Bioinformatics analysis of the potential receptor and therapeutic drugs for Alzheimer's disease with comorbid Parkinson's disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38894850", "kind": "science-record", "revision": 3, "content_hash": "sha256:1f2407ca3caa22749850349e09279b4a10c434ac4572f6c7ca567039d4a219cc", "created_at": "2026-11-01T20:28:58Z", "updated_at": "2026-11-01T22:12:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis of the potential receptor and therapeutic drugs for Alzheimer's disease with comorbid Parkinson's disease.", "doi": "10.3389/fnagi.2024.1411320", "pmid": "38894850", "authors": ["Xuerong Zhou", "Zhifan Liu", "Guiqin Bai", "Bai Dazhang", "Peilin Zhao", "Xiaoming Wang", "Guohui Jiang"], "journal": "Frontiers in aging neuroscience", "year": 2024, "abstract": "Background: Now, there are no sensitive biomarkers for improving Alzheimer's disease (AD) and comorbid Parkinson's disease (PD). The aim of the present study was to analyze differentially expressed genes (DEGs) in brain tissue from AD and PD patients via bioinformatics analysis, as well as to explore precise diagnostic and therapeutic targets for AD and comorbid PD.\nMethods: GFE122063 and GSE7621 data sets from GEO in NCBI, were used to screen differentially expressed genes (DEGs) for AD and PD, and identify the intersected genes, respectively. Intersected genes were analyzed by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, STRING site and Cytoscape were used to construct a protein-protein interaction (PPI) network, CytoNCA algorithm to analyze and evaluate centrality, Mcode plug-in to analyze module, and Cytohubba to screen key genes. Combined GO-KEGG enrichment analysis with Cytoscape algorithm to screen the key gene in AD complicated with PD. Then, the DEGs for AD and PD were imported into the Association Map (CMap) online platform to screen out the top 10 small molecule drugs, and using molecular docking techniques to evaluate the interactions between small molecule drugs and key genes receptors.\nResults: In total, 231 upregulated genes and 300 downregulated genes were identified. GO analysis revealed that the DEGs were highly enriched in signal transduction, and KEGG analysis revealed that the DEGs were associated with the MAPK and PI3K-Akt signaling pathways. Epidermal growth factor receptor (EGFR) was identified as a potential receptor gene in AD and comorbid PD. EGFR was upregulated in both AD and PD, and the proteins that interact with EGFR were enriched in the Ras/Raf/MAPK and PI3K/Akt signaling pathways. Semagacestat was identified as a drug with therapeutic potential for treating AD complicated with PD. There was a high binding affinity between semagacestat and EGFRNTD, with seven hydrogen bonds and one hydrophobic bond.\nDiscussion: Semagacestat may improve the health of patients with AD complicated with PD through the regulation of the Ras/Raf/MAPK and PI3K/Akt signaling pathways by EGFR, providing evidence supporting the structural modification of semagacestat to develop a more effective drug for treating AD complicated with PD.", "claims": [{"id": "claim-method", "statement": "The differences in gene expression profiles between AD patient and PD patient samples were analyzed using the GEO2R online platform (http://ncbi.nlm.nih.gov/geo/geo2r).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38894850", "locator": "sections[4] \"Data sources, quality and variance analysis\" paragraph 2", "quote": "The differences in gene expression profiles between AD patient and PD patient samples were analyzed using the GEO2R online platform (http://ncbi.nlm.nih.gov/geo/geo2r)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data may be found in the GSE122063 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE122063) and GSE7621 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7621) datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38894850", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data may be found in the GSE122063 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE122063) and GSE7621 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7621) datasets."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In total, 231 upregulated genes and 300 downregulated genes were identified.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38894850", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "GFE122063 and GSE7621 data sets from GEO in NCBI, were used to screen differentially expressed genes (DEGs) for AD and PD, and identify the intersected genes, respectively."}, {"asset": "source:pmid:38894850", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "In total, 231 upregulated genes and 300 downregulated genes were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In total, 231 upregulated genes and 300 downregulated genes were identified.", "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:38894850"], "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:GSE122063"], "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:GSE122063"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38894850", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fnagi.2024.1411320", "sha256": "sha256:a7947b5e148303b5eaff6c65ee49598c7fc0bce2f46e2d64aae4c34389f89710", "bytes": 31450, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fnagi.2024.1411320", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11185263", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE122063", "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=GSE122063", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE122063", "version": null, "note": "Publicly available datasets were analyzed in this study. 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