Bioinformatics Genes and Pathway Analysis for Chronic Neuropathic Pain after Spinal Cord Injury.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29164149", "kind": "science-record", "revision": 7, "content_hash": "sha256:0c13f7815c1b8918bca0dcce991a4c729c0f436c20e5672477fe81d40624dcfb", "created_at": "2026-11-01T15:40:29Z", "updated_at": "2026-11-01T21:21:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Genes and Pathway Analysis for Chronic Neuropathic Pain after Spinal Cord Injury.", "doi": "10.1155/2017/6423021", "pmid": "29164149", "authors": ["Guan Zhang", "Ping Yang"], "journal": "BioMed research international", "year": 2017, "abstract": "It is well known spinal cord injury (SCI) can cause chronic neuropathic pain (NP); however its underlying molecular mechanisms remain elusive. This study aimed to disclose differentially expressed genes (DEGs) and activated signaling pathways in association with SCI induced chronic NP, in order to identify its diagnostic and therapeutic targets. Microarray dataset GSE5296 has been downloaded from Gene Expression Omnibus (GEO) database. Significant analysis of microarray (SAM), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and pathway network analysis have been used to compare changes of DEGs and signaling pathways between the SCI and sham-injury group. As a result, DEGs analysis showed there were 592 DEGs with significantly altered expression; among them Ccl3 expression showed the highest upregulation which implicated its association with SCI induced chronic NP. Moreover, KEGG analysis found 209 pathways changed significantly; among them the most significantly activated one is MAPK signaling pathway, which is in line with KEGG analysis results. Our results show Ccl3 is highly associated with SCI induced chronic NP; as the exosomes with Ccl3 can be easily and efficiently detected in peripheral blood, Ccl3 may serve as a potential prognostic target for the diagnosis and treatment of SCI induced chronic NP.", "claims": [{"id": "claim-method", "statement": "Significant analysis of microarray (SAM) is used to study DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29164149", "locator": "sections[5] \"2.3. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE5296"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE5296"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29164149", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2017/6423021", "sha256": "sha256:5dcfa31d9e1cdd2f70dd2521e2f83add55f50abf38d5b37a537df1543a395ae1", "bytes": 43722, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2017/6423021", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC5661087", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE5296", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5296", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE5296", "version": null, "note": "Microarray dataset GSE5296 has been downloaded from Gene Expression Omnibus (GEO) database.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Microarray dataset GSE5296 has been downloaded from Gene Expression Omnibus (GEO) database.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM118664", "GSM118672", "GSM119764", "GSM119765", "GSM119766", "GSM119767", "GSM119768", "GSM119769", "GSM119770", "GSM119771", "GSM119772", "GSM119773", "GSM119774", "GSM119775", "GSM119776", "GSM119777", "GSM119778", "GSM119779", "GSM119780", "GSM119781", "GSM119782", "GSM119783", "GSM119784", "GSM119785", "GSM119786", "GSM119787", "GSM119788", "GSM119789", "GSM119790", "GSM119791", "GSM119792", "GSM119793", "GSM119794", "GSM119795", "GSM119796", "GSM119797", "GSM119798", "GSM119799", "GSM119800", "GSM119801", "GSM119802", "GSM119803", "GSM119804", "GSM119805", "GSM119806", "GSM119807", "GSM119808", "GSM119809", "GSM119810", "GSM119811", "GSM119812", "GSM119813", "GSM119814", "GSM119815", "GSM119816", "GSM119817", "GSM119818", "GSM119819", "GSM119820", "GSM119821", "GSM119822", "GSM119823", "GSM119824", "GSM119825", "GSM119826", "GSM119827", "GSM119828", "GSM119829", "GSM119830", "GSM119831", "GSM119832", "GSM119833", "GSM119834", "GSM119835", "GSM119836", "GSM119837", "GSM119838", "GSM119839", "GSM119840", "GSM119841", "GSM119842", "GSM119843", "GSM119844", "GSM119845", "GSM119846", "GSM119847", "GSM119848", "GSM119849", "GSM119850", "GSM119851", "GSM119852", "GSM119853", "GSM119854", "GSM119855", "GSM119856", "GSM120018"], "sample_count": 96, "group_sizes": null, "group_sizes_basis": null, "platform": "1261", "taxon": "Mus