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Genetic variants associated with Alzheimer’s disease confer different cerebral cortex cell-type population structure

Overview of attention for article published in Genome Medicine, June 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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7 news outlets
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15 X users

Citations

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49 Dimensions

Readers on

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82 Mendeley
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Title
Genetic variants associated with Alzheimer’s disease confer different cerebral cortex cell-type population structure
Published in
Genome Medicine, June 2018
DOI 10.1186/s13073-018-0551-4
Pubmed ID
Authors

Zeran Li, Jorge L. Del-Aguila, Umber Dube, John Budde, Rita Martinez, Kathleen Black, Qingli Xiao, Nigel J. Cairns, The Dominantly Inherited Alzheimer Network (DIAN), Joseph D. Dougherty, Jin-Moo Lee, John C. Morris, Randall J. Bateman, Celeste M. Karch, Carlos Cruchaga, Oscar Harari

Abstract

Alzheimer's disease (AD) is characterized by neuronal loss and astrocytosis in the cerebral cortex. However, the specific effects that pathological mutations and coding variants associated with AD have on the cellular composition of the brain are often ignored. We developed and optimized a cell-type-specific expression reference panel and employed digital deconvolution methods to determine brain cellular distribution in three independent transcriptomic studies. We found that neuronal and astrocyte relative proportions differ between healthy and diseased brains and also among AD cases that carry specific genetic risk variants. Brain carriers of pathogenic mutations in APP, PSEN1, or PSEN2 presented lower neuron and higher astrocyte relative proportions compared to sporadic AD. Similarly, the APOE ε4 allele also showed decreased neuronal and increased astrocyte relative proportions compared to AD non-carriers. In contrast, carriers of variants in TREM2 risk showed a lower degree of neuronal loss compared to matched AD cases in multiple independent studies. These findings suggest that genetic risk factors associated with AD etiology have a specific imprinting in the cellular composition of AD brains. Our digital deconvolution reference panel provides an enhanced understanding of the fundamental molecular mechanisms underlying neurodegeneration, enabling the analysis of large bulk RNA-sequencing studies for cell composition and suggests that correcting for the cellular structure when performing transcriptomic analysis will lead to novel insights of AD.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 17%
Student > Ph. D. Student 13 16%
Student > Bachelor 8 10%
Student > Master 6 7%
Professor > Associate Professor 5 6%
Other 11 13%
Unknown 25 30%
Readers by discipline Count As %
Neuroscience 16 20%
Medicine and Dentistry 11 13%
Biochemistry, Genetics and Molecular Biology 10 12%
Agricultural and Biological Sciences 9 11%
Computer Science 2 2%
Other 7 9%
Unknown 27 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 62. 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 July 2019.
All research outputs
#590,320
of 23,128,387 outputs
Outputs from Genome Medicine
#115
of 1,451 outputs
Outputs of similar age
#14,578
of 329,032 outputs
Outputs of similar age from Genome Medicine
#4
of 24 outputs
Altmetric has tracked 23,128,387 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done particularly well, scoring higher than 92% 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 329,032 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 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.