IDENTIFICATION OF SERUM PROTEIN BIOMARKERS ASSOCIATED WITH CARDIAC MAGNETIC RESONANCE IMAGINGDEFINED SUBCLINICAL CARDIOVASCULAR ABNORMALITIES IN SYSTEMIC SCLEROSIS PATIENTS CHARACTERISE INFLAMMATION.

Abstract

Introduction: Systemic sclerosis-primary heart involvement (SSc-pHI) accounts for up to one-third of SSc-related deaths and clinically apparent pHI portends poor outcome. Early detection and identification of therapeutic targets is needed to improve the management of SSc-pHI. We have previously shown cardiovascular magnetic resonance (CMR)-detected subclinical abnormalities. In this study, we aimed to identify protein biomarkers associated with subclinical CMR-measured abnormalities in SSc patients, and the predominant inflammatory/cardiometabolic pathways implicated. Material(s) and Method(s): Serum from 78 patients from CONVAS ('CONnective Tissue Disease and VASculitis Cohort') and ELCASA ('ELectrophysiology and CArdiac imaging in SclerodermA') cohorts with no history of pHI, pulmonary hypertension, diabetes or more than 2 traditional cardiovascular (CV) risk factors was used to measure levels of 355 proteins across inflammation, cardiometabolic and cardiovascular II/III Olink panels. Generalised linear regression (corrected for multiple testing) was used to identify significant proteins associated with CMR measures of myocardial oedema/fibrosis (MO/MF) [native T1, myocardial extracellular volume (ECV) and late gadolinium enhancement (LGE)] and vascular stiffness (VS) [aortic distensibility]. Subsequently, an expanded physical protein-protein interaction (PPI) network was created (String-DB) with k-means clustering applied to identify enriched clusters and functional analysis performed (GeneOntology and KEGG). Result(s): Seventy out of 355 proteins were associated with MO/MF (64 proteins; 26 positively, 38 negatively) and VS (6 proteins; 2 positively, 4 negatively). Two overlapping proteins associated with focal (LGE) and diffuse (ECV) fibrosis were identified. Proteins identified include those involved in coagulation cascade (estimate =-1.97, 95%CI =-3.63 to-0.31, adj.p = 0.039), carbohydrate binding and opsonisation activities (estimate =-1.31, 95%CI =-2.19 to-0.43, adj.p = 0.006); and cancer and neovascular inflammatory conditions (estimate =-75.79 95%CI =-119.81 to-31.76, adj.p = 0.002). K-means clustering (enrichment p.value < 1.0e-16) identified 4 clusters (Figure 1) with roles in TNF receptor superfamily binding and NF-kappa B signalling pathway (red); Vascular endothelial growth factor-activated receptor activity and Rap1 signalling pathway (yellow); IL-10 receptor activity and JAK-STAT signalling pathway (blue); and FGF activated class receptor binding and ErbB signalling pathway (green). Proteins associated with CMR detected subclinical myocardial tissue oedema/ fibrosis mainly mapped to yellow and blue clusters. Conclusion(s): In this first proteomic study of subclinical SSc-pHI, we have identified 70 protein biomarkers, with MO/MF associated with inflammation and vascular pathways. The next step is to validate these proteins and test the utility of network proteins in an independent patient cohort that could aid detection and diagnosis of SSc-pHI.