This Doctoral Training Centre offers research PhDs in childhood-onset epilepsies.
Projects with a September 2022 start date are listed below. If you would like to know more about a project, please feel free to contact the supervisors of the project. Projects with a September 2023 start date will be advertised in due course.
Primary supervisor: Dr Javier Escudero (School of Engineering)
Predicting epileptic seizures would be highly beneficial to patients. Data science algorithms have shown promise to predict and detect seizures but an aspect not quite fully understood yet is how the occurrence of epileptic seizures depends on the time of the day. In this PhD project, you will have the opportunity to investigate how diverse physiological characteristics interact with circadian and ultradian rhythms to promote the occurrence of seizures, and to develop signal processing and machine learning algorithms that learn the interactions of those rhythms with brain activity features for more accurate seizure prediction.
This PhD project will provide you with an exciting opportunity to receive multi-disciplinary cross-centre training in data science and computational models, while simultaneously exploring different forms of epilepsy, the physiology of the nervous system and the effects of circadian and ultradian rhythms in seizures.
You will be trained on algorithms to explore what collection of variables in continuous brain activity predicts seizures and whether these are dependent on circadian and ultradian patterns. In parallel, you will be trained in the physiological mechanisms underpinning the origin of seizures in chronic-recording high-channel count epileptic encephalopathy rodent models. Your findings will be validated in publicly available datasets of human electroencephalogram recordings. Hence, this PhD will combine analysis of recordings from animal models, to test hypothesis and develop algorithms in more uniform data, and from humans, for a strong translational focus.
Your work will be complementary to previous efforts in the study of circadian and ultradian patterns in seizures, which has thus far not been performed in long-term recordings from well-defined animal models. The work will also delve into recent advances in machine learning algorithms. As such the project is suitable to either: 1) candidates with background in neuroscience and interest in data science and/or machine learning; or 2) to candidates with engineering or computational background and interest in neurophysiology.
Primary supervisor: Prof Michael Cousin (Centre for Discovery Brain Sciences)
Additional supervisors: Dr Emma Wood Centre for Discovery Brain Sciences)
Evidence is accumulating that some childhood-onset epilepsies arise from presynaptic defects (1). The presynapse releases chemical neurotransmitters in response to action potential stimulation and this event is sustained by synaptic vesicle (SV) endocytosis. Mutations in the gene encoding the protein kinase cyclin-dependent kinase-like 5 (CDKL5) result in CDKL5 deficiency disorder (CDD). We have important unpublished data demonstrating that SV endocytosis is specifically disrupted in CDKL5 knockout neurons and that the protein kinase activity of CDKL5 is essential for this role. Therefore, CDKL5 phosphorylates an unidentified presynaptic substrate to control SV endocytosis at the presynapse.
The project aims to
Aim 1) A phospho-proteomic screen of CDKL5 knockout neurons has been performed and has identified potential presynaptic CDKL5 substrates and their phosphorylation sites. These will be validated by western blotting with either phospho-specific antibodies or immunoprecipitation of candidates followed by probing with anti-Ser/Thr antibodies. Rescue experiments will be performed via shRNA-mediated depletion of the endogenous candidates and co-expression of exogenous phospho-null or –mimetic forms in primary cultures of both wild-type and CDKL5 knockout neurons. The student will also have the opportunity to determine how CDKL5-dependent phosphorylation of these candidates affects their molecular interactions by performing affinity chromatography from neuronal lysates with phospho-null and –mimetic candidates.
Aim 2) The student will choose to investigate the physiological role of CDKL5-dependent phosphorylation on either neurotransmission (using slice electrophysiology) or established behavioural defects via viral delivery of phospho-null and –mimetic forms of the candidate into the hippocampus of either wild-type or CDKL5 knockout rats.
