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Targeted myocardial gene expression in failing hearts by RNA sequencing

Overview of attention for article published in Journal of Translational Medicine, November 2016
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Title
Targeted myocardial gene expression in failing hearts by RNA sequencing
Published in
Journal of Translational Medicine, November 2016
DOI 10.1186/s12967-016-1083-6
Pubmed ID
Authors

Kajari Dhar, Alexandra M. Moulton, Eric Rome, Fang Qiu, Jeff Kittrell, Eugenia Raichlin, Ronald Zolty, John Y. Um, Michael J. Moulton, Hesham Basma, Daniel R. Anderson, James D. Eudy, Brian D. Lowes

Abstract

Myocardial recovery with left ventricular assist device (LVAD) therapy is highly variable and difficult to predict. Next generation ribonucleic acid (RNA) sequencing is an innovative, rapid, and quantitative approach to gene expression profiling in small amounts of tissue. Our primary goal was to identify baseline transcriptional profiles in non-ischemic cardiomyopathies that predict myocardial recovery in response to LVAD therapy. We also sought to verify transcriptional differences between failing and non-failing human hearts. RNA was isolated from failing (n = 16) and non-failing (n = 8) human hearts. RNA from each patient was reverse transcribed and quantitatively sequenced on the personal genome machine (PGM) sequencer (Ion torrent) for 95 heart failure candidate genes. Coverage analysis as well as mapping the reads and alignment was done using the Ion Torrent Browser Suite™. Differential expression analyses were conducted by empirical analysis of digital gene expression data in R (edgeR) to identify differential expressed genes between failing and non-failing groups, and between responder and non-responder groups respectively. Targeted cardiac gene messenger RNA (mRNA) expression was analyzed in proportion to the total number of reads. Gene expression profiles from the PGM sequencer were validated by performing RNA sequencing (RNAseq) with the Illumina Hiseq2500 sequencing system. The failing sample population was 75% male with an average age of 50 and a left ventricular ejection fraction (LVEF) of 16%. Myosin light chain kinase (MYLK) and interleukin (IL)-6 genes expression were significantly higher in LVAD responders compared to non-responders. Thirty-six cardiac genes were expressed differentially between failing and non-failing hearts (23 decreased, 13 elevated). MYLK, Beta-1 adrenergic receptor (ADRB1) and myosin heavy chain (MYH)-6 expression were among those significantly decreased in failing hearts compared to non-failing hearts. Natriuretic peptide B (NPPB) and IL-6 were significantly elevated. Targeted gene expression profiles obtained from the Ion torrent PGM sequencer were consistent with those obtained from Illumina HiSeq2500 sequencing system. Heart failure is associated with a network of transcriptional changes involving contractile proteins, metabolism, adrenergic receptors, protein phosphorylation, and signaling factors. Myocardial MYLK and IL-6 expression are positively correlated with ejection fraction (EF) response to LVAD placement. Targeted RNA sequencing of myocardial gene expression can be utilized to predict responders to LVAD therapy and to better characterize transcriptional changes in human heart failure.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Student > Bachelor 7 17%
Researcher 6 14%
Student > Ph. D. Student 4 10%
Lecturer 3 7%
Other 8 19%
Unknown 7 17%
Readers by discipline Count As %
Medicine and Dentistry 13 31%
Biochemistry, Genetics and Molecular Biology 8 19%
Agricultural and Biological Sciences 4 10%
Engineering 2 5%
Immunology and Microbiology 2 5%
Other 4 10%
Unknown 9 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 November 2016.
All research outputs
#17,828,338
of 22,903,988 outputs
Outputs from Journal of Translational Medicine
#2,748
of 4,010 outputs
Outputs of similar age
#286,730
of 415,669 outputs
Outputs of similar age from Journal of Translational Medicine
#55
of 62 outputs
Altmetric has tracked 22,903,988 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,010 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 415,669 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.