Programme led by

Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland

Epilepsy, Seizure Prediction and the Human Volatilome

Mentor: Aoife Morrin (Insight)

Second Mentor: Norman Delanty (FutureNeuro)

The unpredictable nature of seizure occurrence is the primary source of morbidity and mortality in epilepsy . Yet emerging evidence suggests that seizures do not happen without warning, but instead, physiological changes culminating in clinical seizure become increasingly more apparent over time. This time window may offer the possibility of seizure prediction to help protect the patient, and even potential for intervention for seizure prevention.

While changes in intercranial EEG correlate with seizures, implantation of intracranial EEG is not a practical solution for continuous monitoring. Recent research has started to examine the possibility of seizure prediction using scent, or body odour driven by research into other neurological disease states that have been associated with unique odours. Scent reflects the composition of volatile organic compounds (VOCs) emitted from a source, in this case, the body. VOCs are emitted from skin, sweat, breath, and origins of the individual VOCs include the host itself and localized microflora releasing VOCs as metabolites. This research, driven by anecdotal evidence of canine prediction of seizure onsets, has impressively demonstrated canine discrimination of ictal (during seizure) vs inter-ictal (between seizure) vs non-epileptic seizures based on VOC emissions from the skin. On the basis of this, clinical interest in the hypothesis that there exists discriminatory VOC signatures for ictal- and inter-ictal states has been heightened.

The idea is that this project will investigate if a stable, seizure-specific olfactory (or scent-based) signature from skin across individuals, types of seizures and timepoints can be elucidated using GC-MS as the primary technique to profile collected VOCs. Furthermore, we will look at elucidating the pathways driving such emissions to understand its origin to understand how this new knowledge can contribute to seizure forecasting and prediction. Ultimately, we aim to exploit the knowledge from these studies in wearable continuous monitoring to detect seizure-onset in epileptic patients in a time-frame that allows the patient to adapt to this event and/or take steps to minimize/eliminate its impact.

This project would suit a researcher with interest in the study of volatile compounds from the body with experience in VOC sampling and instrumental analysis e.g. GC-MS. The candidate should also have an interest in novel approaches to the analysis and interrogation of such data, e.g. ML, AI.

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