Identification of Potential Inflammation-Related Genes and Key Pathways Associated with Complex Regional Pain Syndrome.

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Thus, we conducted a bioinformatics analysis to identify hub genes and key pathways to determine strategies for more effective treatments of CRPS. Finally, there is only one expression profile of GSE47063 in terms of homo sapiens-based CRPS from the Gene Expression Omnibus (GEO) database, which included four patients and five controls. We explored the differentially expressed genes (DEGs) in the dataset and conducted Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the potential hub genes. A protein-protein interaction (PPI) network was also established; then, according to the score of each hub genes, we used R software to draw the nomogram model to predict the rate of CRPS. Furthermore, GSEA analysis was estimated and assessed by the normalized enrichment score (NES). From the GO and KEGG analysis, we identified the top five hub genes (MMP9, PTGS2, CXCL8, OSM, TLN1); all of the selected DEGs were mainly enriched in their inflammatory response. In addition, the GSEA analysis showed complement and coagulation cascades also play an important role in CRPS. This study, to our knowledge, is the first to conduct further PPI network and GSEA analyses. Thus, targeting excessive inflammation could offer new therapeutic methods for CRPS and related physical and psychiatric disorders.", "claims": [{"id": "claim-method", "statement": "Results are presented in the browser as a table of the top 250 genes ranked by p-value, for RNA-seq; the table is the result of the Wald test when comparing 2 groups of samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37238642", "locator": "sections[4] \"2.2. Differential Expression Analysis\" paragraph 2", "quote": "Results are presented in the browser as a table of the top 250 genes ranked by p-value, for RNA-seq; the table is the result of the Wald test when comparing 2 groups of samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression microarray GSE47063 (9 samples, 2 CRPS I, 2 CRPS II and 5 controls) was downloaded from the GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37238642", "locator": "sections[20] \"notes\" paragraph 1", "quote": "The gene expression microarray GSE47063 (9 samples, 2 CRPS I, 2 CRPS II and 5 controls) was downloaded from the GEO database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using GEO2R/Wald-test differential expression analysis of the GEO GSE47063 microarray dataset, the study identified 37 differentially expressed genes between four CRPS samples and five controls: 33 upregulated and four downregulated.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37238642", "locator": "sections[11] \"3.1. 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