Interpreting a migraine GWAS using gene expression in healthy human brain

Poster (2016)

Authors

S.M.H. Huisman Pattern Recognition and Bioinformatics - EEMCS , Leiden University Medical Center
E Eising Leiden University Medical Center
A.M.E.T.A. Mahfouz Pattern Recognition and Bioinformatics - EEMCS , Leiden University Medical Center
L.S. Vijfhuizen Leiden University Medical Center
B.P.F. Lelieveldt Pattern Recognition and Bioinformatics - EEMCS
Arn M.J.M. van den Maagdenberg Leiden University Medical Center
M.J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS
Research Group
Pattern Recognition and Bioinformatics (EEMCS) (TU Delft)
Copyright: © 2016 S.M.H. Huisman, E Eising, A.M.E.T.A. Mahfouz, L.S. Vijfhuizen, B.P.F. Lelieveldt, AMJM van den Maagdenberg, M.J.T. Reinders
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Published Date

2016-4

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

Migraine is a common brain disorder, with a heritability of 50%. Genome-wide association studies have identified several loci, but interpretation remains challenging. We integrated migraine GWAS data with spatial gene expression data of adult brains from the Allen Human Brain Atlas, to identify specific brain regions and molecular pathways involved in migraine.
We used two complementary methods. First, we clustered all genes into co-expression modules and identified those associated with migraine. Second, we constructed local co-expression networks around high-confidence migraine genes.
Both approaches converge on functions and anatomy.