Literature DB >> 23261005

Impact of β(1)- and β(2)-adrenergic receptor gene single nucleotide polymorphisms on heart rate response to metoprolol prior to coronary computed tomographic angiography.

Vlad Cotarlan1, Alessandra Brofferio, Glenn S Gerhard, Xin Chu, Jamshid Shirani.   

Abstract

A slow, steady heart rate (HR) is necessary for optimal image quality during coronary computed tomographic angiography. Beta blockers are often used, but the goal HR is not achieved in some patients. The aim of this study was to examine the influence of single-nucleotide polymorphisms (SNPs) of the β(1) (codons 49 and 389) and β(2) (codons 16, 27, and 164) adrenergic receptor (AR) genes on HR response to metoprolol in 200 adults (mean age 56 ± 11 years) referred for coronary computed tomographic angiography (using a 64-slice scanner). Oral and intravenous (IV) metoprolol was given to achieve a goal HR of <60 beats/min. Overall, 37 patients (18.5%) did not reach the goal HR despite the administration of oral (181 ± 116 mg) and IV (4.2 ± 9.4 mg) metoprolol. Patients with the β(1)-AR Ser49Gly or Gly49Gly genotype (n = 49) more often failed to reach an optimal HR compared to those with the Ser49Ser genotype (n = 151) (29% vs 15%, p = 0.04), despite receiving higher doses of oral (210 ± 115 vs 172 ± 115 mg, p = 0.048) and IV (7 ± 13 vs 3 ± 8 mg, p = 0.02) metoprolol. Similarly, patients with the β(1)-AR Gly389Gly genotype (n = 11) more often failed to reach an optimal HR compared to those with the Arg389Arg and Arg389Gly genotypes (n = 189) (45% vs 17%, p = 0.02), despite receiving higher doses of IV (13 ± 15 vs 4 ± 9 mg, p = 0.002) but not oral (162 ± 105 vs 182 ± 117 mg, p = 0.50) metoprolol. Multivariate analysis identified β(1)-AR SNPs at codons 49 and 389 and β(2)-AR SNP at codon 27 as independent predictors of suboptimal HR response. In conclusion, these data indicate that the selected SNPs of β(1)-AR and β(2)-AR genes influence HR response to metoprolol in patients who undergo coronary computed tomographic angiography.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23261005     DOI: 10.1016/j.amjcard.2012.11.015

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  5 in total

Review 1.  Germline genetic variants with implications for disease risk and therapeutic outcomes.

Authors:  Amy L Pasternak; Kristen M Ward; Jasmine A Luzum; Vicki L Ellingrod; Daniel L Hertz
Journal:  Physiol Genomics       Date:  2017-09-08       Impact factor: 3.107

2.  β2 -Adrenergic Receptor Gene Affects the Heart Rate Response of β-Blockers: Evidence From 3 Clinical Studies.

Authors:  Mohamed H Shahin; Nihal El Rouby; Daniela J Conrado; Daniel Gonzalez; Yan Gong; Maximilian T Lobmeyer; Amber L Beitelshees; Eric Boerwinkle; John G Gums; Arlene Chapman; Stephen T Turner; Carl J Pepine; Rhonda M Cooper-DeHoff; Julie A Johnson
Journal:  J Clin Pharmacol       Date:  2019-05-14       Impact factor: 3.126

3.  ADRB2 polymorphisms predict the risk of myocardial infarction and coronary artery disease.

Authors:  Dong-Wei Wang; Min Liu; Ping Wang; Xiang Zhan; Yu-Qing Liu; Luo-Sha Zhao
Journal:  Genet Mol Biol       Date:  2015-11-24       Impact factor: 1.771

4.  Relationship between polymorphisms in beta -2 adrenergic receptor gene and ischemic stroke in North Indian Population: a hospital based case control study.

Authors:  Amit Kumar; Manjari Tripathi; Madakasira Vasantha Padma Srivastava; Subbiah Vivekanandhan; Kameshwar Prasad
Journal:  BMC Res Notes       Date:  2014-06-25

5.  Genome-Wide Association Approach Identified Novel Genetic Predictors of Heart Rate Response to β-Blockers.

Authors:  Mohamed H Shahin; Daniela J Conrado; Daniel Gonzalez; Yan Gong; Maximilian T Lobmeyer; Amber L Beitelshees; Eric Boerwinkle; John G Gums; Arlene Chapman; Stephen T Turner; Rhonda M Cooper-DeHoff; Julie A Johnson
Journal:  J Am Heart Assoc       Date:  2018-02-24       Impact factor: 5.501

  5 in total

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