Multi-factor regulatory network and different clusters in hypertrophic obstructive cardiomyopathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34362365", "kind": "science-record", "revision": 8, "content_hash": "sha256:e32c877739c5e4da6bab043200db130e16b37221ba01ec3d691ff459fabcaa09", "created_at": "2026-11-01T15:41:47Z", "updated_at": "2026-11-01T22:47:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Multi-factor regulatory network and different clusters in hypertrophic obstructive cardiomyopathy.", "doi": "10.1186/s12920-021-01036-4", "pmid": "34362365", "authors": ["Xianyu Qin", "Lei Huang", "Sicheng Chen", "Shaoxian Chen", "Pengju Wen", "Yueheng Wu", "Jian Zhuang"], "journal": "BMC medical genomics", "year": 2021, "abstract": "BACKGROUND: Practical biosignatures and thorough understanding of regulatory processes of hypertrophic obstructive cardiomyopathy (HOCM) are still lacking.\nMETHODS: Firstly, public data from GSE36961 and GSE89714 datasets of Gene Expression Omnibus (GEO), Gene database of NCBI (National Center of Biotechnology Information) and Online Mendelian Inheritance in Man (OMIM) database were merged into a candidate gene set of HOCM. Secondly, weighted gene co-expression network analysis (WGCNA) for the candidate gene set was carried out to determine premier co-expressed genes. Thirdly, significant regulators were found out by virtue of a multi-factor regulatory network of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), microRNAs (miRNAs) and transcription factors (TFs) with molecule interreactions from starBase v2.0 database and TRRUST v2 database. Ultimately, HOCM unsupervised clustering and \"tsne\" dimensionality reduction was employed to gain hub genes, whose classification performance was evaluated by a multinomial model of lasso logistic regression analysis binded with receiver operating characteristic (ROC) curve.\nRESULTS: Two HOCM remarkably-interrelated modules were from WGCNA, followed by the recognition of 32 crucial co-expressed genes. The multi-factor regulatory network disclosed 7 primary regulatory agents, containing lncRNAs (XIST, MALAT1, and H19), TFs (SPI1 and SP1) and miRNAs (hsa-miR-29b-39 and has-miR-29a-3p). Four clusters of HOCM and 4 hub genes (COMP, FMOD, AEBP1 and SULF1) significantly expressing in preceding four subtypes were obtained, while ROC curve demonstrated satisfactory performance of clustering and 4 genes.\nCONCLUSIONS: Our consequences furnish valuable resource which may bring about prospective mechanistic and therapeutic anatomization in HOCM.", "claims": [{"id": "claim-method", "statement": "Afterwards, differentially expressed genes (DEGs) were calculated from “limma” algorithm in two respective datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34362365", "locator": "sections[4] \"Data preprocessing and differential expression analysis\" paragraph 2", "quote": "Afterwards, differentially expressed genes (DEGs) were calculated from “limma” algorithm in two respective datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Public data are deposited at Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/, GSE36961 and GPL15389, GSE89714 and GPL11154), Gene database of NCBI (National Center of Biotechnology Information, https://www.ncbi.nlm.nih.gov/gene/), Online Mendelian Inheritance in Man (OMIM, https://omim.org/) databases. All data analyzed in this study are included in the manuscript and supplementary materials.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34362365", "locator": "sections[24] \"notes\" paragraph 1", "quote": "Public data are deposited at Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/, GSE36961 and GPL15389, GSE89714 and GPL11154), Gene database of NCBI (National Center of Biotechnology Information, https://www.ncbi.nlm.nih.gov/gene/), Online Mendelian Inheritance in Man (OMIM, https://omim.org/) databases. 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