Integrative Machine Learning Approach to Explore Glycosylation Signatures and Immune Landscape in Moyamoya Disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40416061", "kind": "science-record", "revision": 4, "content_hash": "sha256:c35fd5b7c0b846b898dd8dff8c7e36cf0dfe4807a0a7e830e3fc6eb4809f4781", "created_at": "2026-11-01T20:30:33Z", "updated_at": "2026-11-01T22:56:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative Machine Learning Approach to Explore Glycosylation Signatures and Immune Landscape in Moyamoya Disease.", "doi": "10.1177/11779322251342412", "pmid": "40416061", "authors": ["Cunxin Tan", "Jing Wang", "Yanru Wang", "Shaoqi Xu", "Zhenyu Zhou", "Junze Zhang", "Shihao He", "Ran Duan"], "journal": "Bioinformatics and biology insights", "year": 2025, "abstract": "Moyamoya disease (MMD) is a rare, chronic cerebrovascular disorder of uncertain etiology. Although abnormal glucose metabolism has been implicated, the contribution of glycosylation-related genes in MMD remains elusive. In this study, we analyzed 2 transcriptome data sets (GSE189993 and GSE131293) from the Gene Expression Omnibus (GEO) database to identify 723 differentially expressed genes (DEGs) between MMD patients and controls. Intersection genes with known glycosylation-related genes underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We utilized machine learning to select key hub genes, followed by immune cell infiltration and correlation analyses. In-depth immune cell analysis indicated that both CFP and MGAT5B were closely tied to various immune components, suggesting potential crosstalk between glycosylation pathways and immune regulation. Notably, CFP was positively associated with pDCs, HLA, and CCR, whereas MGAT5B correlated with B-cells, check-points, and T helper cells but showed a negative relationship with Tregs, hinting at an immunoregulatory mechanism influencing MMD progression. Motif-TF annotation highlighted csibp_M2095 as the motif with the highest normalized enrichment score (NES: 6.57). Reverse microRNA (miRNA)-gene prediction identified 75 miRNAs regulating these focus genes, along with 126 miRNA-miRNA interconnections. Connectivity Map (Cmap) analysis revealed that Chenodeoxycholic acid, MRS-1220, Phenytoin, and Piceid were strongly negatively correlated with MMD expression profiles, suggesting potential therapeutic candidates. Enzyme-linked immunosorbent assays confirmed elevated CFP and MGAT5B and reduced PTPN11 in MMD, aligning with our bioinformatic findings. Moreover, PTPN11 knockdown in human brain microvascular endothelial cells (HBMECs) significantly enhanced tube formation, indicating a role in vascular remodeling. Collectively, these results emphasize the importance of glycosylation-related genes and immune dysregulation in MMD pathogenesis. These findings broaden our understanding of MMD's underlying mechanisms and underscore the necessity of continued research into glycosylation-driven pathways for improved disease management.", "claims": [{"id": "claim-method", "statement": "We performed differential expression analysis using the R package “Limma” to identify the differentially expressed genes (DEGs) with the values of P < .05 and |log2FC| > 1 between MMD and controls.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40416061", "locator": "sections[4] \"Differential expression analysis\" paragraph 2", "quote": "We performed differential expression analysis using the R package “Limma” to identify the differentially expressed genes (DEGs) with the values of P < .05 and |log2FC| > 1 between MMD and controls."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40416061", "locator": "sections[34] \"fn-group\" paragraph 1", "quote": "The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Analysis of two GEO transcriptome data sets identified 723 differentially expressed genes between MMD patients and controls.", "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:40416061"], "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. 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In this study, we analyzed 2 transcriptome data sets (GSE189993 and GSE131293) from the"], "order_basis": "paper_text_order:320", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["our bioinformatic findings. Moreover, PTPN11 knockdown in human brain microvascular endothelial cel"], "order_basis": "paper_text_order:1855", "id": "assay:2"}, {"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": ["d consultations and physical examinations on patients with MMD to ensure that they did not have any und", "ospital (KY-2023-2024-02). We collected 2 mL blood samples from all patients with MMD and centrifuged them a", "ificant. Participants and sample preparation We enrolled 3 Chinese and Han individuals who underwent", "nd demographic characteristics. In addition, we recruited 3 healthy controls (HCs; age range = 18-45 y"], "order_basis": "paper_text_order:3481", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["We performed differential expression analysis using the R package “Limma” to identify the differentially expressed genes (DEGs) with the values of P < .05 and |log2FC| > 1 between MMD and controls."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}