David G Strauss1, Jose Vicente2, Lars Johannesen2, Ksenia Blinova2, Jay W Mason2, Peter Weeke2, Elijah R Behr2, Dan M Roden2, Ray Woosley2, Gulum Kosova2, Michael A Rosenberg2, Christopher Newton-Cheh1. 1. From Office of Clinical Pharmacology, Center for Drug Evaluation and Research (D.G.S., J.V., L.J.) and Office of Science and Engineering Laboratories, Center for Devices and Radiological Health (D.G.S., J.V., L.J., K.B.), US Food and Drug Administration, Silver Spring, MD; BSICoS Group, Aragón Institute for Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain (J.V.); Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden (L.J.); Division of Cardiology, University of Utah, Salt Lake City (J.W.M.); Spaulding Clinical Research, West Bend, WI (J.W.M.); Departments of Medicine (P.W., D.R.), Pharmacology (D.R.), and Biomedical Informatics (D.R.), Vanderbilt University Medical Center, Nashville, TN; Department of Cardiology, Copenhagen University Hospital, Gentofte, Denmark (P.W.); Cardiology Clinical Academic Group, St. George's University of London, London, UK (E.R.B.); AZCERT, Inc, Oro Valley, AZ (R.W.); Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA (G.K., M.A.R., C.N.-C.); Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge (G.K., M.A.R., C.N.-C.); and Division of Cardiac Electrophysiology, Veterans Administration Hospital System of Boston, Harvard Medical School, West Roxbury, MA (M.A.R.). david.strauss@fda.hhs.gov cnewtoncheh@mgh.harvard.edu. 2. From Office of Clinical Pharmacology, Center for Drug Evaluation and Research (D.G.S., J.V., L.J.) and Office of Science and Engineering Laboratories, Center for Devices and Radiological Health (D.G.S., J.V., L.J., K.B.), US Food and Drug Administration, Silver Spring, MD; BSICoS Group, Aragón Institute for Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain (J.V.); Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden (L.J.); Division of Cardiology, University of Utah, Salt Lake City (J.W.M.); Spaulding Clinical Research, West Bend, WI (J.W.M.); Departments of Medicine (P.W., D.R.), Pharmacology (D.R.), and Biomedical Informatics (D.R.), Vanderbilt University Medical Center, Nashville, TN; Department of Cardiology, Copenhagen University Hospital, Gentofte, Denmark (P.W.); Cardiology Clinical Academic Group, St. George's University of London, London, UK (E.R.B.); AZCERT, Inc, Oro Valley, AZ (R.W.); Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA (G.K., M.A.R., C.N.-C.); Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge (G.K., M.A.R., C.N.-C.); and Division of Cardiac Electrophysiology, Veterans Administration Hospital System of Boston, Harvard Medical School, West Roxbury, MA (M.A.R.).
Abstract
BACKGROUND: Drug-induced QT interval prolongation, a risk factor for life-threatening ventricular arrhythmias, is a potential side effect of many marketed and withdrawn medications. The contribution of common genetic variants previously associated with baseline QT interval to drug-induced QT prolongation and arrhythmias is not known. METHODS: We tested the hypothesis that a weighted combination of common genetic variants contributing to QT interval at baseline, identified through genome-wide association studies, can predict individual response to multiple QT-prolonging drugs. Genetic analysis of 22 subjects was performed in a secondary analysis of a randomized, double-blind, placebo-controlled, crossover trial of 3 QT-prolonging drugs with 15 time-matched QT and plasma drug concentration measurements. Subjects received single doses of dofetilide, quinidine, ranolazine, and placebo. The outcome was the correlation between a genetic QT score comprising 61 common genetic variants and the slope of an individual subject's drug-induced increase in heart rate-corrected QT (QTc) versus drug concentration. RESULTS: The genetic QT score was correlated with drug-induced QTc prolongation. Among white subjects, genetic QT score explained 30% of the variability in response to dofetilide (r=0.55; 95% confidence interval, 0.09-0.81; P=0.02), 23% in response to quinidine (r=0.48; 95% confidence interval, -0.03 to 0.79; P=0.06), and 27% in response to ranolazine (r=0.52; 95% confidence interval, 0.05-0.80; P=0.03). Furthermore, the genetic QT score was a significant predictor of drug-induced torsade de pointes in an independent sample of 216 cases compared with 771 controls (r2=12%, P=1×10-7). CONCLUSIONS: We demonstrate that a genetic QT score comprising 61 common genetic variants explains a significant proportion of the variability in drug-induced QT prolongation and is a significant predictor of drug-induced torsade de pointes. These findings highlight an opportunity for recent genetic discoveries to improve individualized risk-benefit assessment for pharmacological therapies. Replication of these findings in larger samples is needed to more precisely estimate variance explained and to establish the individual variants that drive these effects. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01873950.
RCT Entities:
BACKGROUND: Drug-induced QT interval prolongation, a risk factor for life-threatening ventricular arrhythmias, is a potential side effect of many marketed and withdrawn medications. The contribution of common genetic variants previously associated with baseline QT interval to drug-induced QT prolongation and arrhythmias is not known. METHODS: We tested the hypothesis that a weighted combination of common genetic variants contributing to QT interval at baseline, identified through genome-wide association studies, can predict individual response to multiple QT-prolonging drugs. Genetic analysis of 22 subjects was performed in a secondary analysis of a randomized, double-blind, placebo-controlled, crossover trial of 3 QT-prolonging drugs with 15 time-matched QT and plasma drug concentration measurements. Subjects received single doses of dofetilide, quinidine, ranolazine, and placebo. The outcome was the correlation between a genetic QT score comprising 61 common genetic variants and the slope of an individual subject's drug-induced increase in heart rate-corrected QT (QTc) versus drug concentration. RESULTS: The genetic QT score was correlated with drug-induced QTc prolongation. Among white subjects, genetic QT score explained 30% of the variability in response to dofetilide (r=0.55; 95% confidence interval, 0.09-0.81; P=0.02), 23% in response to quinidine (r=0.48; 95% confidence interval, -0.03 to 0.79; P=0.06), and 27% in response to ranolazine (r=0.52; 95% confidence interval, 0.05-0.80; P=0.03). Furthermore, the genetic QT score was a significant predictor of drug-induced torsade de pointes in an independent sample of 216 cases compared with 771 controls (r2=12%, P=1×10-7). CONCLUSIONS: We demonstrate that a genetic QT score comprising 61 common genetic variants explains a significant proportion of the variability in drug-induced QT prolongation and is a significant predictor of drug-induced torsade de pointes. These findings highlight an opportunity for recent genetic discoveries to improve individualized risk-benefit assessment for pharmacological therapies. Replication of these findings in larger samples is needed to more precisely estimate variance explained and to establish the individual variants that drive these effects. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01873950.
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