Abstract
Ferroptosis, characterized by iron accumulation and lipid peroxidation, leads to cell death. Growing evidence suggests the involvement of ferroptosis in sarcopenia. However, the fundamental ferroptosis-related genes (FRGs) for sarcopenia diagnosis, prognosis, and therapy remain elusive. This study aimed to identify molecular biomarkers of ferroptosis in sarcopenia patients. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between normal and sarcopenia samples were identified using the ‘limma’ package in R software. FRGs were extracted from GeneCards and FerrDB databases. Functional enrichment analysis determined the roles of DEGs using the ‘clusterProfiler’ package. A protein-protein network was constructed using Cytoscape software. Immune infiltration analysis and receiver operating characteristic (ROC) analysis were performed. mRNA-miRNA, mRNA-TF, and mRNA-drug interactions were predicted using ENCORI, hTFtarget, and CHIPBase databases. The network was visualized using Cytoscape. We identified 46 FRGs in sarcopenia. Functional enrichment analysis revealed their involvement in critical biological processes, including responses to steroid hormones and glucocorticoids. KEGG enrichment analysis implicated pathways such as carbon metabolism, ferroptosis, and glyoxylate in sarcopenia. Totally, 11 hub genes were identified, and ROC analysis demonstrated their potential as sensitive and specific markers for sarcopenia in both datasets. Additionally, differences in immune cell infiltration were observed between normal and sarcopenia samples. The hub genes identified in this study are closely associated with ferroptosis in sarcopenia and can effectively differentiate sarcopenia from controls. CDKN1A, CS, DLD, FOXO1, HSPB1, LDHA, MDH2, and YWHAZ show high sensitivity and specificity for sarcopenia diagnosis.
Communicated by Ramaswamy H. Sarma
Keywords:
Authors’ contributions
Yanzhong Chen conceptualized and designed the study. Yanzhong Chen and Yaonan Zhang collected and validated the data. Yanzhong Chen analyzed the data. Yanzhong Chen, Sihan Zhang and Hong Ren prepared the manuscript. Hong Ren and Yaonan Zhang revised the manuscript critically. Sihan Zhang searched the relevant references. All authors contributed to the article and approved the submitted version.
Ethics approval
There are no ethical issues involved in this study.
Disclosure statement
The authors have no relevant financial or non-financial interests to disclose.
Data availability statement
The datasets generated during the current study are available in the NCBI (GEO) repository. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8479 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1428.