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Updated: Aug 11, 2026

Isolation and Functional Analysis of Mitochondria from Cultured Cells and Mouse Tissue
Published on: March 23, 2015
Identification and Validation of Mitochondria-Related Genes for Diagnosis of Early-Stage Sepsis
Yanping Zhang1, Yin Xu2, Zeyu Huang3
1Department of Infectious Diseases, The Third People's Hospital of Changzhou, Changzhou, Jiangsu, China.
Objective:
Sepsis is a life-threatening condition with unclear pathogenesis and limited effective treatments. Mitochondrial dysfunction is considered a key factor in sepsis-induced multiple organ failure. This study aimed to identify essential mitochondria-related genes associated with sepsis to improve diagnosis and treatment strategies.
Methods:
High-throughput gene expression data (GSE185263) were analyzed to identify differentially expressed genes (DEGs) in 348 septic patients and 44 healthy controls. Mitochondria-related DEGs were screened using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Two machine-learning algorithms, LASSO and SVM-RFE, were applied to identify mitochondria-associated hub genes.
Results:
We identified 548 DEGs and screened 18 mitochondria-related DEGs. LASSO and SVM-RFE analyses identified 11 genes associated with sepsis diagnosis, showing strong diagnostic abilities through ROC assays. The expression of these 11 genes was examined by quantitative real-time polymerase chain reaction in septic patients and healthy participants, and differential expression of arginase 2 (ARG2), B-cell lymphoma 2-related protein A1 (BCL2A1), interferon alpha inducible protein 27 (IFI27), NADH: ubiquinone oxidoreductase subunit B3 (NDUFB3), stomatin (STOM), and translocator protein (TSPO) were observed. Some gene expression differences remained significant after adjusting for neutrophil and platelet counts.
Conclusions:
These findings suggest that mitochondrial dysfunction plays a critical role in sepsis progression, and the identified genes may serve as biomarkers for early diagnosis and targeted treatment, potentially improving patient outcomes.
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