Arthritis Research & Therapy (Mar 2017)
DNA methylation mediates genotype and smoking interaction in the development of anti-citrullinated peptide antibody-positive rheumatoid arthritis
Abstract
Abstract Background Multiple factors, including interactions between genetic and environmental risks, are important in susceptibility to rheumatoid arthritis (RA). However, the underlying mechanism is not fully understood. This study was undertaken to evaluate whether DNA methylation can mediate the interaction between genotype and smoking in the development of anti-citrullinated peptide antibody (ACPA)-positive RA. Methods We investigated the gene-smoking interactions in DNA methylation using 393 individuals from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA). The interaction between rs6933349 and smoking in the risk of developing ACPA-positive RA was further evaluated in a larger portion of the EIRA (1119 controls and 944 ACPA-positive patients with RA), and in the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) (1556 controls and 792 ACPA-positive patients with RA). Finally, mediation analysis was performed to investigate whether DNA methylation of cg21325723 mediates this gene-environment interaction on the risk of developing of ACPA-positive RA. Results We identified and replicated one significant gene-environment interaction between rs6933349 and smoking in DNA methylation of cg21325723. This gene-smoking interaction is a novel interaction in the risk of developing ACPA-positive in both Caucasian (multiplicative P value = 0.056; additive P value = 0.016) and Asian populations (multiplicative P value = 0.035; additive P value = 0.00027), and it is mediated through DNA methylation of cg21325723. Conclusions We showed that DNA methylation of cg21325723 can mediate the gene-environment interaction between rs6933349 and smoking, impacting the risk of developing ACPA-positive RA, thus being a potential regulator that integrates both internal genetic and external environmental risk factors.
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