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Integration of short non coding RNA and genetic factors for coronary artery disease risk prediction in a prospective study.
Sci. Rep. 16:8364 (2026)
Coronary artery diseases (CADs) continue to be the leading global contributors to multi-morbidity and mortality. Given the significant burden of CADs, there is a critical need to identify novel and effective biomarkers for risk assessment. This study sought to evaluate the potential of serum extracellular vesicle-derived small non-coding RNAs (sncRNAs) as predictive biomarkers for CAD risk. Using next-generation sequencing approach, the levels of extracellular vesicles (EVs)-associated sncRNAs were analysed in serum samples from 91 pre-clinical CAD cases and their matched healthy controls, sourced from the prospective EPICOR cohort. We evaluated the predictive ability of sncRNAs alone and in combination with polygenic risk score (PRS) PGS000329. We identified 44 differentially expressed microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs) (FDR < 0.05), which were then narrowed down to ten significant signals (|log2FC|>0.6) for technical validation. RT-qPCR analysis confirmed the trend of expression for two miRNAs (miR-194-5p and miR-451a) and six piRNAs (piR-20266, piR-23533, piR-27282, piR-28212, piR-1043, piR-619). The ROC curve from a Random Forest model showed a higher discrimination ability of piR-619 and piR-23,533 (AUC = 0.72) compared to the use of traditional risk factors alone (AUC = 0.68). To enhance CAD risk assessment, we integrated genetic data by stratifying the cohort into two groups based on the 80th percentile of the PGS000329. We observed an odds ratio (OR) of 2.8 (95% CI: 1.3-6.4, p = 0.01) using PGS000329 alone. When the model was adjusted to include two piRNAs and smoking status, the OR increased to 3.26 (95% CI: 1.2-9.5, p = 0.02). Even though this study is limited by the absence of an independent replication cohort, these findings suggest that the two piRNAs pattern could contribute to predict the risk of CAD and may provide valuable insights into the underlying pathogenesis of the disease, in particular integrating individual CAD-PRS.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Biomarkers ; Coronary Artery Disease ; Mirnas ; Ngs ; Pirnas ; Polygenic Risk Score; Piwi-interacting Rnas; Cardiovascular-disease; Heart-failure; Micrornas; Regulators; Abundant; Stroke; Impact; Epicor; Cancer
ISSN (print) / ISBN
2045-2322
e-ISSN
2045-2322
Journal
Scientific Reports
Quellenangaben
Volume: 16,
Issue: 1,
Article Number: 8364
Publisher
Springer
Publishing Place
London
Reviewing status
Peer reviewed
Institute(s)
Institute of Epidemiology (EPI)
Grants
Ministero dell'Istruzione, dell'Universit e della Ricerca