A 2 miRNAs-based signature for the diagnosis of atherosclerosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33761890", "kind": "science-record", "revision": 7, "content_hash": "sha256:e0b3c16466c09af8d2ea2e26dfb9b35540c0b535ebe9c65c3fe3a303992669ef", "created_at": "2026-11-01T15:41:30Z", "updated_at": "2026-11-01T22:03:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 2 miRNAs-based signature for the diagnosis of atherosclerosis.", "doi": "10.1186/s12872-021-01960-4", "pmid": "33761890", "authors": ["Xiujiang Han", "Huimin Wang", "Yongjian Li", "Lina Liu", "Sheng Gao"], "journal": "BMC cardiovascular disorders", "year": 2021, "abstract": "BACKGROUND: Atherosclerosis (AS) is a leading cause of vascular disease worldwide. MicroRNAs (miRNAs) play an essential role in the development of AS. However, the miRNAs-based biomarkers for the diagnosis of AS are still limited. Here, we aimed to identify the miRNAs significantly related to AS and construct the predicting model based on these miRNAs for distinguishing the AS patients from healthy cases.\nMETHODS: The miRNA and mRNA expression microarray data of blood samples from patients with AS and healthy cases were obtained from the GSE59421 and GSE20129 of Gene Expression Omnibus (GEO) database, respectively. Weighted Gene Co-expression Network Analysis (WGCNA) was performed to evaluate the correlation of the miRNAs and mRNAs with AS and identify the miRNAs and mRNAs significantly associated with AS. The potentially critical miRNAs were further optimized by functional enrichment analysis. The logistic regression models were constructed based on these optimized miRNAs and validated by threefold cross-validation method.\nRESULTS: WGCNA revealed 42 miRNAs and 532 genes significantly correlated with AS. Functional enrichment analysis identified 12 crucial miRNAs in patients with AS. Moreover, 6 miRNAs among the identified 12 miRNAs, were selected using a stepwise regression model, in which four miRNAs, including hsa-miR-654-5p, hsa-miR-409-3p, hsa-miR-485-5p and hsa-miR-654-3p, were further identified through multivariate regression analysis. The threefold cross-validation method showed that the AUC of logistic regression model based on the four miRNAs was 0.7308, 0.8258, and 0.7483, respectively, with an average AUC of 0.7683.\nCONCLUSION: We identified a total of four miRNAs, including hsa-miR-654-5p and hsa-miR-409-3p, are identified as the potentially critical biomarkers for AS. The logistic regression model based on the identified 2 miRNAs could reliably distinguish the patients with AS from normal cases.", "claims": [{"id": "claim-method", "statement": "The logistic regression models were constructed based on these optimized miRNAs and validated by threefold cross-validation method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33761890", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The logistic regression models were constructed based on these optimized miRNAs and validated by threefold cross-validation method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data were obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33761890", "locator": "sections[21] \"Availability of data and materials\" paragraph 2", "quote": "The data were obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:33761890"], "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:GSE20129"], "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:GSE20129"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33761890", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12872-021-01960-4", "sha256": 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METHODS: The miRNA and mRNA expression microarray data of blood samples from patients with AS"], "order_basis": "paper_text_order:468", "id": "assay:1"}, {"role": "data_generation", "definition_id": "clinical_cohort", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ession microarray data of blood samples from patients with AS and healthy cases were obtained from the", "dentifies 12 miRNAs potentially critical for patients with AS The turquoise miRNA module contained 42 m", "ent analysis identified 12 crucial miRNAs in patients with AS. Moreover, 6 miRNAs among the identified", "fied 2 miRNAs could reliably distinguish the patients with AS from normal cases."], "order_basis": "paper_text_order:487", "id": "assay:2"}, {"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The logistic regression models were constructed based on these optimized miRNAs and validated by threefold cross-validation method."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}