Coronary artery disease in people without standard modifiable risk factors: a clinical, imaging and biomarker assessment.

Abstract

Prevention programs targeting Standard Modifiable cardiovascular Risk Factors (SMuRFs: hypertension, diabetes, hypercholesterolemia, smoking) are critical, yet ST elevation myocardial infarction (STEMI) in the absence of SMuRFs is not infrequent. Clinical outcomes of SMuRF-less STEMI patients have not been adequately assessed. Primary prevention risk assessments using SMuRFs do not adequately capture individual host response to risk factors. Novel markers reflecting disease activity and susceptibility are needed. Aims • Assess proportion of SMuRF-less STEMI patients • Examine outcomes of SMuRF-less STEMI patients • Describe rationale and methodology of the BioHEART cohort study • Assess coronary artery disease (CAD) phenotypes in BioHEART-CT • Assess for novel CAD biomarkers in BioHEART a. plasma metabolites b. IgE-sensitisation to the mammalian oligosaccharide galactose-α-1,3-galactose (α-Gal) Methods & Results The proportion and clinical outcomes of SMuRF-less STEMI patients were assessed in 3 retrospective cohort studies. 15%-25% of STEMI patients without prior CAD have no SMuRFs. SMuRF-less STEMI patients have higher early mortality (11% vs 8%, P<0.0001, n=62,048), with the highest rate in SMuRF-less women (18%). The BioHEART-CT cohort study was established to identify novel biomarkers, mechanistic pathways, and improve risk assessment. Associations between SMuRFs and CAD phenotypes were assessed, identifying marked differences between the sexes. Novel metabolite associations with CAD phenotypes were demonstrated, as were strong associations between α-gal sensitization secondary to tick bites and clinically relevant CAD phenotypes including non-calcified plaque, obstructive CAD and STEMI. Conclusion 15-25% of STEMI patients have no SMuRFs and SMuRF-less STEMI patients have a higher 30-day mortality rate. The BioHEART-CT cohort study utilising precise imaging and molecular phenotyping is well placed for largescale a priori and unbiased biomarker discovery studies.