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Sci. Signal., 20 April 2010 RESEARCH ARTICLESSystems Pharmacology of ArrhythmiasSeth I. Berger, Avi Maayan, and Ravi Iyengar* Department of Pharmacology and Systems Therapeutics and Systems Biology Center New York, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1215, New York, NY 10029, USA. Abstract: Long-QT syndrome (LQTS) is a congenital or drug-induced change in electrical activity of the heart that can lead to fatal arrhythmias. Mutations in 12 genes encoding ion channels and associated proteins are linked with congenital LQTS. With a computational systems biology approach, we found that gene products involved in LQTS formed a distinct functional neighborhood within the human interactome. Other diseases form similarly selective neighborhoods, and comparison of the LQTS neighborhood with other disease-centered neighborhoods suggested a molecular basis for associations between seemingly unrelated diseases that have increased risk of cardiac complications. By combining the LQTS neighborhood with published genome-wide association study data, we identified previously unknown single-nucleotide polymorphisms likely to affect the QT interval. We found that targets of U.S. Food and Drug Administration (FDA)–approved drugs that cause LQTS as an adverse event were enriched in the LQTS neighborhood. With the LQTS neighborhood as a classifier, we predicted drugs likely to have risks for QT effects and we validated these predictions with the FDAs Adverse Events Reporting System, illustrating how network analysis can enhance the detection of adverse drug effects associated with drugs in clinical use. Thus, the identification of disease-selective neighborhoods within the human interactome can be useful for predicting new gene variants involved in disease, explaining the complexity underlying adverse drug side effects, and predicting adverse event susceptibility for new drugs. * To whom correspondence should be addressed. E-mail: Ravi.Iyengar{at}mssm.edu
Citation: S. I. Berger, A. Maayan, R. Iyengar, Systems Pharmacology of Arrhythmias. Sci. Signal. 3, ra30 (2010). The editors suggest the following Related Resources on Science sites:In Science Signaling
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