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Next-generation sequencing-based molecular diagnosis of 82 retinitis pigmentosa probands from Northern Ireland

Overview of attention for article published in Human Genetics, December 2014
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Title
Next-generation sequencing-based molecular diagnosis of 82 retinitis pigmentosa probands from Northern Ireland
Published in
Human Genetics, December 2014
DOI 10.1007/s00439-014-1512-7
Pubmed ID
Authors

Li Zhao, Feng Wang, Hui Wang, Yumei Li, Sharon Alexander, Keqing Wang, Colin E. Willoughby, Jacques E. Zaneveld, Lichun Jiang, Zachry T. Soens, Philip Earle, David Simpson, Giuliana Silvestri, Rui Chen

Abstract

Retinitis pigmentosa (RP) is a group of inherited retinal disorders characterized by progressive photoreceptor degeneration. An accurate molecular diagnosis is essential for disease characterization and clinical prognoses. A retinal capture panel that enriches 186 known retinal disease genes, including 55 known RP genes, was developed. Targeted next-generation sequencing was performed for a cohort of 82 unrelated RP cases from Northern Ireland, including 46 simplex cases and 36 familial cases. Disease-causing mutations were identified in 49 probands, including 28 simplex cases and 21 familial cases, achieving a solving rate of 60 %. In total, 65 pathogenic mutations were found, and 29 of these were novel. Interestingly, the molecular information of 12 probands was neither consistent with their initial inheritance pattern nor clinical diagnosis. Further clinical reassessment resulted in a refinement of the clinical diagnosis in 11 patients. This is the first study to apply next-generation sequencing-based, comprehensive molecular diagnoses to a large number of RP probands from Northern Ireland. Our study shows that molecular information can aid clinical diagnosis, potentially changing treatment options, current family counseling and management.

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Mendeley readers

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Geographical breakdown

Country Count As %
South Africa 1 1%
Unknown 84 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 16%
Researcher 14 16%
Student > Master 9 11%
Student > Bachelor 6 7%
Other 5 6%
Other 17 20%
Unknown 20 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 22%
Agricultural and Biological Sciences 15 18%
Medicine and Dentistry 13 15%
Unspecified 3 4%
Nursing and Health Professions 2 2%
Other 9 11%
Unknown 24 28%
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 05 December 2014.
All research outputs
#20,245,139
of 22,772,779 outputs
Outputs from Human Genetics
#2,815
of 2,951 outputs
Outputs of similar age
#302,151
of 360,775 outputs
Outputs of similar age from Human Genetics
#13
of 18 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,951 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.