Evidence map›Paper›PMID 31984950›Full record

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

Microarray Analysis of Differential Gene Expression in Alzheimer's Disease Identifies Potential Biomarkers with Diagnostic Value.

Liping Liu, Qin Wu, Weiwei Zhong, Yuping Chen, Wenying Zhang, Huiling Ren, Ling Sun, Jihu Sun

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 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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  19. The TRiCky Business of Protein Folding in Health and Disease.Frontiers in cell and developmental biology · 2022
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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

8 authors at 1 institution in 1 country.

Liping LiuPharmaceutical College, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Qin WuMedical Technology College, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Weiwei ZhongSchool of public foundation, Jiangsu Vocational College of Medicine, Yancheng, China (mainland).
Yuping ChenSchool of Basic Medicine, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Wenying ZhangInstitute of Biotechnology, Jiangsu Vocational College of Medicine, Yancheng, China (mainland).
Huiling RenPharmaceutical College, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Ling SunPharmaceutical College, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Jihu SunDepartment of Science and Technology, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China (mainland).
Jiangsu Vocational College of Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Alzheimer disease (AD) is a common and fatal subtype of dementia that remains a challenge to diagnose and treat. This study aimed to identify potential biomarkers that influence the prognosis of AD. MATERIAL AND METHODS A total of 6 gene expression profiles from the Gene Expression Omnibus (GEO) database were assessed for their potential as AD biomarkers. We identified differentially expressed genes (DEGs) using the prediction analysis for microarray (PAM) algorithm and obtained hub genes through the analysis of the protein-protein interaction (PPI) network and module analysis. RESULTS We identified 6 gene expression profiles from the GEO database and assessed their potential as AD biomarkers. Shared gene sets were extracted and integrated into large expression profile matrices. We identified 2514 DEGs including 68 upregulated- and 2446 downregulated genes through analysis of the limma package. We screened 379 significant DEGs including 68 upregulated and 307 downregulated genes for their ability to distinguish AD from control samples using PAM algorithm. Functional enrichment of the 379 target genes was produced from Database for Annotation, Visualization and Integrated Discovery.(DAVID) and included histone function, beta receptor signaling, cell growth, and angiogenesis. The downregulated genes were significantly enriched in MAPK signaling, synaptic signaling, neuronal apoptosis and AD associated pathways. Upon analysis of the PPI network, 32 hub genes including ENO2, CCT2, CALM2, ACACB, ATP5B, MDH1, and PP2CA were screened. Of these hub genes, NFKBIA and ACACB were upregulated and 29 genes were downregulated in AD patients. CONCLUSIONS We screened 379 significant DEGs as potential biomarkers of AD using PAM and obtained 32 hub genes through PPI network and module analysis. These findings reveal new potential AD biomarkers with prognostic and therapeutic value.

Indexed as

Gene Expression ProfilingGene Expression RegulationMicroarray AnalysisAgedAlgorithmsAlzheimer DiseaseBiomarkersDatabases, GeneticDown-RegulationFemaleGene Regulatory NetworksHumansMaleMolecular Sequence AnnotationProtein Interaction MapsReproducibility of ResultsBiomarkersTranscription Factors

Identifiers

PMID31984950
PMCPMC7001516
OpenAlexW3000732473

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.