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Published on: November 23, 2014
Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury
Manyi Zheng1, Yunduo Jiang1, Fangyu Liu1
1The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Heilongjiang, Harbin, China.
Background:
Spinal cord injury (SCI) is a devastating disorder featuring serious motor dysfunction and proprioceptive deficits due to central nervous system (CNS) damage. During its progression, macrophage-microglia (MM) cells are rapidly activated and play pivotal roles in the inflammatory response through various mechanisms. However, limited research has investigated the differential gene expression between the two groups before and after injury, and these important genes may therefore serve as potential biological diagnostic markers.
Methods:
Our study utilized the Gene Expression Omnibus (GEO) data for SCI-related MDEG identification. Key hub genes were screened using multiple machine learning(ML) algorithms. Their predictive potential was subsequently validated using independent datasets, and their association with immune cell infiltration was assessed. An in vitro model of SCI was established, and quantitative polymerase chain reaction (qPCR) experiments were conducted to verify our findings.
Results:
Single-cell RNA sequencing identified 16 distinct cellular subpopulations, among which MM cells were split into four subsets according to functional characteristics. Enrichment analyses, including KEGG, GO, and GSEA, revealed that the MDEGs were closely linked to key biological processes in SCI. From 200 genes associated with critical WGCNA modules, three hub genes, including EMP3, GNGT2, and SGPL1, were identified through four ML algorithms as differentially expressed before and after injury. Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. Preliminary analysis of immune infiltration and gene-immune cell correlation suggests an association with M2 macrophages. Furthermore, in vitro modeling of post-injury inflammation confirmed the elevated expression of EMP3, GNGT2, and SGPL1.
Conclusion:
Our study identifies EMP3, GNGT2, and SGPL1 as potential diagnostic biomarkers associated with MM cells in SCI. The foregoing findings lay a theoretical basis for elucidating their biological roles and formulating future treatment strategies.
Insights
Researchers identified EMP3, GNGT2, and SGPL1 as potential diagnostic biomarkers for spinal cord injury (SCI). These genes are linked to macrophage-microglia (MM) cells and inflammation, offering insights for future SCI treatments.
Area of Science:
- Neuroscience
- Immunology
- Genetics
Background:
- Spinal cord injury (SCI) causes significant motor and proprioceptive deficits due to central nervous system damage.
- Activated macrophage-microglia (MM) cells play a crucial role in SCI-related inflammation.
- Limited research exists on differential gene expression in MM cells before and after SCI, hindering biomarker discovery.
Purpose of the Study:
- To identify novel diagnostic biomarkers for SCI by analyzing differential gene expression in MM cells.
- To screen key hub genes associated with SCI using machine learning algorithms.
- To validate the predictive potential and immune associations of identified genes.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) data for SCI-related differentially expressed gene (DEG) identification.
- Employed multiple machine learning (ML) algorithms to screen key hub genes.
- Validated findings using independent datasets, assessed immune cell infiltration, and conducted in vitro SCI modeling with qPCR.
Main Results:
- Single-cell RNA sequencing identified four MM cell subsets; enrichment analyses linked DEGs to SCI biological processes.
- Three hub genes (EMP3, GNGT2, SGPL1) were identified as differentially expressed before and after SCI using ML algorithms.
- Predictive models showed strong performance; gene-immune cell correlation suggested an association with M2 macrophages; in vitro models confirmed elevated EMP3, GNGT2, and SGPL1 expression.
Conclusions:
- EMP3, GNGT2, and SGPL1 are identified as potential diagnostic biomarkers associated with MM cells in SCI.
- These findings provide a foundation for understanding their biological roles in SCI.
- The study paves the way for developing future therapeutic strategies for spinal cord injury.
