Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36339005", "kind": "science-record", "revision": 5, "content_hash": "sha256:049bcdbc1ffa094df1db524e6c9191ca042932ff56279244af32051ec996f041", "created_at": "2026-11-01T18:15:46Z", "updated_at": "2026-11-01T22:50:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network.", "doi": "10.3389/fgene.2022.1030510", "pmid": "36339005", "authors": ["Hengliang Zhang", "Daphne Merkus", "Pei Zhang", "Huifeng Zhang", "Yanyu Wang", "Laijing Du", "Lakshme Kottu"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that are conducive to the diagnosis or exclusion of ACS, and better understand the pathology of the disease through the analysis of immune cells. Materials and methods: RNA expression profiles for circRNAs (GSE197137), miRNAs (GSE31568), and mRNAs (GSE95368) were obtained from the GEO database, and differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were identified. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. As a final step, a regulatory network has been designed for ceRNA. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Hub genes were validated using a third independent mRNA database GSE60993, and ROC curves were used to evaluate their diagnostic values. The correlation between hub genes and immune cells associated with ACS was then analyzed using single sample gene set enrichment analysis (ssGSEA). Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA (hsa-miR-583, hsa-miR-661, hsa-miR-671-5p, hsa-miR-578), and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, and RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. Based on ROC curve analysis, we found that XPNPEP1 has important significance in preventing ACS occurrence and excluding ACS diagnosis. ACS immune infiltration analysis revealed significant correlations between the other 3 hub genes (UCHL1, GPC6, RAD51) and the immune cells (Eosinophils, T folliculars, Type 2 T helper cells, and Imumature dendritic cells). Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS.", "claims": [{"id": "claim-method", "statement": "DEcircRNA, DEmiRNA, and DEmRNA were obtained using the “limma” package in R version 4.0.3.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36339005", "locator": "sections[4] \"Data processing\" paragraph 2", "quote": "DEcircRNA, DEmiRNA, and DEmRNA were obtained using the “limma” package in R version 4.0.3."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36339005", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36339005", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted.", "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:36339005"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE197137"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE197137"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36339005", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.1030510", "sha256": "sha256:689dc9c525e98980ae14160e4cca7c77d32d5e839301db04f5de492884e6fc5c", "bytes": 39317, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2022.1030510", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9627163", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE197137", "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=GSE197137", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE197137", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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