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Identification of correlated genetic variants jointly associated with rheumatoid arthritis using ridge regression
Yan V Sun1, Kerby A Shedden2, Ji Zhu2
1Department of Epidemiology, School of Public Health, University of Michigan, 109 Observatory, Ann Arbor, Michigan 48109, USA.
Abstract:
Using the North American Rheumatoid Arthritis Consortium genome-wide association dataset, we applied ridged, multiple least-squares regression to identify genetic variants with apparent unique contributions to variation of anti-cyclic citrullinated peptide (anti-CCP), a newly identified clinical risk factor for development of rheumatoid arthritis. Within a 2.7-Mbp region on chromosome 6 around the well studied HLA-DRB1 locus, ridge regression identified a single-nucleotide polymorphism that was associated with anti-CCP variation when including the additive effects of other single-nucleotide polymorphisms in a multivariable analysis, but that showed only a weak direct association with anti-CCP. This suggests that multivariable methods can be used to identify potentially relevant genetic variants in regions of interest that would be difficult to detect based on direct associations.
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