Predictive value of targeted proteomics for coronary plaque morphology in patients with suspected coronary artery disease

Abstract

BackgroundRisk stratification is crucial to improve tailored therapy in patients with suspected coronary artery disease (CAD). This study investigated the ability of targeted proteomics to predict presence of high-risk plaque or absence of coronary atherosclerosis in patients with suspected CAD, defined by coronary computed tomography angiography (CCTA).MethodsPatients with suspected CAD (n = 203) underwent CCTA. Plasma levels of 358 proteins were used to generate machine learning models for the presence of CCTA-defined high-risk plaques or complete absence of coronary atherosclerosis. Performance was tested against a clinical model containing generally available clinical characteristics and conventional biomarkers.FindingsA total of 196 patients with analyzable protein levels (n = 332) was included for analysis. A subset of 35 proteins was identified predicting the presence of high-risk plaques. The developed machine learning model had fair diagnostic performance with an area under the curve (AUC) of 0·79 ± 0·01, outperforming prediction with generally available clinical characteristics (AUC = 0·65 ± 0·04, p < 0·05). Conversely, a different subset of 34 proteins was predictive for the absence of CAD (AUC = 0·85 ± 0·05), again outperforming prediction with generally available characteristics (AUC = 0·70 ± 0·04, p < 0·05).InterpretationUsing machine learning models, trained on targeted proteomics, we defined two complementary protein signatures: one for identification of patients with high-risk plaques and one for identification of patients with absence of CAD. Both biomarker subsets were superior to generally available clinical characteristics and conventional biomarkers in predicting presence of high-risk plaque or absence of coronary atherosclerosis. These promising findings warrant external validation of the value of targeted proteomics to identify cardiovascular risk in outcome studies.FundThis study was supported by an unrestricted research grant from HeartFlow Inc. and partly supported by a European Research Area Network on Cardiovascular Diseases (ERA-CVD) grant (ERA CVD JTC2017, OPERATION). Funders had no influence on trial design, data evaluation, and interpretation.

Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention

“…Thus, GDF-15 was also identified as a predictive candidate in previous studies. 13 , 28 , 31 Similarly, the relevance of plasma MMP12 11 , 13 , 32 , 33 and various chemo/cytokines 28 , 31 , 33 underscore consistency between these studies.…”

“…Based on previous findings, 13 we used targeted proteomics using proteins relating to cardiometabolic disease, CV disease, and inflammation/immune responses. The majority of proteins in our model were related to immune system response; particularly proteins involved in chemotaxis, migration, apoptosis, and angiogenesis.…”

“…In support, we recently identified two complementary protein signatures predicting the presence of high-risk plaque and the absence of coronary atherosclerosis in subjects referred for the analysis of anginal complaints, 12 clearly outperforming the traditional risk algorithm. 13 …”

Artificial Intelligence for Cardiac Imaging-Genetics Research

“…ML algorithms have also shown promise in predicting outcomes, such as imaging surrogates of disease or response to treatment, from complex sets of clinical and genetic variables. For example, to predict the presence or absence of coronary plaques on CT coronary angiography, a gradient boosting classifier was trained on a proteomic assay and identified two distinct protein signatures (85). A subset of these was found to outperform generally available clinical characteristics in the prediction of patients with high risk plaques (AUC = 0.79 vs. AUC = 0.65), while a distinct set outperformed clinical variables in predicting absence of coronary disease (AUC = 0.85 vs. AUC = 0.70).…”

ADAMTS-5 Decreases in Coronary Arteries and Plasma from Patients with Coronary Artery Disease

“…Coronary atherosclerotic disease (CAD) is the most common cardiovascular disease and remains a leading cause of morbidity and mortality worldwide. Narrowing of the arterial lumen and rupture of coronary atherosclerotic plaques with or without luminal thrombosis and vasospasm are currently considered to be the main causes of CAD [1][2][3][4][5]. Several pathophysiologic mechanisms are involved in the process of plaque rupture, including coronary atherosclerotic plaque instability, inflammation, and circumferential wall shear stress.…”