Generation and validation of a mouse model of genetic early onset epilepsy and in cage monitoring of seizure activity

University of Edinburgh

Active award

Student: Grant Marshall

Year Award Started: 2017

Severe epilepsy is often associated with intellectual disability, and unresponsive to drugs. Genome sequencing has allowed us to identify new genes that are mutated in children, causing their epilepsy. However, if we are ever to be able to come up with new, rationally designed, treatments for these children, we need to be able to model the condition in the lab. We can now use a new efficient way of editing genes to recreate specific epilepsy-causing mutations in mice, but the challenge is to find ways in which we can accurately measure spontaneous seizures in these mice without resorting to induced seizures (a severe procedure which doesn’t accurately reflect the human situation). Actual Analytics have developed a system for monitoring mouse behaviour in their home cages. The student will adapt the system, enabling spontaneous seizures to be monitored with minimal stress to the animals. This baseline information could then ultimately be used to test whether treatments lessen the frequency and severity of seizures. In parallel, the student will look at the effects of the mutations on the proteins found in the nerve cells of the mutant mice compared with their normal littermates, gaining new insights into the biological basis of epilepsy.

Research area: Neurological conditions (including stroke)


Professor Catherine Abbott
MRC Institute of Genetics and Molecular Medicine
Professor Douglas Armstrong
School of Informatics

Actual Analytics Ltd