Professor Stephen Wood awarded a £818K grant for research into 'linear and non-linear brain changes over the transition to psychosis'

An MRC grant for approximately £818K has recently been awarded to Professor Stephen Wood for research into – 'Linear and non-linear brain changes over the transition to psychosis'.

In the past decade there has been great interest in studying a group of young people at ultra high risk for psychotic illnesses such as schizophrenia. These people are at hugely increased risk because of a combination of symptoms and personal or family history, and indeed around 20% of them develop psychosis within 12 months of being identified. It is now clear that there are differences in the brains of these at-risk cases when compared to similar participants not at risk, and that these brain differences get greater with the onset of psychotic illness. What is still not known is when these changes occur during the progression. For example, it could be that the changes come before (and somehow cause) the increase in symptoms, which would imply that trying to prevent those brain changes could prevent the illness.

In this study, Professor Wood and his team are proposing to try to find out the exact timing of these brain changes. They will do this by recruiting a sample of young people at ultra high risk of psychosis, and scanning their brains every month or so for a year. By comparing the trajectory of brain changes between those who do and those who do not develop psychosis, they hope to be able to determine the relationship between progression of symptoms and alterations in brain structure. They also aim to show that the rate of change varies across this period, and that the changes happen much faster during the period of transition from being 'at-risk' to having a first psychotic episode.

A further issue for researchers is how to improve the prediction of who eventually develops psychosis, since there are currently a very high number of false positives who are potentially exposed to unnecessary treatment and stigma. One recent approach has been to use brain scans in complex statistical analyses, and this has improved the prediction from around 20% to 80%. However, this has only used a single time point. In this study the team will explore what additional predictive power can be obtained from including longitudinal scans. This approach is already used to help predict the onset of dementia in people with mild cognitive impairment, but has not yet been applied to people at risk for psychosis.