RESEARCH ARTICLE Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures Xinchen Wang1,2,3, Nathan R Tucker4, Gizem Rizki1, Robert Mills4, Peter HL Krijger5,6, Elzo de Wit5,6, Vidya Subramanian1, Eric Bartell1, Xinh-Xinh Nguyen4, Jiangchuan Ye4, Jordan Leyton-Mange4, Elena V Dolmatova4, Pim van der Harst7,8, Wouter de Laat5,6, Patrick T Ellinor2,4, Christopher Newton-Cheh2,4,9, David J Milan4*, Manolis Kellis2,3*, Laurie A Boyer1* 1Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; 2Broad Institute of MIT and Harvard, Cambridge, United States; 3Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, United States; 4Cardiovascular Research Center, Massachusetts General Hospital, Boston, United States; 5Hubrecht Institute-KNAW, University Medical Center Utrecht, Utrecht, Netherlands; 6University Medical Center Utrecht, Utrecht, Netherlands; 7Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands; 8Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands; 9Center for Human Genetic Research, Massachusetts General Hospital, Boston, United States *For correspondence: dmilan@ Abstract Genetic variants identified by genome-wide association studies explain only a modest mgh.harvard.edu (DJM); manoli@ proportion of heritability, suggesting that meaningful associations lie ’hidden’ below current mit.edu (MK);
[email protected] thresholds. Here, we integrate information from association studies with epigenomic maps to (LAB) 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 Competing interests: The not meet genome-wide significance and are missed by existing studies.