Literature DB >> 22726630

Symptomatic response to antiarrhythmic drug therapy is modulated by a common single nucleotide polymorphism in atrial fibrillation.

Babar Parvez1, Joseph Vaglio, Shane Rowan, Raafia Muhammad, Gayle Kucera, Tanya Stubblefield, Shannon Carter, Dan Roden, Dawood Darbar.   

Abstract

OBJECTIVES: This study tested the hypothesis that response to antiarrhythmic drugs (AADs) is modulated by 3 common loci associated with atrial fibrillation (AF).
BACKGROUND: Recent genome-wide association studies have identified 3 loci, on chromosomes 4q25 (near PITX2), 16q22 (in ZFHX3), and 1q21 (in KCNN3), that associate with either typical or lone AF. These findings indicate that variable mechanisms contribute to AF susceptibility, and suggest that response to therapy may be genotype dependent.
METHODS: We studied 478 and 198 Caucasian patients in the discovery cohort and validation cohort, respectively, who were prospectively enrolled in the Vanderbilt AF registry. Response was defined prospectively as successful rhythm control if the patient remained on the same AAD therapy for a minimum of 6 months with ≥75% reduction in symptomatic AF burden. We also evaluated AF recurrence by 12-lead electrocardiogram (ECG) at 3, 6, and 12 months. Symptomatic patients were also given a 24- to 48-h Holter monitor or 30-day event recorder when AF recurrence was not captured by 12-lead ECG.
RESULTS: In the discovery cohort, 399 (83%) patients were successfully rhythm controlled. Multiple clinical variables (including age, hypertension, lone AF) failed to significantly predict response to AADs; however, single nucleotide polymorphism (SNP) rs10033464 at 4q25 was an independent predictor of successful rhythm control in patients with typical AF carrying the ancestral allele (wild type) versus carriers of variant allele (odds ratio [OR]: 4.7, 95% confidence interval [CI]: 1.83 to 12, p = 0.0013. In the validation cohort, 143 (72%) patients met the criteria for successful rhythm control, and rs10033464 was again an independent predictor of successful rhythm control, OR: 1.5, 95% CI: 1.02 to 3.06, p = 0.04. This SNP (rs10033464) was an independent predictor of AF recurrence in the discovery (39% AF recurrence) and validation (38% AF recurrence) cohorts; OR: 3.27, 95% CI: 1.7 to 6, p < 0.001 and OR: 4.3, 95% CI: 1.98 to 9.4, p < 0.001, respectively.
CONCLUSIONS: These results suggest that a common SNP on chromosome 4q25 associated with AF modulates response to AAD therapy and points to a potential role for stratification of therapeutic approaches by genotype.
Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22726630      PMCID: PMC3411889          DOI: 10.1016/j.jacc.2012.01.070

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  31 in total

1.  Pitx2 prevents susceptibility to atrial arrhythmias by inhibiting left-sided pacemaker specification.

Authors:  Jun Wang; Elzbieta Klysik; Subeena Sood; Randy L Johnson; Xander H T Wehrens; James F Martin
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-10       Impact factor: 11.205

2.  Lone auricular fibrillation.

Authors:  W EVANS; P SWANN
Journal:  Br Heart J       Date:  1954-04

3.  PITX2c is expressed in the adult left atrium, and reducing Pitx2c expression promotes atrial fibrillation inducibility and complex changes in gene expression.

Authors:  Paulus Kirchhof; Peter C Kahr; Sven Kaese; Ilaria Piccini; Ismail Vokshi; Hans-Heinrich Scheld; Heinrich Rotering; Lisa Fortmueller; Sandra Laakmann; Sander Verheule; Ulrich Schotten; Larissa Fabritz; Nigel A Brown
Journal:  Circ Cardiovasc Genet       Date:  2011-01-31

4.  Pitx2c and Nkx2-5 are required for the formation and identity of the pulmonary myocardium.

Authors:  Mathilda T M Mommersteeg; Nigel A Brown; Owen W J Prall; Corrie de Gier-de Vries; Richard P Harvey; Antoon F M Moorman; Vincent M Christoffels
Journal:  Circ Res       Date:  2007-09-06       Impact factor: 17.367

5.  Stretch-sensitive KCNQ1 mutation A link between genetic and environmental factors in the pathogenesis of atrial fibrillation?

Authors:  Robyn Otway; Jamie I Vandenberg; Guanglan Guo; Anthony Varghese; M Leticia Castro; Jian Liu; JingTing Zhao; Jane A Bursill; Ken R Wyse; Haley Crotty; Olivia Baddeley; Bruce Walker; Dennis Kuchar; Charles Thorburn; Diane Fatkin
Journal:  J Am Coll Cardiol       Date:  2007-01-22       Impact factor: 24.094

Review 6.  Epidemiology of atrial fibrillation: a current perspective.

Authors:  Lin Y Chen; Win-Kuang Shen
Journal:  Heart Rhythm       Date:  2006-12-15       Impact factor: 6.343

