European BestAgeing Study on microRNA candidates for cardiovascular disease
Background: Circulating miRNAs have emerged as promising biomarker candidates due to their stability and their role in regulating key pathological pathways in cardiovascular disease (CVD). Yet, large-scale, multicenter studies examining their diagnostic and prognostic potential are scarce. This study evaluates the potential of miRNA expression profiles to inform disease classification and risk stratification across major CVD phenotypes, including acute coronary syndrome (ACS), chronic coronary artery disease (CAD), dilated cardiomyopathy (DCM), and ischemic cardiomyopathy (ICM), in a large, multicenter European cohort. Methods: We assessed genome-wide miRNA expression profiles in a total of 1,209 cardiovascular patients and 848 controls in a uniform, standardized fashion, which renders this study one of the largest prospective miRNA studies. To focus on only the most biologically plausible miRNAs for clinical translation, we mined all original studies of miRNA candidates in CVD and performed differential miRNA expression and enrichment analysis. We then trained disease-specific binary classification models to evaluate the diagnostic potential of miRNA signatures. Finally, we evaluated prognosis and disease severity based on distinct miRNA levels. Results: 634 original abstracts were identified, detailing 166 ACS, 181 CAD, 56 DCM, and 182 ICM miRNAs. Without further optimization, the signatures of a priori miRNAs already yielded very good diagnostic performance with ROC AUC of 0.83 – 0.95. There was an improvement when considering additional miRNAs in a discovery setting. Interestingly, in ACS, CAD and DCM we observed a significantly worse prognosis in probands with higher scores in the miRNA signatures, indicating additional prognostic information. Conclusions: The European BestAgeing miRNA study reveals emerging associations of several miRNA signatures with cardiovascular disease discrimination and prognostication, providing a foundation for future external validation and potential clinical translation of this class of markers.
- Type: Other
- Archiver: European Genome-Phenome Archive (EGA)
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
| Dataset ID | Description | Technology | Samples |
|---|---|---|---|
| EGAD00010002788 | Agilent Human miRNA Microarray | 4762 |
