MFGE8, ALB, APOB, APOE, SAA1, A2M, and C3 as Novel Biomarkers for Stress Cardiomyopathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32695227", "kind": "science-record", "revision": 8, "content_hash": "sha256:9aa4897115cb9fbe16fb1725c6dc6e35e1a824b6bdb49fc829992226ec993ebf", "created_at": "2026-11-01T15:41:06Z", "updated_at": "2026-11-01T22:45:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "MFGE8, ALB, APOB, APOE, SAA1, A2M, and C3 as Novel Biomarkers for Stress Cardiomyopathy.", "doi": "10.1155/2020/1615826", "pmid": "32695227", "authors": ["Xiao-Yu Pan", "Zai-Wei Zhang"], "journal": "Cardiovascular therapeutics", "year": 2020, "abstract": "BACKGROUND: Stress cardiomyopathy (SCM) is a transient reversible left ventricular dysfunction that more often occurs in women. Symptoms of SCM patients are similar to those of acute coronary syndrome (ACS), but little is known about biomarkers. The goals of this study were to identify the potentially crucial genes and pathways associated with SCM.\nMETHODS: We analyzed microarray datasets GSE95368 derived from the Gene Expression Omnibus (GEO) database. Firstly, identify the differentially expressed genes (DEGs) between SCM patients in normal patients. Then, the DEGs were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, the protein-protein interaction (PPI) network was constructed and Cytoscape was used to find the key genes.\nRESULTS: In total, 25 DEGs were identified, including 10 upregulated genes and 15 downregulated genes. These DEGs were mainly enriched in ECM-receptor interaction, dilated cardiomyopathy (DCM), human papillomavirus infection, and focal adhesion, whereas in GO function classification, they were mainly enriched in the extracellular region, positive regulation of the multicellular organismal process, establishment of localization, and intracellular vesicle.\nCONCLUSION: Seven hub genes contained APOE, MFGE8, ALB, APOB, SAA1, A2M, and C3 identified as hub genes of SCM, which might be used as diagnostic biomarkers or molecular targets for the treatment of SCM.", "claims": [{"id": "claim-method", "statement": "Then, the expression data were log2 transformed and the limma functional package in R software was used to compare gene expression in SCM and control samples to identify DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32695227", "locator": "sections[4] \"2.2. 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the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7350165", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE95368", "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=GSE95368", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE95368", "version": null, "note": "The data used to support the findings of this study are included within the supplementary information file.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data used to support the findings of this study are included within the supplementary information file.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2508127", "GSM2508128", "GSM2508129", "GSM2508130", "GSM2508131", "GSM2508132", "GSM2508133", "GSM2508134", "GSM2508135", "GSM2508136", "GSM2508137", "GSM2508138", "GSM2508139", "GSM2508140", "GSM2508141", "GSM2508142", "GSM2508143", "GSM2508144", "GSM2508145", "GSM2508146", "GSM2508147", "GSM2508148", "GSM2508149", "GSM2508150", "GSM2508151", "GSM2508152", "GSM2508153", "GSM2508154", "GSM2508155", "GSM2508156", "GSM2508157", "GSM2508158", "GSM2508159", "GSM2508160", "GSM2508161", "GSM2508162", "GSM2508163", "GSM2508164", "GSM2508165", "GSM2508166", "GSM2508167", "GSM2508168", "GSM2508169", "GSM2508170", "GSM2508171", "GSM2508172", "GSM2508173", "GSM2508174"], "sample_count": 48, "group_sizes": null, "group_sizes_basis": null, "platform": "23119", "taxon": "Homo sapiens", "title": "Proteomic Comparison of Acute Myocardial Infarction and Stress Cardiomyopathy in Women", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE95368 not downloaded", "asset:data:geo:GSE95368 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": "Then, the expression data were log2 transformed and the limma functional package in R software was used to compare gene expression in SCM and control samples to identify DEGs."}}, {"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"}}, {"id": "method-3", "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"}}], "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. 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