Interpreting a migraine GWAS using gene expression in healthy human brain

Poster (2016)
Author(s)

S.M.H. Huisman (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)

E Eising (Leiden University Medical Center)

A.M.E.T.A. Mahfouz (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)

L.S. Vijfhuizen (Leiden University Medical Center)

Boudewijn Lelieveldt (TU Delft - Pattern Recognition and Bioinformatics)

Arn M.J.M. van den Maagdenberg (Leiden University Medical Center)

Marcel J.T. Reinders (TU Delft - Pattern Recognition and Bioinformatics)

Research Group
Pattern Recognition and Bioinformatics
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
More Info
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Publication Year
2016
Language
English
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
Research Group
Pattern Recognition and Bioinformatics
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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.

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