Our lab has been focusing on understanding how gene x environment interactions (GxE), especially interactions with adversity, contribute to risk and resilience for depression. Exposure to adverse life events, especially early in life, starting from pregnancy through childhood and adolescence, are among the strongest predictors of future onset of major depression and also predict a more severe disease course, with more chronic and treatment resistant depressive episodes as well as higher co-morbidity with other psychiatric disorders.
Not every individual exposed to adversity, however, will be affected in the same manner and it is clear that other environmental factors but also individual genetic predisposition shape the longtime impact of adversity on the individual. Exploring human genetic variations that increase or reduce disease risk in light of adversity may serve as a tool to identify mechanisms and pathways that promote risk or resilience. Understanding GxE on the molecular, cellular and system level and across development will be necessary for a better mechanistic understanding of the risk factors for depression.
In order to map GxE on these levels the group uses human samples (peripheral tissue as well as postmortem brain tissue) and in vitro models, currently mainly induced pluripotent stem cells-based models, including brain organoids combined with molecular methods including genome-wide association studies, quantitative trait locus analyses, epigenetic measures and single cell sequencing methods. Genetic variants characterized on the molecular and cellular level are then being mapped on different outcomes and in different GxE context. For this, the lab has access to human cohorts, that range from birth cohorts to clinical cohorts and include different adversity exposures. In addition to psychometric data, we also map GxE onto intermediate phenotypes, including neuroimaging, psychophysiological read-out but also novel phenotyping tools, such as virtual reality and smart devices. These intermediate phenotypes are also mapped in the context of challenges, such as a laboratory imaging stress test, fear conditioning and reward anticipation.
By combining these levels of analysis, we aim at better understanding the mechanisms -from molecule to circuit and behavior – that moderate the impact of adversity on risk for depression. This could help defining novel, biology-based diagnoses and optimized treatment strategies.