Offspring of parents with severe mental illnesses have an increased risk for psychiatric disorders and up to one third of them may develop a severe mental illness by early adulthood. Notably, the risk is related to a range of psychiatric disorders and not exclusively to the disorder diagnosed in the parent, indicating that a transdiagnostic staging approach is going to be necessary. A key challenge in research on the early detection of psychiatric disorders is to distinguish those who are going to develop the disorder from those who will not. However, the accuracy of clinical assessment instruments to predict risk propensity in young high-risk individuals is limited because they do not capture relevant pathophysiological mechanisms. Therefore there is urgent need to find complementary data such as biological variables to improve risk prediction in young people at high-risk for developing a psychiatric disorder.

Brain imaging has emerged as a powerful tool to map direct neurobiological processes associated with the development of the illness. Numerous imaging studies have demonstrated that psychiatric disorders are associated with structural and functional brain abnormalities, which are already evident in the early stages of the disorder. More recent brain network studies suggest a more fine-grained interpretation by revealing that brain abnormalities in psychiatric disorders are not solely attributable to changes in local regions and connections but rather emerge from changes in the topology of the network as a whole, the connectome of the brain. These network findings indicate that many mental disorders may be best understood in terms of brain network dysfunction rather then by localized ‘lesions’. Moreover, it has been shown that psychiatric disorders often share underlying brain network pathology, which makes traditional diagnostic boundaries less meaningful. Variability in the configuration of the brain connectome may lead to variability in symptom expression and thereby producing transdiagnostic symptoms

The purpose of this project is to test the clinical utility of structural and functional whole-brain network markers to predict risk propensity in children and adolescents with an increased risk for developing schizophrenia and depression. In particular, we will investigate using graphical theoretical analysis of magnetic resonance imaging (MRI) data whether complex measures of the brain connectome at initial baseline assessments can predict clinical and psychological features at follow-up assessments in offspring of parents with schizophrenia and depression. The results of this project may allow individual risk stratification and the development personalized preventive interventions in individuals at high-risk for mental illnesses. Furthermore, this project may also provide neural targets for assessing the efficacy of novel treatment scenarios.