Skau E, Henriksen E, Wagner P, Hedberg P, Siegbahn A, Leppert J
Eur J Prev Cardiol 24 (15) 1576-1583 [2017-10-00; online 2017-08-01]
Background The Proximity Extension Assay proteomics chip provides a large-scale analysis of 92 biomarkers linked to cardiovascular disease or inflammation. We aimed to identify the biomarkers that best predicted long-term all-cause mortality in patients with acute myocardial infarction. Methods In this prospective cohort study, 92 biomarkers were analysed in 847 consecutive patients from the Västmanland Myocardial Infarction Study with a median follow-up of 6.9 years. Results The mean (± standard deviation) age of the patients was 70 (11.8) years and 32.7% were female. Two hundred and seven patients had died after follow-up. The biomarkers most strongly linked to all-cause mortality were growth differentiation factor 15 (GDF-15) and tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2). Cox regression analysis showed that GDF-15 (hazard ratio 1.25 per unit change, 95% confidence interval, 1.02-1.53, p = 0.031) and TRAIL-R2 (hazard ratio 1.37 per unit change, 95% confidence interval 1.12-1.67, p = 0.002) were independent predictors of long-term all-cause mortality after adjusting for age, gender, diabetes, previous myocardial infarction, stroke, heart failure, hypertension, smoking, hypercholesterolaemia, body mass index, ST-elevation myocardial infarction, left ventricular ejection fraction, troponin I, estimated glomerular filtration rate, N-terminal pro-brain natriuretic peptide and C-reactive protein. The combination of GDF-15 and TRAIL-R2 with established risk factors and biomarkers showed a discriminating accuracy of separating survivors from non-survivors with a cross-validated area under the receiving operating characteristics curve of 0.88 within five years. Conclusion GDF-15 and TRAIL-R2 were the most powerful Proximity Extension Assay chip biomarkers in predicting long-term all-cause mortality in patients with acute myocardial infarction.
Affinity Proteomics Uppsala [Service]
PLA and Single Cell Proteomics [Service]
PubMed 28762762
DOI 10.1177/2047487317725017
Crossref 10.1177/2047487317725017