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2000
Volume 32, Issue 41
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X

Abstract

Background

Sarcopenia, an aseptic chronic inflammatory disease, is a complex and debilitating disease characterized by the progressive degeneration of skeletal muscle. PANoptosis, a novel proinflammatory programmed cell death pathway, has been linked to various diseases. However, the precise role of PANoptosis-related features in sarcopenia remains uncertain.

Methods

According to the intersection of differentially expressed genes (DEGs) in the sarcopenia dataset GSE167186 and the PANoptosis gene set, we classified patients into PANoptosis-related subtypes (PANRS) using consensus clustering. The DEGs of PANRS were intersected with weighted gene co-expression network analysis (WGCNA). Protein-protein interaction network and cytoHubba algorithms were employed to further identify potential genes related to PANoptosis. The most characteristic genes were selected using LASSO regression and validated by ROC curve analysis, followed by relevant immune infiltration analysis. Additionally, small-molecule drug screening was performed using Cmap. The relative expression levels of hub genes in sarcopenia were confirmed by PCR. Finally, single-cell analysis and GSEA were used to examine the distribution and function of hub genes.

Results

Thirty-five candidate genes were identified through WGCNA and PANRS. Machine learning and ROC curve analysis revealed three core genes: , , and , all of which were up-regulated in patients with sarcopenia (<0.01). Immune infiltration analysis indicated that these three diagnostic genes were linked to the activation of NK cells and macrophages. Single-cell analysis demonstrated that was mainly localized in fibroblasts, while and exhibited a uniform distribution. Enrichment analysis indicated that the three hub genes were predominantly associated with the inhibition of energy metabolism.

Conclusion

In this study, the hub genes , , and associated with PANoptosis in sarcopenia were successfully identified through a combination of bioinformatics and experimental verification methods. This establishes a foundation for new candidate diagnostic and therapeutic targets for sarcopenia.

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Exploring PANoptosis Related Novel Diagnostic Biomarkers and Potential Drugs for Sarcopenia based on Machine Learning and Experimental Validation
Curr. Med. Chem. 32, 9464 (2025); https://doi.org/10.2174/0109298673341863241210112605
/content/journals/cmc/10.2174/0109298673341863241210112605
/content/journals/cmc/10.2174/0109298673341863241210112605
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  • Article Type:     Research Article
Keyword(s): biomarker; drug prediction; machine learning; metabolism; PANoptosis; Sarcopenia

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