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Gender Differences in Electrophysiological Gene Expression in Failing and Non-Failing Human Hearts

Overview of attention for article published in PLOS ONE, January 2013
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Title
Gender Differences in Electrophysiological Gene Expression in Failing and Non-Failing Human Hearts
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0054635
Pubmed ID
Authors

Christina M. Ambrosi, Kathryn A. Yamada, Jeanne M. Nerbonne, Igor R. Efimov

Abstract

The increasing availability of human cardiac tissues for study are critically important in increasing our understanding of the impact of gender, age, and other parameters, such as medications and cardiac disease, on arrhythmia susceptibility. In this study, we aimed to compare the mRNA expression of 89 ion channel subunits, calcium handling proteins, and transcription factors important in cardiac conduction and arrhythmogenesis in the left atria (LA) and ventricles (LV) of failing and nonfailing human hearts of both genders. Total RNA samples, prepared from failing male (n = 9) and female (n = 7), and from nonfailing male (n = 9) and female (n = 9) hearts, were probed using custom-designed Taqman gene arrays. Analyses were performed to explore the relationships between gender, failure state, and chamber expression. Hierarchical cluster analysis revealed chamber specific expression patterns, but failed to identify disease- or gender-dependent clustering. Gender-specific analysis showed lower expression levels in transcripts encoding for K(v)4.3, KChIP2, K(v)1.5, and K(ir)3.1 in the failing female as compared with the male LA. Analysis of LV transcripts, however, did not reveal significant differences based on gender. Overall, our data highlight the differential expression and transcriptional remodeling of ion channel subunits in the human heart as a function of gender and cardiac disease. Furthermore, the availability of such data sets will allow for the development of disease-, gender-, and, most importantly, patient-specific cardiac models, with the ability to utilize such information as mRNA expression to predict cardiac phenotype.

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Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 25%
Researcher 16 24%
Student > Bachelor 5 7%
Student > Postgraduate 4 6%
Professor > Associate Professor 4 6%
Other 11 16%
Unknown 11 16%
Readers by discipline Count As %
Medicine and Dentistry 16 24%
Engineering 11 16%
Biochemistry, Genetics and Molecular Biology 7 10%
Agricultural and Biological Sciences 6 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Other 10 15%
Unknown 15 22%