↓ Skip to main content

The arrhythmogenic cardiomyopathy-specific coding and non-coding transcriptome in human cardiac stromal cells

Overview of attention for article published in BMC Genomics, June 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The arrhythmogenic cardiomyopathy-specific coding and non-coding transcriptome in human cardiac stromal cells
Published in
BMC Genomics, June 2018
DOI 10.1186/s12864-018-4876-6
Pubmed ID
Authors

Johannes Rainer, Viviana Meraviglia, Hagen Blankenburg, Chiara Piubelli, Peter P. Pramstaller, Adolfo Paolin, Elisa Cogliati, Giulio Pompilio, Elena Sommariva, Francisco S. Domingues, Alessandra Rossini

Abstract

Arrhythmogenic cardiomyopathy (ACM) is a genetic autosomal disease characterized by abnormal cell-cell adhesion, cardiomyocyte death, progressive fibro-adipose replacement of the myocardium, arrhythmias and sudden death. Several different cell types contribute to the pathogenesis of ACM, including, as recently described, cardiac stromal cells (CStCs). In the present study, we aim to identify ACM-specific expression profiles of human CStCs derived from endomyocardial biopsies of ACM patients and healthy individuals employing TaqMan Low Density Arrays for miRNA expression profiling, and high throughput sequencing for gene expression quantification. We identified 3 miRNAs and 272 genes as significantly differentially expressed at a 5% false discovery rate. Both the differentially expressed genes as well as the target genes of the ACM-specific miRNAs were found to be enriched in cell adhesion-related biological processes. Functional similarity and protein interaction-based network analyses performed on the identified deregulated genes, miRNA targets and known ACM-causative genes revealed clusters of highly related genes involved in cell adhesion, extracellular matrix organization, lipid transport and ephrin receptor signaling. We determined for the first time the coding and non-coding transcriptome characteristic of ACM cardiac stromal cells, finding evidence for a potential contribution of miRNAs, specifically miR-29b-3p, to ACM pathogenesis or phenotype maintenance.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 21%
Researcher 3 16%
Student > Bachelor 2 11%
Lecturer > Senior Lecturer 1 5%
Student > Doctoral Student 1 5%
Other 2 11%
Unknown 6 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 26%
Medicine and Dentistry 3 16%
Agricultural and Biological Sciences 2 11%
Materials Science 1 5%
Unknown 8 42%

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 27 June 2018.
All research outputs
#7,920,225
of 13,145,206 outputs
Outputs from BMC Genomics
#4,457
of 7,741 outputs
Outputs of similar age
#149,406
of 268,718 outputs
Outputs of similar age from BMC Genomics
#4
of 7 outputs
Altmetric has tracked 13,145,206 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 7,741 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 37th percentile – i.e., 37% 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 268,718 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.