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 we still do not know 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, we are proposing to try to find out the exact timing of these brain changes. We 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, we hope to be able to determine the relationship between progression of symptoms and alterations in brain structure. We 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 we 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.

The course of schizophrenia is associated with significant brain changes. Exactly when these changes occur is a matter of debate, with significant evidence now available for progressive volumetric declines early in the illness (the first 12 to 24 months post-onset). However, there is additional evidence for the decline beginning before that, during the prodromal period. In this study we seek to replicate findings of progressive structural brain changes across the transition to psychosis in a group identified as at ultra high risk for psychosis. Furthermore we will extend these findings to establish the precise trajectory of these changes, whether measures of functional connectivity also show such change, and to what extent they can be used in pattern classification algorithms to improve predictions of who will or will not develop a psychotic illness.

We propose to recruit 120 young people meeting criteria for the at-risk mental state, based on the presence of attenuated psychotic symptoms and/or a family history of schizophrenia or personal history of schizotypal personality disorder. Those with the greatest risk of transition to psychosis, along with 24 healthy controls, will be scanned repeatedly over the subsequent year to establish the longitudinal trajectories of brain structural and functional changes over the onset of psychosis. Specifically, we will use a linear mixed model regression approach to capture the dynamics of the pathological processes before and just after transition in both cortical thickness and measures of global network topology.

We will use a machine learning approach to analyse longitudinal brain changes associated with different clinical courses. This will allow us to model transition probabilities and improve prediction of outcome.

We hypothesise that the most rapid brain changes will be seen either side of transition, and that longitudinal brain changes will provide better prediction of later transition than baseline images.

The major beneficiaries of our study are likely to be future patients at risk for psychotic illnesses such as schizophrenia. Successful completion of this proposal will provide significant insight into the neurobiological changes that occur around the onset of psychotic disorders, including an understanding of how these changes relate to symptoms and to what extent they are related to pharmaceutical treatment. Our approach is in complete concordance with the strategies recommended by the MRC's review of mental health research published in 2010, specifically "understanding the biological and social life-course determinants of mental illness", and "identifying individuals at risk in order to target intervention". Furthermore, the study is in line with the MRC Translational Research Strategy to support "the development of new and improved systems and theories for health research", which emphasises the need to "bring discoveries in science closer and faster to the clinic" to "improve prevention, diagnostic and public health strategies in the most effective way".

While it is unlikely that the findings of this study will be exploitable commercially, it is clear that improved techniques for predicting who will develop psychosis can provide important benefits for the design of services, and if progression to psychotic illness can be prevented then this would have clear social and economic benefits.

At a local level, our study will recruit new research associates and provide them with comprehensive training in multidisciplinary psychiatric research. At a global level our findings will extend the understanding of the brain changes that accompany transition to psychotic illnesses and demonstrate how they can be used to improve predictive models. This will contribute to public understanding of the nature of psychotic illnesses and the way in which they develop.

We will evaluate our impact strategy every six months with input from the Early Intervention Service Users Research Group chaired by Dr Broome. We also hope to engage with our research participants to provide the most useful summaries of our findings for publication on the University of Birmingham and YouthSpace websites.