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Next generation sequencing-based molecular diagnosis of retinitis pigmentosa: identification of a novel genotype-phenotype correlation and clinical refinements

Overview of attention for article published in Human Genetics, October 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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2 policy sources
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2 X users
googleplus
1 Google+ user

Citations

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208 Dimensions

Readers on

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146 Mendeley
Title
Next generation sequencing-based molecular diagnosis of retinitis pigmentosa: identification of a novel genotype-phenotype correlation and clinical refinements
Published in
Human Genetics, October 2013
DOI 10.1007/s00439-013-1381-5
Pubmed ID
Authors

Feng Wang, Hui Wang, Han-Fang Tuan, Duy H. Nguyen, Vincent Sun, Vafa Keser, Sara J. Bowne, Lori S. Sullivan, Hongrong Luo, Ling Zhao, Xia Wang, Jacques E. Zaneveld, Jason S. Salvo, Sorath Siddiqui, Louise Mao, Dianna K. Wheaton, David G. Birch, Kari E. Branham, John R. Heckenlively, Cindy Wen, Ken Flagg, Henry Ferreyra, Jacqueline Pei, Ayesha Khan, Huanan Ren, Keqing Wang, Irma Lopez, Raheel Qamar, Juan C. Zenteno, Raul Ayala-Ramirez, Beatriz Buentello-Volante, Qing Fu, David A. Simpson, Yumei Li, Ruifang Sui, Giuliana Silvestri, Stephen P. Daiger, Robert K. Koenekoop, Kang Zhang, Rui Chen

Abstract

Retinitis pigmentosa (RP) is a devastating form of retinal degeneration, with significant social and professional consequences. Molecular genetic information is invaluable for an accurate clinical diagnosis of RP due to its high genetic and clinical heterogeneity. Using a gene capture panel that covers 163 of the currently known retinal disease genes, including 48 RP genes, we performed a comprehensive molecular screening in a collection of 123 RP unsettled probands from a wide variety of ethnic backgrounds, including 113 unrelated simplex and 10 autosomal recessive RP (arRP) cases. As a result, 61 mutations were identified in 45 probands, including 38 novel pathogenic alleles. Interestingly, we observed that phenotype and genotype were not in full agreement in 21 probands. Among them, eight probands were clinically reassessed, resulting in refinement of clinical diagnoses for six of these patients. Finally, recessive mutations in CLN3 were identified in five retinal degeneration patients, including four RP probands and one cone-rod dystrophy patient, suggesting that CLN3 is a novel non-syndromic retinal disease gene. Collectively, our results underscore that, due to the high molecular and clinical heterogeneity of RP, comprehensive screening of all retinal disease genes is effective in identifying novel pathogenic mutations and provides an opportunity to discover new genotype-phenotype correlations. Information gained from this genetic screening will directly aid in patient diagnosis, prognosis, and treatment, as well as allowing appropriate family planning and counseling.

X Demographics

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

Geographical breakdown

Country Count As %
United Kingdom 2 1%
South Africa 1 <1%
Unknown 143 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 23%
Student > Ph. D. Student 32 22%
Other 11 8%
Student > Bachelor 11 8%
Student > Master 10 7%
Other 24 16%
Unknown 24 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 21%
Biochemistry, Genetics and Molecular Biology 29 20%
Medicine and Dentistry 28 19%
Unspecified 5 3%
Nursing and Health Professions 3 2%
Other 14 10%
Unknown 37 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 January 2021.
All research outputs
#3,805,193
of 22,914,829 outputs
Outputs from Human Genetics
#382
of 2,956 outputs
Outputs of similar age
#35,700
of 212,185 outputs
Outputs of similar age from Human Genetics
#5
of 25 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,956 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done well, scoring higher than 87% 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 212,185 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.