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pmid:37228412

APOE as potential biomarkers of moyamoya disease.

Haibin Wu · Jiang Xu · Jiarong Sun · Jian Duan · Jinlin Xiao · Quan Ren · Pengfei Zhou · Jian Yan · Youping Li · Xiaoxing Xiong · Erming Zeng

Frontiers in neurology · 2023 doi:10.3389/fneur.2023.1156894

Paper

complete

Experiment

partial

Data

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Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:37228412
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science-record
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paper object · 10 fields
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title
APOE as potential biomarkers of moyamoya disease.
doi
10.3389/fneur.2023.1156894
pmid
37228412
authors array · 11 items
[0]
Haibin Wu
[1]
Jiang Xu
[2]
Jiarong Sun
[3]
Jian Duan
[4]
Jinlin Xiao
[5]
Quan Ren
[6]
Pengfei Zhou
[7]
Jian Yan
[8]
Youping Li
[9]
Xiaoxing Xiong
[10]
Erming Zeng
journal
Frontiers in neurology
year
2023
abstract
Objective: The mechanisms underpinning Moyamoya disease (MMD) remain unclear, and effective biomarkers remain unknown. The purpose of this study was to identify novel serum biomarkers of MMD. Methods: Serum samples were collected from 23 patients with MMD and 30 healthy controls (HCs). Serum proteins were identified using tandem tandem-mass-tag (TMT) labeling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differentially expressed proteins (DEPs) in the serum samples were identified using the SwissProt database. The DEPs were assessed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, Gene Ontology (GO), and protein-protein interaction (PPI) networks, and hub genes were identified and visualized using Cytoscape software. Microarray datasets GSE157628, GSE189993, and GSE100488 from the Gene Expression Omnibus (GEO) database were collected. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) were identified, and miRNA targets of DEGs were predicted using the miRWalk3.0 database. Serum apolipoprotein E (APOE) levels were compared in 33 MMD patients and 28 Moyamoya syndrome (MMS) patients to investigate the potential of APOE to be as an MMD biomarker. Results: We identified 85 DEPs, of which 34 were up- and 51 down-regulated. Bioinformatics analysis showed that some DEPs were significantly enriched in cholesterol metabolism. A total of 1105 DEGs were identified in the GSE157628 dataset (842 up- and 263 down-regulated), whereas 1290 were identified in the GSE189993 dataset (200 up- and 1,090 down-regulated). The APOE only overlaps with the upregulated gene expression in Proteomic Profiling and in GEO databases. Functional enrichment analysis demonstrated that APOE was associated with cholesterol metabolism. Moreover, 149 miRNAs of APOE were predicted in the miRWalk3.0 database, and hsa-miR-718 was the only DE-miRNA overlap identified in MMD samples. Serum APOE levels were significantly higher in patients with MMD than in those without. The performance of APOE as an individual biomarker to diagnose MMD was remarkable. Conclusions: We present the first description of the protein profile of patients with MMD. APOE was identified as a potential biomarker for MMD. Cholesterol metabolism was found to potentially be related to MMD, which may provide helpful diagnostic and therapeutic insights for MMD.
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In this study, the GEO2R platform (http://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect DEGs and DE-miRNA between MMD and control groups.
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In this study, the GEO2R platform (http://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect DEGs and DE-miRNA between MMD and control groups.
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The study identified 149 predicted miRNAs of APOE, with hsa-miR-718 as the only DE-miRNA overlap identified in MMD samples.
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Moreover, 149 miRNAs of APOE were predicted in the miRWalk3.0 database, and hsa-miR-718 was the only DE-miRNA overlap identified in MMD samples.
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asset:data:geo:GSE157628 not downloaded
[4]
asset:data:geo:GSE189993 licence not read
[5]
asset:data:geo:GSE189993 not downloaded
[6]
asset:data:geo:PXD039975 licence not read
[7]
asset:data:geo:PXD039975 not downloaded
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execution.not_run
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method.reader_named_unmapped
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g combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differentially expressed protein
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uid chromatography-tandem mass spectrometry (LC-MS/MS). Differentially expressed proteins (DEPs) i
[2]
laps with the upregulated gene expression in Proteomic Profiling and in GEO databases. Functional e
