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Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

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Listed:
  • Albert C Yang
  • Shih-Jen Tsai
  • Chen-Jee Hong
  • Cynthia Wang
  • Tai-Jui Chen
  • Ying-Jay Liou
  • Chung-Kang Peng

Abstract

Background: Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods: A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results: With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions: We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control.

Suggested Citation

  • Albert C Yang & Shih-Jen Tsai & Chen-Jee Hong & Cynthia Wang & Tai-Jui Chen & Ying-Jay Liou & Chung-Kang Peng, 2011. "Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-8, May.
  • Handle: RePEc:plo:pone00:0019232
    DOI: 10.1371/journal.pone.0019232
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    Cited by:

    1. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.

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