Identification of sepsis-associated mitochondrial genes through RNA and single-cell sequencing approaches
Background Sepsis ranks among the most formidable clinical challenges, characterized by exorbitant treatment costs and substantial demands on healthcare resources. Mitochondrial dysfunction emerges as a pivotal risk factor in the pathogenesis of sepsis, underscoring the imperative to identify mitoch...
Saved in:
Published in | BMC medical genomics Vol. 17; no. 1; pp. 120 - 14 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
London
BioMed Central
03.05.2024
BioMed Central Ltd BMC |
Subjects | |
Online Access | Get full text |
ISSN | 1755-8794 1755-8794 |
DOI | 10.1186/s12920-024-01891-x |
Cover
Summary: | Background
Sepsis ranks among the most formidable clinical challenges, characterized by exorbitant treatment costs and substantial demands on healthcare resources. Mitochondrial dysfunction emerges as a pivotal risk factor in the pathogenesis of sepsis, underscoring the imperative to identify mitochondrial-related biomarkers. Such biomarkers are crucial for enhancing the accuracy of sepsis diagnostics and prognostication.
Methods
In this study, adhering to the SEPSIS 3.0 criteria, we collected peripheral blood within 24 h of admission from 20 sepsis patients at the ICU of the Southwest Medical University Affiliated Hospital and 10 healthy volunteers as a control group for RNA-seq. The RNA-seq data were utilized to identify differentially expressed RNAs. Concurrently, mitochondrial-associated genes (MiAGs) were retrieved from the MitoCarta3.0 database. The differentially expressed genes were intersected with MiAGs. The intersected genes were then subjected to GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and core genes were filtered using the PPI (Protein-Protein Interaction) network. Subsequently, relevant sepsis datasets (GSE65682, GSE28750, GSE54514, GSE67652, GSE69528, GSE95233) were downloaded from the GEO (Gene Expression Omnibus) database to perform bioinformatic validation of these core genes. Survival analysis was conducted to assess the prognostic value of the core genes, while ROC (Receiver Operating Characteristic) curves determined their diagnostic value, and a meta-analysis confirmed the accuracy of the RNA-seq data. Finally, we collected 5 blood samples (2 normal controls (NC); 2 sepsis; 1 SIRS (Systemic Inflammatory Response Syndrome), and used single-cell sequencing to assess the expression levels of the core genes in the different blood cell types.
Results
Integrating high-throughput sequencing with bioinformatics, this study identified two mitochondrial genes (
COX7B, NDUFA4
) closely linked with sepsis prognosis. Survival analysis demonstrated that patients with lower expression levels of
COX7B
and
NDUFA4
exhibited a higher day survival rate over 28 days, inversely correlating with sepsis mortality. ROC curves highlighted the significant sensitivity and specificity of both genes, with AUC values of 0.985 for
COX7B
and 0.988 for
NDUFA4
, respectively. Meta-analysis indicated significant overexpression of
COX7B
and
NDUFA4
in the sepsis group in contrast to the normal group (
P
< 0.01). Additionally, single-cell RNA sequencing revealed predominant expression of these core genes in monocytes-macrophages, T cells, and B cells.
Conclusion
The mitochondrial-associated genes (MiAGs)
COX7B
and
NDUFA4
are intimately linked with the prognosis of sepsis, offering potential guidance for research into the mechanisms underlying sepsis. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1755-8794 1755-8794 |
DOI: | 10.1186/s12920-024-01891-x |