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pmid:38457553
Construction of LncRNA-mediated CeRNA network for investigating the immune pathogenesis of myocardial infarction.
Dongmei Wei · Yuanting Meng · Hua Fan · Yang Sun · Rongtao Chen
Medicine · 2024 doi:10.1097/MD.0000000000037413
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Experiment
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Data
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Analysis
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Complete file
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However, an immune-related competitive endogenous RNA (ceRNA) network has not been reported in MI.\nMETHODS: The GSE66360, GSE19339, GSE97320, GSE61741, and GSE168281 datasets were acquired from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) from MI patients and healthy controls were screened and an immune-related ceRNA network was constructed. Furthermore, the key long noncoding RNAs(lncRNAs) highly related to the immune mechanism of MI were identified utilizing the random walk with restart algorithm. Finally, the expression of the hub genes was further verified in the GSE66360, GSE19339, and GSE97320 datasets, and quantitativereal-time polymerase chain reaction (qRT-PCR) was performed for the MI patients and healthy controls.\nRESULTS: A total of 184 differentially expressed immune-related genes(DE-IRGs) and 432 DE-miRNAs were obtained, and an immune-related ceRNA network comprising 1421 lncRNAs, 61 DE-miRNAs, and 139 DE-IRGs was constructed. According to the order of stress, betweenness, and closeness, NEAT1, KCNQ1OT1, and XIST were identified as key lncRNAs. Moreover, random walk with restart analysis also suggested that NEAT1, KCNQ1OT1, and XIST are key lncRNAs. Subsequently, a ceRNA network of 10 hub genes and 3 lncRNAs was constructed. Finally, we found that the expression of FCER1G and TYROBP significantly differed between MI patients and control individuals in the GSE66360, GSE19339, and GSE97320 datasets. qRT-PCR revealed that the expression of NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP was significantly elevated in MI tissue samples compared to healthy control tissue samples.\nCONCLUSION: NEAT1, KCNQ1OT1, XIST, FCER1G, and TYROBP are involved in MI and can be used as molecular biomarkers for the screening and diagnosis of MI. Furthermore, the immune system plays an essential role in the onset and progression of MI.", "claims": [{"id": "claim-method", "statement": "The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38457553", "locator": "sections[4] \"2.2. 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"sample_accessions": ["GSM1620819", "GSM1620820", "GSM1620821", "GSM1620822", "GSM1620823", "GSM1620824", "GSM1620825", "GSM1620826", "GSM1620827", "GSM1620828", "GSM1620829", "GSM1620830", "GSM1620831", "GSM1620832", "GSM1620833", "GSM1620834", "GSM1620835", "GSM1620836", "GSM1620837", "GSM1620838", "GSM1620839", "GSM1620840", "GSM1620841", "GSM1620842", "GSM1620843", "GSM1620844", "GSM1620845", "GSM1620846", "GSM1620847", "GSM1620848", "GSM1620849", "GSM1620850", "GSM1620851", "GSM1620852", "GSM1620853", "GSM1620854", "GSM1620855", "GSM1620856", "GSM1620857", "GSM1620858", "GSM1620859", "GSM1620860", "GSM1620861", "GSM1620862", "GSM1620863", "GSM1620864", "GSM1620865", "GSM1620866", "GSM1620867", "GSM1620868", "GSM1620869", "GSM1620870", "GSM1620871", "GSM1620872", "GSM1620873", "GSM1620874", "GSM1620875", "GSM1620876", "GSM1620877", "GSM1620878", "GSM1620879", "GSM1620880", "GSM1620881", "GSM1620882", "GSM1620883", "GSM1620884", "GSM1620885", "GSM1620886", "GSM1620887", 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["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control)."}}, {"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": 0.8, "band": "high", "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", 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE66360", "GSE19339", "GSE97320", "GSE61741", "GSE168281"], "resolved_accessions": ["GSE66360", "GSE19339", "GSE97320", "GSE61741", "GSE168281"], "statements": ["The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request."], "basis": "The paper names GSE66360, GSE19339, GSE97320, GSE61741, GSE168281 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:38457553", "data:geo:GSE168281"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE168281"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:11:05Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 9296, "completion_tokens": 2225, "cached_tokens": 256}}, "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:38457553", "type": "paper", "label": "pmid:38457553"}, {"id": "source:pmid:38457553", "type": "manuscript", "label": "PMID 38457553 full text"}, {"id": "data:geo:GSE168281", "type": "dataset", "label": "GEO GSE168281"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38457553", "type": "paper", "label": "pmid:38457553"}, {"id": "source:pmid:38457553", "type": "manuscript", "label": "PMID 38457553 full text"}, {"id": "data:geo:GSE168281", "type": "dataset", "label": "GEO GSE168281"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38457553", "type": "extraction", "used": ["source:pmid:38457553"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE168281", "type": "accession_resolution", "used": ["data:geo:GSE168281"], "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:38457553", "parent_hash": "sha256:b07401c4ad8762c164abc1b2fc8ccfbbc13beda54e6b50f3da60327757a57bf1", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE168281 licence not read", "asset:data:geo:GSE168281 not downloaded", "asset:data:geo:GSE19339 licence not read", "asset:data:geo:GSE19339 not downloaded", "asset:data:geo:GSE61741 licence not read", "asset:data:geo:GSE61741 not downloaded", "asset:data:geo:GSE66360 licence not read", "asset:data:geo:GSE66360 not downloaded", "asset:data:geo:GSE97320 licence not read", "asset:data:geo:GSE97320 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["The limma package (version 3.46.0)[16] was applied to select the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between the MI and control samples in the GSE66360 and GSE61741 datasets with the following filters: (P < .05, and |log2fold change| ≥ 1.0) (MI vs control)."], "order_basis": "analysis_only", "id": "assay:1"}]}