Evidence map›Paper›PMID 35962894›Full record

ArticleEndocrine2022

Identification of two potential immune-related biomarkers of Graves' disease based on integrated bioinformatics analyses.

Yihan Zhang, Jia Wei, Hong Zhou, Bingxin Li, Ying Chen, Feng Qian, Jingting Liu, Xin Xie, Huanbai Xu

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In one paragraph

Article in Endocrine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 28% 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

2 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

9 authors at 3 institutions in 1 country.

Yihan Zhang *Department of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Jia Wei *Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China.
Hong ZhouDepartment of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Bingxin LiDepartment of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Ying ChenDepartment of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Feng QianEngineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Jingting LiuEngineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Xin XieDepartment of Endocrinology and Metabolism, Shanghai Traditional Chinese and Medicine Integrated Hospital, 18 Baoding Road, Hongkou District, Shanghai, 200080, China. xiexin0929@126.com.
Huanbai XuDepartment of Endocrinology and Metabolism, Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China. huanbaixu@126.com.ORCID 0000-0002-4294-0274
Shanghai Jiao Tong University · CNShanghai Traditional Chinese Medicine Hospital · CNWenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGraves' disease (GD) is an autoimmune disease, the incidence of which is increasing yearly. GD requires long-life therapy. Therefore, the potential immune-related biomarkers of GD need to be studied.

methodIn our study, differentially expressed genes (DEGs) were derived from the online Gene Expression Omnibus (GEO) microarray expression dataset GSE71956. Protein‒protein interaction (PPI) network analyses were used to identify hub genes, which were validated by qPCR. GSEA was used to screen potential pathways and related immune cells. Next, CIBERSORT analysis was used to further explore the immune subtype distribution pattern among hub genes. ROC curves were used to analyze the specificity and sensitivity of hub genes.

result44 DEGs were screened from the GEO dataset. Two hub genes, EEF1A1 and EIF4B, were obtained from the PPI network and validated by qPCR (p < 0.05). GSEA was conducted to identify potential pathways and immune cells related to these the two hub genes. Immune cell subtype analysis revealed that hub genes had extensive associations with many different types of immune cells, particularly resting memory CD4

conclusionOur study revealed two hub genes, EEF1A1 and EIF4B, that are associated with resting memory CD4

Indexed as

Computational BiologyGraves DiseaseBiomarkersBiomarkers, TumorGene Expression Regulation, NeoplasticHumansProtein Interaction MapsBiomarkersBiomarkers, TumorDifferentially expressed genesGraves’ diseaseImmune cell infiltration analysisResting memory CD4+ T cells

Identifiers

PMID35962894
OpenAlexW4291190050

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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.