From Diabetes to Dementia: Identifying Key Genes in the Progression of Cognitive Impairment.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39452046", "kind": "science-record", "revision": 4, "content_hash": "sha256:5114e9e46e46d888abd14b326a7f311110641232d9026e737a7368c8543a996f", "created_at": "2026-11-01T20:29:43Z", "updated_at": "2026-11-01T22:55:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "From Diabetes to Dementia: Identifying Key Genes in the Progression of Cognitive Impairment.", "doi": "10.3390/brainsci14101035", "pmid": "39452046", "authors": ["Zhaoming Cao", "Yage Du", "Guangyi Xu", "He Zhu", "Yinchao Ma", "Ziyuan Wang", "Shaoying Wang", "Yanhui Lu"], "journal": "Brain sciences", "year": 2024, "abstract": "OBJECTIVES: To provide a basis for further research on the molecular mechanisms underlying type 2 diabetes-associated mild cognitive impairment (DCI) using two bioinformatics methods to screen key genes involved in the progression of mild cognitive impairment (MCI) and type 2 diabetes.\nMETHODS: RNA sequencing data of MCI and normal cognition groups, as well as expression profile and sample information data of clinical characteristic data of GSE63060, which contains 160 MCI samples and 104 normal samples, were downloaded from the GEO database. Hub genes were identified using weighted gene co-expression network analysis (WGCNA). Protein-protein interaction (PPI) analysis, combined with least absolute shrinkage and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses, was used to verify the genes. Moreover, RNA sequencing and clinical characteristic data for GSE166502 of 13 type 2 diabetes samples and 13 normal controls were downloaded from the GEO database, and the correlation between the screened genes and type 2 diabetes was verified by difference and ROC curve analyses. In addition, we collected clinical biopsies to validate the results.\nRESULTS: Based on WGCNA, 10 modules were integrated, and six were correlated with MCI. Six hub genes associated with MCI (TOMM7, SNRPG, COX7C, UQCRQ, RPL31, and RPS24) were identified using the LASSO algorithm. The ROC curve was screened by integrating the GEO database, and revealed COX7C, SNRPG, TOMM7, and RPS24 as key genes in the progression of type 2 diabetes.\nCONCLUSIONS: COX7C, SNRPG, TOMM7, and RPS24 are involved in MCI and type 2 diabetes progression. Therefore, the molecular mechanisms of these four genes in the development of type 2 diabetes-associated MCI should be studied.", "claims": [{"id": "claim-method", "statement": "The Student’s t-test was used to analyze the differences in MCI eigengenes between the type 2 diabetes and control group samples; p < 0.05 was considered statistically significant. A ROC curve was constructed to evaluate the ability of the differentially expressed genes to predict the occurrence of type 2 diabetes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39452046", "locator": "sections[17] \"4.6. Analysis of the Role of MCI Key Eigengenes in Type 2 Diabetes\" paragraph 2", "quote": "The Student’s t-test was used to analyze the differences in MCI eigengenes between the type 2 diabetes and control group samples; p < 0.05 was considered statistically significant. A ROC curve was constructed to evaluate the ability of the differentially expressed genes to predict the occurrence of type 2 diabetes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data supporting the findings of this study are openly available in the GENE EXPRESSION OMNIBUS(GEO) at https://www.ncbi.nlm.nih.gov/geo/ (accessed on 4 May 2023).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39452046", "locator": "sections[28] \"notes\" paragraph 1", "quote": "The data supporting the findings of this study are openly available in the GENE EXPRESSION OMNIBUS(GEO) at https://www.ncbi.nlm.nih.gov/geo/ (accessed on 4 May 2023)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The results were COX7C (AUC = 0.705; 95% CI: 0.540–0.854), SNRPG (AUC = 0.916; 95% CI: 0.832–0.980), TOMM7 (AUC = 0.873; 95% CI: 0.769–0.959), and RPS24 (AUC = 0.881; 95% CI: 0.778–0.963).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "The results were COX7C (AUC = 0.705; 95% CI: 0.540–0.854), SNRPG (AUC = 0.916; 95% CI: 0.832–0.980), TOMM7 (AUC = 0.873; 95% CI: 0.769–0.959), and RPS24 (AUC = 0.881; 95% CI: 0.778–0.963)."}, "evidence": [{"asset": "source:pmid:39452046", "locator": "sections[8] \"2.6. The Diagnostic Value of MCI Key Genes in Type 2 Diabetes\" paragraph 2", "quote": "The results were COX7C (AUC = 0.705; 95% CI: 0.540–0.854), SNRPG (AUC = 0.916; 95% CI: 0.832–0.980), TOMM7 (AUC = 0.873; 95% CI: 0.769–0.959), and RPS24 (AUC = 0.881; 95% CI: 0.778–0.963)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The results were COX7C (AUC = 0.705; 95% CI: 0.540–0.854), SNRPG (AUC = 0.916; 95% CI: 0.832–0.980), TOMM7 (AUC = 0.873; 95% CI: 0.769–0.959), and RPS24 (AUC = 0.881; 95% CI: 0.778–0.963).", "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:39452046"], "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:GSE166502"], "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:GSE166502"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39452046", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/brainsci14101035", "sha256": 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METHODS: RNA sequencing data of MCI and normal cognition groups, as", "ses, was used to verify the genes. Moreover, RNA sequencing and clinical characteristic data for GSE1665"], "order_basis": "paper_text_order:344", "id": "assay:1"}, {"role": "analysis", "definition_id": "diagnostic_evaluation", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The Student’s t-test was used to analyze the differences in MCI eigengenes between the type 2 diabetes and control group samples; p < 0.05 was considered statistically significant. A ROC curve was constructed to evaluate the ability of the differentially expressed genes to predict the occurrence of type 2 diabetes."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}