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Genomic analyses implicate noncoding de novo variants in congenital heart disease

Authors :
Daniel Bernstein
Martin Tristani-Firouzi
Jane W. Newburger
Sarah U. Morton
Diane E. Dickel
Lauren K. Wasson
Seong Won Kim
Jonathan G. Seidman
Martina Brueckner
Hongjian Qi
Elizabeth Goldmuntz
George A. Porter
Eric E. Schadt
Olga G. Troyanskaya
Kathryn B. Manheimer
Jian Zhou
Jason Homsy
Michael Parfenov
Steven R. DePalma
Bruce D. Gelb
Andrew Farrell
Alexander Kitaygorodsky
Matt Velinder
Gabor T. Marth
Richard B. Kim
Nihir Patel
Jonathan R. Kaltman
Felix Richter
Deepak Srivastava
Kathleen M. Chen
Yufeng Shen
Joshua M. Gorham
Christine E. Seidman
Alessandro Giardini
Wendy K. Chung
Source :
Nature Genetics. 52:769-777
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

Details

ISSN :
15461718 and 10614036
Volume :
52
Database :
OpenAIRE
Journal :
Nature Genetics
Accession number :
edsair.doi...........f24be7160476aa52e32f103edff9347b