musculus", "title": "Spinal Cord Injury Murine Model", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:29164149:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:d450e320c0b8f28e621b6cd06c5d70af3f2b3a9609c3fd8fd75f3ec27da3bf68", "bytes": 1609, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[1]#tab1", "version": null, "note": "Top 10 significantly enriched up- and downregulated DEGs. The P values associated with each term are calculated by the Fisher Exact Test which represents the “degree of enrichment.” Q-value is the correction for multiple comparison by Benjamini and Hochberg [33]. The rank was according to the difference determined by d Score, fold change, and P value. The top ten largest differences in DEGs were screen with fold change > 2 and P < 0.05, and the maximum change of gene expression profile was upregulation of Ccl3.", "structure": {"pmcid": "PMC5661087", "section_index": 8, "section_title": "3.2. Screening of Differentially Expressed Genes from T8 Lesion Centre (Ccl3 Was the Maximum Changed Gene Expression Profile among the 592 DEGs)", "row_count": 11, "column_count": 10}, "table": {"label": "Table 1", "caption": "Top 10 significantly enriched up- and downregulated DEGs. The P values associated with each term are calculated by the Fisher Exact Test which represents the “degree of enrichment.” Q-value is the correction for multiple comparison by Benjamini and Hochberg [33]. The rank was according to the difference determined by d Score, fold change, and P value. The top ten largest differences in DEGs were screen with fold change > 2 and P < 0.05, and the maximum change of gene expression profile was upregulation of Ccl3.", "rows": [["DEGs", "Accession number", "Signal of control", "Signal of experimental", "d Score", "Fold change", "P value", "q-value", "Expression change", "Rank"], ["Ccl3", "NM_011337", "5.37", "8.81", "10.04", "10.91", "2.20E − 05", "0", "Up", "1"], ["Atf3", "NM_007498", "6.12", "9.18", "10.10", "8.37", "2.20E − 05", "0", "Up", "2"], ["Plek", "NM_019549", "6.67", "9.20", "8.10", "5.77", "2.20E − 05", "0", "Up", "3"], ["Ctla2b", "NM_001145801", "5.45", "7.90", "8.08", "5.45", "2.20E − 05", "0", "Up", "4"], ["Bcl2a1a", "NM_007534", "7.23", "9.59", "8.37", "5.14", "2.20E − 05", "0", "Up", "5"], ["Ch25h", "NM_009890", "6.82", "9.13", "8.27", "4.95", "2.20E − 05", "0", "Up", "6"], ["Plek", "NM_019549", "5.87", "8.12", "7.58", "4.76", "2.20E − 05", "0", "Up", "7"], ["Tnfaip3", "NM_001166402", "5.75", "7.45", "8.12", "3.24", "2.20E − 05", "0", "Up", "8"], ["Tgif1", "NM_001164074", "6.05", "7.59", "8.52", "2.91", "2.20E − 05", "0", "Up", "9"], ["Gpr84", "NM_030720", "6.31", "7.83", "7.92", "2.86", "2.20E − 05", "0", "Up", "10"]], "row_count": 11, "column_count": 10, "numeric_cells": 82, "header_rows": 1, "locator": "section[8]/table-wrap[1]#tab1"}}, {"id": "asset:table:pmid:29164149:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:42dd2a847fa3d7c4ff6276fb141a74eb49475f11a03b87c9157e491f7188864a", "bytes": 1352, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[9]/table-wrap[1]#tab2", "version": null, "note": "Top 10 GO terms and KEGG pathways enrichment results of DEGs. Significantly enriched GO terms and KEGG pathways with FDR < 0.05 were screened out. KEGG biological pathway enrichment analysis found that MAPK signaling pathway (enrichment score = 5.68, P = 3.38E − 74, and FDR = 8.78E − 72) was the most important one among the 209 pathways according to the enrichment score.", "structure": {"pmcid": "PMC5661087", "section_index": 9, "section_title": "3.3. KEGG Pathway Enrichment Analysis from T8 Lesion Centre (MAPK Signaling Pathway Was the Most Important among the 209 Pathways)", "row_count": 11, "column_count": 6}, "table": {"label": "Table 2", "caption": "Top 10 GO terms and KEGG pathways enrichment results of DEGs. Significantly enriched GO terms and KEGG pathways with FDR < 0.05 were screened out. KEGG biological pathway enrichment analysis found that MAPK signaling pathway (enrichment score = 5.68, P = 3.38E − 74, and FDR = 8.78E − 72) was the most important one among the 209 pathways according to the enrichment score.", "rows": [["Pathway ID", "Pathway name", "Enrichment score", "P value", "FDR", "Rank"], ["4010", "MAPK signaling pathway", "5.68", "3.38E − 74", "8.78E − 72", "1"], ["1100", "Metabolic pathways", "2.73", "3.22E − 65", "4.19E − 63", "2"], ["4151", "PI3K-Akt signaling pathway", "4.31", "8.74E − 57", "7.57E − 55", "3"], ["5200", "Pathways in cancer", "4.36", "2.57E − 53", "1.67E − 51", "4"], ["4380", "Osteoclast differentiation", "6.77", "2.20E − 52", "1.14E − 50", "5"], ["5166", "HTLV-I infection", "4.54", "6.12E − 52", "2.65E − 50", "6"], ["4810", "Regulation of actin cytoskeleton", "5.06", "3.43E − 49", "1.28E − 47", "7"], ["4062", "Chemokine signaling pathway", "5.26", "6.63E − 49", "2.15E − 47", "8"], ["4510", "Focal adhesion", "5.11", "2.31E − 47", "6.68E − 46", "9"], ["5205", "Proteoglycans in cancer", "4.73", "3.22E − 45", "8.36E − 44", "10"]], "row_count": 11, "column_count": 6, "numeric_cells": 50, "header_rows": 1, "locator": "section[9]/table-wrap[1]#tab2"}}, {"id": "asset:table:pmid:29164149:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:20e1a0c85bd9a2c5f341b65e4268d4c8afa036e928ad2bfbb07c0f3394c1aa24", "bytes": 1168, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#tab3", "version": null, "note": "The top 10 altered pathways of network analyses. The outdegree and indegree represent, respectively, the number of upstream and downstream signal pathways. The degree represents the sum of the outdegree and indegree. In the top 10 altered pathway interaction nets with 111 nodes and 404 relationships between each other, MAPK signaling pathway was the most important one with the largest degree (outdegree = 5, indegree = 39, and degree = 44).", "structure": {"pmcid": "PMC5661087", "section_index": 10, "section_title": "3.4. Pathway Network Analyses from T8 Lesion Centre (MAPK Signaling Pathway Was Also the Most Important Pathway)", "row_count": 11, "column_count": 6}, "table": {"label": "Table 3", "caption": "The top 10 altered pathways of network analyses. The outdegree and indegree represent, respectively, the number of upstream and downstream signal pathways. The degree represents the sum of the outdegree and indegree. In the top 10 altered pathway interaction nets with 111 nodes and 404 relationships between each other, MAPK signaling pathway was the most important one with the largest degree (outdegree = 5, indegree = 39, and degree = 44).", "rows": [["Pathway ID", "Pathway name", "Outdegree", "Indegree", "Degree", "Rank"], ["4010", "MAPK signaling pathway", "5", "39", "44", "1"], ["4210", "Apoptosis", "3", "29", "32", "2"], ["5200", "Pathways in cancer", "28", "0", "28", "3"], ["4110", "Cell cycle", "3", "20", "23", "4"], ["10", "Glycolysis/gluconeogenesis", "5", "15", "20", "5"], ["4020", "Calcium signaling pathway", "5", "14", "19", "6"], ["4115", "p53 signaling pathway", "2", "17", "19", "7"], ["4310", "Wnt signaling pathway", "8", "9", "17", "8"], ["4060", "Cytokine-cytokine receptor interaction", "0", "16", "16", "9"], ["620", "Pyruvate metabolism", "7", "8", "15", "10"]], "row_count": 11, "column_count": 6, "numeric_cells": 51, "header_rows": 1, "locator": "section[10]/table-wrap[1]#tab3"}}, {"id": "asset:table:pmid:29164149:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:7200530ff6e793c15c954fae62d8b619221c3fa065331ab2998297fbd3eedc24", "bytes": 2467, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#tab4", "version": null, "note": "Top 10 DEGs and pathways between sham-injury and injury in lesion centre at different time points. At different time points, top 10 DEGs and pathways between sham-injury and injury in lesion centre are showed, respectively.", "structure": {"pmcid": "PMC5661087", "section_index": 11, "section_title": "3.5. Systematic Analysis of DEGs and Altered Pathway in Different Section and Time Points by SAM and KEGG", "row_count": 12, "column_count": 3}, "table": {"label": "Table 4", "caption": "Top 10 DEGs and pathways between sham-injury and injury in lesion centre at different time points. At different time points, top 10 DEGs and pathways between sham-injury and injury in lesion centre are showed, respectively.", "rows": [["Time point", "Top 10 DEGs between sham-injury and injury in lesion centre", "Top 10 pathways between sham-injury and injury in lesion centre"], ["0.5 h", "Npas4, Gm2083, Socs3, Socs3, Fosb, Ccl3, II6, Cyr61, Ptgs2, Myh1", "Pathways in cancer, MAPK signaling pathway, Transcriptional misregulation in cancer, focal adhesion, proteoglycans in cancer, PI3K-Akt signaling pathway, hippo signaling pathway, HTLV-I infection, regulation of actin cytoskeleton, metabolic pathways"], [""], ["4 h", "Ucn2, Gm2083, Atf3, Hspa1b, Hspa1b, Ccl3, C330006P03Rik, Hspa1a, Hspa1b, Egr3", "Metabolic pathways, MAPK signaling