Evidence map›Paper›PMID 27812736›Full record

ArticleImmunogenetics2017

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis.

Wei Xia, Jian Wu, Fei-Yan Deng, Long-Fei Wu, Yong-Hong Zhang, Yu-Fan Guo, Shu-Feng Lei

Abstract read
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In one paragraph

Article in Immunogenetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 7 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

7 authors at 2 institutions in 1 country.

Wei XiaCenter for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
Jian WuDepartment of Rheumatology, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People's Republic of China.
Fei-Yan DengCenter for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
Long-Fei WuCenter for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
Yong-Hong ZhangJiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
Yu-Fan GuoDepartment of Rheumatology, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People's Republic of China. gyf3636@sina.com.cn.
Shu-Feng LeiCenter for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China. leisf@suda.edu.cn.
Soochow University · CNFirst Affiliated Hospital of Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Indexed as

Gene Expression ProfilingGene Regulatory NetworksArthritis, RheumatoidBiomarkersComputational BiologyHumansPolymorphism, Single NucleotideProtein Interaction MapsBiomarkersIntegrative analysisMulti-dataset analysisRheumatoid arthritisShared genetic marker

Identifiers

PMID27812736
OpenAlexW2546723728

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.