Evidence map›Paper›PMID 34290731›Full record

ArticleFrontiers in genetics2021

Prediction of a Competing Endogenous RNA Co-expression Network by Comprehensive Methods in Systemic Sclerosis-Related Interstitial Lung Disease.

Yue-Mei Yan, Ji-Na Zheng, Li-Wei Wu, Qian-Wen Rao, Qiao-Rong Yang, Di Gao, Qiang Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

9 citing papers in PubMed, 11 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 3 institutions in 1 country.

Yue-Mei YanDepartment of Dermatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Ji-Na ZhengDepartment of Dermatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Li-Wei WuDepartment of Thoracic Surgery, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Qian-Wen RaoMinhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China.
Qiao-Rong YangDepartment of Dermatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Di GaoDepartment of Dermatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Qiang WangDepartment of Dermatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Fudan University · CNZhongshan Hospital · CNShanghai Public Health Clinical Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic sclerosis (SSc) is an immune-mediated connective tissue disease characterized by fibrosis of multi-organs, and SSc-related interstitial lung disease (SSc-ILD) is a leading cause of morbidity and mortality. To explore molecular biological mechanisms of SSc-ILD, we constructed a competing endogenous RNA (ceRNA) network for prediction. Expression profiling data were obtained from the Gene Expression Omnibus (GEO) database, and differential expressed mRNAs and miRNAs analysis was further conducted between normal lung tissue and SSc lung tissue. Also, the interactions of miRNA-lncRNA, miRNA-mRNA, and lncRNA-mRNA were predicted by online databases including starBase, LncBase, miRTarBase, and LncACTdb. The ceRNA network containing 11 lncRNAs, 7 miRNAs, and 20 mRNAs were constructed. Based on hub genes and miRNAs identified by weighted correlation network analysis (WGCNA) method, three core sub-networks-SNHG16, LIN01128, RP11-834C11.4(LINC02381)/hsa-let-7f-5p/IL6, LINC01128/has-miR-21-5p/PTX3, and LINC00665/hsa-miR-155-5p/PLS1-were obtained. Combined with previous studies and enrichment analyses, the lncRNA-mediated network affected LPS-induced inflammatory and immune processes, fibrosis development, and tumor microenvironment variations. The ceRNA network, especially three core sub-networks, may be served as early biomarkers and potential targets for SSc, which also provides further insights into the occurrence, progression, and accurate treatment of SSc at the molecular level.

Indexed as

competing endogenous RNA networkGene Expression OmnibusSNHG16systemic sclerosisweighted correlation network analysis

Identifiers

PMID34290731
PMCPMC8287190
OpenAlexW3183683162

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.