pathway, pathways in cancer, PI3K-Akt signaling pathway, HTLV-I infection, focal adhesion, proteoglycans in cancer, osteoclast differentiation, transcriptional misregulation in cancer, olfactory transduction"], [""], ["24 h", "Gm2083, Socs3, Chi3l3, Adam8, Gp49a, Hmox1, Serpine1, Tgm1, A130040M12Rik, Tnc", "Metabolic pathways, MAPK signaling pathway, pathways in cancer, HTLV-I infection, PI3K-Akt signaling pathway, focal adhesion, protein processing in endoplasmic reticulum, regulation of actin cytoskeleton, Epstein-Barr virus infection, proteoglycans in cancer"], [""], ["3 d", "Gpnmb, Cd36, Abca1, Cd5l, Cd36, Ccnb1, Thbs1, Rrm2, Rrm2, Sprr1a", "Metabolic pathways, HTLV-I infection, pathways in cancer, focal adhesion, regulation of actin cytoskeleton, PI3K-Akt signaling pathway, proteoglycans in cancer, MAPK signaling pathway, lysosome, osteoclast differentiation"], [""], ["7 d", "Gpnmb, Gp49a, Cd36, Cd36, Ms4a7, Cd5l, C3ar1, Clec7a, Cd68, Atp6v0d2", "Focal adhesion, PI3K-Akt signaling pathway, metabolic pathways, pathways in cancer, proteoglycans in cancer, MAPK signaling pathway, regulation of actin cytoskeleton, osteoclast differentiation, HTLV-I infection, tuberculosis"], [""], ["28 d", "Gpnmb, Clec7a, Cst7, Gp49a, Lgals3, Cd68, C3ar1, Ms4a7, Sprr1a, Cd48", "Metabolic pathways, MAPK signaling pathway, pathways in cancer, HTLV-I infection, focal adhesion, proteoglycans in cancer, PI3K-Akt signaling pathway, regulation of actin cytoskeleton, chemokine signaling pathway, phagosome"]], "row_count": 12, "column_count": 3, "numeric_cells": 14, "header_rows": 1, "locator": "section[11]/table-wrap[1]#tab4"}}, {"id": "asset:table:pmid:29164149:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f0db91065da59e7098c0c48428f7b98218fa064555b45dd7284bdf3333fd6723", "bytes": 1546, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[2]#tab5", "version": null, "note": "Top 10 DEGs and pathways between sham-injury and injury in different sections. By processing data from all time points in each section, top 10 DEGs and pathways between sham-injury and injury are showed, respectively.", "structure": {"pmcid": "PMC5661087", "section_index": 11, "section_title": "3.5. Systematic Analysis of DEGs and Altered Pathway in Different Section and Time Points by SAM and KEGG", "row_count": 6, "column_count": 3}, "table": {"label": "Table 5", "caption": "Top 10 DEGs and pathways between sham-injury and injury in different sections. By processing data from all time points in each section, top 10 DEGs and pathways between sham-injury and injury are showed, respectively.", "rows": [["Section", "Top 10 DEGs between sham-injury and injury", "Top 10 pathways between sham-injury and injury"], ["rostral regions", "Ccl3, Plek, Slc15a3, Bcl2a1a, Plek, Tlr2, Ccl4, Clec7a, Plek, Palld", "Osteoclast differentiation, cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, phagosome, Chagas disease (American trypanosomiasis), leishmaniasis, toll-like receptor signaling pathway, chemokine signaling pathway, tuberculosis, transcriptional misregulation in cancer"], [""], ["lesion centre", "Ccl3, Atf3, Plek, Ctla2b, Bcl2a1a, Ch25h, Plek, Tnfaip3, Tgif1, Gpr84", "MAPK signaling pathway, metabolic pathways, PI3K-Akt signaling pathway, pathways in cancer, osteoclast differentiation, HTLV-I infection, regulation of actin cytoskeleton, chemokine signaling pathway, Focal adhesion, proteoglycans in cancer"], [""], ["caudal regions", "Atf3, Tlr2, Irgm1, Trim30d, S1pr3, Bcl2a1a, Slc45a3, Plek, Trim30a, Zfp36l1", "Tuberculosis, phagosome, Staphylococcus aureus infection, leishmaniasis, osteoclast differentiation, antigen processing and presentation, herpes simplex infection, Fc gamma R-mediated phagocytosis, viral myocarditis, Toll-like receptor signaling pathway"]], "row_count": 6, "column_count": 3, "numeric_cells": 5, "header_rows": 1, "locator": "section[11]/table-wrap[2]#tab5"}}], "gaps": ["asset:data:geo:GSE5296 not downloaded", "asset:data:geo:GSE5296 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-3", "family": null, "specific": null, "label": "Significant analysis of microarray (SAM)", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Significant analysis of microarray (SAM) is used to study DEGs."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pearson_r"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pearson."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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