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Whole-exome sequencing in amyotrophic lateral sclerosis suggests NEK1 is a risk gene in Chinese

Overview of attention for article published in Genome Medicine, November 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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1 news outlet
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6 X users

Citations

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Title
Whole-exome sequencing in amyotrophic lateral sclerosis suggests NEK1 is a risk gene in Chinese
Published in
Genome Medicine, November 2017
DOI 10.1186/s13073-017-0487-0
Pubmed ID
Authors

Jacob Gratten, Qiongyi Zhao, Beben Benyamin, Fleur Garton, Ji He, Paul J. Leo, Marie Mangelsdorf, Lisa Anderson, Zong-Hong Zhang, Lu Chen, Xiang-Ding Chen, Katie Cremin, Hong-Weng Deng, Janette Edson, Ying-Ying Han, Jessica Harris, Anjali K. Henders, Zi-Bing Jin, Zhongshan Li, Yong Lin, Xiaolu Liu, Mhairi Marshall, Bryan J. Mowry, Shu Ran, David C. Reutens, Sharon Song, Li-Jun Tan, Lu Tang, Robyn H. Wallace, Lawrie Wheeler, Jinyu Wu, Jian Yang, Huji Xu, Peter M. Visscher, Perry F. Bartlett, Matthew A. Brown, Naomi R. Wray, Dongsheng Fan

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease characterised by the degeneration of motor neurons, which are responsible for voluntary movement. There remains limited understanding of disease aetiology, with median survival of ALS of three years and no effective treatment. Identifying genes that contribute to ALS susceptibility is an important step towards understanding aetiology. The vast majority of published human genetic studies, including for ALS, have used samples of European ancestry. The importance of trans-ethnic studies in human genetic studies is widely recognised, yet a dearth of studies of non-European ancestries remains. Here, we report analyses of novel whole-exome sequencing (WES) data from Chinese ALS and control individuals. WES data were generated for 610 ALS cases and 460 controls drawn from Chinese populations. We assessed evidence for an excess of rare damaging mutations at the gene level and the gene set level, considering only singleton variants filtered to have allele frequency less than 5 × 10(-5) in reference databases. To meta-analyse our results with a published study of European ancestry, we used a Cochran-Mantel-Haenszel test to compare gene-level variant counts in cases vs controls. No gene passed the genome-wide significance threshold with ALS in Chinese samples alone. Combining rare variant counts in Chinese with those from the largest WES study of European ancestry resulted in three genes surpassing genome-wide significance: TBK1 (p = 8.3 × 10(-12)), SOD1 (p = 8.9 × 10(-9)) and NEK1 (p = 1.1 × 10(-9)). In the Chinese data alone, SOD1 and NEK1 were nominally significantly associated with ALS (p = 0.04 and p = 7 × 10(-3), respectively) and the case/control frequencies of rare coding variants in these genes were similar in Chinese and Europeans (SOD1: 1.5%/0.2% vs 0.9%/0.1%, NEK1 1.8%/0.4% vs 1.9%/0.8%). This was also true for TBK1 (1.2%/0.2% vs 1.4%/0.4%), but the association with ALS in Chinese was not significant (p = 0.14). While SOD1 is already recognised as an ALS-associated gene in Chinese, we provide novel evidence for association of NEK1 with ALS in Chinese, reporting variants in these genes not previously found in Europeans.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 22%
Researcher 7 9%
Student > Doctoral Student 7 9%
Professor 6 7%
Other 6 7%
Other 17 21%
Unknown 20 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 22%
Medicine and Dentistry 14 17%
Neuroscience 9 11%
Agricultural and Biological Sciences 8 10%
Nursing and Health Professions 4 5%
Other 4 5%
Unknown 24 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 July 2018.
All research outputs
#2,303,519
of 24,271,113 outputs
Outputs from Genome Medicine
#521
of 1,499 outputs
Outputs of similar age
#49,977
of 439,798 outputs
Outputs of similar age from Genome Medicine
#15
of 32 outputs
Altmetric has tracked 24,271,113 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,499 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has gotten more attention than average, scoring higher than 65% 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 439,798 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 88% of its contemporaries.
We're also able to compare this research output to 32 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 56% of its contemporaries.