@article {5978,
	title = {Drug-gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval.},
	journal = {Pharmacogenomics J},
	volume = {14},
	year = {2014},
	month = {2014 Feb},
	pages = {6-13},
	abstract = {<p>Variability in response to drug use is common and heritable, suggesting that genome-wide pharmacogenomics studies may help explain the {\textquoteright}missing heritability{\textquoteright} 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 {\texttimes} 10(-8)). Simulations suggested that additional efforts, including longitudinal modeling to increase statistical power, are likely needed to identify potentially important pharmacogenomic effects.</p>},
	keywords = {Computer Simulation, Cross-Sectional Studies, Drug-Related Side Effects and Adverse Reactions, Electrocardiography, European Continental Ancestry Group, Gene-Environment Interaction, Genome-Wide Association Study, Humans, Linear Models, Long QT Syndrome, Markov Chains, Pharmacogenetics, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable},
	issn = {1473-1150},
	doi = {10.1038/tpj.2013.4},
	author = {Avery, C L and Sitlani, C M and Arking, D E and Arnett, D K and Bis, J C and Boerwinkle, E and Buckley, B M and Ida Chen, Y-D and de Craen, A J M and Eijgelsheim, M and Enquobahrie, D and Evans, D S and Ford, I and Garcia, M E and Gudnason, V and Harris, T B and Heckbert, S R and Hochner, H and Hofman, A and Hsueh, W-C and Isaacs, A and Jukema, J W and Knekt, P and Kors, J A and Krijthe, B P and Kristiansson, K and Laaksonen, M and Liu, Y and Li, X and Macfarlane, P W and Newton-Cheh, C and Nieminen, M S and Oostra, B A and Peloso, G M and Porthan, K and Rice, K and Rivadeneira, F F and Rotter, J I and Salomaa, V and Sattar, N and Siscovick, D S and Slagboom, P E and Smith, A V and Sotoodehnia, N and Stott, D J and Stricker, B H and St{\"u}rmer, T and Trompet, S and Uitterlinden, A G and van Duijn, C and Westendorp, R G J and Witteman, J C and Whitsel, E A and Psaty, B M}
}
@article {7491,
	title = {Pharmacogenomics study of thiazide diuretics and QT interval in multi-ethnic populations: the cohorts for heart and aging research in genomic epidemiology.},
	journal = {Pharmacogenomics J},
	year = {2017},
	month = {2017 Jul 18},
	abstract = {<p>Thiazide diuretics, commonly used antihypertensives, may cause QT interval (QT) prolongation, a risk factor for highly fatal and difficult to predict ventricular arrhythmias. We examined whether common single-nucleotide polymorphisms (SNPs) modified the association between thiazide use and QT or its component parts (QRS interval, JT interval) by performing ancestry-specific, trans-ethnic and cross-phenotype genome-wide analyses of European (66\%), African American (15\%) and Hispanic (19\%) populations (N=78 199), leveraging longitudinal data, incorporating corrected standard errors to account for underestimation of interaction estimate variances and evaluating evidence for pathway enrichment. Although no loci achieved genome-wide significance (P<5 {\texttimes} 10(-8)), we found suggestive evidence (P<5 {\texttimes} 10(-6)) for SNPs modifying the thiazide-QT association at 22 loci, including ion transport loci (for example, NELL1, KCNQ3). The biologic plausibility of our suggestive results and simulations demonstrating modest power to detect interaction effects at genome-wide significant levels indicate that larger studies and innovative statistical methods are warranted in future efforts evaluating thiazide-SNP interactions.The Pharmacogenomics Journal advance online publication, 18 July 2017; doi:10.1038/tpj.2017.10.</p>},
	issn = {1473-1150},
	doi = {10.1038/tpj.2017.10},
	author = {Seyerle, A A and Sitlani, C M and Noordam, R and Gogarten, S M and Li, J and Li, X and Evans, D S and Sun, F and Laaksonen, M A and Isaacs, A and Kristiansson, K and Highland, H M and Stewart, J D and Harris, T B and Trompet, S and Bis, J C and Peloso, G M and Brody, J A and Broer, L and Busch, E L and Duan, Q and Stilp, A M and O{\textquoteright}Donnell, C J and Macfarlane, P W and Floyd, J S and Kors, J A and Lin, H J and Li-Gao, R and Sofer, T and M{\'e}ndez-Gir{\'a}ldez, R and Cummings, S R and Heckbert, S R and Hofman, A and Ford, I and Li, Y and Launer, L J and Porthan, K and Newton-Cheh, C and Napier, M D and Kerr, K F and Reiner, A P and Rice, K M and Roach, J and Buckley, B M and Soliman, E Z and de Mutsert, R and Sotoodehnia, N and Uitterlinden, A G and North, K E and Lee, C R and Gudnason, V and St{\"u}rmer, T and Rosendaal, F R and Taylor, K D and Wiggins, K L and Wilson, J G and Chen, Y-DI and Kaplan, R C and Wilhelmsen, K and Cupples, L A and Salomaa, V and van Duijn, C and Jukema, J W and Liu, Y and Mook-Kanamori, D O and Lange, L A and Vasan, R S and Smith, A V and Stricker, B H and Laurie, C C and Rotter, J I and Whitsel, E A and Psaty, B M and Avery, C L}
}
