Evidence map›Paper›PMID 41855523›Full record

ArticleEpigenetics2026

Global analyses of genomic and epigenomic influences on gene expression reveal

Caitlin Lahue, Sriram Ravindran, Aryan Dalal, Rozeta Avetisyan, Christoph D Rau

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Epigenetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Caitlin LahueDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Sriram RavindranDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Aryan DalalDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Rozeta AvetisyanDepartment of Anesthesiology, Division of Molecular Medicine, University of California, Los Angeles, CA, USA.
Christoph D RauDepartment of Genetics and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-0782-207X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart failure arises from maladaptive remodelling driven by genetic and epigenetic networks. Using a systems genetics framework, we mapped how DNA variants and CpG methylation shape cardiac transcriptomes during beta adrenergic stress in the Hybrid Mouse Diversity Panel, a cohort of over 100 fully inbred mouse strains. Expression QTLs (eQTLs), methylation QTLs (mQTLs) and methylation-driven eQTLs (emQTLs) were generated from over 13k expressed genes and 200k hypervariable CpGs in left ventricles. We discovered hundreds of regulatory 'hotspots' that control large portions of the genome, including several that regulate over 10% of the transcriptome and/or methylome. Approximately 16% of these hotspots overlapped with prior GWAS or EWAS signals. We focus on a hotspot on chromosome 12 and identify the serpine peptidase inhibitor

Indexed as

CatecholaminesHeart FailureSerpinsAcute-Phase ProteinsAnimalsDNA MethylationEpigenesis, GeneticEpigenomicsGene Expression RegulationMaleMiceMyocytes, CardiacQuantitative Trait LociRatsAcute-Phase ProteinsCatecholaminesSerpina3n protein, mouseSerpinsanimal modelsepigeneticsEWASGWASHeart failure

Identifiers

PMID41855523
PMCPMC13003858

What Socratic 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 Socratic graph.