Evidence map›Paper›PMID 32849787›Full record

ArticleFrontiers in genetics2020

Comprehensive Construction of a Circular RNA-Associated Competing Endogenous RNA Network Identified Novel Circular RNAs in Hypertrophic Cardiomyopathy by Integrated Analysis.

Qi Guo, Junjie Wang, Runlu Sun, Zhijian He, Qian Chen, Wenhao Liu, Maoxiong Wu, Jinlan Bao, Zhaoyu Liu, Jingfeng Wang and 1 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Circular RNAs as Novel Biomarkers and Application in Cardiovascular Diseases.Advances in experimental medicine and biology · 2025
    Review
  4. CircRNA-mediated regulation of cardiovascular disease.Frontiers in cardiovascular medicine · 2024
    Review
  5. The Landscape of Circular RNAs in Cardiovascular Diseases.International journal of molecular sciences · 2023
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
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

11 authors.

Qi GuoDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Junjie WangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Runlu SunDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Zhijian HeDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Qian ChenDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Wenhao LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Maoxiong WuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jinlan BaoDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Zhaoyu LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jingfeng WangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Yuling ZhangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertrophic cardiomyopathy (HCM), the most common heritable cardiomyopathy, is associated with a high risk of sudden cardiac death. The complexity and behavior of the circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network in HCM have not been thoroughly elucidated. Plasma circRNA and messenger RNA (mRNA) expression profiles were acquired by using a microarray. Weighted correlation network analysis (WGCNA) and linear models for microarray data (Limma) were used to analyze microarray data. Gene modules, consisting of genes with high correlations, were detected and represented by a designated color. The ceRNA network, including circRNA, microRNA (miRNA), and mRNA, was constructed based on the "ceRNA hypothesis" using an integrated systems biology method. By WGCNA, two modules, namely magenta and red modules, were identified as being positively correlated with HCM. In the combined analysis of WGCNA and Limma, 36 hub circRNAs in the magenta module and 83 hub circRNAs in the red module were significantly upregulated compared with the controls. By coexpression analysis, 270 circRNA-mRNA pairs were identified with a coefficient ≥0.9 and

Indexed as

circular RNAscompeting endogenous RNA networkhypertrophic cardiomyopathymicroarrayweighted correlation network analysis

Identifiers

PMID32849787
PMCPMC7399352

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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.