Evidence map›Paper›PMID 36915798›Full record

ArticleAmerican journal of translational research2023

Comprehensive analysis of immune-related genes for classification and immune microenvironment of asthma.

Bin Feng, Tong Zhou, Zhiyi Guo, Jieyu Jin, Sheng Zhang, Jun Qiu, Jun Cao, Jia Li, Xia Peng, Juan Wang and 4 more

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 10 citations in OpenAlex.

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  5. Identification of immune infiltration-related ZNF480 for predicting prognosis in breast cancer.American journal of clinical and experimental immunology · 2025
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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

14 authors at 5 institutions in 2 countries.

Bin FengCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Tong ZhouMedical College of Soochow University Suzhou 215006, Jiangsu, China.
Zhiyi GuoMedical College of Soochow University Suzhou 215006, Jiangsu, China.
Jieyu JinCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Sheng ZhangCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Jun QiuCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Jun CaoCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Jia LiDepartment of Laboratory Medicine, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine Shanghai 201209, China.
Xia PengDepartment of Laboratory Medicine, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine Shanghai 201209, China.
Juan WangDepartment of Laboratory Medicine, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine Shanghai 201209, China.
Yanru XingBasecare Medical Device Co., Ltd. Suzhou 215006, China.
Renxin JiThe School of International Medical Technology of Shanghai Sanda University Shanghai 201209, China.
Longwei QiaoCenter for Reproduction and Genetics, School of Gusu, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University Suzhou 215006, Jiangsu, China.
Yuting LiangCenter for Clinical Laboratory, The First Affiliated Hospital of Soochow University Suzhou 215006, Jiangsu, China.
Soochow University · CNShanghai Jiao Tong University · CNSanda University · CNSuzhou Municipal Hospital · CNThe Medical Device (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the effects of immune-related genes (IRGs) and immune landscape of induced sputum, and develop novel, non-invasive diagnostic molecular therapeutic targets for asthma.

methodsGSE76262 datasets were used to identify differentially expressed IRGs in asthma. Key IRGs were detected using a protein-protein interaction network. Receiver operating characteristic (ROC) curves were analyzed to investigate the diagnostic value of key IRGs. Gene set enrichment analysis (GSEA) was performed with WebGestalt. Single-sample gene set enrichment analysis and CIBERSORT were used to investigate the immune landscape of induced sputum.

resultsA total of 75 potential IRGs were associated with asthma, most of which were involved in the NF-kappa B signaling pathway. ROC analysis showed AUC values for the hub pathway ranging from 0.676-0.767, with moderate diagnostic value for asthma. We also identified IRGs-related cytokines (TNF-α, IL-1β, IL-8 and IL-6) in 76 asthma and 91 control serum samples to further explore diagnostic efficacy, showing a cumulative AUC of 0.998 for these four related cytokines. Analysis of immune cell infiltration levels showed that follicular helper T cells, activated dendritic cells, activated mast cells and eosinophils were significantly higher and macrophages M0 and macrophages M2 were significantly reduced in sputum from patients with asthma.

conclusionsIRGs-related cytokines and immune infiltration may contribute to the diagnosis and immune classification of asthma.

Indexed as

asthmabioinformaticsImmune-related genesinduced sputum

Identifiers

PMID36915798
PMCPMC10006808
OpenAlexW4324128778

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