Related Experiment Video
Updated: Jun 25, 2025
Tissue-specific miRNA Expression Profiling in Mouse Heart Sections Using In Situ Hybridization
Published on: September 15, 2018
Unveiling MiRNA-124 as a biomarker in hypertrophic cardiomyopathy: An innovative approach using machine learning and
Maria Pisklova1, German Osmak1
1E.I. Chazov National Medical Research Center for Cardiology, Academician Chazov st. 15a, 121552 Moscow, Russia; Pirogov Russian National Research Medical University, Ostrovitianov st. 1, 117997 Moscow, Russia.
Insights
Researchers identified miR-124-3p as a key regulator in hypertrophic cardiomyopathy (HCM) pathogenesis. This microRNA (miRNA) targets key genes involved in the RhoA signaling pathway, offering new diagnostic and therapeutic insights for HCM.
Area of Science:
- Cardiovascular Research
- Molecular Biology
- Genomics
Background:
- Hypertrophic cardiomyopathy (HCM) is a hereditary heart condition with poorly understood mechanisms.
- Both monogenic and polygenic forms of HCM are increasingly recognized.
- Transcriptomic profiling offers a powerful approach to investigate complex diseases like HCM.
Purpose of the Study:
- To develop a novel computational method for identifying disease-associated microRNAs (miRNAs) using transcriptomic data.
- To investigate the role of miRNAs in the pathogenesis of hypertrophic cardiomyopathy (HCM).
Main Methods:
- Applied Monte Carlo simulation and machine learning to transcriptomic data for HCM classification.
- Identified key genes from high-capacity classifiers.
- Selected miRNAs targeting multiple key genes, focusing on miR-124-3p.
- Validated miR-124-3p association with HCM using an independent dataset.
Main Results:
- Developed a novel computational approach to identify disease-associated miRNAs.
- Identified 16 key genes critical for HCM classification.
- Discovered miR-124-3p as a significant miRNA associated with HCM.
- Confirmed miR-124-3p's involvement in the RhoA signaling pathway.
Conclusions:
- Proposed a new method for analyzing transcriptomic data to find disease-associated miRNAs.
- Identified miR-124-3p as a potential regulator in hypertrophic cardiomyopathy pathogenesis.
- Highlighted the role of miR-124-3p in the RhoA signaling pathway relevant to HCM.
Background:
Hypertrophic cardiomyopathy (HCM) is a widespread hereditary cardiac pathology characterized by thickened heart walls and rearrangement of cardiomyocytes. Despite extensive research, the mechanisms underlying HCM development remain poorly understood, impeding the development of effective therapeutic and diagnostic strategies. Recent studies have suggested a polygenic nature of HCM development alongside monogenic forms. Transcriptomic profiling is a valuable tool for investigating such diseases. In this study, we propose a novel approach to study regulatory microRNAs (miRNAs) in the context of HCM, utilizing state-of-the-art data analysis tools.
Methods And Results:
Our method involves applying the Monte Carlo simulation and machine learning algorithm to transcriptomic data to generate high-capacity classifiers for HCM. From these classifiers, we extract key genes crucial for their performance, resulting in the identification of 16 key genes. Subsequently, we narrow down the pool of miRNAs by selecting those that may target the greatest number of key genes within the best models. We particularly focused on miR-124-3p, which we validated to have an association with HCM on an independent dataset. Subsequent investigation of its function revealed involvement of miR-124-3p in the RhoA signaling pathway.
Conclusions:
In this study we propose a new approach to analyze transcriptomic data to search for microRNAs associated with a disease. Using this approach for transcriptomic profiling data of patients with HCM, we identified miR-124-3p as a potential regulator of the RhoA signaling pathway in the pathogenesis of HCM.
