Evidence map›Paper›PMID 31184315›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2019

Association of Key Genes and Pathways with Atopic Dermatitis by Bioinformatics Analysis.

Jie Zhu, Zheng Wang, Fengzhe Chen

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

12 citing papers in PubMed.

  1. Article
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  7. Article
  8. Type 2 Inflammation Contributes to Skin Barrier Dysfunction in Atopic Dermatitis.JID innovations : skin science from molecules to population health · 2022
    Review
  9. Article
  10. Review
  11. Article
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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

3 authors.

Jie ZhuDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Jinan, Shandong, China (mainland).
Zheng WangDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Jinan, Shandong, China (mainland).
Fengzhe ChenDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Jinan, Shandong, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Atopic dermatitis is a chronic inflammatory disease of the skin. It has a high prevalence worldwide and affected persons are prone to recurrent attacks, seriously affecting the physical and mental of patients. The exact etiology of the disease is still unclear. MATERIAL AND METHODS There are 7 datasets on atopic dermatitis in the Gene Expression Omnibus database, including 142 lesional and 134 non-lesional skin biopsy samples. Differential analysis was performed after datasets were integrated by robust multi-array average method. Functional modules of GSE99802 were explored by weighted gene co-expression network analysis. The 4 most important modules were enriched into the pathways by Metascape. RESULTS Significantly differentially expressed genes included 41 upregulated and 10 downregulated genes. The following 5 of the most important upregulated genes had the strongest association with atopic dermatitis. SERPINB3&4 promote inflammation and impaired skin barrier function in the early stage of atopic dermatitis. S100A9 aggravates the inflammatory response by inducing the activation of toll-like receptor 4, neutrophil chemotaxis, neutrophilic inflammation, and the amplification of interleukin-8. MMP1 is the key protease of skin collagen degradation, keeping the extracellular matrix in dynamic balance. MMP12 induces the aggregation of various inflammatory cells into inflammatory tissue. The enriched pathways of each module mainly include Cellular responses to external stimuli, Metabolism of RNA and Translation, and Infectious disease. CONCLUSIONS The associated pathways and genes not only help us understand the molecular mechanism of the disease, but also provide research directions or targets for accurate diagnosis and treatment.

Indexed as

Cluster AnalysisComputational BiologyDatabases, GeneticDermatitis, AtopicGene ExpressionGene Expression ProfilingGenetic Association StudiesHumansOligonucleotide Array Sequence AnalysisSkin

Identifiers

PMID31184315
PMCPMC6582687

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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.