Decoding Potential Cuproptosis-Related Genes in Sarcopenia: A Multi-Omics Network Analysis.

Area of Science:

• Biochemistry and Molecular Biology
• Gerontology
• Genetics and Genomics

Background:

• Sarcopenia, an age-related muscle disorder, lacks effective diagnostic and therapeutic strategies.
• Cuproptosis, a copper-dependent cell death, is implicated in muscle atrophy, but its role in sarcopenia is unclear.

Purpose of the Study:

• To investigate the association between cuproptosis and sarcopenia.
• To identify potential diagnostic biomarkers and therapeutic targets for sarcopenia.

Main Methods:

• Integrated bioinformatics analysis of GEO datasets (GSE1428, GSE25941) including differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA).
• Intersection of cuproptosis-related genes (CRGs) with differentially expressed genes (DEGs) and WGCNA modules to identify sarcopenia-associated cuproptosis DEGs (SAR-CUP DEGs).
• Machine learning algorithms (LASSO, RF, SVM) and experimental validation (RT-qPCR) were employed.

Main Results:

• Identified 367 DEGs and 7 co-expression modules, with 14 SAR-CUP DEGs enriched in mitochondrial energy metabolism.
• SLC25A12 and PABPC4 were identified as hub genes with strong diagnostic value (AUCs 0.879 and 0.858, respectively).
• Downregulation of SLC25A12 and PABPC4 was confirmed in a D-galactose-induced sarcopenia cell model.

Conclusions:

• SLC25A12 and PABPC4 are promising biomarkers linking copper metabolism dysregulation to sarcopenia.
• These genes represent potential targets for sarcopenia diagnosis and therapy.
• Further research into copper metabolism modulation may offer novel therapeutic avenues for age-related muscle loss.