Abstract: Rheumatoid arthritis (RA) is a complex polygenic inflammatory disease associated with accelerated atherosclerosis and increased risk of cardiovascular (CV) disease. Previous genome-wide association studies have described SMAD3 rs17228212 polymorphism as an important signal associated with CV events. The aim of the present study was to evaluate for the first time the relationship between this gene polymorphism and the susceptibility to CV manifestations and its potential association with the presence of subclinical atherosclerosis assessed by the evaluation of carotid intima-media thickness (cIMT) in patients with RA. Methods: One thousand eight hundred and ninety-seven patients fulfilling classification criteria for RA were genotyped for SMAD3 rs17228212 gene polymorphism through TaqMan genotyping assay. Also, subclinical atherosclerosis determined by the assessment of cIMT was analyzed in a subgroup of these patients by carotid ultrasonography. Results: No statistically significant differences were observed when allele frequencies of RA patients with or without CV events were compared. Nevertheless, when RA patients were stratified according to anti-cyclic citrullinated peptide (anti-CCP) status, we found that in RA patients who were negative for anti-CCP antibodies, the presence of C allele of SMAD3 rs17228212 polymorphism conferred a protective effect against the risk of cerebrovascular accident (CVA) after adjustment for demographic and classic CV risk factors (HR [95%CI]=0.36 [0.14?0.94], p=0.038) in a Cox regression model. Additionally, correlation between the presence of C allele of SMAD3 rs17228212 polymorphism and lower values of cIMT was found after adjustment for demographic and classic CV risk factors (p-value=0.0094) in the anti-CCP negative RA patients. Conclusions: Our results revealed that SMAD3 rs17228212 gene variant is associated with lower risk of CVA and less severe subclinical atherosclerosis in RA patients negative for anti-CCP antibodies. These findings may have importance to establish predictive models of CV disease in RA patients according to anti-CCP status.

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