Rheumatoid Arthritis and the Risk of Cardiovascular Disease: Biomarkers Risk Prediction and Underlying Mechanisms

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PROJECT ABSTRACT Inflammation contributes substantially to atherosclerotic cardiovascular disease (CVD) in the general population. Epidemiology, basic science and randomized clinical trial data support the importance of this relationship. Patients with systemic inflammatory conditions, such as rheumatoid arthritis (RA), can provide important insights into this relationship because of their more extreme systemic inflammatory phenotype. Investigators have appreciated the elevated risk of CVD experienced by RA patients: the risk of MI and stroke are both elevated in RA compared with the general population, contributing to a shortened lifespan. CVD risk stratification in RA is imprecise and general population tools are not accurate. Most attempts at improving CVD risk stratification have added clinical RA factors to existing population risk tools. Easily assessed protein biomarkers would likely enhance CVD risk prediction. The literature strongly suggests relationships between > 20 biomarkers shared by RA and CVD. These relationships have never been studied systematically across diseases. The overarching goal of this proposal is to identify protein biomarkers for CVD in RA patients, leveraging the structure of a controlled trial and rigorous methods for deriving and validating a risk score. We complement the robust biomarker analyses with high-dimensional cellular immuneprofiling, which has the potential to link specific cell types mechanistically to protein biomarkers and to identify new cellular biomarkers. We conducted a randomized controlled trial, the TARGET trial, to examine whether specific treatments for RA produce reductions in CV risk as measured by FDG PET/CT. This trial, funded by NIH (U01 AR068043) allowed us to prospectively characterize RA patients, collect biospecimens before and after treatment, and conduct baseline and 24-week FDG PET/CT scans to assess vascular inflammation. Analyses are still ongoing to determine whether different RA treatments translate into differential changes in CV risk. We propose to leverage the TARGET study cohort, dataset and biorepository for the following aims. Aim 1: To use a comprehensive biomarker panel to derive and validate a CV risk score for patients with RA. The TARGET trial provides biospecimens, patient phenotypes, and a broad biomarker discovery panel that will have been run as an in-kind donation. We hypothesize that adding biomarkers to the Pooled Cohort Equation and variables related to RA disease activity will significantly improve prediction of CV outcomes in RA patients. Aim 2: To elucidate cellular immune mechanisms linking RA and CVD through scRNA-seq profiling. We will use single cell transcriptomic and surface proteomics (CITE-seq) to study PBMCs from a subset of TARGET patients, including both responders and non-responders based on FDG PET/CT, to identify circulating immune cell populations associated with CV risk and CV biomarkers. We hypothesize that specific immune cell populations will associate with CV risk at baseline and will decrease in abundance or activation state after treatment in parallel with CV risk. Further, these treatments will differ in their effects on relevant cell populations.