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Discovery and functional prioritization of Parkinson’s disease candidate genes from large-scale whole exome sequencing

Overview of attention for article published in Genome Biology, January 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
42 X users
facebook
1 Facebook page

Citations

dimensions_citation
95 Dimensions

Readers on

mendeley
238 Mendeley
citeulike
3 CiteULike
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Title
Discovery and functional prioritization of Parkinson’s disease candidate genes from large-scale whole exome sequencing
Published in
Genome Biology, January 2017
DOI 10.1186/s13059-017-1147-9
Pubmed ID
Authors

Iris E. Jansen, Hui Ye, Sasja Heetveld, Marie C. Lechler, Helen Michels, Renée I. Seinstra, Steven J. Lubbe, Valérie Drouet, Suzanne Lesage, Elisa Majounie, J. Raphael Gibbs, Mike A. Nalls, Mina Ryten, Juan A. Botia, Jana Vandrovcova, Javier Simon-Sanchez, Melissa Castillo-Lizardo, Patrizia Rizzu, Cornelis Blauwendraat, Amit K. Chouhan, Yarong Li, Puja Yogi, Najaf Amin, Cornelia M. van Duijn, International Parkinson’s Disease Genetics Consortium (IPGDC), Huw R. Morris, Alexis Brice, Andrew B. Singleton, Della C. David, Ellen A. Nollen, Shushant Jain, Joshua M. Shulman, Peter Heutink

Abstract

Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 42 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 238 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Switzerland 1 <1%
Brazil 1 <1%
Unknown 234 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 21%
Student > Ph. D. Student 41 17%
Student > Master 22 9%
Student > Bachelor 19 8%
Other 12 5%
Other 40 17%
Unknown 54 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 52 22%
Agricultural and Biological Sciences 41 17%
Neuroscience 31 13%
Medicine and Dentistry 21 9%
Computer Science 5 2%
Other 18 8%
Unknown 70 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 15 December 2017.
All research outputs
#943,445
of 25,394,764 outputs
Outputs from Genome Biology
#664
of 4,470 outputs
Outputs of similar age
#20,396
of 424,234 outputs
Outputs of similar age from Genome Biology
#13
of 61 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 85% 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 424,234 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.