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Genome-wide meta-analysis for rheumatoid arthritis

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Abstract

Meta-analysis is being increasingly used as a tool for integrating data from different studies of complex phenotypes, because the power of any one study to identify causal loci is limited. We applied a novel meta-analytical approach (Loesgen et al. in Genet Epidemiol 21(Suppl 1):S142–S147, 2001) in compiling results from four studies of rheumatoid arthritis in Caucasians including two studies from NARAC (Jawaheer et al. in Am J Hum Genet 68:927–936, 2001; Jawaheer et al. in Arthritis Rheum 48:906–916, 2003), one study from the UK (MacKay et al. in Arthritis Rheum 46:632–639, 2001) and one from France (Cornelis et al. in Proc Natl Acad Sci USA 95:10746–10750, 1998). For each study, we obtained NPL scores by performing interval mapping (2 cM intervals) using GeneHunter2 (Kruglyak et al. in Am J Hum Genet 58:1347–1363, 1996; Markianos et al. in Am J Hum Genet 68:963–977, 2001). The marker maps differed among the three consortium groups, therefore, the marker maps were aligned after the interval mapping was completed and the NPL scores that were within 1 cM of each other were combined using the method of Loesgen et al. (Genet Epidemiol 21(Suppl 1):S142–S147, 2001) by calculating the weighted average of the NPL score. This approach avoids some problems in analysis encountered by using GeneHunter2 when some markers in the sample are not genotyped. This procedure provided marginal evidence (P<0.05) of linkage on chromosome 1, 2, 5 and 18, strong evidence (P<0.01) on chromosomes 8 and 16, and overwhelming evidence in the HLA region of chromosome 6.

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Acknowledgements

The authors would like to thank all of the researchers involved in NARAC, ARC and ECRAF, specifically Jane Worthington (ARC) and Sally John (ARC) for their cooperation and generous use of the data for this investigation. This research was supported by a cancer prevention fellowship funded by the National Cancer Institute grant K07CA093592–02 and funds provided by the National Arthritis and Musculoskeletal and Skin Disease and the National Institute of Allergy and Infectious Diseases under grant R01-AR44422 and ES09912. The authors do not have any financial or personal relationships with other people or organizations that would bias this work.

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Authors and Affiliations

  1. Department of Epidemiology, UT MD Anderson Cancer Center, 1155 Pressler Street - Unit 1340, Houston, TX, 77030, USA

    Carol J. Etzel, Wei V. Chen & Christopher I. Amos

  2. ARC Epidemiology Unit, University of Manchester, Manchester, UK

    Neil Shepard

  3. Center for Neurobehavioral Genetics, University of California Los Angeles, Los Angeles, CA, USA

    Damini Jawaheer

  4. Genethon-Centre National de le Rechereche Scientifique Unite de Recherche Associee, Evry, France

    Francois Cornelis

  5. Department of Biological Chemistry, UC Davis, Davis, CA, USA

    Michael F. Seldin

  6. Robert S. Boas Center for Genomics and Human Genetics, The Feinstein Institute for Medical Research, North Shore LIJ Health System, Manhasset, NY, USA

    Peter K. Gregersen

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  1. Carol J. Etzel
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for the North American Rheumatoid Arthritis Consortium

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Correspondence to Carol J. Etzel.

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Etzel, C.J., Chen, W.V., Shepard, N. et al. Genome-wide meta-analysis for rheumatoid arthritis. Hum Genet 119, 634–641 (2006). https://doi.org/10.1007/s00439-006-0171-8

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