Proteomic characterisation of the early rheumatoid arthritis-cardiovascular disease multimorbid axis
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Background
Inflammation contributes to the increased risk of cardiovascular disease (CVD) observed in people with rheumatoid arthritis (RA), with increased prevalence observed from time of diagnosis. Subclinical vascular and myocardial abnormalities can be detected with cardiovascular magnetic resonance (CMR) imaging in otherwise low risk individuals. Identifying associated circulating markers could enable diagnostics and implicate biological pathways of RA-CVD. The study’s objective was to identify blood-based proteins associated with CMR measures of vascular and myocardial abnormality and associated inflammatory and/or cardio-metabolic pathways in a new-onset RA cohort.
Methods
Serum samples (baseline/pre-treatment, N = 75 and year 1, N = 71) from CADERA (Coronary Artery Disease Evaluation in Rheumatoid Arthritis) participants, a subgroup of a randomised controlled trial, who underwent CMR, were used to measure 334 proteins across 4 pre-defined Olink panels (Inflammation, Cardiovascular-II, Cardiovascular-III, Cardiometabolic). Bayesian mixed effects regression analyses, unsupervised hierarchical clustering and protein network analyses were applied. Normalised protein expression from 334 Olink proteins were used as exposures in the regression analyses. CMR measures of vascular stiffness (aortic distensibility and stiffness index) and myocardial tissue characteristics (native T1, myocardial extracellular volume and late gadolinium enhancement) were each used as individual outcomes in regression analyses. Associations were considered significant at 95% threshold for credible intervals. An expanded physical protein-protein interaction (PPI) network created using the significant (seed) proteins was subjected to topological and enrichment analysis to identify enriched biological pathways.
Results
54/334 proteins were associated significantly with CMR measures at baseline (7 - vascular; 48 - myocardial tissue characteristics; Coagulation factor 11 with both). Two proteins, TNFSF13B (B-cell activating factor) and CRTAC1, were associated with CMR measures at baseline, were sensitive to change over time and co-varied with changes in CMR measure. Topological analysis of expanded PPI network revealed GRB2 as most connected (degree score=64; closeness score=118.83) and four key signalling pathways, including JAK-STAT and EGFR tyrosine kinase inhibitor resistance, emerged as significant.
Conclusions
This first proteomic study of treatment-naïve early RA and subclinical cardiovascular pathology identifies proteins that could aid diagnostic test development and implicates signalling pathways in the RA-cardiovascular axis to inform on our understanding of the basis of RA-CVD.
