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Recurrence of the T666M calcium channel CACNA1A gene mutation in familial hemiplegic migraine with progressive cerebellar ataxia.

American journal of human genetics | 1999

Familial hemiplegic migraine (HM) is an autosomal dominant migraine with aura. In 20% of HM families, HM is associated with a mild permanent cerebellar ataxia (PCA). The CACNA1A gene encoding the alpha1A subunit of P/Q-type voltage-gated calcium channels is involved in 50% of unselected HM families and in all families with HM/PCA. Four CACNA1A missense mutations have been identified in HM: two in pure HM and two in HM/PCA. Different CACNA1A mutations have been identified in other autosomal dominant conditions: mutations leading to a truncated protein in episodic ataxia type 2 (EA2), small expansions of a CAG trinucleotide in spinocerebellar ataxia type 6 and also in three families with EA2 features, and, finally, a missense mutation in a single family suffering from episodic ataxia and severe progressive PCA. We screened 16 families and 3 nonfamilial case patients affected by HM/PCA for specific CACNA1A mutations and found nine families and one nonfamilial case with the same T666M mutation, one new mutation (D715E) in one family, and no CAG repeat expansion. Both T666M and D715E substitutions were absent in 12 probands belonging to pure HM families whose disease appears to be linked to CACNA1A. Finally, haplotyping with neighboring markers suggested that T666M arose through recurrent mutational events. These data could indicate that the PCA observed in 20% of HM families results from specific pathophysiologic mechanisms.

Pubmed ID: 9915947 RIS Download

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Motif Mutation Analysis for Regulatory Genomic Elements (tool)

RRID:SCR_021902

Software package that integrates genome wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. Optimized to work with chromatin accessibility assays such as ATAC-seq or DNase I hypersensitivity, as well as transcription factor binding data collected by ChIP-seq. Used to identify combinations of cell type specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.

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