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Identification of Potential Biomarkers Associated with Impaired Fatty Acid Oxidation in Aged Skeletal Muscle Using
Haoyang Gao1, Fangjie Yang1, Jiabin Wu1
1Shanghai Key Lab of Human Performance, Shanghai University of Sport, 650 Qingyuan Ring Road, Yangpu District, Shanghai 200438, China.
Biomolecules
|July 28, 2026
Summary
Researchers identified three key genes, CKMT2, ACTC1, and FOXO3, as potential biomarkers for impaired fatty acid oxidation (FAO) in aging skeletal muscle. An artificial neural network model using these genes shows promise for predicting sarcopenia, offering new therapeutic targets.
Area of Science:
- Molecular Biology
- Bioinformatics
- Gerontology
Background:
- Impaired fatty acid oxidation (FAO) is a significant factor in skeletal muscle aging and sarcopenia.
- Key regulatory molecules driving age-related FAO decline in muscle remain poorly understood.
- Identifying reliable biomarkers is crucial for understanding and potentially treating sarcopenia.
Purpose of the Study:
- To identify candidate biomarkers linked to impaired FAO in aged skeletal muscle.
- To characterize the biological functions and regulatory mechanisms of these biomarkers.
- To validate the expression patterns of identified biomarkers in aging models.
Main Methods:
- Integrated bioinformatics analyses of skeletal muscle aging transcriptomic datasets (GSE1428, GSE674).
- Screening of differentially expressed FAO-related genes (DE-FAOGs) and hub genes using machine learning (Random Forest, Boruta) and PPI networks.
- Validation of hub gene expression (CKMT2, ACTC1, FOXO3) via qRT-PCR in aged mice and C2C12 cells.
Main Results:
- Identified 69 DE-FAOGs enriched in mitochondrial function and energy metabolism pathways.
- Screened three hub genes: CKMT2, ACTC1, and FOXO3, showing strong discriminatory power.
- An artificial neural network (ANN) model using these three genes achieved high predictive accuracy (AUC 0.992/0.964).
Conclusions:
- CKMT2, ACTC1, and FOXO3 are potential biomarkers for impaired FAO in aged skeletal muscle.
- The three-gene ANN model demonstrates significant potential for predicting sarcopenia.
- These findings offer novel insights into sarcopenia's metabolic mechanisms and potential therapeutic targets.
