In many areas of medicine, biological markers of disesase state have transformed diagnosis and treatment allocation. Psychiatry lags behind: disorders are still diagnosed by symptoms and no biomarkers have been found. However, addressing this is a formidable task because of a lack of analysis tools to understand the complex disruptions of mental disorders at multiple levels – from the level of brain circuits to behaviour. In addition, mental disorders are very heterogeneous at each of these levels. This means, for example, that different biological causes can result in the same symptoms and that two individuals with the same disorder can have very different symptom profiles.
The aim of this proposal is to provide a set of next generation analysis tools to solve this problem. More speficially, the project aims to stratify mental disorders on the basis of biological markers derived from brain imaging data derived from tens of thousands of people and quantitative measures of behaviour from smartphone-based monitoring.
We will build models to chart variation in multiple aspects of brain organisation across large brain imaging samples from more than 40,000 individuals based on ‘brain growth charting’ methodology we have developed. This will provide a platform to understand the shared and distinct mechanisms of mental disorders at the level of the individual. In addition, this project aims to develop innovative machine learning tools that will:
1. understand the dynamics of behavioural measures derived from smartphone monitoring
2. understand interplay between brain systems and the behaviours they underpin and how this gives rise to mental disorders
3. Integrate complementary information from behavioural and biological data
4. Stratify mental disorders in a way that cuts across diagnostic classifications and accommodates different mechanisms converging on the same symptoms.
These innovations will have far-reaching impact but in this project, we will apply them to predicting trajectories of resilience and risk in major depression and bipolar disorder which are a leading cause of worldwide disease burden.
The ultimate aim of this project is to develop a set of tools for psychiatry that will facilitate early, personalized intervention, preventative treatments and a better understanding of disorder entities.