Format

Send to

Choose Destination
Pharmacogenomics J. 2014 Feb;14(1):6-13. doi: 10.1038/tpj.2013.4. Epub 2013 Mar 5.

Drug-gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval.

Author information

1
Department of Epidemiology, Bank of America Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
2
Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.
3
McKusick-Nathans Institute of Genetic Medicine and Department of Medicine, Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
4
Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA.
5
Division of Epidemiology and Center for Human Genetics, The University of Texas Health Science Center, Houston, TX, USA.
6
Department of Pharmacology and Therapeutics, University College Cork, Cork, UK.
7
Cedars-Sinai Medical Center, Los Angeles, CA, USA.
8
Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
9
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
10
California Pacific Medical Center Research Institute, San Francisco, CA, USA.
11
Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK.
12
Laboratory of Epidemiology, Demography, and Biometry, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA.
13
Icelandic Heart Association, Kopavogur, Iceland.
14
1] Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA [2] Department of Epidemiology, University of Washington, Seattle, WA, USA.
15
1] Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands [2] Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands.
16
Department of Medicine, University of California, San Francisco, CA, USA.
17
1] Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Centre for Medical Systems Biology, Leiden, The Netherlands.
18
Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
19
THL-National Institute for Health and Welfare, Helsinki, Finland.
20
1] Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands [2] Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands.
21
Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA.
22
Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
23
1] Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA [2] Center for Human Genetic Research, Cardiovascular Research Center, Harvard Medical School, Boston, MA, USA [3] Massachusetts General Hospital, Boston, MA, USA.
24
Division of Cardiology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland.
25
1] National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA [2] Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA.
26
Department of Biostatistics, University of Washington, Seattle, WA, USA.
27
1] Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands [2] Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands [3] Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
28
BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK.
29
Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
30
Division of Cardiology, University of Washington, Seattle, WA, USA.
31
Academic Section of Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
32
1] Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands [2] Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands [3] Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands [4] Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
33
1] Department of Epidemiology, Bank of America Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA [2] Departments of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
34
1] Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA [2] Department of Epidemiology, University of Washington, Seattle, WA, USA [3] Departments of Medicine, University of Washington, Seattle, WA, USA [4] Department of Health Services, University of Washington, Seattle, WA, USA [5] Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA.

Abstract

Variability in response to drug use is common and heritable, suggesting that genome-wide pharmacogenomics studies may help explain the 'missing heritability' of complex traits. Here, we describe four independent analyses in 33 781 participants of European ancestry from 10 cohorts that were designed to identify genetic variants modifying the effects of drugs on QT interval duration (QT). Each analysis cross-sectionally examined four therapeutic classes: thiazide diuretics (prevalence of use=13.0%), tri/tetracyclic antidepressants (2.6%), sulfonylurea hypoglycemic agents (2.9%) and QT-prolonging drugs as classified by the University of Arizona Center for Education and Research on Therapeutics (4.4%). Drug-gene interactions were estimated using covariable-adjusted linear regression and results were combined with fixed-effects meta-analysis. Although drug-single-nucleotide polymorphism (SNP) interactions were biologically plausible and variables were well-measured, findings from the four cross-sectional meta-analyses were null (Pinteraction>5.0 × 10(-8)). Simulations suggested that additional efforts, including longitudinal modeling to increase statistical power, are likely needed to identify potentially important pharmacogenomic effects.

PMID:
23459443
PMCID:
PMC3766418
DOI:
10.1038/tpj.2013.4
[Indexed for MEDLINE]
Free PMC Article

Publication types, MeSH terms, Grant support

Publication types

MeSH terms

Grant support

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center