Predicting outcome in acute myocardial infarction: an analysis investigating 175 circulating biomarkers.

AIMS There is a paucity of studies comprehensively comparing the prognostic value of larger arrays of biomarkers indicative of different pathobiological axes in acute myocardial infarction (MI). METHODS AND RESULTS  In this explorative investigation, we simultaneously analysed 175 circulating biomarkers reflecting different inflammatory traits, coagulation activity, endothelial dysfunction, atherogenesis, myocardial dysfunction and damage, apoptosis, kidney function, glucose-, and lipid metabolism. Measurements were performed in samples from 1099 MI patients (SWEDEHEART registry) applying two newer multimarker panels [Proximity Extension Assay (Olink Bioscience), Multiple Reaction Monitoring mass spectrometry]. The prognostic value of biomarkers regarding all-cause mortality, recurrent MI, and heart failure hospitalizations (median follow-up ≤6.6 years) was studied using Lasso analysis, a penalized logistic regression model that considers all biomarkers simultaneously while minimizing the risk for spurious findings. Tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2), ovarian cancer-related tumour marker CA 125 (CA-125), and fibroblast growth factor 23 (FGF-23) consistently predicted all-cause mortality in crude and age/sex-adjusted analyses. Growth-differentiation factor 15 (GDF-15) was strongly predictive in the crude model. TRAIL-R2 and B-type natriuretic peptide (BNP) consistently predicted heart failure hospitalizations. No biomarker predicted recurrent MI. The prognostic value of all biomarkers was abrogated following additional adjustment for clinical variables owing to our rigorous statistical approach. CONCLUSION Apart from biomarkers with established prognostic value (i.e. BNP and to some extent GDF-15), several 'novel' biomarkers (i.e. TRAIL-R2, CA-125, FGF-23) emerged as risk predictors in patients with MI. Our data warrant further investigation regarding the utility of these biomarkers for clinical decision-making in acute MI.

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