# MicroRNA-143-3p and miR-452-5p: A Fingerprint for the Diagnosis of Aortic Stenosis in the Geriatric Population

## TL;DR

This study identifies two microRNAs, miR-143-3p and miR-452-5p, as potential biomarkers for diagnosing aortic stenosis in elderly patients when combined with echocardiographic data.

## Contribution

The study introduces a novel multiparametric model combining two miRNAs with echocardiographic parameters to improve AS diagnosis in the geriatric population.

## Key findings

- Fifty-four miRNAs were differentially expressed in AS patients compared to controls.
- miR-143-3p and miR-452-5p were significantly upregulated in AS patients.
- A multiparametric model using these miRNAs and echocardiographic data achieved 78.2% sensitivity and 70.7% specificity.

## Abstract

Background/Objectives: Aortic stenosis (AS) is the most common valvular pathology in the geriatric population and is the primary cause of valve replacement. However, misdiagnoses and delays in treatment are common due to comorbidities, frailty, and sedentary lifestyles among elderly individuals. MicroRNAs (miRNAs) are highly conserved molecular regulators involved in various cellular processes and have gained recognition as reliable biomarkers in cardiovascular diseases. In the present study, we evaluated plasma miRNAs as potential biomarkers for the early diagnosis of AS in the geriatric population to identify early therapeutic strategies. Methods: This prospective, case–control study included 87 individuals over 75 years of age. The participants were divided into AS (n = 58) and control (n = 29) groups. Results: Fifty-four miRNAs were differentially expressed between patients with AS and controls. Among those genes, 29 were upregulated and 25 were downregulated in patients with AS relative to controls. We selected seven candidate genes (miR-185-5p, miR-143-3p, miR-370-3p, let-7d-3p, miR-452-5p, miR-6787-3p, and miR-21-3p) for experimental validation by qRT–PCR. Only miR-143-3p and miR-452-5p were significantly upregulated in the plasma of patients with AS compared with controls. We developed a multiparametric model by combining the two-miRNA signature with echocardiographic parameters (left ventricular ejection fraction, stroke volume, and global longitudinal strain) to increase diagnostic power; this model yielded sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values of 78.2%, 70.7%, and 0.837, respectively. Conclusions: In clinical practice, the use of a multiparametric model involving this set of miRNAs combined with echocardiographic variables may improve the accuracy of AS diagnosis and risk stratification.