7.  Variants in ZFHX3 are associated with atrial fibrillation in individuals of European ancestry.

Authors:  Emelia J Benjamin; Kenneth M Rice; Dan E Arking; Arne Pfeufer; Charlotte van Noord; Albert V Smith; Renate B Schnabel; Joshua C Bis; Eric Boerwinkle; Moritz F Sinner; Abbas Dehghan; Steven A Lubitz; Ralph B D'Agostino; Thomas Lumley; Georg B Ehret; Jan Heeringa; Thor Aspelund; Christopher Newton-Cheh; Martin G Larson; Kristin D Marciante; Elsayed Z Soliman; Fernando Rivadeneira; Thomas J Wang; Gudny Eiríksdottir; Daniel Levy; Bruce M Psaty; Man Li; Alanna M Chamberlain; Albert Hofman; Ramachandran S Vasan; Tamara B Harris; Jerome I Rotter; W H Linda Kao; Sunil K Agarwal; Bruno H Ch Stricker; Ke Wang; Lenore J Launer; Nicholas L Smith; Aravinda Chakravarti; André G Uitterlinden; Philip A Wolf; Nona Sotoodehnia; Anna Köttgen; Cornelia M van Duijn; Thomas Meitinger; Martina Mueller; Siegfried Perz; Gerhard Steinbeck; H-Erich Wichmann; Kathryn L Lunetta; Susan R Heckbert; Vilmundur Gudnason; Alvaro Alonso; Stefan Kääb; Patrick T Ellinor; Jacqueline C M Witteman
Journal:  Nat Genet       Date:  2009-07-13       Impact factor: 38.330

8.  Common variants in KCNN3 are associated with lone atrial fibrillation.

Authors:  Patrick T Ellinor; Kathryn L Lunetta; Nicole L Glazer; Arne Pfeufer; Alvaro Alonso; Mina K Chung; Moritz F Sinner; Paul I W de Bakker; Martina Mueller; Steven A Lubitz; Ervin Fox; Dawood Darbar; Nicholas L Smith; Jonathan D Smith; Renate B Schnabel; Elsayed Z Soliman; Kenneth M Rice; David R Van Wagoner; Britt-M Beckmann; Charlotte van Noord; Ke Wang; Georg B Ehret; Jerome I Rotter; Stanley L Hazen; Gerhard Steinbeck; Albert V Smith; Lenore J Launer; Tamara B Harris; Seiko Makino; Mari Nelis; David J Milan; Siegfried Perz; Tõnu Esko; Anna Köttgen; Susanne Moebus; Christopher Newton-Cheh; Man Li; Stefan Möhlenkamp; Thomas J Wang; W H Linda Kao; Ramachandran S Vasan; Markus M Nöthen; Calum A MacRae; Bruno H Ch Stricker; Albert Hofman; André G Uitterlinden; Daniel Levy; Eric Boerwinkle; Andres Metspalu; Eric J Topol; Aravinda Chakravarti; Vilmundur Gudnason; Bruce M Psaty; Dan M Roden; Thomas Meitinger; H-Erich Wichmann; Jacqueline C M Witteman; John Barnard; Dan E Arking; Emelia J Benjamin; Susan R Heckbert; Stefan Kääb
Journal:  Nat Genet       Date:  2010-02-21       Impact factor: 38.330

9.  Polymorphism modulates symptomatic response to antiarrhythmic drug therapy in patients with lone atrial fibrillation.

Authors:  Dawood Darbar; Alison A Motsinger; Marylyn D Ritchie; James V Gainer; Dan M Roden
Journal:  Heart Rhythm       Date:  2007-02-09       Impact factor: 6.343

10.  Prevalence, age distribution, and gender of patients with atrial fibrillation. Analysis and implications.

Authors:  W M Feinberg; J L Blackshear; A Laupacis; R Kronmal; R G Hart
Journal:  Arch Intern Med       Date:  1995-03-13
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  55 in total

1.  Can polymorphisms predict response to antiarrhythmic drugs in atrial fibrillation?

Authors:  James P Daubert; Geoffrey S Pitt
Journal:  J Am Coll Cardiol       Date:  2012-06-20       Impact factor: 24.094

Review 2.  Genome-wide association studies of late-onset cardiovascular disease.

Authors:  J Gustav Smith; Christopher Newton-Cheh
Journal:  J Mol Cell Cardiol       Date:  2015-04-11       Impact factor: 5.000

Review 3.  Cardiovascular pharmacogenomics: current status and future directions.

Authors:  Dan M Roden
Journal:  J Hum Genet       Date:  2015-07-16       Impact factor: 3.172

Review 4.  Emerging directions in the genetics of atrial fibrillation.

Authors:  Nathan R Tucker; Patrick T Ellinor
Journal:  Circ Res       Date:  2014-04-25       Impact factor: 17.367

5.  Germline versus somatic mutations in genetic atrial fibrillation.

Authors:  Mark McCauley; Dawood Darbar
Journal:  Heart Rhythm       Date:  2017-07-20       Impact factor: 6.343

Review 6.  Imaging for Risk Stratification in Atrial Fibrillation with Heart Failure.

Authors:  Kennosuke Yamashita; Ravi Ranjan
Journal:  Cardiol Clin       Date:  2019-02-22       Impact factor: 2.213

Review 7.  The Genetic Basis of Coronary Artery Disease and Atrial Fibrillation: A Search for Disease Mechanisms and Therapeutic Targets.

Authors:  Jacques Neelankavil; Christoph D Rau; Yibin Wang
Journal:  J Cardiothorac Vasc Anesth       Date:  2015-01-23       Impact factor: 2.628

Review 8.  The Role of Pharmacogenetics in Atrial Fibrillation Therapeutics: Is Personalized Therapy in Sight?

Authors:  Dawood Darbar
Journal:  J Cardiovasc Pharmacol       Date:  2016-01       Impact factor: 3.105

9.  Common genetic polymorphism at 4q25 locus predicts atrial fibrillation recurrence after successful cardioversion.

Authors:  Babar Parvez; M Benjamin Shoemaker; Raafia Muhammad; Rachael Richardson; Lan Jiang; Marcia A Blair; Dan M Roden; Dawood Darbar
Journal:  Heart Rhythm       Date:  2013-02-19       Impact factor: 6.343

10.  Strategies for Risk Analysis and Disease Classification in Atrial Fibrillation.

Authors:  Sara Adelman; Georges Daoud; Peter J Mohler
Journal:  J Cardiovasc Electrophysiol       Date:  2016-09-20
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