Abstract
Rheumatoid arthritis is a clinically and genetically heterogeneous disease. Anti-cyclic citrullinated (anti-CCP) antibodies have a high specificity for rheumatoid arthritis and levels correlate with disease severity. The focus of this study was to examine whether analyzing anti-CCP levels could increase the power of linkage analysis by identifying a more homogeneous subset of rheumatoid arthritis patients. We also wanted to compare linkage signals when analyzing anti-CCP levels as dichotomized (CCP_binary), categorical (CCP_cat), and continuous traits, with and without transformation (log_CCP and CCP_cont). Illumina single-nucleotide polymorphism scans of the North American Rheumatoid Arthritis Consortium families were analyzed for four chromosomes (6, 7, 11, 22) using nonparametric linkage (NPL) (rheumatoid arthritis and CCP_binary), regress (CCP_cat and Log_CCP), and deviates (CCP_cont) analysis options as implemented in Merlin. Similar linkage results were obtained from analyses of rheumatoid arthritis, CCP_binary, and CCP_cont. The only exception was that we observed improved linkage signals and a narrower region for CCP_binary as compared to a clinical diagnosis of rheumatoid arthritis alone on chromosome 7, a region which previously showed variation in linkage results with rheumatoid arthritis according to anti-CCP levels. Analyses of CCP_cat and Log_CCP had little power to detect linkage. Our data suggested that linkage analyses of anti-CCP levels may facilitate identification of rheumatoid arthritis genes but quantitative analyses did not further improve power. Our study also highlighted that quantitative trait linkage results are highly sensitive to phenotype transformation and analytic approaches.
Highlights
Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease affecting about 1% of the population
A high-density SNP analysis of 642 families affected with RA collected by the North American Rheumatoid Arthritis Consortium (NARAC), the largest single linkage study of RA, identified two new linkage regions, 11p and 2q [6]
These findings reflect the genetic complexity of the disease and suggest that analysis of a more homogeneous RA phenotype might increase the power of linkage analysis
Summary
Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease affecting about 1% of the population. Other chromosome regions (11q, 10q, 14q, 6p, 6q, 16q, 12p, etc.) and candidate genes (PTPN22, CTLA4, PADI4) have been identified by whole-genome linkage scans and association studies [15]. A high-density SNP analysis of 642 families affected with RA collected by the North American Rheumatoid Arthritis Consortium (NARAC), the largest single linkage study of RA, identified two new linkage regions, 11p and 2q [6]. These findings reflect the genetic complexity of the disease and suggest that analysis of a more homogeneous RA phenotype might increase the power of linkage analysis. Most previous studies have analyzed RA as a dichotomous trait, which could lead to a power loss if RA is a naturally quantitative trait [7]
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