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Post-operative atrial fibrillation examined using whole-genome RNA sequencing in human left atrial tissue

Overview of attention for article published in BMC Medical Genomics, May 2017
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Title
Post-operative atrial fibrillation examined using whole-genome RNA sequencing in human left atrial tissue
Published in
BMC Medical Genomics, May 2017
DOI 10.1186/s12920-017-0270-5
Pubmed ID
Authors

Martin I Sigurdsson, Louis Saddic, Mahyar Heydarpour, Tzuu-Wang Chang, Prem Shekar, Sary Aranki, Gregory S Couper, Stanton K. Shernan, Jochen D. Muehlschlegel, Simon C. Body

Abstract

Both ambulatory atrial fibrillation (AF) and post-operative AF (poAF) are associated with substantial morbidity and mortality. Analyzing the tissue-specific gene expression in the left atrium (LA) can identify novel genes associated with AF and further the understanding of the mechanism by which previously identified genetic variants associated with AF mediate their effects. LA free wall samples were obtained intraoperatively immediately prior to mitral valve surgery in 62 Caucasian individuals. Gene expression was quantified on mRNA harvested from these samples using RNA sequencing. An expression quantitative trait loci (eQTL) analysis was performed, comparing gene expression between different genotypes of 1.0 million genetic markers, emphasizing genomic regions and genes associated with AF. Comparison of whole-genome expression between patients who later developed poAF and those who did not identified 23 differentially expressed genes. These included genes associated with the resting membrane potential modified by potassium currents, as well as genes within Wnt signaling and cyclic GMP metabolism. The eQTL analysis identified 16,139 cis eQTL relationships in the LA, including several involving genes and single nucleotide polymorphisms (SNPs) linked to AF. A previous relationship between rs3744029 and MYOZ1 expression was confirmed, and a novel relationship between rs6795970 and the expression of the SCN10A gene was identified. The current study is the first analysis of the human LA expression landscape using high-throughput RNA sequencing. Several novel genes and variants likely involved in AF pathogenesis were identified, thus furthering the understanding of how variants associated with AF mediate their effects via altered gene expression. ClinicalTrials.gov ID: NCT00833313 , registered 5. January 2009.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 17%
Researcher 6 15%
Student > Bachelor 5 12%
Student > Doctoral Student 3 7%
Other 3 7%
Other 10 24%
Unknown 7 17%
Readers by discipline Count As %
Medicine and Dentistry 16 39%
Biochemistry, Genetics and Molecular Biology 9 22%
Agricultural and Biological Sciences 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Computer Science 1 2%
Other 3 7%
Unknown 8 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 May 2017.
All research outputs
#14,906,275
of 24,135,931 outputs
Outputs from BMC Medical Genomics
#567
of 1,302 outputs
Outputs of similar age
#171,587
of 314,592 outputs
Outputs of similar age from BMC Medical Genomics
#10
of 20 outputs
Altmetric has tracked 24,135,931 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,302 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 54% of its peers.
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 314,592 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.