Evidence map›Paper›PMID 30279543›Full record

ArticleScientific reports2018

A novel system-level approach using RNA-sequencing data identifies miR-30-5p and miR-142a-5p as key regulators of apoptosis in myocardial infarction.

Jin Ock Kim, Jei Hyoung Park, Taeyong Kim, Seong Eui Hong, Ji Young Lee, Kyoung Jin Nho, Chunghee Cho, Yong Sook Kim, Wan Seok Kang, Youngkeun Ahn and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.0field-weighted citation impact, top 29% 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

18 citing papers in PubMed, 31 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Matricellular protein CCN1 promotes collagen alignment and scar integrity after myocardial infarction.Matrix biology : journal of the International Society for Matrix Biology · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
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 at 2 institutions in 1 country.

Jin Ock KimSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Jei Hyoung ParkSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Taeyong KimSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Seong Eui HongSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Ji Young LeeSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Kyoung Jin NhoSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Chunghee ChoSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea.
Yong Sook KimDepartment of Cardiology, Chonnam National University Hospital, Gwangju, Korea.
Wan Seok KangDepartment of Cardiology, Chonnam National University Hospital, Gwangju, Korea.
Youngkeun AhnDepartment of Cardiology, Chonnam National University Hospital, Gwangju, Korea.
Do Han KimSchool of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005, Korea. dhkim@gist.ac.kr.
Gwangju Institute of Science and Technology · KRChonnam National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study identified microRNAs involved in myocardial infarction (MI) through a novel system-level approach using RNA sequencing data in an MI mouse model. This approach involved the extraction of DEGs and DEmiRs from RNA-seq data in sham and MI samples and the subsequent selection of two miRNAs: miR-30-5p (family) and miR-142a-5p, which were downregulated and upregulated in MI, respectively. Gene Set Enrichment Analysis (GSEA) using the predicted targets of the two miRNAs suggested that apoptosis is an essential gene ontology (GO)-associated term. In vitro functional assays using neonatal rat ventricular myocytes (NRVMs) demonstrated that miR-30-5p is anti-apoptotic and miR-142a-5p is pro-apoptotic. Luciferase assays showed that the apoptotic genes, Picalm and Skil, and the anti-apoptotic genes, Ghr and Kitl, are direct targets of miR-30-5p and miR-142a-5p, respectively. siRNA studies verified the results of the luciferase assays for target validation. The results of the system-level high throughput approach identified a pair of functionally antagonistic miRNAs and their targets in MI. This study provides an in-depth analysis of the role of miRNAs in the pathogenesis of MI which could lead to the development of therapeutic tools. The system-level approach could be used to identify miRNAs involved in variety of other diseases.

Indexed as

AnimalsApoptosisCarrier ProteinsDisease Models, AnimalMaleMiceMice, Inbred C57BLMicroRNAsMonomeric Clathrin Assembly ProteinsMyocardial InfarctionMyocytes, CardiacProto-Oncogene ProteinsRatsRats, Sprague-DawleyCarrier ProteinsMicroRNAsMirn142 microRNA, mouseMIRN142 microRNA, ratMirn30d microRNA, mouseMIRN30 microRNA, ratMonomeric Clathrin Assembly ProteinsPICALM protein, mousePicalm protein, ratProto-Oncogene ProteinsSkil protein, mousesomatotropin-binding protein

Identifiers

PMID30279543
PMCPMC6168573
OpenAlexW2893078978

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.