Exploring and Validating the Molecular Mechanisms Linking Fatty Acid Metabolism and Sarcopenia.

Sarcopenia is an ageing-related disease characterised primarily by skeletal muscle functional decline. Despite of fatty acid metabolism (FAM) affecting oxidative stress within muscle tissue, the key roles of critical genes linking FAM and sarcopenia are unclear. The GSE8479, GSE1428, and GSE136344 datasets were downloaded and intersected for identifying FAM-related differentially expressed genes (FAMRDEGs) screened by enrichment analysis, LASSO regression, and Support Vector Machine (SVM) analyses. Cytoscape software was used for visualising mRNA-transcription factor (TF) and mRNA-miRNA networks. In addition, ROC curves of key genes were plotted to evaluate their diagnostic significance. A Fatty Acid Metabolism Score (FAM-Score) was conducted and immune cell infiltration analysis was conducted. The qPCR assay was performed to analyse the levels of screened critical genes. A total of 109 FAMRDEGs were obtained, and the LASSO regression and SVM models screened 14 of these genes. The network included 7 key genes with 54 miRNAs and 9 hub genes with 102 TFs. There were 6 types of immune cell infiltration showing statistical significance. The FABP3 (P < 0.001), PECR (P < 0.01), and OPN3 (P < 0.001) mRNA expression markedly increased in sarcopenia versus control groups. In contrast, sarcopenia group showed remarkably reduced PCTP (P < 0.001), SREBF2 (P < 0.001), and PPARGC1A (P < 0.05) levels. This study provides reference indicators for FAM-associated auxiliary biomarkers of sarcopenia and preliminarily establishes effective machine learning models for further mechanistic exploration.