, Dan ; Easton, Doug ; Evans, David ; Leung, Hin-Tak ; Marchini, Jonathan L. ; Morris, Andrew P. ; Spencer, Chris C. A. ; Tobin, Martin D. ; Attwood, Antony P. ; Boorman, James P. ; Cant, Barbara ; Everson, Ursula ; Hussey, Judith M. ; Jolley, Jennifer D. ; Knight, Alexandra S. ; Koch, Kerstin ; Meech, Elizabeth ; Nutland, Sarah ; Prowse, Christopher V. ; Stevens, Helen E. ; Taylor, Niall C. ; Walters, Graham R. ; Walker, Neil M. ; Watkins, Nicholas A. ; Winzer, Thilo ; Jones, Richard W. ; McArdle, Wendy L. ; Ring, Susan M. ; Strachan, David P. ; Pembrey, Marcus ; Breen, Gerome ; St Clair, David ; Caesar, Sian ; Gordon-Smith, Katherine ; Jones, Lisa ; Fraser, Christine ; Green, Elain K. ; Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat. / Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. In: Nature. 2007 ; Vol. 447, No. 7145. pp. 661-678.
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AU - Clayton, David G.

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AU - Deloukas, Panos

AU - Duncanson, Audrey

AU - Kwiatkowski, Dominic P.

AU - McCarthy, Mark I.

AU - Ouwehand, Willem H.

AU - Samani, Nilesh J.

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AU - Attwood, Antony P.

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AU - Cant, Barbara

AU - Everson, Ursula

AU - Hussey, Judith M.

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AU - Taylor, Niall C.

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AU - Walker, Neil M.

AU - Watkins, Nicholas A.

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AU - McArdle, Wendy L.

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AU - Strachan, David P.

AU - Pembrey, Marcus

AU - Breen, Gerome

AU - St Clair, David

AU - Caesar, Sian

AU - Gordon-Smith, Katherine

AU - Jones, Lisa

AU - Fraser, Christine

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AU - Biol RA Genet & Genom Study Syndicate, Wellcome Trust Case Control Consortium, Breast Canc Susceptib Collaborat

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N2 - There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

AB - There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

KW - single-nucleotide polymorphisms

KW - coronary-artery-disease

KW - mitochondrial c-1-tetrahydrofolate synthase

KW - lymphoid tyrosine phosphatase

KW - rheumatoid-arthritis families

KW - inflammatory-bowel-disease

KW - multilocus genotype data

KW - affected sibling pairs

KW - type-1 diabetes locus

KW - bipolar disorder

U2 - 10.1038/nature05911

DO - 10.1038/nature05911

M3 - Literature review

VL - 447

SP - 661

EP - 678

JO - Nature

JF - Nature

SN - 0028-0836

IS - 7145

ER -