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Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, and its candidate biomarkers have not yet been fully elucidated in previous studies. Therefore, with the present study, we aim to define and verify effective biomarkers of ALS by bioinformatics. Here, we employed differentially expressed gene (DEG) analysis, weighted gene co-expression network analysis (WGCNA), enrichment analysis, immune infiltration analysis, and protein–protein interaction (PPI) to identify biomarkers of ALS. To validate the biomarkers, we isolated the lumbar spinal cord from mice and characterized them using Western blotting and immunofluorescence. The results showed that Dhrs4 expression in the spinal cord was upregulated with the progression of SOD1 G93A  mice, and the upregulation of DHRS4 and its synergistic DHRS3 might be primarily associated with the activation of the complement cascade in the immune system (C1QA, C1QB, C1QC, C3, and ITGB2), which might be a novel mechanism that induces spinal neurodegeneration in ALS. We propose that DHRS4 and its synergistic DHRS3 are promising molecular markers for detecting ALS progression.

frontiers in immunology

Identification of Molecular Correlations Between DHRS4 and Progressive Neurodegeneration in Amyotrophic Lateral Sclerosis By Gene Co-Expression Network Analysis