The diagnostic significance of integrating m6A modification and immune microenvironment features based on bioinformatic investigation in aortic dissection.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36105536", "kind": "science-record", "revision": 5, "content_hash": "sha256:4243d16957e40db66743b52f06d7c7368c85be866265d2f47a3f6e696487b84e", "created_at": "2026-11-01T18:15:21Z", "updated_at": "2026-11-01T22:50:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The diagnostic significance of integrating m6A modification and immune microenvironment features based on bioinformatic investigation in aortic dissection.", "doi": "10.3389/fcvm.2022.948002", "pmid": "36105536", "authors": ["Ruiming Guo", "Jia Dai", "Hao Xu", "Suhua Zang", "Liang Zhang", "Ning Ma", "Xin Zhang", "Lixuan Zhao", "Hong Luo", "Donghai Liu", "Jian Zhang"], "journal": "Frontiers in cardiovascular medicine", "year": 2022, "abstract": "Purpose: The aim of this study was to investigate the role of m6A modification and the immune microenvironment (IME) features in aortic dissection (AD) and establish a clinical diagnostic model for AD based on m6A and IME factors.\nMethods: GSE52093, GSE98770, GSE147026, GSE153434, and GSE107844 datasets were downloaded from the GEO database. The expression of 21 m6A genes including m6A writers, erasers, readers, and immune cell infiltrates was analyzed in AD and healthy samples by differential analysis and ssGSEA method, respectively. Both correlation analyses between m6A genes and immune cells were conducted by Pearson and Spearman analysis. XGboost was used to dissect the major m6A genes with significant influences on AD. AD samples were classified into two subgroups via consensus cluster and principal component analysis (PCA) analysis, respectively. Among each subgroup, paramount IME features were evaluated. Random forest (RF) was used to figure out key genes from AD and healthy shared differentially expressed genes (DEGs) and two AD subgroups after gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, we constructed an AD diagnostic model combining important m6A regulatory genes and assessed its efficacy.\nResults: Among 21 m6A genes, WTAP, HNRNPC, and FTO were upregulated in AD samples, while IGF2BP1 was downregulated compared with healthy samples. Immune cell infiltrating analysis revealed that YTHDF1 was positively correlated with γδT cell level, while FTO was negatively correlated with activated CD4+ T cell abundance. FTO and IGF2BP1 were identified to be crucial genes that facilitate AD development according to the XGboost algorithm. Notably, patients with AD could be classified into two subgroups among which 21 m6A gene expression profiles and IME features differ from each other via consensus cluster analysis. The RF identified SYNC and MAPK1IP1L as the crucial genes from common 657 shared common genes in 1,141 DEGs between high and low m6A scores of AD groups. Interestingly, the AD diagnostic model coordinating SYNC and MAPK1IP1L with FTO and IGF2BP1 performed well in distinguishing AD samples.\nConclusion: This study indicated that FTO and IGF2BP1 were involved in the IME of AD. Integrating FTO and IGF2BP1 and MAPK1IP1L key genes in AD with a high m6A level context would provide clues for forthcoming AD diagnosis and therapy.", "claims": [{"id": "claim-method", "statement": "The expression of 21 m6A genes including m6A writers, erasers, readers, and immune cell infiltrates was analyzed in AD and healthy samples by differential analysis and ssGSEA method, respectively. Both correlation analyses between m6A genes and immune cells were conducted by Pearson and Spearman analysis. XGboost was used to dissect the major m6A genes with significant influences on AD. AD samples were classified into two subgroups via consensus cluster and principal component analysis (PCA) analysis, respectively.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36105536", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The expression of 21 m6A genes including m6A writers, erasers, readers, and immune cell infiltrates was analyzed in AD and healthy samples by differential analysis and ssGSEA method, respectively. Both correlation analyses between m6A genes and immune cells were conducted by Pearson and Spearman analysis. XGboost was used to dissect the major m6A genes with significant influences on AD. AD samples were classified into two subgroups via consensus cluster and principal component analysis (PCA) analysis, respectively."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36105536", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our study elucidated that m6A modification makes great contributions to the consolidation of the AD immune contexture. FTO and IGF2BP1 were identified as the predominant m6A genes in remodeling IME of AD, and SYNC and MAPK1IP1L were verified as the key genes in AD with a high m6A level context.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36105536", "locator": "sections[20] \"Conclusion\" paragraph 2", "quote": "Our study elucidated that m6A modification makes great contributions to the consolidation of the AD immune contexture. FTO and IGF2BP1 were identified as the predominant m6A genes in remodeling IME of AD, and SYNC and MAPK1IP1L were verified as the key genes in AD with a high m6A level context."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our study elucidated that m6A modification makes great contributions to the consolidation of the AD immune contexture. FTO and IGF2BP1 were identified as the predominant m6A genes in remodeling IME of AD, and SYNC and MAPK1IP1L were verified as the key genes in AD with a high m6A level context.", "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:36105536"], "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:GSE107844"], "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:GSE107844"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36105536", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2022.948002", "sha256": 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Both correlation analyses between m6A genes and immune cells were conducted by Pearson and Spearman analysis. XGboost was used to dissect the major m6A genes with significant influences on AD. 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