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Genetic variations and associated pathophysiology in the management of epilepsy

Overview of attention for article published in The application of clinical genetics, August 2011
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Genetic variations and associated pathophysiology in the management of epilepsy
Published in
The application of clinical genetics, August 2011
DOI 10.2147/tacg.s7407
Pubmed ID

Leanne Dibbens, Mulley


The genomic era has enabled the application of molecular tools to the solution of many of the genetic epilepsies, with and without comorbidities. Massively parallel sequencing has recently reinvigorated gene discovery for the monogenic epilepsies. Recurrent and novel copy number variants have given much-needed impetus to the advancement of our understanding of epilepsies with complex inheritance. Superimposed upon that is the phenotypic blurring by presumed genetic modifiers scattering the effects of the primary mutation. The genotype-first approach has uncovered associated syndrome constellations, of which epilepsy is only one of the syndromes. As the molecular genetic basis for the epilepsies unravels, it will increasingly influence the classification and diagnosis of the epilepsies. The ultimate goal of the molecular revolution has to be the design of treatment protocols based on genetic profiles, and cracking the 30% of epilepsies refractory to current medications, but that still lies well into the future. The current focus is on the scientific basis for epilepsy. Understanding its genetic causes and biophysical mechanisms is where we are currently positioned: prizing the causes of epilepsy "out of the shadows" and exposing its underlying mechanisms beyond even the ion-channels.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 29%
Researcher 5 24%
Other 2 10%
Professor 2 10%
Lecturer > Senior Lecturer 1 5%
Other 3 14%
Unknown 2 10%
Readers by discipline Count As %
Medicine and Dentistry 8 38%
Agricultural and Biological Sciences 5 24%
Biochemistry, Genetics and Molecular Biology 3 14%
Computer Science 1 5%
Unknown 4 19%