Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35126952", "kind": "science-record", "revision": 5, "content_hash": "sha256:84a67047086a135667df058211a058d31c81aba070e77a736df1252b67a63ffc", "created_at": "2026-11-01T17:36:52Z", "updated_at": "2026-11-01T22:48:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Dysfunctional Network and Mutation Genes of Hypertrophic Cardiomyopathy.", "doi": "10.1155/2022/8680178", "pmid": "35126952", "authors": ["Yunwen Cui", "Cheng Liu", "Jian Luo", "Jie Liang"], "journal": "Journal of healthcare engineering", "year": 2022, "abstract": "BACKGROUND: Hypertrophic cardiomyopathy (HCM) is a group of heterogeneous diseases that affects the myocardium. It is also a common familial disease. The symptoms are not common and easy to find.\nOBJECTIVE: In this paper, we aim to explore and analyze the dysfunctional gene network related to hypertrophic cardiomyopathy, and the key target genes with diagnostic and therapeutic significance for HCM were screened.\nMETHODS: The gene expression profiles of 37 samples (GSE130036) were downloaded from the GEO database. Differential analysis was used to identify the related dysregulated genes in patients with HCM. Enrichment analysis identified the biological function and signaling pathway of these differentially expressed genes. Then, PPI network was built and verified in the GSE36961 dataset. Finally, the gene of single-nucleotide variants (SNVs) in HCM samples was screened by means of maftools.\nRESULTS: In this study, 920 differentially expressed genes were obtained, and these genes were mainly related to metabolism-related signaling pathways. 187 interacting genes were identified by PPI network analysis, and the expression trends of C1QB, F13A1, CD163, FCN3, PLA2G2A, and CHRDL2 were verified by another dataset and quantitative real-time polymerase chain reaction. ROC curve analysis showed that they had certain clinical diagnostic ability, and they were the potential key dysfunctional genes of HCM. In addition, we found that PRMT5 mutation was the most frequent in HCM samples, which may affect the pathogenesis of HCM.\nCONCLUSION: Therefore, the key genes and enrichment results identified by our analysis may provide a reference for the occurrence and development mechanism of HCM. In addition, mutations in PRMT5 may be a useful therapeutic and diagnostic target for HCM. Our results also provide an independent quantitative assessment of functional limitations in patients with unknown history.", "claims": [{"id": "claim-method", "statement": "The limma package was used in R to screen DEGs between HCM and healthy control samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35126952", "locator": "sections[3] \"2.1. GEO Dataset and Differentially Expressed Genes (DEGs)\" paragraph 3", "quote": "The limma package was used in R to screen DEGs between HCM and healthy control samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35126952", "locator": "sections[17] \"Data Availability\" paragraph 2", "quote": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified C1QB, F13A1, CD163, FCN3, PLA2G2A, and CHRDL2 as potential key dysfunctional genes of HCM and found that PRMT5 had the highest mutation rate in HCM samples.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35126952", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "In this study, 920 differentially expressed genes were obtained, and these genes were mainly related to metabolism-related signaling pathways."}, {"asset": "source:pmid:35126952", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "ROC curve analysis showed that they had certain clinical diagnostic ability, and they were the potential key dysfunctional genes of HCM."}, {"asset": "source:pmid:35126952", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "In addition, we found that PRMT5 mutation was the most frequent in HCM samples, which may affect the pathogenesis of HCM."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified C1QB, F13A1, CD163, FCN3, PLA2G2A, and CHRDL2 as potential key dysfunctional genes of HCM and found that PRMT5 had the highest mutation rate in HCM samples.", "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:35126952"], "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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