Evidence map›Paper›PMID 27162171›Full record

ArticleeLife2016

Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.

Xinchen Wang, Nathan R Tucker, Gizem Rizki, Robert Mills, Peter Hl Krijger, Elzo de Wit, Vidya Subramanian, Eric Bartell, Xinh-Xinh Nguyen, Jiangchuan Ye and 9 more

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 4 pooled it
–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

77 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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17 more citing papers are in PubMed but not listed here.

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

19 authors.

Xinchen WangDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United States.ORCID 0000-0002-5198-6581
Nathan R TuckerCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Gizem RizkiDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United States.
Robert MillsCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Peter Hl KrijgerHubrecht Institute-KNAW, University Medical Center Utrecht, Utrecht, Netherlands.
Elzo de WitHubrecht Institute-KNAW, University Medical Center Utrecht, Utrecht, Netherlands.
Vidya SubramanianDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United States.
Eric BartellDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United States.
Xinh-Xinh NguyenCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Jiangchuan YeCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Jordan Leyton-MangeCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Elena V DolmatovaCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Pim van der HarstDepartment of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Wouter de LaatHubrecht Institute-KNAW, University Medical Center Utrecht, Utrecht, Netherlands.
Patrick T EllinorBroad Institute of MIT and Harvard, Cambridge, United States.
Christopher Newton-ChehBroad Institute of MIT and Harvard, Cambridge, United States.
David J MilanCardiovascular Research Center, Massachusetts General Hospital, Boston, United States.
Manolis KellisBroad Institute of MIT and Harvard, Cambridge, United States.
Laurie A BoyerDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United States.

Funding

IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
MULTIDISCIPLINARY RESEARCH TRAINING IN CARDIOLOGYT32HL007208 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Patrick Thomas Ellinor, David E Sosnovik · 1985 to 2026
$16.1M
Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
The Epigenetic Landscape of Heart DevelopmentU01HL098179 · NHLBI · J. DAVID GLADSTONE INSTITUTES · PI BOYER, LAURIE A, BRUNEAU, BENOIT GAETAN · 2009 to 2014
$10.0M
EDAC: ENCODE Data Analysis CenterU41HG007000 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI WENG, ZHIPING · 2012 to 2016
$9.8M
Regulatory Morif Discovery in the Human Genome Using Comparative GenomicsR01HG004037 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2007 to 2015
$3.9M
Interpreting non-coding variants using epigenomics, regulatory models, & validation experimentsR01HG008155 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2015 to 2017
$2.3M
High Throughput Screening for Chemical Modifiers of Long QT SyndromeR01HL109004 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MILAN, DAVID J · 2011 to 2013
$1.5M
Comparative analysis and regulatory architecture of epigenomics datasetsR01GM113708 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2015 to 2017
$852k
NHGRI NIH HHS R01 HG004037NHGRI NIH HHS R01 HG008155NHGRI NIH HHS T32 HG002295NHGRI NIH HHS U41 HG007000NHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL109004NHLBI NIH HHS T32 HL007208NHLBI NIH HHS U01 HL098179NIGMS NIH HHS R01 GM113708
6 · The paper itself

Abstract

Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration. We apply functional criteria to identify loci associated with QT interval that do not meet genome-wide significance and are missed by existing studies. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. We experimentally validate the molecular, gene-regulatory, cellular and organismal phenotypes of these sub-threshold loci, demonstrating that most sub-threshold loci have regulatory consequences and that genetic perturbation of nearby genes causes cardiac phenotypes in mouse. Our work provides a general approach for improving the detection of novel loci associated with complex human traits.

Indexed as

EpigenomicsGenetic LociGenome-Wide Association StudyAnimalsHeart Conduction SystemHumansMicecomplex traitsenhancersepigenomicsevolutionary biologygenome-wide association studygenomicsheritabilityhumanhuman biologymedicinemousezebrafish

Identifiers

PMID27162171
PMCPMC4862755

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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.