1. The shared epitope hypothesis in rheumatoid arthritis: evaluation of alternative classification criteria in a large UK Caucasian cohort.
- Author
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Morgan AW, Haroon-Rashid L, Martin SG, Gooi HC, Worthington J, Thomson W, Barrett JH, and Emery P
- Subjects
- HLA-DR Antigens genetics, HLA-DRB1 Chains, Humans, United Kingdom, Arthritis, Rheumatoid classification, Arthritis, Rheumatoid genetics, Epitopes, White People
- Abstract
Objective: Many classification systems for the HLA-DRB1 allelic association with rheumatoid arthritis (RA) have been reported, but few have been validated in additional populations. We sought to evaluate 3 different DRB1 allele classification systems in a large cohort of Caucasian RA patients and control subjects in the UK., Methods: HLA-DRB1 typing was undertaken in 1,325 Caucasian RA patients and 462 healthy Caucasian controls who were residents of the UK. Logistic regression analyses were performed to investigate the different classification systems., Results: We confirmed the association between the susceptibility alleles S2 and S3P, as proposed by Tezenas du Montcel, and the presence of RA in UK Caucasians. A significant hierarchy of risk was observed within the S3P allele group. There was no evidence of a significant association between DRB1*1001 and RA. Our data did not support the hypothesis that an isoleucine at position 67 conferred protection against RA, other than in contrast to the susceptibility alleles. However, the presence of an aspartic acid at amino acid 70 did appear to confer some degree of protection., Conclusion: We were unable to fully substantiate any of the 3 recent revisions of the shared epitope hypothesis in this large cohort of Caucasian RA patients and control subjects in the UK. This reinforces the importance of evaluating disease susceptibility alleles in different Caucasian populations as well as in other ethnic groups. In particular, it will be important to clarify the precise DRB1 association in a given population before DRB1 genotyping is incorporated into clinical diagnostic or treatment algorithms.
- Published
- 2008
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