Identification of Neurotrophic Factor Related Biomarkers and Mechanistic Insights into Neuropathic Pain via Integrated Bioinformatics Analysis

Neurotrophic factors are closely associated with the development of neuropathic pain (NPP), yet their underlying mechanisms remain unclear. This study aims to identify key biomarkers and explore their potential mechanisms using integrated bioinformatics approaches. The data sets of NPP were retrieved from public databases. Single-cell RNA sequencing analysis of mouse dorsal root ganglion (DRG) was executed to identify and annotate cell clusters. Differential expression analyses, Friend analysis, and expression validation were executed to screen biomarkers. Gene-gene interaction (GGI) network construction and enrichment analyses were used to explore the relevant functions of the biomarkers. Immune microenvironment differences between case and control were assessed by single sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm. Mendelian randomization (MR) analysis explored potential causal relationships between biomarkers and NPP. Cellular communication and pseudotime analyses further elucidated intercellular interactions and differentiation trajectories in key cell populations. Single-cell analysis of mouse DRG identified 10 cell types. There was a significant difference in satellite glial cells (SGCs) between the two groups, and their proportion in the NPP case group was significantly reduced. Differential expression analyses revealed 792 highly expressed genes of SGCs, 556 differentially expressed genes related to neurotrophic factor-related gene (NFRG) scores, and 701 differentially expressed genes in bulk RNA-seq data set. Intersection analysis identified five biomarkers: Myo10, Rhoq, Sema6a, Spata13, and Id4. GSEA analysis revealed their involvement in key pathways, including ribosomes, p53 signaling, oxidative phosphorylation, and neuroactive ligand-receptor interaction. Immune microenvironment analysis highlighted correlations between Myo10 and M2 macrophages. MR analysis demonstrated a potential causal link between Myo10 and drug-induced neuropathy, as well as Sema6a with reduced risk of sciatica. Cell communication and pseudotime analyses indicated enhanced SGC interactions and increased biomarker expression during late differentiation stages. This study identified five neurotrophic factor-related biomarkers (Myo10, Rhoq, Sema6a, Spata13, and Id4), providing novel targets for the diagnosis and treatment of NPP.

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Publication Details

Journal
ACS Omega
Published
2025-11-15
DOI
https://doi.org/10.1021/acsomega.5c07765
Citations
1
Primary Topic
Pain Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
1.16
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article

Identification of Neurotrophic Factor Related Biomarkers and Mechanistic Insights into Neuropathic Pain via Integrated Bioinformatics Analysis

J. Liu, Zhen Zhang, Xiangrui Li, Changsheng Li et al.
1 citations
ACS Omega
Pain Mechanisms and Treatments
1.16
article

Identification of Neurotrophic Factor Related Biomarkers and Mechanistic Insights into Neuropathic Pain via Integrated Bioinformatics Analysis

J. Liu, Zhen Zhang, Xiangrui Li, Changsheng Li, Xihua Lu
article en
1 citations

Abstract

Neurotrophic factors are closely associated with the development of neuropathic pain (NPP), yet their underlying mechanisms remain unclear. This study aims to identify key biomarkers and explore their potential mechanisms using integrated bioinformatics approaches. The data sets of NPP were retrieved from public databases. Single-cell RNA sequencing analysis of mouse dorsal root ganglion (DRG) was executed to identify and annotate cell clusters. Differential expression analyses, Friend analysis, and expression validation were executed to screen biomarkers. Gene-gene interaction (GGI) network construction and enrichment analyses were used to explore the relevant functions of the biomarkers. Immune microenvironment differences between case and control were assessed by single sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm. Mendelian randomization (MR) analysis explored potential causal relationships between biomarkers and NPP. Cellular communication and pseudotime analyses further elucidated intercellular interactions and differentiation trajectories in key cell populations. Single-cell analysis of mouse DRG identified 10 cell types. There was a significant difference in satellite glial cells (SGCs) between the two groups, and their proportion in the NPP case group was significantly reduced. Differential expression analyses revealed 792 highly expressed genes of SGCs, 556 differentially expressed genes related to neurotrophic factor-related gene (NFRG) scores, and 701 differentially expressed genes in bulk RNA-seq data set. Intersection analysis identified five biomarkers: Myo10, Rhoq, Sema6a, Spata13, and Id4. GSEA analysis revealed their involvement in key pathways, including ribosomes, p53 signaling, oxidative phosphorylation, and neuroactive ligand-receptor interaction. Immune microenvironment analysis highlighted correlations between Myo10 and M2 macrophages. MR analysis demonstrated a potential causal link between Myo10 and drug-induced neuropathy, as well as Sema6a with reduced risk of sciatica. Cell communication and pseudotime analyses indicated enhanced SGC interactions and increased biomarker expression during late differentiation stages. This study identified five neurotrophic factor-related biomarkers (Myo10, Rhoq, Sema6a, Spata13, and Id4), providing novel targets for the diagnosis and treatment of NPP.

ACS OmegaVol. 10(47)
Zhengzhou University (CN), Henan Cancer Hospital (CN), Third Affiliated Hospital of Zhengzhou University (CN)
Openalex Percentile: Top 16%
Pain Mechanisms and Treatments
1.16
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