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Twin concordance data for rheumatoid arthritis (RA) on their own provide only limited insight into the relative genetic and environmental contribution to the disease. We applied quantitative genetic methods to assess the heritability of RA and to examine for evidence of differences in the genetic contribution according to sex, age, and clinical disease characteristics.Data were analyzed from 2 previously published nationwide studies of twins with RA conducted in Finland and the United Kingdom. Heritability was assessed by variance components analysis. Differences in the genetic contribution by sex, age, age at disease onset, and clinical characteristics were examined by stratification. The power of the twin study design to detect these differences was examined through simulation.The heritability of RA was 65% (95% confidence interval [95% CI] 50-77) in the Finnish data and 53% (95% CI 40-65) in the UK data. There was no significant difference in the strength of the genetic contribution according to sex, age, age at onset, or disease severity subgroup. Both study designs had power to detect a contribution of at least 40% from the common family environment, and a difference in the genetic contribution of at least 50% between subgroups.Genetic factors have a substantial contribution to RA in the population, accounting for approximately 60% of the variation in liability to disease. Although tempered by power considerations, there is no evidence in these twin data that the overall genetic contribution to RA differs by sex, age, age at disease onset, and disease severity.

Original publication

DOI

10.1002/1529-0131(200001)43:1<30::aid-anr5>3.0.co;2-b

Type

Journal article

Journal

Arthritis and rheumatism

Publication Date

01/2000

Volume

43

Pages

30 - 37

Addresses

Twin Research and Genetic Epidemiology Unit, St. Thomas' Hospital, London, UK.

Keywords

Humans, Arthritis, Rheumatoid, Genetic Predisposition to Disease, Cohort Studies, Cross-Sectional Studies, Quantitative Trait, Heritable, Genetic Heterogeneity, Models, Genetic, Adult, Aged, Middle Aged, Finland, Female, Male, United Kingdom