Identification of novel biomarkers and immune characteristics of spinal cord injury based on comprehensive bioinformatic analysis: A retrospective observational study

The exact mechanisms underlying spinal cord injury are not fully understood, and effective treatments are scarce. Therefore, there is an urgent need to identify novel biomarkers that can guide therapy for spinal cord injury. This retrospective observational study used bioinformatics technologies to identify key biomarkers associated with spinal cord injury by analyzing gene expression data from the GEO database. The study aimed to identify hub genes related to spinal cord injury and investigate potential therapeutic targets. In this study, we identified differentially expressed genes using logFC threshold and P -value as criteria. We evaluated 22 distinct immune cell types for dispersion using the CIBERSORT algorithm. We used weighted gene co-expression network analysis (WGCNA) and machine learning methods to identify hub genes. Finally, we created drug-biomarker network, miRNA-mRNA network, and transcription factor-mRNA network for potential molecular targets and small molecule medicines. Through integrated analysis, we identified four key biomarkers cyclin-dependent kinase inhibitor 1A ( Cdkn1a ), growth arrest and DNA damage inducible alpha ( Gadd45a ), Ninjurin2 ( Ninj2 ) and regulator of G protein signaling 6 ( Rgs6 ). These biomarkers are closely associated with various immune cells and inflammation-related pathways. Additionally, we also predicted 272 miRNAs, 117 transcription factors, and 56 drugs as the hub gene-related therapeutic targets. Functional enrichment analysis revealed that these genes are involved in regulating the immunoinflammatory response following spinal cord injury. Further validation analyses indicated that the expression trends of these biomarkers were consistent across spinal cord injury samples at different time points. This work utilizes bioinformatics techniques to identify hub genes related to spinal cord injury, providing novel targets for treatment and enhancing our understanding of the injury process.

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Publication Details

Journal
NeuroMarkers.
Published
2025-03-22
DOI
https://doi.org/10.1016/j.neumar.2025.100077
Citations
1
Primary Topic
Spinal Cord Injury Research
Type
article
Field-Weighted Citation Impact
1.47
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article

Identification of novel biomarkers and immune characteristics of spinal cord injury based on comprehensive bioinformatic analysis: A retrospective observational study

Xiaowei Zha
1 citations
NeuroMarkers.
Spinal Cord Injury Research
1.47
article

Identification of novel biomarkers and immune characteristics of spinal cord injury based on comprehensive bioinformatic analysis: A retrospective observational study

Xiaowei Zha
article en
1 citations

Abstract

The exact mechanisms underlying spinal cord injury are not fully understood, and effective treatments are scarce. Therefore, there is an urgent need to identify novel biomarkers that can guide therapy for spinal cord injury. This retrospective observational study used bioinformatics technologies to identify key biomarkers associated with spinal cord injury by analyzing gene expression data from the GEO database. The study aimed to identify hub genes related to spinal cord injury and investigate potential therapeutic targets. In this study, we identified differentially expressed genes using logFC threshold and P -value as criteria. We evaluated 22 distinct immune cell types for dispersion using the CIBERSORT algorithm. We used weighted gene co-expression network analysis (WGCNA) and machine learning methods to identify hub genes. Finally, we created drug-biomarker network, miRNA-mRNA network, and transcription factor-mRNA network for potential molecular targets and small molecule medicines. Through integrated analysis, we identified four key biomarkers cyclin-dependent kinase inhibitor 1A ( Cdkn1a ), growth arrest and DNA damage inducible alpha ( Gadd45a ), Ninjurin2 ( Ninj2 ) and regulator of G protein signaling 6 ( Rgs6 ). These biomarkers are closely associated with various immune cells and inflammation-related pathways. Additionally, we also predicted 272 miRNAs, 117 transcription factors, and 56 drugs as the hub gene-related therapeutic targets. Functional enrichment analysis revealed that these genes are involved in regulating the immunoinflammatory response following spinal cord injury. Further validation analyses indicated that the expression trends of these biomarkers were consistent across spinal cord injury samples at different time points. This work utilizes bioinformatics techniques to identify hub genes related to spinal cord injury, providing novel targets for treatment and enhancing our understanding of the injury process.

NeuroMarkers.Vol. 2(2)
Heidelberg University (DE), University Hospital Heidelberg (DE)
Good health and well-being
Openalex Percentile: Top 22%
Spinal Cord Injury Research
1.47
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Identification of novel biomarkers and immune characteristics of spinal cord injury based on comprehensive bioinformatic analysis: A retrospective observational study — Xiaowei Zha · NeuroMarkers. (2025) | TGRS Research Map | TGRS