Evidence map›Paper›PMID 39484431›Full record

ArticlebioRxiv : the preprint server for biology2024

Mapping DNA Methylation to Cardiac Pathologies Induced by Beta-Adrenergic Stimulation in a Large Panel of Mice.

Caitlin Lahue, Eleanor Wong, Aryan Dalal, Wilson Tan Lek Wen, Shuxun Ren, Roger Foo, Yibin Wang, Christoph D Rau

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Caitlin LahueDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill.
Eleanor WongGenome Institute of Singapore.
Aryan DalalDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill.
Wilson Tan Lek WenGenome Institute of Singapore.
Shuxun RenCardiovascular Research Institute, Duke-NUS Medical School, National University of Singapore.
Roger FooGenome Institute of Singapore.
Yibin WangCardiovascular Research Institute, Duke-NUS Medical School, National University of Singapore.
Christoph D RauDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill.

Funding

Elucidating the Role of Multinuclearity in Healthy and Diseased Mammalian CardiomyocytesR01HL162636 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Christoph Daniel Rau · 2023 to 2026
$1.9M
Discovery of Novel Epigenetic Regulators of Heart Failure in a Panel of MiceR00HL138301 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RAU, CHRISTOPH DANIEL · 2020 to 2022
$747k
NHLBI NIH HHS R00 HL138301NHLBI NIH HHS R01 HL162636
6 · The paper itself

Abstract

Background: Heart failure (HF) is a leading cause of morbidity and mortality worldwide, with over 18 million deaths annually. Despite extensive research, genetic and environmental factors contributing to HF remain complex and poorly understood. Recent studies suggest that epigenetic modifications, such as DNA methylation, may play a crucial role in regulating HF-associated phenotypes. In this study, we leverage the Hybrid Mouse Diversity Panel (HMDP), a cohort of over 100 inbred mouse strains, to investigate the role of DNA methylation in HF progression. Objective: We aim to identify epigenetic modifications associated with HF by integrating DNA methylation data with gene expression and phenotypic traits. Using isoproterenol (ISO)-induced cardiac hypertrophy and failure in HMDP mice, we explore the relationship between methylation patterns and HF susceptibility. Methods: We performed reduced representational bisulfite sequencing (RRBS) to capture DNA methylation at single-nucleotide resolution in the left ventricles of 90 HMDP mouse strains under both control and ISO-treated conditions. We identified differentially methylated regions (DMRs) and performed an epigenome-wide association study (EWAS) using the MACAU algorithm. We identified likely candidate genes within each locus through integration of our results with previously reported sequence variation, gene expression, and HF-related phenotypes. Results: Our EWAS identified 56 CpG loci significantly associated with HF phenotypes, including 18 loci where baseline DNA methylation predicted post-ISO HF progression. Key candidate genes, such as Prkag2, Anks1, and Mospd3, were identified based on their epigenetic regulation and association with HF traits. In vitro follow-up on a number of genes confirmed that knockdown of Anks1 and Mospd3 in NRVMs resulted in significant alterations in cell size and blunting of ISO-induced hypertrophy, demonstrating their functional relevance in HF pathology.Furthermore, treatment with the DNA methyltransferase inhibitor RG108 in ISO-treated BTBRT mice significantly reduced cardiac hypertrophy and preserved ejection fraction compared to mice only treated with ISO, highlighting the therapeutic potential of targeting DNA methylation in HF. Differential expression analysis revealed that RG108 treatment restored the expression of several methylation-sensitive genes, further supporting the role of epigenetic regulation in HF. Conclusion: Our study demonstrates a clear interplay between DNA methylation, gene expression, and HF-associated phenotypes. We identified several novel epigenetic loci and candidate genes that contribute to HF progression, offering new insights into the molecular mechanisms of HF. These findings underscore the importance of epigenetic regulation in cardiac disease and suggest potential therapeutic strategies for modifying HF outcomes through targeting DNA methylation.

Indexed as

cardiac hypertrophyDNA methylationepigenome-wide association studyEWASgene expressionheart failureHybrid Mouse Diversity Panelisoproterenolmethylation inhibitors

Identifiers

PMID39484431
PMCPMC11527189

What OpenQuestion holds

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LicenceCC BY-NC
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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.