| Autor: |
Daniele Andreini, Eleonora Melotti, Chiara Vavassori, Mattia Chiesa, Luca Piacentini, Edoardo Conte, Saima Mushtaq, Martina Manzoni, Eleonora Cipriani, Paolo M. Ravagnani, Antonio L. Bartorelli, Gualtiero I. Colombo |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Biomedicines, Vol 10, Iss 6, p 1309 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2227-9059 |
| DOI: |
10.3390/biomedicines10061309 |
| Popis: |
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 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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