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Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas

Overview of attention for article published in Human Genetics, February 2016
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
19 tweeters
facebook
1 Facebook page

Citations

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17 Dimensions

Readers on

mendeley
69 Mendeley
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1 CiteULike
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Title
Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas
Published in
Human Genetics, February 2016
DOI 10.1007/s00439-016-1638-x
Pubmed ID
Authors

Else Eising, Sjoerd M. H. Huisman, Ahmed Mahfouz, Lisanne S. Vijfhuizen, Verneri Anttila, Bendik S. Winsvold, Tobias Kurth, M. Arfan Ikram, Tobias Freilinger, Jaakko Kaprio, Dorret I. Boomsma, Cornelia M. van Duijn, Marjo-Riitta R. Järvelin, John-Anker Zwart, Lydia Quaye, David P. Strachan, Christian Kubisch, Martin Dichgans, George Davey Smith, Kari Stefansson, Aarno Palotie, Daniel I. Chasman, Michel D. Ferrari, Gisela M. Terwindt, Boukje de Vries, Dale R. Nyholt, Boudewijn P. F. Lelieveldt, Arn M. J. M. van den Maagdenberg, Marcel J. T. Reinders

Abstract

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

Twitter Demographics

The data shown below were collected from the profiles of 19 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Finland 1 1%
Luxembourg 1 1%
China 1 1%
Netherlands 1 1%
Unknown 64 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 26%
Student > Ph. D. Student 17 25%
Student > Bachelor 9 13%
Student > Master 8 12%
Professor 4 6%
Other 13 19%
Readers by discipline Count As %
Medicine and Dentistry 17 25%
Agricultural and Biological Sciences 17 25%
Biochemistry, Genetics and Molecular Biology 11 16%
Unspecified 6 9%
Computer Science 6 9%
Other 12 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 18 November 2016.
All research outputs
#1,119,816
of 12,215,443 outputs
Outputs from Human Genetics
#113
of 2,462 outputs
Outputs of similar age
#37,952
of 291,634 outputs
Outputs of similar age from Human Genetics
#4
of 30 outputs
Altmetric has tracked 12,215,443 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 2,462 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% 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 291,634 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 86% of its contemporaries.
We're also able to compare this research output to 30 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 90% of its contemporaries.