↓ Skip to main content

Presenilin E318G variant and Alzheimer’s disease risk: the Cache County study

Overview of attention for article published in BMC Genomics, June 2016
Altmetric Badge

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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
32 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Presenilin E318G variant and Alzheimer’s disease risk: the Cache County study
Published in
BMC Genomics, June 2016
DOI 10.1186/s12864-016-2786-z
Pubmed ID
Authors

Ariel A. Hippen, Mark T. W. Ebbert, Maria C. Norton, JoAnn T. Tschanz, Ronald G. Munger, Christopher D. Corcoran, John S. K. Kauwe

Abstract

Alzheimer's disease is the leading cause of dementia in the elderly and the third most common cause of death in the United States. A vast number of genes regulate Alzheimer's disease, including Presenilin 1 (PSEN1). Multiple studies have attempted to locate novel variants in the PSEN1 gene that affect Alzheimer's disease status. A recent study suggested that one of these variants, PSEN1 E318G (rs17125721), significantly affects Alzheimer's disease status in a large case-control dataset, particularly in connection with the APOEε4 allele. Our study looks at the same variant in the Cache County Study on Memory and Aging, a large population-based dataset. We tested for association between E318G genotype and Alzheimer's disease status by running a series of Fisher's exact tests. We also performed logistic regression to test for an additive effect of E318G genotype on Alzheimer's disease status and for the existence of an interaction between E318G and APOEε4. In our Fisher's exact test, it appeared that APOEε4 carriers with an E318G allele have slightly higher risk for AD than those without the allele (3.3 vs. 3.8); however, the 95 % confidence intervals of those estimates overlapped completely, indicating non-significance. Our logistic regression model found a positive but non-significant main effect for E318G (p = 0.895). The interaction term between E318G and APOEε4 was also non-significant (p = 0.689). Our findings do not provide significant support for E318G as a risk factor for AD in APOEε4 carriers. Our calculations indicated that the overall sample used in the logistic regression models was adequately powered to detect the sort of effect sizes observed previously. However, the power analyses of our Fisher's exact tests indicate that our partitioned data was underpowered, particularly in regards to the low number of E318G carriers, both AD cases and controls, in the Cache county dataset. Thus, the differences in types of datasets used may help to explain the difference in effect magnitudes seen. Analyses in additional case-control datasets will be required to understand fully the effect of E318G on Alzheimer's disease status.

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

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Lecturer 3 9%
Student > Doctoral Student 3 9%
Researcher 3 9%
Student > Bachelor 2 6%
Other 7 22%
Unknown 8 25%
Readers by discipline Count As %
Neuroscience 7 22%
Medicine and Dentistry 5 16%
Biochemistry, Genetics and Molecular Biology 3 9%
Psychology 1 3%
Business, Management and Accounting 1 3%
Other 2 6%
Unknown 13 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 08 July 2016.
All research outputs
#3,132,406
of 22,880,230 outputs
Outputs from BMC Genomics
#1,179
of 10,666 outputs
Outputs of similar age
#58,134
of 352,012 outputs
Outputs of similar age from BMC Genomics
#38
of 226 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,666 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 88% 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 352,012 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 83% of its contemporaries.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.