This analysis demonstrates improved diagnostic biomarkers for sarcopenia using a six-gene model, highlighting mitochondrial dysfunction and immune involvement.
Age‐related mitochondrial dysfunction is a primary cause of muscle degeneration. We aimed to identify mitochondria‐related differentially expressed genes (MR‐DEGs) and construct a diagnostic model to improve the diagnosis of sarcopenia. Transcriptomic datasets GSE226151 (training) and GSE1428 (validation) were downloaded from GEO. Mitochondria‐related genes (MRGs) were sourced from human MitoCarta 3.0, and MR‐DEGs were screened as intersections of sarcopenia‐related genes, DEGs, and MRGs. Optimal biomarkers were selected using univariate logistic regression and LASSO regression. A diagnostic model was further estimated, and the diagnostic value was determined using receiver operating characteristic (ROC) curves. Finally, interaction networks and immune correlation analyses of the optimal MR‐DEGs were assessed. Six optimal MR‐DEGs ( ACOT11, BCO2, MRPL4, NDUFB9, UQCR10 , and CASP8 ) were identified. The model achieved area under the curve (AUC) values of 0.935 and 0.899, respectively, in the GSE226151 and GSE1428. Significant immune correlations emerged; CD56 bright natural killer cells and neutrophils were correlated with MR‐DEGs expression (all p < 0.05). Network analysis revealed 20 co‐regulated genes that were significantly enriched in functions such as ATP synthesis‐coupled electron transport, mitochondrial respiration, and oxidative phosphorylation. Our six‐MR‐DEG diagnostic model demonstrated a robust clinical potential for sarcopenia diagnosis, with validation across platforms and significant pathophysiological relevance to mitochondrial immune dysregulation.
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Zhenyi Jia (2025) studied this question.
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