Rheumatoid arthritis, cardiovascular imaging and disease associations in UK Biobank

Background Rheumatoid arthritis (RA) is an immune-mediated inflammatory disease that is associated with increased cardiovascular morbidity and mortality. Despite its recognised cardiovascular burden, the mechanisms linking systemic inflammation to adverse cardiac outcomes remain unclear. Purpose This study uses rich clinical, cardiovascular magnetic resonance (CMR), and genetic data in UK Biobank to quantify novel observational and genetic associations between RA, and cardiovascular disease (CVD) and imaging outcomes. Methods We evaluated the associations between RA and cardio-metabolic diseases, including ischaemic heart disease (IHD), myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), arrhythmias, non-ischaemic cardiomyopathy (NICM), pericardial disease, stroke, peripheral vascular disease (PVD), venous thromboembolism (VTE), diabetes, hypertension and hypercholesterolaemia. Multivariable logistic regression, together with Cox proportional hazard and linear regression models, were used to examine associations with clinical events, and with CMR metrics. Models were adjusted for demographics and cardiovascular risk factors. Two-sample Mendelian Randomisation (MR) analysis used genome-wide association studies (GWAS) of RA (22,350 cases; 74,823 controls of European ancestry) and CVDs from the FinnGen consortium (224,737 individuals) and six GWAS of CMR metrics. Causal estimates were derived using inverse-variance weighting, with additional methods applied for robustness and pleiotropy adjustments. Bonferroni correction was applied for multiple testing (α < 0.0056). Results A total of 1,474 participants with RA [mean age 59.9, (70.4%) female, 97.4% of European ethnicity] and 493,630 controls [mean age 56.5, (54.2%) female, 96.6% European] were identified. Multivariable analysis demonstrated that participants with RA had significantly higher odds of prevalent cardiovascular and metabolic diseases compared to control. RA was associated with an increased incidence of all CVDs examined, with the strongest associations observed for pericardial diseases (HR=2.88; 95%CI: 2.04, 4.06; p<0.001), HF (HR=1.92; 95%CI: 1.63, 2.27; p<0.001), and NICM (HR=1.69; 95%CI: 1.06, 2.68; p=0.03). MR analyses provided genetic evidence linking RA susceptibility to an increased risk of acute MI (OR=1.07; 95%CI: 1.02, 1.09; p=0.009), arrhythmia (OR=1.05; 95%CI: 1.02, 1.06; p<0.001), and IHD (OR=1.05; 95%CI = 1.01, 1.06; p=0.036). No significant observational or causal (MR) associations were found between RA and CMR metrics (Figure 1). Conclusion By integrating observational and genetic evidence, this study highlights the increased cardiovascular burden in RA patients. Using state-of-the-art MR methods, it provides evidence of causal associations between RA with ischaemic CVDs and arrhythmias, underscoring the need for early cardiovascular risk stratification and a multidisciplinary approach to optimise management in this high-risk population.Figure 1