Genetic Screening of Plasticity Regulating Nogo-Type Signaling Genes in Migraine

Migraine is the sixth most prevalent disease in the world and a substantial number of experiments have been conducted to analyze potential differences between the migraine brain and the healthy brain. Results from these investigations point to the possibility that development and aggravation of migr...

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Bibliographic Details
Published in:Brain sciences 2020-01, Vol.10 (1), p.5
Main Authors: Smedfors, Gabriella, Liesecke, Franziska, Ran, Caroline, Olson, Lars, Karlsson, Tobias E, Carmine Belin, Andrea
Format: Article
Language:English
Subjects:
Age
Brain
Genetic screening
Glycoproteins
Haplotypes
Headache
Headaches
Ligands
Migraine
Nogo protein
Plasticity
Single-nucleotide polymorphism
Substantia grisea
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Summary:Migraine is the sixth most prevalent disease in the world and a substantial number of experiments have been conducted to analyze potential differences between the migraine brain and the healthy brain. Results from these investigations point to the possibility that development and aggravation of migraine may include grey matter plasticity. Nogo-type signaling is a potent plasticity regulating system in the CNS and consists of ligands, receptors, co-receptors and modulators with a dynamic age- and activity-related expression in cortical and subcortical regions. Here we investigated a potential link between migraine and five key Nogo-type signaling genes: , , , and by screening 15 single nucleotide polymorphisms (SNPs) within these genes. In a large Swedish migraine cohort (749 migraine patients and 4032 controls), using a logistic regression with sex as covariate, we found that there was no such association. In addition, a haplotype analysis was performed which revealed three haplotype blocks. These blocks had no significant association with migraine. However, to robustly conclude that Nogo-type genotypes signaling do not influence the prevalence of migraine, further studies are encouraged.
ISSN:2076-3425
2076-3425
DOI:10.3390/brainsci10010005