Differential Expression of mRNAs in the Brain Tissues of Patients with Alzheimer's Disease Based on GEO Expression Profile and Its Clinical Significance.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30918899", "kind": "science-record", "revision": 6, "content_hash": "sha256:710ba6ff6f0f050df343fcdbe7d448862930be0b28912d7ccb172cbc18f83539", "created_at": "2026-11-01T15:40:43Z", "updated_at": "2026-11-01T22:43:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Differential Expression of mRNAs in the Brain Tissues of Patients with Alzheimer's Disease Based on GEO Expression Profile and Its Clinical Significance.", "doi": "10.1155/2019/8179145", "pmid": "30918899", "authors": ["Guowei Ma", "Mingyan Liu", "Ke Du", "Xin Zhong", "Shiqiang Gong", "Linchi Jiao", "Minjie Wei"], "journal": "BioMed research international", "year": 2019, "abstract": "BACKGROUND: Early diagnosis of Alzheimer's disease (AD) is an urgent point for AD prevention and treatment. The biomarkers of AD still remain indefinite. Based on the bioinformatics analysis of mRNA differential expressions in the brain tissues and the peripheral blood samples of Alzheimer's disease (AD) patients, we investigated the target mRNAs that could be used as an AD biomarker and developed a new effective, practical clinical examination program.\nMETHODS: We compared the AD peripheral blood mononuclear cells (PBMCs) expression dataset (GEO accession GSE4226 and GSE18309) with AD brain tissue expression datasets (GEO accessions GSE1297 and GSE5281) from GEO in the present study. The GEO gene database was used to download the appropriate gene expression profiles to analyze the differential mRNA expressions between brain tissue and blood of AD patients and normal elderly. The Venn diagram was used to screen out the differential expression of mRNAs between the brain tissue and blood. The protein-protein interaction network map (PPI) was used to view the correlation between the possible genes. GO (gene ontology) and KEGG (Kyoto Gene and Genomic Encyclopedia) were used for gene enrichment analysis to determine the major affected genes and the function or pathway.\nRESULTS: Bioinformatics analysis revealed that there were differentially expressed genes in peripheral blood and hippocampus of AD patients. There were 4958 differential mRNAs in GSE18309, 577 differential mRNAs in GSE4226 in AD PBMCs sample, 7464 differential mRNAs in GSE5281, and 317 differential mRNAs in GSE129 in AD brain tissues, when comparing between AD patients and healthy elderly. Two mRNAs of RAB7A and ITGB1 coexpressed in hippocampus and peripheral blood were screened. Furthermore, functions of differential genes were enriched by the PPI network map, GO, and KEGG analysis, and finally the chemotaxis, adhesion, and inflammatory reactions were found out, respectively.\nCONCLUSIONS: ITGB1 and RAB7A mRNA expressions were both changed in hippocampus and PBMCs, highly suggested being used as an AD biomarker with AD. Also, according to the results of this analysis, it is indicated that we can test the blood routine of the elderly for 2-3 years at a frequency of 6 months or one year. When a patient continuously detects the inflammatory manifestations, it is indicated as a potentially high-risk AD patient for AD prevention.", "claims": [{"id": "claim-method", "statement": "Difference analysis was performed by GEO2R analysis with P < 0.05 and |logFC| > 1 as cutoff values for screening differentially expressed genes (DEGs).