Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits-Reference-Cited by-同舟云学术

Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits

Published:2020-08 Issue:4 Volume:13 Page:
ISSN:2574-8300
Container-title:Circulation: Genomic and Precision Medicine
language:en
Short-container-title:Circ: Genomic and Precision Medicine

Author:

Baldassari Antoine R.¹,Sitlani Colleen M.²,Highland Heather M.¹^ORCID,Arking Dan E.³^ORCID,Buyske Steve⁴,Darbar Dawood⁵^ORCID,Gondalia Rahul¹,Graff Misa¹,Guo Xiuqing⁶⁷^ORCID,Heckbert Susan R.⁸^ORCID,Hindorff Lucia A.⁹,Hodonsky Chani J.¹,Ida Chen Yii-Der⁶⁷,Kaplan Robert C.¹⁰^ORCID,Peters Ulrike¹¹,Post Wendy¹²,Reiner Alex P.¹¹^ORCID,Rotter Jerome I.⁶⁷^ORCID,Shohet Ralph V.¹³,Seyerle Amanda A.¹^ORCID,Sotoodehnia Nona⁸,Tao Ran¹⁴,Taylor Kent D.⁶⁷,Wojcik Genevieve L.¹⁵,Yao Jie⁶⁷^ORCID,Kenny Eimear E.¹⁶¹⁷¹⁸¹⁹,Lin Henry J.⁶⁷,Soliman Elsayed Z.²⁰^ORCID,Whitsel Eric A.¹,North Kari E.¹²¹^ORCID,Kooperberg Charles¹¹^ORCID,Avery Christy L.¹

Affiliation:

1. Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill.

2. Cardiovascular Health Research Unit, Department of Medicine (C.M.S.), University of Washington, Seattle.xs

3. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (D.E.A.).

4. Department of Statistics and Biostatistics, Rutgers University, New Brunswick, NJ (S.B.).

5. Department of Medicine, University of Illinois at Chicago (D.D.).

6. Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.).

7. Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.).

8. Cardiovascular Health Research Unit, Division of Cardiology, Department of Medicine (S.R.H., N.S.), University of Washington, Seattle.

9. Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (L.A.H.).

10. Albert Einstein College of Medicine, Bronx, NY (R.C.K.).

11. Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA (U.P., A.P.R., C.K.).

12. Departments of Medicine and Epidemiology, Johns Hopkins University, Baltimore, MD (W.P.).

13. Center for Cardiovascular Research, John A. Burns School of Medicine, Honolulu, HI (R.V.S.).

14. Department of Biostatistics, Vanderbilt University, Nashville, TN (R.T.).

15. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (G.L.W.).

16. Center for Genomic Health (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY.

17. Charles Bronfman Institute of Personalized Medicine (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY.

18. Department of Genetics and Genomic Sciences (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY.

19. Department of Medicine (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY.

20. Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, NC (E.Z.S.).

21. Carolina Center for Genome Sciences (K.E.N.), University of North Carolina at Chapel Hill.

Abstract

Background: We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci. Methods: We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test. Results: We identified 6 novels ( CD36, PITX2, EMB, ZNF592, YPEL2 , and BC043580 ) and 87 known loci (adaptive sum of powered score test P <5×10 −9 ). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci. Conclusions: Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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