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Biomarker Signatures in Time-Course Progression of Neuropathic Pain at Spinal Cord Level Based on Bioinformatics and

Kexin Li1, Ruoxi Wang1, He Zhu1

  • 1Department of Anesthesiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China.

Biomolecules
|September 27, 2025
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Summary

This study identifies key genes changing over time in neuropathic pain (NP) using bioinformatics. These temporal gene signatures may offer new targets for pain relief medications.

Keywords:
RNA sequencingWGNCAmachine learningneuropathic painspared nerve injuryspinal cordtime course program

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Area of Science:

  • Neuroscience
  • Genomics
  • Bioinformatics

Background:

  • Neuropathic pain (NP) is a chronic pain condition with complex underlying mechanisms.
  • Current therapeutic strategies for NP are often inadequate.
  • Understanding the temporal molecular changes in NP is crucial for developing effective treatments.

Purpose of the Study:

  • To identify temporal transcriptomic changes in neuropathic pain.
  • To discover novel gene biomarkers associated with NP development and progression.
  • To explore potential therapeutic targets for NP management.

Main Methods:

  • Utilized bioinformatics and machine learning algorithms on mouse models of neuropathic pain.
  • Performed differential gene expression (DEG) analysis across multiple time points (day 3, 7, 14).
  • Integrated machine learning models (LASSO, RF, SVM-RFE) and Weighted Gene Co-expression Network Analysis (WGCNA) to identify key genes and temporal patterns.

Main Results:

  • Identified 54 common differentially expressed genes (DEGs) across time points, enriched in immune response and cell signaling pathways.
  • Discovered 11 shared DEGs integrating time-series signatures with common DEGs, including potential key genes like Ngfr and Ankrd1.
  • Validated temporal gene expression via quantitative RT-PCR and found correlations with monocyte infiltration.

Conclusions:

  • Identified novel genes with time-series expression patterns as potential biomarkers for neuropathic pain.
  • These findings highlight the role of temporal transcriptomic changes in NP pathogenesis.
  • The study suggests potential novel therapeutic targets for developing new analgesics for neuropathic pain.