Evidence map›Paper›PMID 37987017›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Deciphering epistatic genetic regulation of cardiac hypertrophy.

Qianru Wang, Tiffany M Tang, Michelle Youlton, Chad S Weldy, Ana M Kenney, Omer Ronen, J Weston Hughes, Elizabeth T Chin, Shirley C Sutton, Abhineet Agarwal and 14 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors at 10 institutions in 2 countries.

Qianru WangDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.ORCID 0000-0002-7219-7522
Tiffany M TangDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Michelle YoultonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
Chad S WeldyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.ORCID 0000-0003-4652-6422
Ana M KenneyDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Omer RonenDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
J Weston HughesDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Elizabeth T ChinDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
Shirley C SuttonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
Abhineet AgarwalDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Xiao LiDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Merle BehrFaculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany.
Karl KumbierDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.
Christine S MoravecDepartment of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
W H Wilson TangDepartment of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
Kenneth B MarguliesDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Thomas P CappolaDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Atul J ButteBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Rima ArnaoutBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
James B BrownDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
James R PriestDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.ORCID 0000-0002-8349-4784
Victoria N ParikhDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
Bin YuDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Euan A AshleyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
Stanford University · USUniversity of California, Santa Cruz · USChan Zuckerberg Initiative (United States) · USUniversity of California, Berkeley · USUniversity of California, San Francisco · USHospital of the University of Pennsylvania · USCleveland Clinic · USCleveland Clinic Lerner College of Medicine · USLawrence Berkeley National Laboratory · USUniversity of Regensburg · DE

Funding

Integrative genomics of human heart failureR01HL105993 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI ASHLEY, EUAN A, CAPPOLA, THOMAS P. · 2011 to 2014
$8.9M
MTSS1 in Myocardial DiseaseR01HL141232 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI THOMAS P. CAPPOLA, Scott Michael Damrauer · 2019 to 2026
$4.7M
Structure function relationships from deep mutational scanning in human cardiomyopathyR01HL144843 · NHLBI · STANFORD UNIVERSITY · PI ASHLEY, EUAN A · 2020 to 2023
$2.8M
DMS/NIGMS 2: A Stability Driven Recommendation System for Efficient Disease Mechanistic DiscoveryR01GM152718 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI Bin Yu · 2023 to 2026
$1.2M
The Role of RBM20 Sequence and Expression in Dilated CardiomyopathiesK08HL143185 · NHLBI · STANFORD UNIVERSITY · PI PARIKH, VICTORIA · 2019 to 2023
$725k
ADAR mediated RNA editing is a causal mechanism in coronary artery diseaseK08HL167699 · NHLBI · STANFORD UNIVERSITY · PI Chad S Weldy · 2023 to 2026
$664k
A transcriptional network which governs smooth muscle transition is mediated by causal coronary artery disease gene PDGFDF32HL160067 · NHLBI · STANFORD UNIVERSITY · PI WELDY, CHAD S · 2021 to 2022
$135k
NHLBI NIH HHS F32 HL160067NHLBI NIH HHS K08 HL143185NHLBI NIH HHS K08 HL167699NHLBI NIH HHS L30 HL159413NHLBI NIH HHS R01 HL105993NHLBI NIH HHS R01 HL141232NHLBI NIH HHS R01 HL144843NIGMS NIH HHS R01 GM152718
6 · The paper itself

Abstract

Although genetic variant effects often interact non-additively, strategies to uncover epistasis remain in their infancy. Here, we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, using deep learning-derived left ventricular mass estimates from 29,661 UK Biobank cardiac MRIs. We report epistatic variants near

Identifiers

PMID37987017
PMCPMC10659487
OpenAlexW4388523022

What Socratic 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 Socratic graph.