Dataset Information

Clustering heart rate dynamics is associated with ?-adrenergic receptor polymorphisms: analysis by information-based similarity index.

ABSTRACT: BACKGROUND: Genetic polymorphisms in the gene encoding the ?-adrenergic receptors (?-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 ?-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 ?-AR polymorphisms: ?(1)-AR Ser49Gly, ?(2)-AR Arg16Gly and ?(2)-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 ?(2)-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 ?-AR polymorphisms. Our results provide evidence that ?(2)-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control.

SUBMITTER: Yang AC

PROVIDER: S-EPMC3087751 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Clustering heart rate dynamics is associated with β-adrenergic receptor polymorphisms: analysis by information-based similarity index.

Yang Albert C AC Tsai Shih-Jen SJ Hong Chen-Jee CJ Wang Cynthia C Chen Tai-Jui TJ Liou Ying-Jay YJ Peng Chung-Kang CK

PloS one 20110504 5

<h4>Background</h4>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.<h4>Methods</h4>A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6 ± 10.8 years, range 19 to 6 ...[more]

PMID: 21573230

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Project description:BackgroundBiological knowledge, and therefore Gene Ontology annotation sets, for human genes is incomplete. Recent studies have reported that biases in available GO annotations result in biased estimates of functional similarities of genes, but it is still unclear what the effect of incompleteness itself may be, even in the absence of bias. Pairwise gene similarities are used in a number of contexts, including gene "functional similarity" clustering and the related problem of functional ontology structure inference, but it is not known how different similarity measures or clustering methods perform on this task, and how the clusters are affected by annotation completeness.ResultsWe developed representations of both "complete" and "incomplete" GO annotation datasets based on experimentally-supported annotations from the GO database-specifically designed to model the incompleteness of human gene annotations-and computed semantic similarities for each set using a variety of different published measures. We then assessed the clusters derived from these measures using two different clustering methods: hierarchical clustering, and the CliXO algorithm. We find the CliXO algorithm, combined with appropriate measures, performs better than hierarchical clustering in reconstructing GO both when the data are complete, and incomplete. Some measures, particularly those that create a pairwise gene similarity by averaging over all pairwise annotation similarities, had consistently poor performance, and a few measures, such as Lin best-matched average and Relevance maximum, were generally among the best performers for a broad range in annotation completeness and types of GO classes. Finally, we show that for semantic similarity-based clustering, the multicellular organism process branch of the GO biological process ontology is more challenging to represent than the cellular process branch.ConclusionsWe assessed the effects of annotation completeness on the distribution of pairwise gene semantic similarity scores, and subsequent effects on the clusters derived from these scores. Our results suggest combinations of semantic similarity measures, gene-level scoring methods and clustering method that perform best for functional gene clustering using annotation sets of varying completeness. Overall, our results underscore the importance of increasing the completeness of GO annotations to for supporting computational analyses of gene function.

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Dataset Information

Clustering heart rate dynamics is associated with ?-adrenergic receptor polymorphisms: analysis by information-based similarity index.

Publications

Clustering heart rate dynamics is associated with β-adrenergic receptor polymorphisms: analysis by information-based similarity index.

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