Evidence map›Paper›PMID 31989994›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

Related Network and Differential Expression Analyses Identify Nuclear Genes and Pathways in the Hippocampus of Alzheimer Disease.

Xuemei Quan, Huo Liang, Ya Chen, Qixiong Qin, Yunfei Wei, Zhijian Liang

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Xuemei QuanDepartment of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
Huo LiangDepartment of Rehabilitation, Guangxi International Zhuang Medicine Hospital, Nanning, Guangxi, China (mainland).
Ya ChenDepartment of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
Qixiong QinDepartment of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
Yunfei WeiDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
Zhijian LiangDepartment of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland).
Guangxi Medical University · CNFirst Affiliated Hospital of GuangXi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Alzheimer disease (AD) is a typical progressive and destructive neurodegenerative disease that has been studied extensively. However, genetic features and molecular mechanisms underlying AD remain unclear. Here we used bioinformatics to investigate the candidate nuclear genes involved in the molecular mechanisms of AD. MATERIAL AND METHODS First, we used Gene Expression Omnibus (GEO) database to obtain the expression profiles of the mRNAs from hippocampus microarray and identify differentially expressed genes (DEGs) the plier algorithm. Second, functional annotation and visualization of the DEGs were conducted by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, BioGRID, IntAct, STRING, and Cytoscape were utilized to construct a protein-protein interaction (PPI) network. Hub genes were analytically obtained from the PPI network and the microRNA (miRNA)-target network. RESULTS Two hippocampus microarrays (GSE5281 and GSE48350) were obtained from the GEO database, comprising 161 and 253 cases separately. Among these, 118 upregulated genes and 694 downregulated genes were identified. The upregulated DEGs were mainly involved in positive regulation of transcription from RNA polymerase II promoter, positive regulation of cartilage development, and response to wounding. The downregulated DEGs were enriched in chemical synaptic transmission, neurotransmitter secretion, and learning. By combining the results of PPI and miRNA-target network, 8 genes and 2 hub miRNAs were identified, including YWHAZ, DLG4, AGAP2, EGFR, TGFBR3, PSD3, RDX, BRWD1, and hsa-miR-106b-5p and hsa-miR-93-5p. These target genes are highly enriched in various key pathways, such as amyloid-beta formation, regulation of cardiocyte differentiation, and actin cytoskeleton reorganization. CONCLUSIONS In this study, YWHAZ, DLG4, AGAP2, EGFR, TGFBR3, PSD3, RDX, and BRWD1 were identified as candidate genes for future molecular studies in AD, which is expected to improve our understanding of its cause and potential molecular mechanisms. Nuclear genes, DEGs, and related networks identified by integrated bioinformatics analysis may serve as diagnostic and therapeutic targets for AD.

Indexed as

Gene Expression ProfilingGene Expression RegulationGene Regulatory NetworksAlzheimer DiseaseCell NucleusCluster AnalysisGene OntologyHippocampusHumansMicroRNAsNeurotransmitter AgentsProtein Interaction MapsSignal TransductionMicroRNAsNeurotransmitter Agents

Identifiers

PMID31989994
PMCPMC7001513
OpenAlexW2999374981

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.