Evidence map›Paper›PMID 34367470›Full record

ArticleOxidative medicine and cellular longevity2021

Integrated Analysis of Weighted Gene Coexpression Network Analysis Identifying Six Genes as Novel Biomarkers for Alzheimer's Disease.

Tingting Zhang, Nanyang Liu, Wei Wei, Zhen Zhang, Hao Li

Abstract read
In one paragraph

Article in Oxidative medicine and cellular longevity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Tingting ZhangCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.ORCID https://orcid.org/0000-0001-9141-2593
Nanyang LiuDepartment of Geratology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.
Wei WeiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Zhen ZhangDepartment of Geratology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.
Hao LiDepartment of Geratology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.ORCID https://orcid.org/0000-0001-8502-2556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is a chronic progressive neurodegenerative disease; however, there are no comprehensive therapeutic interventions. Therefore, this study is aimed at identifying novel molecular targets that may improve the diagnosis and treatment of patients with AD.

methodsIn our study, GSE5281 microarray dataset from the GEO database was collected and screened for differential expression analysis. Genes with a

resultsIn total, 4674 DEGs were identified. Nine distinct coexpression modules were identified via WGCNA; among these modules, the blue module showed the highest positive correlation with AD (

conclusionsUsing the WGCNA and LASSO models, our findings provide a better understanding of the role of biomarkers

Indexed as

Gene Expression ProfilingGene Regulatory NetworksProtein Interaction MapsAlzheimer DiseaseBiomarkersCase-Control StudiesHumansMicroarray AnalysisPrognosisROC CurveBiomarkers

Identifiers

PMID34367470
PMCPMC8339876

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