Ghosh S, Babron MC, Amos CI, Briollais L, Chen P, Chen WV, Chiu WF, Drigalenko E, Etzel CJ, Hamshere ML, Holmans PA, Margaritte-Jeannin P, Lebrec JJP, Lin S, Lin WY, Mandhyan DD, Nishchenko I, Schaid DJ, Seguardo R, Shete S, Taylor K, Tayo BO, Wan S, Wei LY, Wu CO, Yang XR. Linkage analyses of rheumatoid arthritis and related quantitative phenotypes: the GAW15 experience.
Genet Epidemiol 2007;
31 Suppl 1:S86-95. [PMID:
18046767 DOI:
10.1002/gepi.20284]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The group that formed on the theme of linkage analyses of rheumatoid arthritis RA and related phenotypes (Group 10) in the Genetic Analysis Workshop 15 comprised 18 sets of investigators. Two data sets were available: one was a real set provided by the North American Rheumatoid Arthritis Consortium and collaborators in Canada, France (European Consortium Of Rheumatoid Arthritis Families) and the UK; the other was a simulated data set modelled after the real data set. Whereas a majority of the investigators analyzed the RA affection status as a binary phenotype, a few contributions considered data on correlated quantitative traits such as anti-cyclic citrullinated peptide and rheumatoid factor-immunoglobulin M. The different investigators applied a wide spectrum of linkage methods. As expected, most methods could identify the human leukocyfeantigen region on chromosome 6 as a major genetic factor for RA. In addition, some novel chromosomal regions provided significant evidence of linkage in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect linkage.
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