Systematic review evaluates microRNA signatures' roles as biomarkers in cardiovascular diseases, suggesting clinical potential.
Cardiovascular diseases remain the leading contributors to global morbidity and mortality, and current diagnostic and prognostic tools do not fully capture disease-specific molecular changes. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and are increasingly being investigated as stable circulating biomarkers in cardiovascular disorders. This systematic review aimed to qualitatively synthesise evidence on microRNA signatures associated with cardiovascular diseases and evaluate their diagnostic, prognostic, predictive, severity-related, and treatment-response relevance. A systematic search was conducted in PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, and Google Scholar using microRNA-, cardiovascular disease-, and biomarker-related terms. Original studies reporting extractable microRNA findings in cardiovascular disease populations or clinically relevant translational models with human validation were included. Review articles were used only for background context. Eleven eligible studies were qualitatively synthesised; no meta-analysis was performed because of heterogeneity in cardiovascular phenotypes, biospecimens, analytical platforms, and outcomes. The review found that plasma and serum microRNA signatures were associated with acute myocardial infarction, coronary artery disease, postoperative atrial fibrillation, heart failure, HFpEF, pulmonary arterial hypertension, coronary artery calcification, and cardiovascular risk burden. Multi-microRNA panels generally showed stronger clinical performance than single markers. The evidence base was limited by heterogeneity in study populations, cardiovascular phenotypes, biospecimen sources, miRNA extraction and profiling platforms, normalisation approaches, outcome definitions, and limited standardisation across miRNA platforms. Overall, microRNA signatures represent promising minimally invasive biomarkers for cardiovascular disease characterisation, although standardised validation remains essential before clinical implementation.
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Mahapatra et al. (2026) studied this question.
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