Therefore, the student will be trained in state-of-the-art molecular neuroscience techniques (primary neuronal culture, generation of molecular tools, live cell fluorescence imaging acquisition and analysis, determination of interaction partners via GST-pull downs and immunoprecipitation, virus design and delivery, slice electrophysiology / behavioural analysis) to determine the role of a key epilepsy gene, CDKL5, in synaptic, circuit and behavioural function.
(1) Bonnycastle K, Davenport EC, Cousin MA. Presynaptic dysfunction in neurodevelopmental disorders: Insights from the synaptic vesicle life cycle. Journal of neurochemistry. 2021 157:179-207.
Primary supervisor:Prof Richard Chin (Child Life and Health)
Additional supervisors: Dr Bonnie Auyeung (School of Philosophy, Psychology and Language Sciences)
Childhood-onset epilepsies, forty percent of which are due to monogenic causes (1), are associated with negative sequela across the lifespan, including poor academic achievement, difficulties with social and behavioural functioning, and high rates of unemployment. Early identification of cognitive and or behavioural problems in childhood-onset epilepsies, provides opportunities for early intervention for those affected that may have long-lasting positive effects on their later life. However, cognitive and or behavioural problems in childhood-onset epilepsies are often undiagnosed and or poorly managed (2).
Not all cognitive and or behavioural problems may be present at the time of epilepsy diagnosis so periodically screening for such problems is paramount (3). Further, some children will have improvement in their cognitive and or behavioural problems after epilepsy diagnosis and adequate seizure control, whilst others will have persistent problems despite good seizure control and others will have persistent problems along with seizures that are refractory to treatments. Thus, neurodevelopmental trajectories in childhood-onset epilepsies may vary.
We have established a unique Scottish cohort (N=59) of well-phenotyped early-onset childhood epilepsies (onset before age five years of age) diagnosed between May 2013 and June 2015. There are early initial psychometric neurodevelopmental data within 3 months of diagnosis, concomitant diagnostic MRI and EEG data, and genetic information available for the cohort. Fifty percent of children in that cohort had learning and or behavioural comorbidities on initial testing. Results were fed back to their respective clinicians, but it is uncertain if any interventions resulted. It is also unknown if any have improved or if any have developed cognitive and or behavioural problems since the initial study. We also have access to another unique Norwegian cohort of children with epilepsy (N=606), many with monogenic childhood-onset epilepsies, in which we have sequential pre-epilepsy and post-epilepsy diagnosis developmental data at fixed cohort ages, in addition to similar sociodemographic and clinical data as the Scottish cohort.
We hypothesise that more than 70% of children with early-onset epilepsy will have cognitive/behavioural problems at 6-8 years follow-up after epilepsy diagnosis, and a combination of clinical, sociodemographic, EEG, imaging and genetic factors would enhance the prediction of neuropsychological outcomes.
The specific aims of this studentship are to:
1) Determine neuropyschological outcomes at follow up
2) Describe neurodevelopmental trajectories
3) Identify clinical, sociodemographic, MRI, EEG, and genetic risk factors for poor neuropsychological outcomes.
Thus, this project will provide you with well-rounded multi-disciplinary training in clinical epidemiology, neurodevelopmental psychology, and statistics.
1. Zhang D, Liu X, Deng X. Genetic basis of pediatric epilepsy syndromes. Exp Ther Med. 2017 May;13(5):2129-2133. doi: 10.3892/etm.2017.4267. Epub 2017 Mar 27. PMID: 28565819; PMCID: PMC5443213.
2. Reilly C, Atkinson P, Das KB, Chin RF, Aylett SE, Burch V, Gillberg C, Scott RC, Neville BG. Neurobehavioral comorbidities in children with active epilepsy: a population-based study. Pediatrics. 2014 Jun;133(6):e1586-93
3. Nickels, K., Zaccariello, M., Hamiwka, L. et al. Cognitive and neurodevelopmental comorbidities in paediatric epilepsy. Nat Rev Neurol 12, 465–476 (2016