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Molecular analysis of inherited cardiomyopathy using next generation semiconductor sequencing technologies

Overview of attention for article published in Journal of Translational Medicine, August 2018
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Title
Molecular analysis of inherited cardiomyopathy using next generation semiconductor sequencing technologies
Published in
Journal of Translational Medicine, August 2018
DOI 10.1186/s12967-018-1605-5
Pubmed ID
Authors

Chaoxia Lu, Wei Wu, Fang Liu, Kunqi Yang, Jiacheng Li, Yaping Liu, Rongrong Wang, Nuo Si, Peng Gao, Yongtai Liu, Shuyang Zhang, Xue Zhang

Abstract

Cardiomyopathies are the most common clinical and genetic heterogeneity cardiac diseases, and genetic contribution in particular plays a major role in patients with primary cardiomyopathies. The aim of this study is to investigate cases of inherited cardiomyopathy (IC) for potential disease-causing mutations in 64 genes reported to be associated with IC. A total of 110 independent cases or families diagnosed with various primary cardiomyopathies, including hypertrophic cardiomyopathy, dilated cardiomyopathy, restrictive cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, left ventricular non-compaction, and undefined cardiomyopathy, were collected after informed consent. A custom designed panel, including 64 genes, was screened using next generation sequencing on the Ion Torrent PGM platform. The best candidate disease-causing variants were verified by Sanger sequencing. A total of 78 variants in 73 patients were identified. After excluding the variants predicted to be benign and VUS, 26 pathogenic or likely pathogenic variants were verified in 26 probands (23.6%), including a homozygous variant in the SLC25A4 gene. Of these variants, 15 have been reported in the Human Gene Mutation Database or ClinVar database, while 11 are novel. The majority of variants were observed in the MYH7 (8/26) and MYBPC3 (6/26) gene. Titin (TTN) truncating mutations account for 13% in our dilated cardiomyopathy cases (3/23). This study provides an overview of the genetic aberrations in this cohort of Chinese IC patients and demonstrates the power of next generation sequencing in IC. Genetic results can provide precise clinical diagnosis and guidance regarding medical care for some individuals.

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X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 12%
Student > Ph. D. Student 4 12%
Researcher 3 9%
Student > Doctoral Student 2 6%
Student > Master 2 6%
Other 2 6%
Unknown 16 48%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 24%
Medicine and Dentistry 5 15%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Agricultural and Biological Sciences 1 3%
Nursing and Health Professions 1 3%
Other 2 6%
Unknown 15 45%
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 01 September 2018.
All research outputs
#17,989,170
of 23,102,082 outputs
Outputs from Journal of Translational Medicine
#2,783
of 4,055 outputs
Outputs of similar age
#240,211
of 334,790 outputs
Outputs of similar age from Journal of Translational Medicine
#39
of 86 outputs
Altmetric has tracked 23,102,082 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 4,055 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. 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 334,790 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.