Machine learning integration in microRNA-based markers for cardiovascular diseases: A systematic review

Table 1 Characteristics of the selected studies that met the inclusion criteria

Ref.	Setting	CVD	Sample size	Identified miRNAs	Role	Main outcome
Kayvanpour et al[8], 2021	Germany	ACS	66 ACS patients and 68 healthy controls; 148 suspected ACS patients initially enrolled	Top 10 miRNAs selected via ANOVA F-value: MiR-142-5p, miR-151a-3p, miR-145-5p, miR-186-5p, miR-191-5p, miR-29c-5p, miR-30d-5p, miR-342-5p, miR-362-5p, and miR-589-5p	Diagnosis of ACS	Machine learning models, including neural networks, classified ACS with high diagnostic performance
Ren et al[13], 2024	United States	AMI/STEMI	24 screening samples; n = 6 each for no known CAD, known CAD, STEMI-pre, and STEMI-PCI; validation samples also used	Already identified: MiR-499, miR-1, miR-208b. Newly identified: MiR-331-3p, miR-142-5p, miR-200b-3p, miR-132-3p, miR-3605-5p, miR-18a-5p, miR-423-5p, miR-543, miR-301a-3p	Diagnosis and differentiation of AMI/STEMI from stable CAD	SCAD/LASSO regularized LR identified a 9-miRNA profile that differentiated no known CAD, known CAD, STEMI-pre, and STEMI-PCI, with ROC curves approaching 1 in selected comparisons; explored for rapid point-of-care diagnosis using MIX.miR ion-exchange membrane technology
Samadishadlou et al[14], 2023	Iran	AMI and stable CAD	Healthy (51), CAD (46), AMI (111)	Differentially expressed: Hsa-miR-21-3p, hsa-miR-32-3p, hsa-miR-186-5p. Additionally selected via AUC-ROC: Hsa-miR-197-5p, hsa-miR-29a-5p, hsa-miR-296-5p	Diagnosis of AMI; differentiating AMI from healthy samples and from CAD	Peripheral blood mononuclear cell-derived miRNA signatures were used to differentiate healthy controls, stable CAD, and MI samples
Samadishadlou et al[15], 2024	Iran	AMI	Training set: 62 MI and 94 healthy controls; independent test set: 8 MI and 6 healthy controls	Hsa-miR-375-3p, hsa-miR-601, hsa-miR-34a-5p, hsa-miR-29c-5p, hsa-miR-330-5p, hsa-miR-199b-5p, hsa-miR-142-3p, hsa-miR-200a-3p, hsa-miR-132-5p, hsa-miR-133a-3p	Diagnosis of early-stage AMI	ML model identified 10 miRNAs with accuracy of 0.86 and AUC of 0.83 for diagnosing AMI
Reel et al[16], 2025	United Kingdom	Essential HTN subtypes	Cushing’s syndrome (35), primary aldosteronism (109), paraganglioma/pheochromocytoma (75), primary HTN (111)	Hsa-miR-15a-5p, hsa-miR-32-5p, hsa-miR-485-3p, hsa-miR-495-3p, hsa-miR-1260a, hsa-miR-186-5p, hsa-miR-195-5p, hsa-miR-326, hsa-miR-139-5p, hsa-miR-133a-3p, hsa-miR-223-3p	Differentiation of endocrine HTN subtypes from primary HTN	Models trained with the miRNAs achieved balanced accuracy of 0.71-0.89 and AUCs of 0.8-0.9 in differentiating HTN subtypes and other conditions
Sajid et al[17], 2024	Pakistan	CAD	CAD cases (58), controls without CAD/stenosis < 50% (55)	MiR-21, miR-33a, miR-133a, miR-145, miR-146a	Diagnosis of CAD	ML models using miRNA biomarkers showed good diagnostic performance for angiography-defined CAD
Yerukala Sathipati et al[18], 2025	United States	Post-operative AF after CABG	Cases (7), controls (8)	Hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-184, hsa-let-7a-5p, hsa-miR-124-3p, hsa-miR-200a-3p, hsa-miR-423-5p, hsa-miR-96-5p, hsa-miR-100-5p, hsa-miR-17-5p	Prediction of post-operative AF after CABG	10 pre-operative circulating miRNA signatures were used to develop ML models for predicting POAF after CABG
Jusic et al[19], 2023	Luxembourg/Bosnia and Herzegovina	HTN	89 cases, 85 controls	MiR-361-3p and miR-501-5p	Diagnosis of HTN	SVM model using the two miRNAs plus clinical characteristics achieved accuracy of 0.87, specificity of 0.91, sensitivity of 0.83, and AUC of 0.90
Errington et al[20], 2021	United Kingdom	PAH	64 cases, 43 disease and healthy controls	MiR-636 and miR-187-5p	Diagnosis of PAH	Models using the two miRNAs showed high diagnostic accuracy in differentiating PAH patients from healthy controls

CVD: Cardiovascular disease, CAD: Coronary artery disease, HTN: Hypertension; AMI: Acute myocardial infarction; ACS: Acute coronary syndrome, AF: Atrial fibrillation, PAH: Pulmonary arterial hypertension, CABG: Coronary artery bypass grafting; miRNA: MicroRNA; STEMI: ST elevation myocardial infarction; PCI: Percutaneous coronary intervention; SCAD: Smoothly clipped absolute deviation; LASSO: Least absolute shrinkage and selection operator; LR: Logistic regression; ROC: Receiver operating characteristic; MI: Myocardial infarction; AUC: Area under the curve; POAF: Post-operative atrial fibrillation; SVM: Support vector machines.