Evidence map›Paper›PMID 40027824›Full record

ArticlebioRxiv : the preprint server for biology2025

Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci.

Dennis Hecker, Xiaoning Song, Nina Baumgarten, Anastasiia Diagel, Nikoletta Katsaouni, Ling Li, Shuangyue Li, Ranjan Kumar Maji, Fatemeh Behjati Ardakani, Lijiang Ma and 6 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

16 authors.

Dennis HeckerDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.
Xiaoning SongDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.
Nina BaumgartenDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.
Anastasiia DiagelDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.
Nikoletta KatsaouniDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.
Ling LiDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.ORCID 0000-0002-3280-9475
Shuangyue LiDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.
Ranjan Kumar MajiDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.
Fatemeh Behjati ArdakaniDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.
Lijiang MaDepartment of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York 10029, USA.
Daniel TewsGerman Center for Child and Adolescent Health (DZKJ), Partner Site Ulm.
Martin WabitschGerman Center for Child and Adolescent Health (DZKJ), Partner Site Ulm.
Johan L M BjörkegrenDepartment of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York 10029, USA.
Heribert SchunkertDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.
Zhifen ChenDepartment of Cardiology, German Heart Centre Munich, School of Medicine and Health, Technical University of Munich, 80636 Munich, Germany.
Marcel H SchulzDepartment of Medicine, Institute for Computational Genomic Medicine, Goethe University Frankfurt, 60590 Frankfurt, Germany.

Funding

Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
NCATS NIH HHS UL1 TR004419
6 · The paper itself

Abstract

Coronary artery disease (CAD) is the leading cause of death worldwide. Recently, hundreds of genomic loci have been shown to increase CAD risk, however, the molecular mechanisms underlying signals from CAD risk loci remain largely unclear. We sought to pinpoint the candidate causal coding and non-coding genes of CAD risk loci in a cell type-specific fashion. We integrated the latest statistics of CAD genetics from over one million individuals with epigenetic data from 45 relevant cell types to identify genes whose regulation is affected by CAD-associated single nucleotide variants (SNVs) via epigenetic mechanisms. Applying two statistical approaches, we identified 1,580 genes likely involved in CAD, about half of which have not been associated with the disease so far. Enrichment analysis and phenome-wide association studies linked the novel candidate genes to disease-specific pathways and CAD risk factors, corroborating their disease relevance. We showed that CAD-SNVs are enriched to regulate gene expression by affecting the binding of transcription factors (TFs) with cellular specificity. Of all the candidate genes, 23.5% represented non-coding RNAs (ncRNA), which likewise showed strong cell type specificity. We conducted a proof-of-concept biological validation for the novel CAD ncRNA gene

Indexed as

Coronary artery diseaseCRISPR/Cas9epigeneticsGene-Based Association Test (GATES)genome-wide association studies (GWAS)non-coding RNA genesSNP exploration and analysis using epigenomics data (SNEEP)

Identifiers

PMID40027824
PMCPMC11870499

What OpenQuestion holds

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LicenceCC BY-NC
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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.