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Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study

Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study
Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study
Objectives: The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis.

Methods: The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44 449 individuals), and de novo in 14 534 independent samples, all of European descent.

Results: None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects.

Conclusions: Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.
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Panoutsopoulou, K.
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Zeggini, E.
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Panoutsopoulou, K., Southam, L., Elliott, K.S., Wrayner, N., Zhai, G., Beazley, C., Thorleifsson, G., Arden, N.K., Carr, A., Chapman, K., Deloukas, P., Doherty, M., McCaskie, A., Ollier, W.E., Ralston, S.H., Spector, T.D., Valdes, A.M., Wallis, G.A., Wilkinson, J.M., Arden, E., Battley, K., Blackburn, H., Bianco, F.J., Bumpstead, S., Cupples, L.A., Day-Williams, A.G., Dixon, K., Doherty, S.A., Esko, T., Evangelou, E., Felson, D., Gomez-Reino, J.J., Gonzalez, A., Gordon, A., Gwilliam, R., Halldorsson, B.V., Hauksson, V.B., Hofman, A., Ioanndis, J.P., Ingvarsson, T., Jonsdottir, I., Jonsson, H., Keen, R., Kerkhof, H.J., Kloppenburg, M.G., Koller, N., Lakenberg, N., Lane, N.E., Lee, A.T., Metspalu, A., Meulenbelt, I., Nevitt, M.C., O'Neill, F., Parimi, N., Potter, S.C., Rego-Perez, I., Riancho, J.A., Sherburn, K., Slagboom, P.E., Stefansson, K., Styrkarsdottir, U., Sumillera, M., Swift, D., Thorsteinsdottir, U., Tsezou, A., Uitterlinden, A.G., van Meurs, J.B., Watkins, B., Wheeler, M., Mitchell, S., Zhu, Y., Zmuda, J.M., Zeggini, E. and Loughlin, J. (2011) Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study. Annals of the Rheumatic Diseases, 70, 864-867. (doi:10.1136/ard.2010.141473). (PMID:21177295)

Record type: Article

Abstract

Objectives: The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis.

Methods: The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44 449 individuals), and de novo in 14 534 independent samples, all of European descent.

Results: None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects.

Conclusions: Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.

This record has no associated files available for download.

More information

Published date: May 2011

Identifiers

Local EPrints ID: 192555
URI: http://eprints.soton.ac.uk/id/eprint/192555
ISSN: 0003-4967
PURE UUID: febdf757-c584-499c-9c91-75e1e3e0e96c

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Date deposited: 06 Jul 2011 09:09
Last modified: 14 Mar 2024 03:51

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Contributors

Author: K. Panoutsopoulou
Author: L. Southam
Author: K.S. Elliott
Author: N. Wrayner
Author: G. Zhai
Author: C. Beazley
Author: G. Thorleifsson
Author: N.K. Arden
Author: A. Carr
Author: K. Chapman
Author: P. Deloukas
Author: M. Doherty
Author: A. McCaskie
Author: W.E. Ollier
Author: S.H. Ralston
Author: T.D. Spector
Author: A.M. Valdes
Author: G.A. Wallis
Author: J.M. Wilkinson
Author: E. Arden
Author: K. Battley
Author: H. Blackburn
Author: F.J. Bianco
Author: S. Bumpstead
Author: L.A. Cupples
Author: A.G. Day-Williams
Author: K. Dixon
Author: S.A. Doherty
Author: T. Esko
Author: E. Evangelou
Author: D. Felson
Author: J.J. Gomez-Reino
Author: A. Gonzalez
Author: A. Gordon
Author: R. Gwilliam
Author: B.V. Halldorsson
Author: V.B. Hauksson
Author: A. Hofman
Author: J.P. Ioanndis
Author: T. Ingvarsson
Author: I. Jonsdottir
Author: H. Jonsson
Author: R. Keen
Author: H.J. Kerkhof
Author: M.G. Kloppenburg
Author: N. Koller
Author: N. Lakenberg
Author: N.E. Lane
Author: A.T. Lee
Author: A. Metspalu
Author: I. Meulenbelt
Author: M.C. Nevitt
Author: F. O'Neill
Author: N. Parimi
Author: S.C. Potter
Author: I. Rego-Perez
Author: J.A. Riancho
Author: K. Sherburn
Author: P.E. Slagboom
Author: K. Stefansson
Author: U. Styrkarsdottir
Author: M. Sumillera
Author: D. Swift
Author: U. Thorsteinsdottir
Author: A. Tsezou
Author: A.G. Uitterlinden
Author: J.B. van Meurs
Author: B. Watkins
Author: M. Wheeler
Author: S. Mitchell
Author: Y. Zhu
Author: J.M. Zmuda
Author: E. Zeggini
Author: J. Loughlin

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