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30918899", "locator": "sections[5] \"2.3. Difference Analysis\" paragraph 2", "quote": "Difference analysis was performed by GEO2R analysis with P < 0.05 and |logFC| > 1 as cutoff values for screening differentially expressed genes (DEGs)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30918899", "locator": "sections[11] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are available from the corresponding author upon request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:30918899"], "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:GSE1297"], "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:GSE1297"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30918899", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2019/8179145", "sha256": 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"asset:table:pmid:30918899:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:90e36c7c6b519459d74ccca3687bdc2a044f69fb218e6675d002aa50fc0fc0a9", "bytes": 2340, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[1]/table-wrap[1]#tab1", "version": null, "note": "Current mainstream detection methods of AD.", "structure": {"pmcid": "PMC6413412", "section_index": 1, "section_title": "1. Introduction", "row_count": 10, "column_count": 4}, "table": {"label": "Table 1", "caption": "Current mainstream detection methods of AD.", "rows": [["Detection method", "Principle", "Advantage", "Disadvantage"], ["MMSE", "The most common scale of intelligence impairment at present. Illiteracy ≤ 17 points, primary school degree ≤ 20 points, middle school degree ≤ 22 points, college degree ≤ 23 points, indicates the impairment of cognitive function.", "Low cost, concise content, less time for measurement, and easy to be accepted by the elderly", "Only screening the patients with moderate-to-severe symptoms"], [""], ["Structural imaging: head CT (thin scan) and MRI (coronal) scanning", "Diagnostic imaging techniques show significant atrophy of the cerebral cortex, especially in the hippocampus and medial temporal lobe, supporting the clinical diagnosis of AD.", "Used to exclude other underlying diseases and to identify specific imaging findings of AD", "Convenience not as good as MMSE, expensive cost, hospital equipment support, low penetration rate"], [""], ["18FDG-PET", "It shows the reduction of glucose metabolism in the dome and upper/posterior temporal region, posterior cingulate cortex, and anterior cranial lobe, revealing specific abnormal changes in AD. In the late period of AD, the frontal lobe metabolism was reduced.", "Improving the reliability of dementia diagnosis and being suitable for the differential diagnosis of AD and other dementia", "Convenience not as good as MMSE, expensive cost, specific equipment support needed, penetration rate"], [""], ["EEG", "The EEG of AD is characterized by a decrease in alpha wave, an increase in theta wave, and a decrease in the average frequency.", "Used for the differential diagnosis of AD, providing early evidence of prion disease or other brain diseases", "33% of patients with early AD are normal without change in EEG and low penetration rate"], [""], ["Biological markers", "Dynamically observing the progression of the disease by using proteins or miRNAs in body fluids such as peripheral blood, cerebrospinal fluid, and urine biology as markers to increase the specificity of the diagnosis.", "Noninvasive, simple and inexpensive, and of low price", "Low repeatability, problems with accuracy and specificity, lack of standards"]], "row_count": 10, "column_count": 4, "numeric_cells": 3, "header_rows": 1, "locator": "section[1]/table-wrap[1]#tab1"}}, {"id": "asset:table:pmid:30918899:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:d728d7fa07f5ad1171d3f97ffef02ba41a53e90666770e98708b323ae393b432", "bytes": 611, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[6]/table-wrap[1]#tab2", "version": null, "note": "GEO microarray datasets.", "structure": {"pmcid": "PMC6413412", "section_index": 6, "section_title": "3. Results", "row_count": 8, "column_count": 5}, "table": {"label": "Table 2", "caption": "GEO microarray datasets.", "rows": [["Chip serial number", "Elderly sample", "AD sample", "Resource", "Platform"], ["GSE1297", "9", "22", "Hippocampus", "GPL1211 NIA MGC, Mammalian Genome Collection"], [""], ["GSE5281", "13", "10", "Hippocampus", "GPL1211 NIA MGC, Mammalian Genome Collection"], [""], ["GSE18309", "3", "6", "PBMCs", "GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array"], [""], ["GSE4226", "14", "14", "PBMCs", "GPL96 [HG-U133A] Affymetrix Human Genome U133A Array"]], "row_count": 8, "column_count": 5, "numeric_cells": 16, "header_rows": 1, "locator": "section[6]/table-wrap[1]#tab2"}}, {"id": "asset:table:pmid:30918899:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:7df060693a77bb630ce93f426b14c73f6f004cdc21d77dcd56a9aa8b1f90622f", "bytes": 2111, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[6]/table-wrap[2]#tab3", "version": null, "note": "TOP lowest term P value corrected with Bonferroni step-down of RAB7A and ITGB1.", "structure": {"pmcid": "PMC6413412", "section_index": 6, "section_title": "3. Results", "row_count": 24, "column_count": 7}, "table": {"label": "Table 3", "caption": "TOP lowest term P value corrected with Bonferroni step-down of RAB7A and ITGB1.", "rows": [["CHIP", "GOID", "GO Term", "Number of Genes", "Associated genes (%)", "Term P value", "Term P value corrected with Bonferroni step-down"], ["GSE4226", "GO:0044403", "Symbiosis, encompassing mutualism through parasitism", "113", "10.53122", "5.98E-33", "1.23E-30"], ["GO:0016032", "Viral process", "109", "10.62378", "4.57E-32", "9.32E-30"], ["GO:0019058", "Viral life cycle", "74", "15.16394", "1.85E-31", "3.76E-29"], ["GO:0009056", "Catabolic process", "146", "5.968929", "4.54E-17", "8.63E-15"], ["GO:0034613", "Cellular protein localization", "121", "6.547619", "6.10E-17", "1.15E-14"], [""], ["GSE18309", "GO:0006955", "Immune response", "314", "14.47672", "1.25E-08", "8.10E-06"], ["GO:0040011", "Locomotion", "443", "24.7072", "8.99E-11", "6.07E-08"], ["GO:0032879", "Regulation of localization", "601", "22.68781", "8.00E-08", "5.08E-05"], ["GO:0045321", "Leukocyte activation", "178", "13.69231", "3.53E-07", "2.20E-04"], ["GO:0023052", "Signaling", "1386", "20.76716", "4.25E-07", "2.64E-04"], [""], ["GSE1297", "GO:0044699", "Single-organism process", "248", "1.814856", "1.08E-07", "1.16E-05"], ["GO:0044763", "Single-organism cellular process", "213", "1.933551", "1.77E-07", "1.86E-05"], ["GO:0048522", "Positive regulation of cellular process", "117", "2.322811", "7.89E-07", "8.13E-05"], ["GO:0048518", "Positive regulation of biological process", "125", "2.214349", "3.47E-06", "3.51E-04"], ["GO:0007154", "Cell communication", "139", "2.078039", "2.60E-05", "0.002369"], [""], ["GSE5281", "GO:0010604", "Positive regulation of macromolecule metabolic process", "1215", "39.69291", "4.13E-28", "4.28E-25"], ["GO:0009893", "Positive regulation of metabolic process", "1299", "39.23286", "8.40E-28", "8.72E-25"], ["GO:0006996", "Organelle organization", "1460", "38.04065", "1.36E-24", "1.40E-21"], ["GO:0048523", "Negative regulation of cellular process", "1681", "36.92882", "6.16E-22", "6.32E-19"], ["GO:0009966", "Regulation of signal transduction", "1131", "38.67989", "3.85E-21", "3.94E-18"]], "row_count": 24, "column_count": 7, "numeric_cells": 104, "header_rows": 1, "locator": "section[6]/table-wrap[2]#tab3"}}], "gaps": ["asset:data:geo:GSE1297 not downloaded", "asset:data:geo:GSE1297 licence not read", "asset:data:geo:GSE18309 not downloaded", "asset:data:geo:GSE18309 licence not read", "asset:data:geo:GSE4226 not downloaded", "asset:data:geo:GSE4226 licence not read", "asset:data:geo:GSE5281 not downloaded", "asset:data:geo:GSE5281 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Difference analysis was performed by GEO2R analysis with P < 0.05 and |logFC| > 1 as cutoff values for screening differentially expressed genes (DEGs)."}}, {"id": "method-2", "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"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE4226", "GSE18309", "GSE1297", "GSE5281"], "resolved_accessions": ["GSE4226", "GSE18309", "GSE1297", "GSE5281"], "statements": ["The data used to support the findings of this study are available from the corresponding author upon request."], "basis": "The paper names GSE4226, GSE18309, GSE1297, GSE5281 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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