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Whole-exome sequencing identifies novel pathogenic mutations and putative phenotype-influencing variants in Polish limb-girdle muscular dystrophy patients

Overview of attention for article published in Human Genomics, July 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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1 policy source
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2 X users
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1 Wikipedia page

Citations

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41 Dimensions

Readers on

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56 Mendeley
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Title
Whole-exome sequencing identifies novel pathogenic mutations and putative phenotype-influencing variants in Polish limb-girdle muscular dystrophy patients
Published in
Human Genomics, July 2018
DOI 10.1186/s40246-018-0167-1
Pubmed ID
Authors

Jakub Piotr Fichna, Anna Macias, Marcin Piechota, Michał Korostyński, Anna Potulska-Chromik, Maria Jolanta Redowicz, Cezary Zekanowski

Abstract

Limb girdle muscular dystrophies (LGMD) are a group of heterogeneous hereditary myopathies with similar clinical symptoms. Disease onset and progression are highly variable, with an elusive genetic background, and around 50% cases lacking molecular diagnosis. Whole exome sequencing (WES) was performed in 73 patients with clinically diagnosed LGMD. A filtering strategy aimed at identification of variants related to the disease included integrative analysis of WES data and human phenotype ontology (HPO) terms, analysis of genes expressed in muscle, analysis of the disease-associated interactome and copy number variants analysis. Genetic diagnosis was possible in 68.5% of cases. On average, 36.3 rare variants in genes associated with various muscle diseases per patient were found that could relate to the clinical phenotype. The putative causative mutations were mostly in LGMD-associated genes, but also in genes not included in the current LGMD classification (DMD, COL6A2, and COL6A3). In three patients, mutations in two genes were suggested as the joint cause of the disease (CAPN3+MYH7, COL6A3+CACNA1S, DYSF+MYH7). Moreover, a variety of phenotype-influencing variants were postulated, including in patients with an identified already known primary pathogenic mutation. We hypothesize that LGMD could be better described as oligogenic disorders in which dominant clinical presentation can result from the combined effect of mutations in a set of genes. In this view, the inter- and intrafamilial variability could reflect a specific genetic background and the presence of sets of phenotype-influencing or co-causative mutations in genes that either interact with the known LGMD-associated genes or are a part of the same pathways or structures.

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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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 18%
Student > Ph. D. Student 7 13%
Researcher 5 9%
Student > Doctoral Student 4 7%
Student > Postgraduate 4 7%
Other 8 14%
Unknown 18 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 27%
Medicine and Dentistry 9 16%
Neuroscience 5 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Veterinary Science and Veterinary Medicine 2 4%
Other 5 9%
Unknown 18 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 November 2022.
All research outputs
#4,978,221
of 26,017,215 outputs
Outputs from Human Genomics
#119
of 577 outputs
Outputs of similar age
#87,578
of 344,233 outputs
Outputs of similar age from Human Genomics
#4
of 11 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 577 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 77% 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 344,233 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 11 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 63% of its contemporaries.