High-frequency metabolite profiling and the incidence of recurrent cardiac events in patients with post-acute coronary syndrome
Purpose: The aim of this study was to study temporal changes in metabolite profiles in patients with post-acute coronary syndrome (ACS), in particular prior to the development of recurrent ACS (reACS). Methods: BIOMArCS (BIOMarker study to identify the Acute risk of a Coronary Syndrome) is a prospective study including patients admitted for ACS, who underwent high-frequency blood sampling during 1-year follow-up. Within BIOMArCS, we performed a nested case-cohort analysis of 158 patients (28 cases of reACS). We determined 151 metabolites by nuclear magnetic resonance in seven (median) blood samples per patient. Temporal evolution of the metabolites and their relation with reACS was assessed by joint modelling. Results are reported as adjusted (for clinical factors) hazard ratios (aHRs). Results: Median age was 64 (25th–75th percentiles; 56–72) years and 78% were men. After multiple testing correction (p < 0.001), high concentrations of extremely large very low density lipoprotein (VLDL) particles (aHR 1.60/SD increase; 95%CI 1.25–2.08), very large VLDL particles (aHR 1.60/SD increase; 95%CI 1.25–2.08) and large VLDL particles (aHR 1.56/SD increase; 95%CI 1.22–2.05) were significantly associated with reACS. Moreover, these longitudinal particle concentrations showed a steady increase over time prior to reACS. Among the other metabolites, no significant associations were observed. Conclusion: Post-ACS patients with persistent high concentrations of extremely large, very large and large VLDL particles have increased risk of reACS within 1 year.
|Atherosclerosis, lipids, metabolite kinetics, repeated measurements, VLDL|
|Organisation||Department of Cardiology|
Vroegindewey, M.M, van den Berg, V.J, Oemrawsingh, R.M, Kardys, I, Asselbergs, F.W, van der Harst, P, … Boersma, H. (2020). High-frequency metabolite profiling and the incidence of recurrent cardiac events in patients with post-acute coronary syndrome. Biomarkers. doi:10.1080/1354750X.2020.1731762