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Combinatorial Pharmacogenetic Interactions of Bucindolol and β1, α2C Adrenergic Receptor Polymorphisms

Overview of attention for article published in PLOS ONE, October 2012
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Title
Combinatorial Pharmacogenetic Interactions of Bucindolol and β1, α2C Adrenergic Receptor Polymorphisms
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0044324
Pubmed ID
Authors

Christopher M. O'Connor, Mona Fiuzat, Peter E. Carson, Inder S. Anand, Jonathan F. Plehn, Stephen S. Gottlieb, Marc A. Silver, JoAnn Lindenfeld, Alan B. Miller, Michel White, Ryan Walsh, Penny Nelson, Allen Medway, Gordon Davis, Alastair D. Robertson, J. David Port, James Carr, Guinevere A. Murphy, Laura C. Lazzeroni, William T. Abraham, Stephen B. Liggett, Michael R. Bristow

Abstract

Pharmacogenetics involves complex interactions of gene products affecting pharmacodynamics and pharmacokinetics, but there is little information on the interaction of multiple genetic modifiers of drug response. Bucindolol is a β-blocker/sympatholytic agent whose efficacy is modulated by polymorphisms in the primary target (β(1) adrenergic receptor [AR] Arg389 Gly on cardiac myocytes) and a secondary target modifier (α(2C) AR Ins [wild-type (Wt)] 322-325 deletion [Del] on cardiac adrenergic neurons). The major allele homozygotes and minor allele carriers of each polymorphism are respectively associated with efficacy enhancement and loss, creating the possibility for genotype combination interactions that can be measured by clinical trial methodology.

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The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Other 5 19%
Professor 4 15%
Professor > Associate Professor 3 12%
Student > Bachelor 2 8%
Researcher 2 8%
Other 5 19%
Unknown 5 19%
Readers by discipline Count As %
Medicine and Dentistry 8 31%
Agricultural and Biological Sciences 6 23%
Biochemistry, Genetics and Molecular Biology 2 8%
Computer Science 1 4%
Nursing and Health Professions 1 4%
Other 2 8%
Unknown 6 23%