Evidence map›Paper›PMID 36118895›Full record

ArticleFrontiers in genetics2022

Identification of potential key genes for immune infiltration in childhood asthma by data mining and biological validation.

Zhili Wang, Yu He, Yupeng Cun, Qinyuan Li, Yan Zhao, Zhengxiu Luo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

4 citing papers in PubMed, 3 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.

Zhili WangMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Yu HeMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Yupeng CunMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Qinyuan LiMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Yan ZhaoMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Zhengxiu LuoDepartment of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNChildren's Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asthma is the most common chronic condition among children; however, the underlying molecular mechanism remains unclear. Dysregulated immune response and different infiltration states of immune cells are critical for asthma pathogenesis. Here, three childhood asthma gene expression datasets were used to detect key genes, immune cells, and pathways involved in childhood asthma. From these datasets, 33 common differentially expressed genes (DEGs) were identified, which showed enrichment in the T helper 1 (Th1) and T helper 2 (Th2) cell differentiation pathway and the T helper 17 (Th17) cell differentiation pathway. Using the weighted gene co-expression network analysis (WGCNA), CD3D and CD3G were identified as key genes closely correlated with childhood asthma. Upregulation of CD3D and CD3G was further validated in bronchoalveolar lavage cells from childhood asthmatics with control individuals by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The immune cell infiltration analysis indicated that CD3D and CD3G were negatively correlated with increased resting mast cells and eosinophils, and highly correlated with several cell markers of Th1, Th2, and Th17 cells. In addition, we found that CD3D and CD3G were closely related to the Th1 and Th2 cell differentiation pathway and the Th17 cell differentiation pathway. Our results reveal the important roles of two key genes and immune infiltration in the pathogenesis of childhood asthma. Thus, this study provides a new perspective for exploring potential molecular targets for childhood asthma treatment.

Indexed as

asthmachildhooddata miningimmune infiltrationmicroarayRNA-seq

Identifiers

PMID36118895
PMCPMC9479007
OpenAlexW4294218904

What OpenQuestion holds

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LicenceCC BY
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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.