Abstract
Identification of individuals who are at risk of suffering from acute coronary syndromes (ACS) may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases). Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75). ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664), which was similar to Framingham risk scoring (c-statistics = 0.644) in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP), combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751) resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001) and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007). In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice.
Highlights
Coronary artery disease (CAD) and its complications such as acute coronary syndrome (ACS) are a leading cause of morbidity and mortality worldwide [1]
To identify ACS-specific prognostic urinary peptide biomarkers potentially discriminating between individuals with and without future ACS events, we compared the Capillary Electrophoresis–Mass Spectrometry (CE-MS)-based urinary proteome profiles of 84 fatal and non-fatal ACS cases occurring within a mean time interval of 2.34 ± 1.48 years during follow-up after urine sampling and 84 age- and sex-matched controls
Since this had previously led to the identification of urinary peptide biomarkers characteristic of atherosclerosis [30], CAD [7,31,32], we hypothesized that urinary proteome/peptidome profiles contain peptide biomarkers indicative of different pathophysiological aspects in the progression of atherosclerotic plaques towards the inflamed, unstable, “vulnerable”, thin-cap fibroatheromas that are prone to rupture, and cause thrombotic occlusion of coronary arteries presenting as ACS
Summary
Coronary artery disease (CAD) and its complications such as acute coronary syndrome (ACS) are a leading cause of morbidity and mortality worldwide [1]. Several directions have been taken to search for the ideal methods for predicting future cardiovascular events, including simple clinical risk scoring systems such as the Framingham Risk Score and non-invasive techniques such as carotid intima-media thickness measurements by ultrasound. Reliable biomarkers to predict future ACS-events could lead to improved risk stratification, enable earlier interventions and potentially reduce the incidence of ACS. Yin et al used mass spectrometry based plasma proteomics to identify protein biomarkers for the new onset of acute myocardial infarction (AMI) during a 3-year follow up in the Framingham Heart Study offspring cohort [5]. A multi-marker model composed of seven plasma proteins thereby reached a median C-statistic of 0.84 and exceeded models with regular clinical covariates
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