Original Article

Genetic association with rheumatoid arthritis—Genetic Analysis Workshop 15: summary of contributions from Group 2

  1. Marsha A. Wilcox1,*,
  2. Zhong Li2,3,
  3. Will Tapper4

Article first published online: 28 NOV 2007

DOI: 10.1002/gepi.20276

Issue

Genetic Epidemiology

Genetic Epidemiology

Supplement: Genetic Analysis Workshop 15: Summaries of the Design and Analysis of Genomic Data

Volume 31, Issue S1, pages S12–S21, 2007

Additional Information

How to Cite

Wilcox, M. A., Li, Z. and Tapper, W. (2007), Genetic association with rheumatoid arthritis—Genetic Analysis Workshop 15: summary of contributions from Group 2. Genet. Epidemiol., 31: S12–S21. doi: 10.1002/gepi.20276

Author Information

  1. 1

    i3 Drug Safety, Waltham, Massachusetts

  2. 2

    Department of Computational Genetics, High Throughput Biology Inc., Livingston, New Jersy

  3. 3

    Center for Computational Biology and Bioinformatics, Columbia University, New York, New York

  4. 4

    Human Genetics Division, University of Southampton, Southampton General Hospital, Southampton, United Kingdom

*i3 Drug Safety, 950 Winter Street, Waltham, MA 02451

Publication History

  1. Issue published online: 28 NOV 2007
  2. Article first published online: 28 NOV 2007

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Keywords:

  • genome-wide association;
  • chromosome 6;
  • chromosome 18q21;
  • HLA;
  • PTPN22;
  • search algorithms

Abstract

The papers in presentation group 2 of Genetic Analysis Workshop 15 (GAW15) conducted association analyses of rheumatoid arthritis data. The analyses were carried out primarily in the data provided by the North American Rheumatoid Arthritis Consortium (NARAC). One group conducted analyses in the data provided by the Canadian Rheumatoid Arthritis Genetics Study (CRAGS). Analysis strategies included genome-wide scans, the examination of candidate genes, and investigations of a region of interest on chromosome 18q21. Most authors employed relatively new methods, proposed extensions of existing methods, or introduced completely novel methods for aspects of association analysis. There were several common observations; a group of papers using a variety of methods found stronger association, on chromosomes 6 and 18 and in candidate gene PTPN22 among women with early onset. Generally, models that considered haplotypes or multiple markers showed stronger evidence for association than did single marker analyses. Genet. Epidemiol. 31 (Suppl. 1):S12–S21, 2007. © 2007 Wiley-Liss, Inc.

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