New Diagnostic and Therapeutic Targets for Spinal Cord Injury: GRN Gene.

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Studies showed that many N6-methyladenosine (m6A) RNA methylation profiles are hypomethylated after SCI, which are related to neural regeneration and different m6A marker genes. In addition, immune cell infiltration may significantly affect the development and progression of SCI. Therefore, we attempted to identify the correlation between SCI-related biomarkers and m6A methylation regulators in order to classify them. To this end, we collected two gene expression profile datasets (GSE464 and GSE45006) from the GEO database, performed differential expression analysis between pairs before and after SCI, and identified 19 constant differentially expressed genes (DEGs). We found that the constant differential genes were strongly correlated with m6A methylation regulators, which could modulate the immune microenvironment of SCI. Next, this paper used a consensus clustering algorithm to classify SCI patients into three subtypes. There are significant differences between 19 constant DEGs and 28 immune cells among different subtypes. Finally, the correlation analysis of the intersection genes between constant DEGs and immune genes was performed, and GRN was identified as a potential immune biomarker for SCI.", "claims": [{"id": "claim-method", "statement": "In this study, the limma package in R [17] was used to perform differential expression analysis on the combined microarray datasets and set at p value less than 0.05 to obtain DEGs of different time points (1 day, 14 days and week > 4).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40736401", "locator": "sections[5] \"Identification of Differentially Expressed Genes\" paragraph 2", "quote": "In this study, the limma package in R [17] was used to perform differential expression analysis on the combined microarray datasets and set at p value less than 0.05 to obtain DEGs of different time points (1 day, 14 days and week > 4)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available in GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40736401", "locator": "sections[30] \"Data Availability Statement\" paragraph 2", "quote": "The data that support the findings of this study are available in GEO database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "GRN was identified as a potential immunobiological marker for SCI, with an AUC of 0.665 for predicting the occurrence of SCI and 0.667 for predicting the degree of injury.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40736401", "locator": "sections[19] \"Identification of Potential Immunobiological Markers of SCI Severity\" paragraph 2", "quote": "The GSE151371 dataset showed that the expression of GRN in the peripheral blood of SCI patients was significantly higher than that of normal samples (Figure 6B), and its expression was correlated with the age of patients (Figure 6C) and low expression in elderly patients, but not with gender (Figure 6D)."}, {"asset": "source:pmid:40736401", "locator": "sections[19] \"Identification of Potential Immunobiological Markers of SCI Severity\" paragraph 2", "quote": "Among them, the AUC for predicting the occurrence of SCI was 0.665. The AUC for predicting the degree of injury was 0.667. This means that GRN has specific predictive efficacy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "GRN was identified as a potential immunobiological marker for SCI, with an AUC of 0.665 for predicting the occurrence of SCI and 0.667 for predicting the degree of injury.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40736401"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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