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Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

Overview of attention for article published in Frontiers in Neuroscience, January 2016
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
11 news outlets
blogs
2 blogs
policy
1 policy source
twitter
27 X users
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Readers on

mendeley
346 Mendeley
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Title
Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment
Published in
Frontiers in Neuroscience, January 2016
DOI 10.3389/fnins.2016.00016
Pubmed ID
Authors

Nathan G. Skene, Seth G. N. Grant

Abstract

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 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 346 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 <1%
Netherlands 1 <1%
Unknown 342 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 73 21%
Researcher 73 21%
Student > Master 36 10%
Student > Bachelor 30 9%
Student > Doctoral Student 12 3%
Other 45 13%
Unknown 77 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 18%
Neuroscience 63 18%
Biochemistry, Genetics and Molecular Biology 62 18%
Medicine and Dentistry 21 6%
Engineering 10 3%
Other 45 13%
Unknown 81 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 119. 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 05 July 2022.
All research outputs
#350,656
of 25,371,288 outputs
Outputs from Frontiers in Neuroscience
#153
of 11,538 outputs
Outputs of similar age
#6,318
of 405,724 outputs
Outputs of similar age from Frontiers in Neuroscience
#2
of 169 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done particularly well, scoring higher than 98% 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 405,724 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 98% of its contemporaries.
We're also able to compare this research output to 169 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 98% of its contemporaries.