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Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience

Overview of attention for article published in Genome Medicine, November 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#8 of 1,610)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
75 news outlets
blogs
4 blogs
twitter
64 X users
facebook
1 Facebook page
googleplus
2 Google+ users

Citations

dimensions_citation
72 Dimensions

Readers on

mendeley
145 Mendeley
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Title
Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience
Published in
Genome Medicine, November 2017
DOI 10.1186/s13073-017-0486-1
Pubmed ID
Authors

Perry G. Ridge, Celeste M. Karch, Simon Hsu, Ivan Arano, Craig C. Teerlink, Mark T. W. Ebbert, Josue D. Gonzalez Murcia, James M. Farnham, Anna R. Damato, Mariet Allen, Xue Wang, Oscar Harari, Victoria M. Fernandez, Rita Guerreiro, Jose Bras, John Hardy, Ronald Munger, Maria Norton, Celeste Sassi, Andrew Singleton, Steven G. Younkin, Dennis W. Dickson, Todd E. Golde, Nathan D. Price, Nilüfer Ertekin-Taner, Carlos Cruchaga, Alison M. Goate, Christopher Corcoran, JoAnn Tschanz, Lisa A. Cannon-Albright, John S. K. Kauwe, for the Alzheimer’s Disease Neuroimaging Initiative

Abstract

While age and the APOE ε4 allele are major risk factors for Alzheimer's disease (AD), a small percentage of individuals with these risk factors exhibit AD resilience by living well beyond 75 years of age without any clinical symptoms of cognitive decline. We used over 200 "AD resilient" individuals and an innovative, pedigree-based approach to identify genetic variants that segregate with AD resilience. First, we performed linkage analyses in pedigrees with resilient individuals and a statistical excess of AD deaths. Second, we used whole genome sequences to identify candidate SNPs in significant linkage regions. Third, we replicated SNPs from the linkage peaks that reduced risk for AD in an independent dataset and in a gene-based test. Finally, we experimentally characterized replicated SNPs. Rs142787485 in RAB10 confers significant protection against AD (p value = 0.0184, odds ratio = 0.5853). Moreover, we replicated this association in an independent series of unrelated individuals (p value = 0.028, odds ratio = 0.69) and used a gene-based test to confirm a role for RAB10 variants in modifying AD risk (p value = 0.002). Experimentally, we demonstrated that knockdown of RAB10 resulted in a significant decrease in Aβ42 (p value = 0.0003) and in the Aβ42/Aβ40 ratio (p value = 0.0001) in neuroblastoma cells. We also found that RAB10 expression is significantly elevated in human AD brains (p value = 0.04). Our results suggest that RAB10 could be a promising therapeutic target for AD prevention. In addition, our gene discovery approach can be expanded and adapted to other phenotypes, thus serving as a model for future efforts to identify rare variants for AD and other complex human diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 64 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 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 145 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 18%
Researcher 20 14%
Student > Master 11 8%
Professor 10 7%
Student > Bachelor 10 7%
Other 24 17%
Unknown 44 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 19%
Neuroscience 21 14%
Agricultural and Biological Sciences 15 10%
Medicine and Dentistry 14 10%
Psychology 5 3%
Other 13 9%
Unknown 49 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 633. 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 19 June 2023.
All research outputs
#35,516
of 25,732,188 outputs
Outputs from Genome Medicine
#8
of 1,610 outputs
Outputs of similar age
#738
of 448,675 outputs
Outputs of similar age from Genome Medicine
#1
of 35 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,610 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one has done particularly well, scoring higher than 99% 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 448,675 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 99% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.