Despite recent advances, the etiology and pathogenesis of rheumatoid arthritis (RA) remain unknown. The proposed research seeks to improve our understanding of the genetic factors important in the predisposition and expression of RA by applying the techniques of genetic epidemiology and molecular genetics. A cohort of multiplex and simplex families of RA will be identified using a family history questionnaire and a defined sampling from surveying 1000 consecutive outpatients with RA. From our pilot data, we expect this survey to identify a minimum of 250 multiplex families with RA. In a randomly selected subset of 100 multiplex and 50 simplex families, the affection status of family members will be verified using a detailed structured history and physical examination, and serum rheumatoid factor testing. Affection status will be categorized into those who are definitely unaffected, possibly affected and definitely affected (i.e., having RA by 1987 ARA criteria). To avoid misclassification errors and address the problem of disease heterogeneity, these categories will be further subdivided into a total of seven subgroups based on clinical and laboratory features. Cells and sera will be collected from individuals in the randomly selected multiplex and simplex families to identify genetic markers have been reported to be associated with RA. These markers will be defined by specific allosera (i.e, HLA-A, B, C,and DR specificities), and allele-specific oligonucleotide c-DNA probes (e.g., DR beta I and DQ beta alleles). The family history data and molecular genetic data will be analyzed from several different perspectives. 1) Four specific genetic models will be tested against the observed family data.
The aim i s to determine whether the (a) environmental model (i.e., chance aggregation), (b) multifactorial model (i.e., polygenes and environment), (c) major gene model (i.e., dominant, recessive or additive) or (d) mixed model (i.e., major gene and additional polygenic factors) provides the best explanation of the observed pattern of familial aggregation. 2) Utilizing the data from the detailed clinical evaluation and serum rheumatoid factor testing, a more specific model of the relationship of HLA to RA will be tested. 3) The role of HLA genes will be examined utilizing the HLA typing and molecular genetic data in combined segregation and linkage analyses. 4) Based on demographic factors (i.e., age and gender), serum rheumatoid factor measurement and the HLA marker data, the risk of affection for any first-degree relative of the probands will be determined. This study combines epidemiologic, classical genetic, and molecular genetic techniques into a powerful methodology which utilizes simplex and multiplex families of disease to define the genetic the genetic determinants related to the development and prognosis of rheumatoid arthritis.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
First Independent Research Support & Transition (FIRST) Awards (R29)
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Epidemiology and Disease Control Subcommittee 2 (EDC)
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University of Pittsburgh
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Kwoh, C K; Venglish, C; Lynn, A H et al. (1996) Age, sex, and the familial risk of rheumatoid arthritis. Am J Epidemiol 144:15-24
Lynn, A H; Kwoh, C K; Venglish, C M et al. (1995) Genetic epidemiology of rheumatoid arthritis. Am J Hum Genet 57:150-9
Weidmann, E; Elder, E M; Trucco, M et al. (1993) Usage of T-cell receptor V beta chain genes in fresh and cultured tumor-infiltrating lymphocytes from human melanoma. Int J Cancer 54:383-90
McCarty, D J; Kwoh, C K; LaPorte, R E (1992) The importance of incidence registries for connective tissue diseases. J Rheumatol 19:1-7