Identification of potential crucial genes in atrial fibrillation: a bioinformatic analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32682418", "kind": "science-record", "revision": 8, "content_hash": "sha256:0ffba3b528182eee18a90a673e1f4dab383b2a82b9fd795346d30a162e603a30", "created_at": "2026-11-01T15:41:06Z", "updated_at": "2026-11-01T22:45:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of potential crucial genes in atrial fibrillation: a bioinformatic analysis.", "doi": "10.1186/s12920-020-00754-5", "pmid": "32682418", "authors": ["Junguo Zhang", "Xin Huang", "Xiaojie Wang", "Yanhui Gao", "Li Liu", "Ziyi Li", "Xuejiao Chen", "Jie Zeng", "Zebing Ye", "Guowei Li"], "journal": "BMC medical genomics", "year": 2020, "abstract": "BACKGROUND: Atrial fibrillation (AF) is at least partially heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets.\nMETHODS: Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was used to explore the interaction between potential crucial genes and AF.\nRESULT: We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 or ≤ 2/3 (|log2 FC| ≥ 0.58) and 5 with FC ≥ 2 or ≤ 0.5 (|log2 FC| ≥ 1) of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.\nCONCLUSIONS: The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.", "claims": [{"id": "claim-method", "statement": "To assess differential expression, using the “limma” package of R software, a linear model was fitted and a simple empirical Bayes model was used to moderate standard errors [11].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32682418", "locator": "sections[5] \"Identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "To assess differential expression, using the “limma” package of R software, a linear model was fitted and a simple empirical Bayes model was used to moderate standard errors [11]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray datasets (GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975) for this study are openly available in Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115574, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31821, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE79768, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41177 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14975, respectively (last accessed on 27 Dec 2019).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32682418", "locator": "sections[24] \"notes\" paragraph 1", "quote": "Microarray datasets (GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975) for this study are openly available in Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115574, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31821, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE79768, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41177 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14975, respectively (last accessed on 27 Dec 2019)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:32682418"], "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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"taxon": "Homo sapiens", "title": "Gene expression data from human left and right atrial tissues in patients with degenerative MR in SR and AFib.", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE14975", "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=GSE14975", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE14975", "version": null, "note": "Microarray datasets (GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975) for this study are openly available in Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115574, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31821, 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{"label": "Table 2", "caption": "The DEGs of merged data set with the use of criteria of adjust P value < 0.05 and |log2FC| ≥ 1", "rows": [["Gene", "Log2FC", "AveExpr", "t", "P value", "adjust P value", "B"], ["IGFBP2", "1.1746", "9.5881", "−6.0548", "< 0.0001", "0.0006", "8.0172"], ["C1orf105", "−1.0560", "7.2935", "5.6106", "< 0.0001", "0.0011", "6.3668"], ["FHL2", "1.1255", "9.9882", "−5.4755", "< 0.0001", "0.0016", "5.8742"], ["CHGB", "1.0836", "8.5851", "−5.3090", "< 0.0001", "0.0025", "5.2745"], ["ATP1B4", "1.0469", "5.0220", "−4.3592", "< 0.0001", "0.0283", "2.0308"]], "row_count": 6, "column_count": 7, "numeric_cells": 31, "header_rows": 1, "locator": "section[10]/table-wrap[1]#Tab2"}}, {"id": "asset:table:pmid:32682418:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:efb3b6ec84abb3bbacc21717ed659e2ea2e7987fc8e0bff7c7e56b9eac691445", "bytes": 977, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#Tab3", "version": null, "note": "Significant enriched GO terms and pathways of DEGs", "structure": {"pmcid": "PMC7368672", "section_index": 11, "section_title": "Functional enrichment analyses of DEGs", "row_count": 10, "column_count": 7}, "table": {"label": "Table 