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pmid:39396083

Identification of cuproptosis-related genes in Alzheimer's disease based on bioinformatic analysis.

Ming-Ming Ma · Jing Zhao · Ling Liu · Cai-Ying Wu

European journal of medical research · 2024 doi:10.1186/s40001-024-02093-y

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Experiment

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pmid:39396083
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2026-11-01T20:29:37Z
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title
Identification of cuproptosis-related genes in Alzheimer's disease based on bioinformatic analysis.
doi
10.1186/s40001-024-02093-y
pmid
39396083
authors array · 4 items
[0]
Ming-Ming Ma
[1]
Jing Zhao
[2]
Ling Liu
[3]
Cai-Ying Wu
journal
European journal of medical research
year
2024
abstract
OBJECTIVE: To explore the role of cuproptosis in Alzheimer's disease (AD). METHODS: An AD-related microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database (GSE140830). Weighted gene co-expression network analysis was used to identify AD-related modular genes. The Venn analysis was performed to obtain module genes associated with apoptosis and cuproptosis. Besides, we conducted an enrichment analysis of overlapped genes and constructed the protein-protein interaction (PPI) network, followed by screening hub genes and those significantly associated with AD were used to construct models of apoptosis and cuproptosis, respectively. Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models. Finally, the accuracy and reliability of AD prediction models were verified by GSE26927. RESULTS: We obtained 42 module genes related to apoptosis and 9 module genes related to cuproptosis. The enrichment analysis results revealed MAPK signaling pathway as the common signaling pathway of apoptosis- and cuproptosis-related genes. Next, the hub genes associated with apoptosis (TRADD, FADD, BIRC2, and CASP2) and cuproptosis (MAP2K1, SLC31A1, and PDHB) in AD were identified, which were used to construct apoptosis and cuproptosis models to distinguish AD patients from the control group (P < 0.05). The ROC, DCA, and subgroup analysis results showed that apoptosis-related models and cuproptosis-related models had comparable ability in predicting AD. GSE26927 further confirmed that the two models have comparable predictive effects for AD. CONCLUSIONS: The cuproptosis model had a certain performance in predicting AD. Three hub genes (MAP2K1, SLC31A1, and PDHB) closely related to cuproptosis in AD might serve as biomarkers for AD diagnosis and treatment.
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Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models.
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Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models.
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The datasets used and/or analyzed during the current study are available from the corresponding authors upon reasonable request.
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sections[26] "notes" paragraph 1
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The datasets used and/or analyzed during the current study are available from the corresponding authors upon reasonable request.
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The cuproptosis model had a certain performance in predicting AD.
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sections[0] "Abstract" paragraph 4
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The cuproptosis model had a certain performance in predicting AD.
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The cuproptosis model had a certain performance in predicting AD.
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https://doi.org/10.1186/s40001-024-02093-y
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15988
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Homo sapiens
title
Systems-level analysis of peripheral blood gene expression in dementia patients reveals an innate immune response shared across multiple disorders [ftd]
resolution_checked_at
2026-11-01T20:16:08Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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licence_read
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118
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6255
taxon
Homo sapiens
title
Common neuroinflammatory pathways in neurodegenerative diseases.
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2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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false
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Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models.
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tier
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The datasets used and/or analyzed during the current study are available from the corresponding authors upon reasonable request.
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The paper names GSE140830, GSE26927 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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minimax
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minimax
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[0]
eimer's disease (AD). METHODS: An AD-related microarray dataset was downloaded from the Gene Express
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[0]
ormed to obtain module genes associated with apoptosis and cuproptosis. Besides, we conducted an en
[1]
ted with AD were used to construct models of apoptosis and cuproptosis, respectively. Further, rece
[2]
ULTS: We obtained 42 module genes related to apoptosis and 9 module genes related to cuproptosis. T
[3]
g pathway as the common signaling pathway of apoptosis- and cuproptosis-related genes. Next, the hu
order_basis
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assay:2
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Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39396083", "kind": "science-record", "revision": 3, "content_hash": "sha256:3579b6c61708862e231ae5f1faea4f54d841a6e85b1204cc50714784f3cd758c", "created_at": "2026-11-01T20:29:37Z", "updated_at": "2026-11-01T22:12:54Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of cuproptosis-related genes in Alzheimer's disease based on bioinformatic analysis.", "doi": "10.1186/s40001-024-02093-y", "pmid": "39396083", "authors": ["Ming-Ming Ma", "Jing Zhao", "Ling Liu", "Cai-Ying Wu"], "journal": "European journal of medical research", "year": 2024, "abstract": "OBJECTIVE: To explore the role of cuproptosis in Alzheimer's disease (AD).\nMETHODS: An AD-related microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database (GSE140830). Weighted gene co-expression network analysis was used to identify AD-related modular genes. The Venn analysis was performed to obtain module genes associated with apoptosis and cuproptosis. Besides, we conducted an enrichment analysis of overlapped genes and constructed the protein-protein interaction (PPI) network, followed by screening hub genes and those significantly associated with AD were used to construct models of apoptosis and cuproptosis, respectively. Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models. Finally, the accuracy and reliability of AD prediction models were verified by GSE26927.\nRESULTS: We obtained 42 module genes related to apoptosis and 9 module genes related to cuproptosis. The enrichment analysis results revealed MAPK signaling pathway as the common signaling pathway of apoptosis- and cuproptosis-related genes. Next, the hub genes associated with apoptosis (TRADD, FADD, BIRC2, and CASP2) and cuproptosis (MAP2K1, SLC31A1, and PDHB) in AD were identified, which were used to construct apoptosis and cuproptosis models to distinguish AD patients from the control group (P < 0.05). The ROC, DCA, and subgroup analysis results showed that apoptosis-related models and cuproptosis-related models had comparable ability in predicting AD. GSE26927 further confirmed that the two models have comparable predictive effects for AD.\nCONCLUSIONS: The cuproptosis model had a certain performance in predicting AD. Three hub genes (MAP2K1, SLC31A1, and PDHB) closely related to cuproptosis in AD might serve as biomarkers for AD diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39396083", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Further, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and subgroup analysis were used to compare the AD prediction performance of two models."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding authors upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39396083", "locator": "sections[26] \"notes\" paragraph 1", "quote": "The datasets used and/or analyzed during the current study are available from the corresponding authors upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The cuproptosis model had a certain performance in predicting AD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39396083", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The cuproptosis model had a certain performance in predicting AD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The cuproptosis model had a certain performance in predicting AD.", "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:39396083"], "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:GSE140830"], "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:GSE140830"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39396083", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s40001-024-02093-y", "sha256": 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METHODS: An AD-related microarray dataset was downloaded from the Gene Express"], "order_basis": "paper_text_order:153", "id": "assay:1"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ormed to obtain module genes associated with apoptosis and cuproptosis. Besides, we conducted an en", "ted with AD were used to construct models of apoptosis and cuproptosis, respectively. Further, rece", "ULTS: We obtained 42 module genes related to apoptosis and 9 module genes related to cuproptosis. T", "g pathway as the common signaling pathway of apoptosis- and cuproptosis-related genes. 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