Evidence map›Paper›PMID 33883925›Full record

ArticlePharmacogenomics and personalized medicine2021

Assessment of Weighted Gene Co-Expression Network Analysis to Explore Key Pathways and Novel Biomarkers in Muscular Dystrophy.

Xiaoxue Xu, Yuehan Hao, Jiao Wu, Jing Zhao, Shuang Xiong

Open access · goldAbstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

8 citing papers in PubMed, 13 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

5 authors at 3 institutions in 1 country.

Xiaoxue XuDepartment of Neurology, The First Hospital of China Medical University, Shenyang, People's Republic of China.
Yuehan HaoDepartment of Neurology, The First Hospital of China Medical University, Shenyang, People's Republic of China.
Jiao WuDepartment of Neurology, The People's Hospital of Liaoning Province, Shenyang, People's Republic of China.
Jing ZhaoDepartment of Neurology, The First Hospital of China Medical University, Shenyang, People's Republic of China.
Shuang XiongLiaoning Academy of Analytic Science, Construction Engineering Center of Important Technology Innovation and Research and Development Base in Liaoning Province, Shenyang, People's Republic of China.
First Hospital of China Medical University · CNChina Medical University · CNLiaoning Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to explore the key molecular pathways involved in Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) and thereby identify hub genes to be potentially used as novel biomarkers using a bioinformatics approach.

methodsRaw GSE109178 data were collected from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted on the top 50% of altered genes. The key modules associated with the clinical features of DMD and BMD were identified. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID website. A protein-protein interaction (PPI) network was constructed using the STRING website. MCODE, together with the Cytohubba plug-ins of Cytoscape, screened out the potential hub genes, which were subsequently verified via receiver operating characteristic (ROC) curves in other datasets.

resultsAmong the 11 modules obtained, the black module was predominantly associated with pathology and DMD, whereas the light-green module was primarily related to age and BMD. Functional enrichment assessments indicated that the genes in the black module were primarily clustered in "immune response" and "phagosome," whereas the ones in the light-green module were chiefly enriched in "protein polyubiquitination". Eleven essential genes were eventually identified, including

conclusionOverall, our findings may be useful for investigating the mechanisms underlying DMD and BMD. In addition, the hub genes discovered might serve as novel molecular markers correlated with dystrophinopathies.

Indexed as

Becker muscular dystrophybiomarkerDuchenne muscular dystrophypathwayWGCNA

Identifiers

PMID33883925
PMCPMC8053709
OpenAlexW3155600430

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.