Identification of key genes and signaling pathways associated with dementia with Lewy bodies and Parkinson's disease dementia using bioinformatics.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36970514", "kind": "science-record", "revision": 3, "content_hash": "sha256:49ccf3ea3af6a6ec35c01d233aceeff302fec1e69c588fad127991f18c741354", "created_at": "2026-11-01T19:01:37Z", "updated_at": "2026-11-01T22:09:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes and signaling pathways associated with dementia with Lewy bodies and Parkinson's disease dementia using bioinformatics.", "doi": "10.3389/fneur.2023.1029370", "pmid": "36970514", "authors": ["Jing Xu", "Jia Li", "Ya-Juan Sun", "Wei Quan", "Li Liu", "Qing-Hui Zhang", "Yi-Dan Qin", "Xiao-Chen Pei", "Hang Su", "Jia-Jun Chen"], "journal": "Frontiers in neurology", "year": 2023, "abstract": "Objective: Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are collectively known as Lewy body dementia (LBD). Considering the heterogeneous nature of LBD and the different constellations of symptoms with which patients can present, the exact molecular mechanism underlying the differences between these two isoforms is still unknown. Therefore, this study aimed to explore the biomarkers and potential mechanisms that distinguish between PDD and DLB.\nMethods: The mRNA expression profile dataset of GSE150696 was acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between 12 DLB and 12 PDD were identified from Brodmann area 9 of human postmortem brains using GEO2R. A series of bioinformatics methods were applied to identify the potential signaling pathways involved, and a protein-protein interaction (PPI) network was constructed. Weighted gene co-expression network analysis (WGCNA) was used to further investigate the relationship between gene co-expression and different LBD subtypes. Hub genes that are strongly associated with PDD and DLB were obtained from the intersection of DEGs and selected modules by WGCNA.\nResults: A total of 1,864 DEGs between PDD and DLB were filtered by the online analysis tool GEO2R. We found that the most significant GO- and KEGG-enriched terms are involved in the establishment of the vesicle localization and pathways of neurodegeneration-multiple diseases. Glycerolipid metabolism and viral myocarditis were enriched in the PDD group. A B-cell receptor signaling pathway and one carbon pool by folate correlated with DLB in the results obtained from the GSEA. We found several clusters of co-expressed genes which we designated by colors in our WGCNA analysis. Furthermore, we identified seven upregulated genes, namely, SNAP25, GRIN2A, GABRG2, GABRA1, GRIA1, SLC17A6, and SYN1, which are significantly correlated with PDD.\nConclusion: The seven hub genes and the signaling pathways we identified may be involved in the heterogeneous pathogenesis of PDD and DLB.", "claims": [{"id": "claim-method", "statement": "The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect differentially expressed genes (DEGs) between PDD and DLB samples, and the P-value and |log (FC)| (FC-fold change) were calculated.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36970514", "locator": "sections[4] \"2.2. Data processing of differentially expressed genes\" paragraph 2", "quote": "The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect differentially expressed genes (DEGs) between PDD and DLB samples, and the P-value and |log (FC)| (FC-fold change) were calculated."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36970514", "locator": "sections[19] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Furthermore, we identified seven upregulated genes, namely, SNAP25, GRIN2A, GABRG2, GABRA1, GRIA1, SLC17A6, and SYN1, which are significantly correlated with PDD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36970514", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Furthermore, we identified seven upregulated genes, namely, SNAP25, GRIN2A, GABRG2, GABRA1, GRIA1, SLC17A6, and SYN1, which are significantly correlated with PDD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Furthermore, we identified seven upregulated genes, namely, SNAP25, GRIN2A, GABRG2, GABRA1, GRIA1, SLC17A6, and SYN1, which are significantly correlated with PDD.", "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:36970514"], "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:GSE150696"], "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:GSE150696"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36970514", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fneur.2023.1029370", "sha256": "sha256:864ab36efd90e3d7821adb210546601bb687ef4d34be4316291d6477f938df8f", "bytes": 49655, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fneur.2023.1029370", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10034123", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE150696", "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=GSE150696", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE150696", "version": null, "note": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4556850", "GSM4556851", "GSM4556852", "GSM4556853", "GSM4556854", "GSM4556855", "GSM4556856", "GSM4556857", "GSM4556858", "GSM4556859", "GSM4556860", "GSM4556861", "GSM4556862", "GSM4556863", "GSM4556864", "GSM4556865", "GSM4556866", "GSM4556867", "GSM4556868", "GSM4556869", "GSM4556870", "GSM4556872", "GSM4556875", "GSM4556876", "GSM4556877", "GSM4556878", "GSM4556879", "GSM4556880", "GSM4556881", "GSM4556882", "GSM4556883", "GSM4556884", "GSM4556885", "GSM4556886", "GSM4556887", "GSM4556888", "GSM4556889", "GSM4556890", "GSM4556891", "GSM4556892", "GSM4556893", "GSM4556894"], "sample_count": 42, "group_sizes": null, "group_sizes_basis": null, "platform": "17585", "taxon": "Homo sapiens", "title": "Transcriptome profiling of prefrontal cortex (BA9) in neurodegenerative dementia using Affymetrix Human Transcriptome Array 2.0", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE150696 not downloaded", "asset:data:geo:GSE150696 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-2", "family": null, "specific": null, "label": "GEO2R differential expression analysis", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect differentially expressed genes (DEGs) between PDD and DLB samples, and the P-value and |log (FC)| (FC-fold change) were calculated."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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