Evidence map›Paper›PMID 35364782›Full record

ArticleImmunologic research2022

Identification of novel genes in Behcet's disease using integrated bioinformatic analysis.

Si Chen, Haolong Li, Haoting Zhan, Xiaoli Zeng, Hui Yuan, Yongzhe Li

Open access · hybridAbstract read
In one paragraph

Article in Immunologic research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Si ChenDepartment of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, People's Republic of China.
Haolong LiDepartment of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, People's Republic of China.
Haoting ZhanDepartment of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, People's Republic of China.
Xiaoli ZengDepartment of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Hui YuanDepartment of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Yongzhe LiDepartment of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 Shuaifuyuan, Beijing, 100730, People's Republic of China. yongzhelipumch@126.com.ORCID 0000-0002-7968-6767
Capital Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Behcet's disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein-protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD.

Indexed as

Behcet SyndromeComputational BiologyGene Expression ProfilingGene OntologyHumansProtein Interaction MapsBehcet’s diseaseDifferentially expressed genesIntegrated analysisMicroarrayRobust rank aggregation

Identifiers

PMID35364782
PMCPMC9273552
OpenAlexW4225605529

What OpenQuestion holds

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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 OpenQuestion graph.