Previous studies have shown that rheumatoid arthritis aggregates within families. However, no formal genetic analysis of rheumatoid arthritis in pedigrees together with other autoimmune diseases has been reported. We hypothesized that there are genetic factors in common in rheumatoid arthritis and other autoimmune diseases. Results of odds-ratio regression and complex segregation analysis in a sample of 43 Caucasian pedigrees ascertained through a rheumatoid arthritis proband or matched control proband, revealed a very strong genetic influence on the occurrence of both rheumatoid arthritis and other autoimmune diseases. In an analysis of rheumatoid arthritis alone, only one inter-class measure, parent-sibling, resulted in positive evidence of aggregation. However, three inter-class measures (parent-sibling, sibling-offspring, and parent-offspring pairs) showed significant evidence of familial aggregation with odds-ratio regression analysis of rheumatoid arthritis together with all other autoimmune diseases. Segregation analysis of rheumatoid arthritis alone revealed that the mixed model, including both polygenic and major gene components, was the most parsimonious. Similarly, segregation analysis of rheumatoid arthritis together with other autoimmune diseases revealed that a mixed model fitted the data significantly better than either major gene or polygenic models. These results were consistent with a previous study which concluded that several genes, including one with a major effect, is responsible for rheumatoid arthritis in families. Our data showed that this conclusion also held when the phenotype was defined as rheumatoid arthritis and/or other autoimmune diseases, suggesting that several major autoimmune diseases result from pleiotropic effects of a single major gene on a polygenic background.

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The Pima genealogy can be anticipated to provide valuable information for the genetic study of diseases other than RA. Defining an isolated population as the "unit" in which to assess familial aggregation may be advantageous, especially if there are a limited number of cases in the study population.