Construction and analysis of competing endogenous RNA network and patterns of immune infiltration in abdominal aortic aneurysm.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35990982", "kind": "science-record", "revision": 5, "content_hash": "sha256:163f835d58d6c69939bd976f7a689a6ff34219856bc3c530c41d5deb9fd6f4d7", "created_at": "2026-11-01T18:15:07Z", "updated_at": "2026-11-01T22:49:50Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and analysis of competing endogenous RNA network and patterns of immune infiltration in abdominal aortic aneurysm.", "doi": "10.3389/fcvm.2022.955838", "pmid": "35990982", "authors": ["Liang Chen", "Shuangshuang Wang", "Zheyu Wang", "Yuting Liu", "Yi Xu", "Shuofei Yang", "Guanhua Xue"], "journal": "Frontiers in cardiovascular medicine", "year": 2022, "abstract": "Background: Various studies have highlighted the role of circular RNAs (circRNAs) as critical molecular regulators in cardiovascular diseases, but its role in abdominal aortic aneurysm (AAA) is unclear. This study explores the potential molecular mechanisms of AAA based on the circRNA-microRNA (miRNA)-mRNA competing endogenous RNA (ceRNA) network and immune cell infiltration patterns.\nMethods: The expression profiles of circRNAs (GSE144431) and mRNAs (GSE57691 and GSE47472) were obtained from the Gene Expression Omnibus (GEO). Then, the differentially expressed circRNAs (DEcircRNAs) and mRNAs (DEmRNAs) between AAA patients and healthy control samples, and the target miRNAs of these DEmRNAs and DEcircRNAs were identified. Based on the miRNA-DEmRNAs and miRNA-DEcircRNAs pairs, the ceRNA network was constructed. Furthermore, the proportion of the 22 immune cell types in AAA patients was assessed using cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. The expressions of key genes and immune cell infiltration were validated using clinical specimens.\nResults: A total of 214 DEmRNAs were identified in the GSE57691 and GSE47472 datasets, and 517 DEcircRNAs were identified in the GSE144431 dataset. The ceRNA network included 19 circRNAs, 36 mRNAs, and 68 miRNAs. Two key genes, PPARG and FOXO1, were identified among the hub genes of the established protein-protein interaction between mRNAs in the ceRNA network. Moreover, seven types of immune cells were differentially expressed between AAA patients and healthy control samples. Hub genes in ceRNA, such as FOXO1, HSPA8, and RAB5C, positively correlated with resting CD4 memory T cells or M1 macrophages, or both.\nConclusion: In conclusion, a ceRNA interaction axis was constructed. The composition of infiltrating immune cells was analyzed in the abdominal aorta of AAA patients and healthy control samples. This may help identify potential therapeutic targets for AAA.", "claims": [{"id": "claim-method", "statement": "The differentially expressed mRNAs (DEmRNAs) and circRNAs (DEcircRNAs) between the AAA patients and the healthy control group were analyzed and compared using the “Linear Models for Microarray Data (limma)” R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35990982", "locator": "sections[3] \"Data collection and differential expression analysis\" paragraph 3", "quote": "The differentially expressed mRNAs (DEmRNAs) and circRNAs (DEcircRNAs) between the AAA patients and the healthy control group were analyzed and compared using the “Linear Models for Microarray Data (limma)” R package."}], "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:35990982", "locator": "sections[21] \"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": "The ceRNA network included 19 circRNAs, 36 mRNAs, and 68 miRNAs.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35990982", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The ceRNA network included 19 circRNAs, 36 mRNAs, and 68 miRNAs."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The ceRNA network included 19 circRNAs, 36 mRNAs, and 68 miRNAs.", "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:35990982"], "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:GSE144431"], "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:GSE144431"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35990982", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2022.955838", "sha256": "sha256:75628e11ce9a636a008d5f188370c6c24a8eee3733d521300ce50715bf9897d6", "bytes": 50809, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcvm.2022.955838", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9386163", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE144431", "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=GSE144431", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE144431", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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