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Whole-Blood Transcriptional Profiles Enable Early Prediction of the Presence of Coronary Atherosclerosis and High-Risk Plaque Features at Coronary CT Angiography.

ABSTRACT: Existing tools to estimate cardiovascular (CV) risk have sub-optimal predictive capacities. In this setting, non-invasive imaging techniques and omics biomarkers could improve risk-prediction models for CV events. This study aimed to identify gene expression patterns in whole blood that could differentiate patients with severe coronary atherosclerosis from subjects with a complete absence of detectable coronary artery disease and to assess associations of gene expression patterns with plaque features in coronary CT angiography (CCTA). Patients undergoing CCTA for suspected coronary artery disease (CAD) were enrolled. Coronary stenosis was quantified and CCTA plaque features were assessed. The whole-blood transcriptome was analyzed with RNA sequencing. We detected highly significant differences in the circulating transcriptome between patients with high-degree coronary stenosis (≥70%) in the CCTA and subjects with an absence of coronary plaque. Notably, regression analysis revealed expression signatures associated with the Leaman score, the segment involved score, the segment stenosis score, and plaque volume with density <150 HU at CCTA. This pilot study shows that patients with significant coronary stenosis are characterized by whole-blood transcriptome profiles that may discriminate them from patients without CAD. Furthermore, our results suggest that whole-blood transcriptional profiles may predict plaque characteristics.

SUBMITTER: Andreini D

PROVIDER: S-EPMC9219643 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Whole-Blood Transcriptional Profiles Enable Early Prediction of the Presence of Coronary Atherosclerosis and High-Risk Plaque Features at Coronary CT Angiography.

Andreini Daniele D Melotti Eleonora E Vavassori Chiara C Chiesa Mattia M Piacentini Luca L Conte Edoardo E Mushtaq Saima S Manzoni Martina M Cipriani Eleonora E Ravagnani Paolo M PM Bartorelli Antonio L AL Colombo Gualtiero I GI

Biomedicines 20220602 6

Existing tools to estimate cardiovascular (CV) risk have sub-optimal predictive capacities. In this setting, non-invasive imaging techniques and omics biomarkers could improve risk-prediction models for CV events. This study aimed to identify gene expression patterns in whole blood that could differentiate patients with severe coronary atherosclerosis from subjects with a complete absence of detectable coronary artery disease and to assess associations of gene expression patterns with plaque fea ...[more]

PMID: 35740331

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Project description:Purpose To assess the relationship between total, calcified, and noncalcified coronary plaque burdens throughout the entire coronary vasculature at coronary computed tomographic (CT) angiography in relationship to cardiovascular risk factors in asymptomatic individuals with low-to-moderate risk. Materials and Methods This HIPAA-compliant study had institutional review board approval, and written informed consent was obtained. Two hundred two subjects were recruited to an ongoing prospective study designed to evaluate the effect of HMG-CoA reductase inhibitors on atherosclerosis. Eligible subjects were asymptomatic individuals older than 55 years who were eligible for statin therapy. Coronary CT angiography was performed by using a 320-detector row scanner. Coronary wall thickness and plaque were evaluated in all epicardial coronary arteries greater than 2 mm in diameter. Images were analyzed by using dedicated software involving an adaptive lumen attenuation algorithm. Total plaque index (calcified plus noncalcified plaque) was defined as plaque volume divided by vessel length. Multivariable regression analysis was performed to determine the relationship between risk factors and plaque indexes. Results The mean age of the subjects was 65.5 years ± 6.9 (standard deviation) (36% women), and the median coronary artery calcium (CAC) score was 73 (interquartile range, 1-434). The total coronary plaque index was higher in men than in women (42.06 mm(2) ± 9.22 vs 34.33 mm(2) ± 8.35; P < .001). In multivariable analysis controlling for all risk factors, total plaque index remained higher in men than in women (by 5.01 mm(2); P = .03) and in those with higher simvastatin doses (by 0.44 mm(2)/10 mg simvastatin dose equivalent; P = .02). Noncalcified plaque index was positively correlated with systolic blood pressure (β = 0.80 mm(2)/10 mm Hg; P = .03), diabetes (β = 4.47 mm(2); P = .03), and low-density lipoprotein (LDL) cholesterol level (β = 0.04 mm(2)/mg/dL; P = .02); the association with LDL cholesterol level remained significant (P = .02) after additional adjustment for the CAC score. Conclusion LDL cholesterol level, systolic blood pressure, and diabetes were associated with noncalcified plaque burden at coronary CT angiography in asymptomatic individuals with low-to-moderate risk. (©) RSNA, 2015 Online supplemental material is available for this article.

Dataset Information

Whole-Blood Transcriptional Profiles Enable Early Prediction of the Presence of Coronary Atherosclerosis and High-Risk Plaque Features at Coronary CT Angiography.

Publications

Whole-Blood Transcriptional Profiles Enable Early Prediction of the Presence of Coronary Atherosclerosis and High-Risk Plaque Features at Coronary CT Angiography.

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