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  5. A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium

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Article
English
2016

A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium

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English
2016
Journal of Medical Genetics
Vol 54 (5)
DOI: 10.1136/jmedgenet-2016-104112

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Frits R. Rosendaal
Frits R. Rosendaal

Leiden University

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Raymond Noordam
Colleen M. Sitlani
Christy L. Avery
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Abstract

<h3>Background</h3> Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals. <h3>Methods and results</h3> We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in <i>BRE</i> (β=56.3, p<sub>interaction</sub>=3.9e<sup>−9</sup>) and rs9830388 in <i>UBE2E2</i> (β=25.2, p<sub>interaction</sub>=1.7e<sup>−8</sup>). In Hispanic/Latino cohorts, rs2291477 in <i>TGFBR3</i> significantly modified the association between TCAs and QT intervals (β=9.3, p<sub>interaction</sub>=2.55e<sup>−8</sup>). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (p<sub>interaction</sub>&gt;0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries. <h3>Conclusions</h3> Among Europeans, TCA interactions with variants in <i>BRE</i> and <i>UBE2E2</i> were identified in relation to RR intervals. Among Hispanic/Latinos, variants in <i>TGFBR3</i> modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.

How to cite this publication

Raymond Noordam, Colleen M. Sitlani, Christy L. Avery, James D. Stewart, Stephanie M. Gogarten, Kerri L. Wiggins, Stella Trompet, Helen R. Warren, Fangui Sun, Daniel S. Evans, Xiaohui Li, Jin Li, Albert V. Smith, Joshua C. Bis, Jennifer A. Brody, Evan L. Busch, Mark J. Caulfield, Yii‐Der I. Chen, Steven R. Cummings, L. Adrienne Cupples, Qing Duan, Oscar H. Franco, Raúl Méndez-Giráldez, Tamara B. Harris, Susan R. Heckbert, Diana van Heemst, Albert Hofman, James S. Floyd, Jan A. Kors, Lenore J. Launer, Yun Li, Ruifang Li‐Gao, Leslie A. Lange, Henry J. Lin, Renée de Mutsert, Melanie Napier, Christopher Newton‐Cheh, Neil R Poulter, Alexander P. Reiner, Kenneth Rice, Jeffrey Roach, Carlos J. Rodríguez, Frits R. Rosendaal, Naveed Sattar, Peter Sever, Amanda A. Seyerle, P. Eline Slagboom, Elsayed Z. Soliman, Nona Sotoodehnia, David J. Stott, Til Stürmer‎, Kent D. Taylor, Timothy A. Thornton, André G. Uitterlinden, Kirk C. Wilhelmsen, James G. Wilson, Vilmundur Guðnason, J. Wouter Jukema, Cathy C. Laurie, Yongmei Liu, Dennis O. Mook‐Kanamori, Patricia B. Munroe, Jerome I. Rotter, Ramachandran S. Vasan, Bruce M. Psaty, Bruno H. Stricker, Eric A. Whitsel (2016). A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Journal of Medical Genetics, 54(5), pp. 313-323, DOI: 10.1136/jmedgenet-2016-104112.

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Publication Details

Type

Article

Year

2016

Authors

67

Datasets

0

Total Files

0

Language

English

Journal

Journal of Medical Genetics

DOI

10.1136/jmedgenet-2016-104112

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