Conceptualising depression as a complex network of interacting symptoms: implications on the effects of antidepressants and genetic risk. (360G-Wellcome-224920_Z_22_Z)

Depression is mental disease with a complex and heterogeneous presentation. We can conceptualise it as a network of symptoms that can cluster together, reciprocally cause each other and interact in intricate ways, rather than one mental disorder with a common cause. We aim to use network analysis to reveal new information about the genetic risk of developing depression, as well as the progression of pharmacological treatment with common antidepressants. Using large existing datasets, we will build networks of polygenic risk scores for depression and symptoms of childhood internalising disorders to observe the developmental trajectory of the association between genetic risk and symptomatology. We will incorporate brain imaging measures to investigate their role as intermediate phenotypes between genes and behaviour. In addition, we will study the network dynamics of antidepressant treatment. Analysing previously collected data, we will test how changes in low-level affective processing interact with higher-order symptoms. We will collect new neuroimaging data to observe changes in brain activity during antidepressant treatment and their relation to individual symptoms. Through this work, we aim to better understand how the genetic liability to depression is related to its phenotype, as well as how pharmacological treatment brings about an amelioration of depressive symptoms.