3", "caption": "Significant enriched GO terms and pathways of DEGs", "rows": [["", "Term", "Count", "Genes", "P value", "adjust P value", "Q value"], ["GO terms"], ["GO:0031994", "insulin-like growth factor I binding", "2", "IGFBP2/IGFBP3", "0.0001", "0.0168", "0.0121"], ["GO:0005520", "insulin-like growth factor binding", "2", "IGFBP2/IGFBP3", "0.0006", "0.0433", "0.0311"], ["KEGG Pathway"], ["hsa04978", "Mineral absorption", "2", "SLC26A9/ATP1B4", "0.0033", "0.2088", "0.2088"], ["hsa04020", "Calcium signaling pathway", "2", "CXCR4/ HTR2B", "0.0332", "0.2741", "0.2741"], ["hsa04964", "Proximal tubule bicarbonate reclamation", "1", "ATP1B4", "0.0343", "0.2741", "0.2741"], ["Reactome Pathway"], ["R-HSA-381426", "Regulation of Insulin-like Growth Factor (IGF) transport and uptake by Insulin-like GrowthFactor Binding Proteins (IGFBPs)", "3", "IGFBP2/ IGFBP3/ CHGB", "0.0008", "0.0632", "0.0435"]], "row_count": 10, "column_count": 7, "numeric_cells": 31, "header_rows": 1, "locator": "section[11]/table-wrap[1]#Tab3"}}], "gaps": ["asset:data:geo:GSE115574 not downloaded", "asset:data:geo:GSE115574 licence not read", "asset:data:geo:GSE14975 not downloaded", "asset:data:geo:GSE14975 licence not read", "asset:data:geo:GSE31821 not downloaded", "asset:data:geo:GSE31821 licence not read", "asset:data:geo:GSE41177 not downloaded", "asset:data:geo:GSE41177 licence not read", "asset:data:geo:GSE79768 not downloaded", "asset:data:geo:GSE79768 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To assess differential expression, using the “limma” package of R software, a linear model was fitted and a simple empirical Bayes model was used to moderate standard errors [11]."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "Protein-protein interaction"}}], "targets": [], "gaps": []}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE115574", "GSE31821", "GSE79768", "GSE41177", "GSE14975"], "resolved_accessions": ["GSE115574", "GSE31821", "GSE79768", "GSE41177", "GSE14975"], "statements": ["Microarray datasets (GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975) for this study are openly available in Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115574, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31821, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE79768, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41177 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14975, respectively (last accessed on 27 Dec 2019)."], "basis": "The paper names GSE115574, GSE31821, GSE79768, GSE41177, GSE14975 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:32682418", "data:geo:GSE115574", "asset:table:pmid:32682418:1", "asset:table:pmid:32682418:2", "asset:table:pmid:32682418:3"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE115574"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:21:12Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 21499, "completion_tokens": 1974, "cached_tokens": 656}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:32682418", "type": "paper", "label": "pmid:32682418"}, {"id": "source:pmid:32682418", "type": "manuscript", "label": "PMID 32682418 full text"}, {"id": "data:geo:GSE115574", "type": "dataset", "label": "GEO GSE115574"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:32682418", "type": "paper", "label": "pmid:32682418"}, {"id": "source:pmid:32682418", "type": "manuscript", "label": "PMID 32682418 full text"}, {"id": "data:geo:GSE115574", "type": "dataset", "label": "GEO GSE115574"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-32682418", "type": "extraction", "used": ["source:pmid:32682418"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE115574", "type": "accession_resolution", "used": ["data:geo:GSE115574"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:32682418", "parent_hash": "sha256:1988e2f69475e9f67025d4196c1058f1440cc88575b60893255c051b8eeb176f", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE115574 licence not read", "asset:data:geo:GSE115574 not downloaded", "asset:data:geo:GSE14975 licence not read", "asset:data:geo:GSE14975 not downloaded", "asset:data:geo:GSE31821 licence not read", "asset:data:geo:GSE31821 not downloaded", "asset:data:geo:GSE41177 licence not read", "asset:data:geo:GSE41177 not downloaded", "asset:data:geo:GSE79768 licence not read", "asset:data:geo:GSE79768 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["rmatic analyses of public datasets. METHODS: Microarray data sets of GSE115574, GSE31821, GSE79768,", ") database were retrieved. After merging all microarray data and adjusting batch effect, differentia"], "order_basis": "paper_text_order:385", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["To assess differential expression, using the “limma” package of R software, a linear model was fitted and a simple empirical Bayes model was used to moderate standard errors [11]."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}