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37228412", "kind": "science-record", "revision": 3, "content_hash": "sha256:c6bc7a03ddc4b44a88e2ef7b923dc15821c8f5646f41edc77400de7a745e289f", "created_at": "2026-11-01T19:01:56Z", "updated_at": "2026-11-01T22:09:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "APOE as potential biomarkers of moyamoya disease.", "doi": "10.3389/fneur.2023.1156894", "pmid": "37228412", "authors": ["Haibin Wu", "Jiang Xu", "Jiarong Sun", "Jian Duan", "Jinlin Xiao", "Quan Ren", "Pengfei Zhou", "Jian Yan", "Youping Li", "Xiaoxing Xiong", "Erming Zeng"], "journal": "Frontiers in neurology", "year": 2023, "abstract": "Objective: The mechanisms underpinning Moyamoya disease (MMD) remain unclear, and effective biomarkers remain unknown. The purpose of this study was to identify novel serum biomarkers of MMD.\nMethods: Serum samples were collected from 23 patients with MMD and 30 healthy controls (HCs). Serum proteins were identified using tandem tandem-mass-tag (TMT) labeling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differentially expressed proteins (DEPs) in the serum samples were identified using the SwissProt database. The DEPs were assessed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, Gene Ontology (GO), and protein-protein interaction (PPI) networks, and hub genes were identified and visualized using Cytoscape software. Microarray datasets GSE157628, GSE189993, and GSE100488 from the Gene Expression Omnibus (GEO) database were collected. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) were identified, and miRNA targets of DEGs were predicted using the miRWalk3.0 database. Serum apolipoprotein E (APOE) levels were compared in 33 MMD patients and 28 Moyamoya syndrome (MMS) patients to investigate the potential of APOE to be as an MMD biomarker.\nResults: We identified 85 DEPs, of which 34 were up- and 51 down-regulated. Bioinformatics analysis showed that some DEPs were significantly enriched in cholesterol metabolism. A total of 1105 DEGs were identified in the GSE157628 dataset (842 up- and 263 down-regulated), whereas 1290 were identified in the GSE189993 dataset (200 up- and 1,090 down-regulated). The APOE only overlaps with the upregulated gene expression in Proteomic Profiling and in GEO databases. Functional enrichment analysis demonstrated that APOE was associated with cholesterol metabolism. Moreover, 149 miRNAs of APOE were predicted in the miRWalk3.0 database, and hsa-miR-718 was the only DE-miRNA overlap identified in MMD samples. Serum APOE levels were significantly higher in patients with MMD than in those without. The performance of APOE as an individual biomarker to diagnose MMD was remarkable.\nConclusions: We present the first description of the protein profile of patients with MMD. APOE was identified as a potential biomarker for MMD. Cholesterol metabolism was found to potentially be related to MMD, which may provide helpful diagnostic and therapeutic insights for MMD.", "claims": [{"id": "claim-method", "statement": "In this study, the GEO2R platform (http://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect DEGs and DE-miRNA between MMD and control groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37228412", "locator": "sections[7] \"2.5. 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This data can be found here: ProteomeXchange, https://www.proteomexchange.org/, PXD039975."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 149 predicted miRNAs of APOE, with hsa-miR-718 as the only DE-miRNA overlap identified in MMD samples.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37228412", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Moreover, 149 miRNAs of APOE were predicted in the miRWalk3.0 database, and hsa-miR-718 was the only DE-miRNA overlap identified in MMD samples."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study identified 149 predicted miRNAs of APOE, with hsa-miR-718 as the only DE-miRNA overlap identified in MMD samples.", "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:37228412"], "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:GSE100488"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:student_t", "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:GSE100488"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:student_t"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37228412", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fneur.2023.1156894", "sha256": "sha256:203bfa2c0cf36d59b306eb0d92b8536365d918ac3ad2eeec7a360883c6a09f44", "bytes": 25354, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fneur.2023.1156894", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10203507", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE100488", "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=GSE100488", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE100488", "version": null, "note": "The original contributions presented in the study are publicly available. 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This data can be found here: ProteomeXchange, https://www.proteomexchange.org/, PXD039975.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are publicly available. 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