Higher burden of rare frameshift indels in genes related to synaptic transmission separate familial hemiplegic migraine from common types of migraine

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Background: Familial hemiplegic migraine (FHM) is a rare form of migraine with aura that often has an autosomal dominant mode of inheritance. Rare mutations in the CACNA1A, ATP1A2 and SCN1A genes can all cause FHM revealing genetic heterogeneity in the disorder. Furthermore, only a small subset of the affected individuals has a causal mutation. We set out to investigate what differentiates patients with FHM with no mutation in any known FHM gene from patients with common types of migraine in both familial and sporadic cases. Methods: 2558 male and female participants from a migraine cohort from the Danish Headache Center were included. 112 had FHM; 743 had familial migraine; and 1703 had sporadic migraine. Using a linear regression model, we analysed for over-representation of rare functional variants in FHM versus familial migraine and sporadic migraine. Post hoc analyses included pathway analysis and testing for tissue specificity. Results: We found that patients with FHM have significantly more rare frameshift indels compared with patients with familial migraine and sporadic migraine. Pathway analysis revealed that the 'ligand-gated ion channel activity' and 'G protein-coupled receptor downstream signalling' pathways were significantly associated with mutated genes. We moreover found that the mutated genes showed tissue specificity towards nervous tissue and muscle tissue. Conclusion: We show that patients with FHM compared with patients with common types of migraine suffer from a higher load of rare frameshift indels in genes associated with synaptic signalling in the central nervous system and possibly in muscle tissue contributing to vascular dysfunction.

Original languageEnglish
Article number106640
JournalJournal of Medical Genetics
Publication statusPublished - 1 Jan 2020

    Research areas

  • clinical genetics, genetics, headache (including migraine), neurology

ID: 236321582