Genetic associations in peripheral joint osteoarthritis and spinal degenerative disease: a systematic review. Issue 5 (24th August 2007)

• Record Type: Journal Article
• Authors: Ryder, J J; Garrison, K; Song, F; Hooper, L; Skinner, J; Loke, Y; Loughlin, J; Higgins, J P T; MacGregor, A J
• Is Part Of: Annals of the rheumatic diseases. Volume 67:Issue 5(2008)
• Page Start: 584
• Page End: 591
• Publication Date: 2007-08-24
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/ard.2007.073874
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : We conducted a systematic review of genetic association studies for osteoarthritis of the peripheral joints (OA) and spinal degenerative disease (SDD). Electronic searches were carried out for any English language article reporting on a gene association study for either OA or SDD published up until the end of 2006. A team of seven reviewers used a standardised template to extract data in duplicate. In all, 90 studies fulfilled our inclusion criteria, reporting a total of 94 significant associations from 83 different genes. We found relatively few instances in which a specific gene–disease association had been analysed by more than one study, and there were 14 cases in which significant associations were replicated in independent studies (at joints associated with the AGC1, ASPN, COL9A2, COL9A3, COL11A2, ESR1, FZRB, HFE, IL1A, IL1RN, PTGS2 and VDR genes). Methodological and reporting problems were widespread, including failure to report full results, missing population details, multiple testing, and over-reliance on subgroup analysis. In summary, the complex phenotypes of OA and SDD may have made it difficult for researchers to focus their efforts. The field is dominated by isolated analyses of disparate potential associations, a problem that is amplified by the frequent analysis of different polymorphisms within individual genes. Flaws in study methodology and interpretation undoubtedly increase the risk of publication bias. Closer adherence to published recommendations (in particular those produced by HuGENet) will help to ensure that future studies are well-designed and build on current understanding, rather than simply adding to the growing bank of potential associations.