Computational framework for analyzing miRNA-mRNA interactions in sarcopenia: Insights into age-related muscular degeneration

Aspects of molecular medicine Pub Date : 2025-03-07 DOI:10.1016/j.amolm.2025.100070

Sarvesh Sabarathinam , Akash Jayaraman , Ramesh Venkatachalapathy , Subhiksha Shekar

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引用次数: 0

Abstract

Background

Sarcopenia, an age-related loss of skeletal muscle mass and function, impairs mobility, fragility, and quality of life. Despite progress in pathophysiology, molecular processes remain unknown. Recent research has investigated miRNAs as biomarkers for sarcopenia diagnosis and therapy. This work analyses differentially expressed genes (DEGs) and predicts miRNA-mRNA interactions using ML methods like XG-Boost and SHAP to find biomarkers.

Objective

This work evaluated the function of miRNA-mRNA interactions in sarcopenia pathogenesis and identified possible biomarkers by transcriptome analysis utilizing machine learning.

Methods

High-throughput mRNA sequencing datasets (GSE111006, GSE111010, and GSE111016) from GEO database were combined, pre-processed, and normalized using TPM and DESeq2 methods. XG-Boost regression analysis used 80/20 training and testing sets. SHAP analysis was used to evaluate model data and find significant DEGs. PPI networks were created using the STRING database, while miRNA-mRNA interactions were predicted using Encori and displayed with Cytoscape. The degree scores of miRNA-mRNA interactions were utilized to find biomarkers.

Results

XG-Boost and SHAP analysis revealed 20 influential DEGs linked to sarcopenia. With 97% accuracy, the model predicted accurately. PPI network research identified six hub genes: NTRK2, PCK1, DSP, SCD, MMRN1, and EDIL3. MiRNA-mRNA interaction analysis found miR-186–5p as the highest-degree biomarker candidate (36). MiR-186–5p was linked to muscle metabolism, hypertrophy, and exercise response.

Conclusion

The study found miR-186–5p to be a promising biomarker for sarcopenia using an integrated machine learning technique. The findings show that miR-186–5p may be a diagnostic and therapeutic target for sarcopenia, revealing its pathogenesis and enabling tailored treatments. Experimental research is needed to prove its therapeutic value.

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分析肌肉减少症中miRNA-mRNA相互作用的计算框架：对年龄相关肌肉变性的见解

骨骼肌减少症是一种与年龄相关的骨骼肌质量和功能的丧失，会损害活动能力、脆弱性和生活质量。尽管在病理生理学上取得了进展，但分子过程仍然未知。最近的研究已经研究了mirna作为肌肉减少症诊断和治疗的生物标志物。这项工作分析了差异表达基因（DEGs），并使用ML方法（如XG-Boost和SHAP）预测miRNA-mRNA相互作用，以寻找生物标志物。目的研究miRNA-mRNA相互作用在肌肉减少症发病机制中的作用，并利用机器学习进行转录组分析，确定可能的生物标志物。方法采用TPM和DESeq2方法对GEO数据库中的高通量mRNA测序数据集（GSE111006、GSE111010和GSE111016）进行组合、预处理和归一化处理。XG-Boost回归分析采用80/20训练集和测试集。采用SHAP分析对模型数据进行评价，发现显著的deg。使用STRING数据库创建PPI网络，使用Encori预测miRNA-mRNA相互作用，并使用Cytoscape显示。利用miRNA-mRNA相互作用的程度评分来寻找生物标志物。结果xg - boost和SHAP分析揭示了与肌少症相关的20个有影响的deg。该模型预测准确，准确率达97%。PPI网络研究确定了6个枢纽基因：NTRK2、PCK1、DSP、SCD、MMRN1和EDIL3。MiRNA-mRNA相互作用分析发现miR-186-5p是最高级别的生物标志物候选物（36）。MiR-186-5p与肌肉代谢、肥大和运动反应有关。研究发现miR-186-5p是一种有前途的肌肉减少症生物标志物，使用集成的机器学习技术。研究结果表明，miR-186-5p可能是肌少症的诊断和治疗靶点，揭示其发病机制并实现定制治疗。其治疗价值有待实验研究证实。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Aspects of molecular medicine Molecular Biology, Molecular Medicine

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审稿时长

38 days