Understanding Autism Spectrum Disorders at the epigenetic and metabolomic level

This project forms part of a wider multidisciplinary programme of research spanning across the ETHEREAL programme. This project aims to discover how different environmental factors might impact on the biological system of a child living with ASD at the epigenetic and metabolic level. Using advanced computational methods such as AI and control theory this information will be used to predict biological, clinical, and psychological outcomes. 

The main aim is to discover how different factors in a child's immediate environment might change their epigenetic and biochemical characteristics which in turn, might change their other physiological processes leading to mental illness.

For this purpose, ETHEREAL will recruit 400 adolescents with ASD from 3 countries - the UK, Ireland and Romania and each adolescent will be clinically followed up for 9 months. This will generate a rich set of data spanning from their daily lifestyle and personal environmental factors, consequent changes in their genetic and metabolomic signatures to their mental states. This data will be used to model the process using advanced computational methods such as AI and control theory informed by cutting-edge biological, clinical, and psychological knowledge.

Once modelled, the resulting algorithm will be installed in the mobile device of a child with ASD, which will continuously monitor their environmental factors and help the child to manage the most important factors in their immediate environment to prevent mental illness. 

This PhD studentship will involve metabolic profiling using 1H NMR spectroscopy and mass spectrometry and epigenetic characterisation using the 850K Human Methylation array. The resulting datasets will also be interrogated using multivariate statistical analysis.