ArticleFrontiers in genetics2025
Exploration of biomarkers associated with histone lactylation modification in spinal cord injury.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Histone lactylation-mediated glycolysis-ferroptosis axis in neurological diseases.Frontiers in molecular neuroscience · 2026Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The biological roles of histone lactylation (HLA) modification-related genes (HLMRGs) in spinal cord injury (SCI) remain unclear. This study aimed to investigate the expression patterns and molecular mechanisms of HLMRGs in SCI through bioinformatics approaches. Methods: Data from GSE151371, GSE47681, and 10 HLMRGs were analyzed. Subsequently, biomarkers were identified based on receiver operating characteristic (ROC) curves, followed by logistic regression modeling and nomogram construction. Gene set enrichment analysis (GSEA) was performed to assess the functional roles of these biomarkers. Clustering analysis of samples based on biomarkers revealed distinct groups, and differentially expressed genes between these groups were analyzed. Inter-cluster comparisons were conducted to examine Hallmark pathways, HLA genes, and immune functions. Weighted gene co-expression network analysis (WGCNA) was applied to identify cluster-related module genes, which were further used for protein-protein interaction (PPI) network construction to pinpoint key proteins. Networks linking miRNAs, transcription factors (TFs), and biomarkers, as well as drug-biomarker interactions, were established. The expression of biomarkers was validated through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results: In GSE151371, eight biomarkers ( Conclusion: In summary, 8 biomarkers playing an important role in SCI were identified, providing a reference for the application of HLMRGs in SCI.
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