Dense genome-wide linkage analysis of rheumatoid arthritis, including covariates.

ABSTRACT

OBJECTIVE: Rheumatoid arthritis (RA) is a heterogeneous disease that exhibits a complex genetic component. Previous RA genome scans confirmed the involvement of the HLA region and generated data on suggestive signals at non-HLA regions, albeit with few overlaps in findings between studies. The present study was undertaken to detect potential RA gene regions and to estimate the number of true RA gene regions, taking into account the heterogeneity of RA, through performance of a dense genome scan. METHODS: In a study of 88 French Caucasian families (105 RA sibpairs), 1,088 microsatellite markers were genotyped (3.3-cM genome scan), and a multipoint model-free linkage analysis was performed. The statistical assessment of the results relied on 10,000 computer simulations. A covariate-based multipoint model-free linkage analysis was performed on the locations of regions with suggestive evidence for linkage. RESULTS: Involvement of the HLA region was strongly confirmed (P = 6 x 10(-5)), and 19 non-HLA regions showed suggestive evidence for linkage (P < 0.05); 9 of these overlapped with regions suggested in other published RA genome scans. A routine 12-cM genome scan with the same families would have detected only 7 of the 19 regions, including only 4 of the 9 overlapping regions. From the 10,000 computer simulations, we estimated that 8 +/- 4 regions (mean +/- SD) were true-positives. RA covariate-based analysis provided additional linkage evidence for 3 regions, with age at disease onset, erosions, and HLA-DRB1 shared epitope as covariates. CONCLUSION: The results of this study provide evidence of 19 non-HLA RA gene regions, with an estimate of 8 +/- 4 as true-positives, and provide additional evidence for 3 regions from covariate-based analysis.