Evidence map›Paper›PMID 30866692›Full record

ArticleJournal of the American Heart Association2019

Glucocorticoid Receptor-Binding and Transcriptome Signature in Cardiomyocytes.

Elena Severinova, Saleena Alikunju, Wei Deng, Puneet Dhawan, Nazish Sayed, Danish Sayed

Open access · goldAbstract read
In one paragraph

Article in Journal of the American Heart Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
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  4. Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

6 authors at 3 institutions in 1 country.

Elena Severinova1 Department of Cell Biology and Molecular Medicine Rutgers New Jersey Medical School Newark NJ.
Saleena Alikunju1 Department of Cell Biology and Molecular Medicine Rutgers New Jersey Medical School Newark NJ.
Wei Deng1 Department of Cell Biology and Molecular Medicine Rutgers New Jersey Medical School Newark NJ.
Puneet Dhawan2 Genomics Center Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School Newark NJ.
Nazish Sayed3 Cardiovascular Institute Stanford University Stanford CA.
Danish Sayed1 Department of Cell Biology and Molecular Medicine Rutgers New Jersey Medical School Newark NJ.
Rutgers, The State University of New Jersey · USRutgers New Jersey Medical SchoolCardiovascular Institute of the South · US

Funding

T32 Training Program in Mechanisms and Innovation in Vascular DiseaseT32HL098049 · NHLBI · STANFORD UNIVERSITY · PI Nicholas James Leeper, Philip S Tsao · 2010 to 2026
$6.3M
NOVEL POSTTRANSCRIPTIONAL REGULATORS OF STRESS HORMONE GLUCOCORTICOID RECEPTOR–DEPENDENT GENE TRANSCRIPTION DURING CARDIAC HYPERTROPHY AND FAILURER01HL128799 · NHLBI · RBHS-NEW JERSEY MEDICAL SCHOOL · PI SAYED, DANISH · 2016 to 2020
$2.0M
NHLBI NIH HHS R01 HL128799
6 · The paper itself

Abstract

Background An increase in serum cortisol has been identified as a risk factor for cardiac failure, which highlights the impact of glucocorticoid signaling in cardiomyocytes and its influence in the progression of failure. Dexamethasone, a synthetic glucocorticoid, is sufficient for induction of cardiomyocyte hypertrophy, but little is known of the glucocorticoid receptor (GR) genome-binding and -dependent transcriptional changes that mediate this phenotype. Methods and Results In this study using high-resolution sequencing, we identified genomic targets of GR and associated change in the transcriptome after 1 and 24 hours of dexamethasone treatment. We showed that GR associates with 6482 genes in the cardiac genome, with differential regulation of 738 genes. Interestingly, alignment of the chromatin immunoprecipitation and RNA sequencing data show that, after 1 hour, 69% of differentially regulated genes are associated with GR and identify as regulators of RNA pol II-dependent transcription. Conversely, after 24 hours only 45% of regulated genes are associated with GR and involved in dilated and hypertrophic cardiomyopathies as well as other growth-related pathways. In addition, our data also reveal that a majority of genes (76.42%) associated with GR show incremental changes in transcript abundance and are genes involved in basic cellular processes that might be regulated by the dynamics of promoter-paused RNA pol II, as seen in hearts undergoing hypertrophy. In vivo administration of dexamethasone resulted in similar changes in the cardiac transcriptome, as seen in isolated cardiomyocytes. Conclusions Our data reveal genome-wide GR binding sites in cardiomyocytes, identify novel targets and GR-dependent change in the transcriptome that induces and contributes to cardiomyocyte hypertrophy.

Indexed as

Gene Expression RegulationAnimalsAnimals, NewbornCardiomyopathy, HypertrophicCells, CulturedDisease Models, AnimalMyocytes, CardiacPromoter Regions, GeneticRatsRats, Sprague-DawleyReceptors, GlucocorticoidRNASignal TransductionTranscriptomeReceptors, GlucocorticoidRNAdexamethasonegene expression/regulationgene transcriptiongenome‐wide analysisglucocorticoid receptorglucocorticoid receptor–dependent transcriptionhypertrophic transcriptomehypertrophy

Identifiers

PMID30866692
PMCPMC6475044
OpenAlexW2921286955

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.