Evidence map›Paper›PMID 30338905›Full record

ArticleJournal of cellular and molecular medicine2019

Systematic identification and analysis of dysregulated miRNA and transcription factor feed-forward loops in hypertrophic cardiomyopathy.

Hongbo Shi, Jiayao Li, Qiong Song, Liang Cheng, Haoran Sun, Wenjing Fan, Jianfei Li, Zhenzhen Wang, Guangde Zhang

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.2field-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

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Hypertrophic cardiomyopathy inThe journal of cardiovascular aging · 2024
    Article
  6. Posttranscriptional Regulation by Proteins and Noncoding RNAs.Advances in experimental medicine and biology · 2024
    Article
  7. Computational and structural biotechnology journal · 2023
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. 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

9 authors at 1 institution in 1 country.

Hongbo ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.ORCID 0000-0002-0538-3026
Jiayao LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qiong SongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Liang ChengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Haoran SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Wenjing FanDepartment of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Jianfei LiEmergency Cardiovascular Medicine, Inner Mongolia Autonomous Region People's Hospital, Hohhot, China.
Zhenzhen WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Guangde ZhangDepartment of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiovascular disease. Although some genes and miRNAs related with HCM have been studied, the molecular regulatory mechanisms between miRNAs and transcription factors (TFs) in HCM have not been systematically elucidated. In this study, we proposed a novel method for identifying dysregulated miRNA-TF feed-forward loops (FFLs) by integrating sample matched miRNA and gene expression profiles and experimentally verified interactions of TF-target gene and miRNA-target gene. We identified 316 dysregulated miRNA-TF FFLs in HCM, which were confirmed to be closely related with HCM from various perspectives. Subpathway enrichment analysis demonstrated that the method was outperformed by the existing method. Furthermore, we systematically analysed the global architecture and feature of gene regulation by miRNAs and TFs in HCM, and the FFL composed of hsa-miR-17-5p, FASN and STAT3 was inferred to play critical roles in HCM. Additionally, we identified two panels of biomarkers defined by three TFs (CEBPB, HIF1A, and STAT3) and four miRNAs (hsa-miR-155-5p, hsa-miR-17-5p, hsa-miR-20a-5p, and hsa-miR-181a-5p) in a discovery cohort of 126 samples, which could differentiate HCM patients from healthy controls with better performance. Our work provides HCM-related dysregulated miRNA-TF FFLs for further experimental study, and provides candidate biomarkers for HCM diagnosis and treatment.

Indexed as

BiomarkersCardiomyopathy, HypertrophicFeedback, PhysiologicalGene Expression ProfilingGene Regulatory NetworksHumansMicroRNAsReproducibility of ResultsSTAT3 Transcription FactorTranscription FactorsBiomarkersMicroRNAsSTAT3 protein, humanSTAT3 Transcription FactorTranscription Factorsfeed-forward loopmiRNAtranscription factor

Identifiers

PMID30338905
PMCPMC6307764
OpenAlexW2897461421

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.