Many psychiatric disorders are heritable which has been shown in various family and twin studies. But it is only since sequencing of the human genome that there is a chance to identify the involved genes. Big studies with hundreds of patients scan millions of genetic variants, which may contribute to the disorders.
For some of them, e.g. schizophrenia or bipolar disorder, such risk genes could be identified. But there is not only one single gene variant that causes a disorder, but rather a number of genes that belong to different systems of the human body. This makes it difficult to understand their individual pathogenic process.
In our working group genetics in Greifswald we take the already identified risk genes as an initial step. We want to determine if these risk markers are also associated with other diseases and in this way understand the co-occurrence of the psychiatric disorders. This can be other psychiatric disorders like schizophrenia or bipolar disorder but also other common diseases like type 2 diabetes, overweight (in cooperation with WG Obesity in psychiatric disorders) or cardio-vascular disorders. The aim is to determine subjects that are at higher risk for the specific disorder in an early stage.
In addition to genetic factors, also environmental influences play a key role; especially in psychiatric disorders. These environmental influences include early childhood trauma or stressful environment as well as lifestyle factors like smoking or obesity. We want to examine to what extend the environmental factors add additional risk or if specific genetic variants only have an effect in presence of the environmental factor. This is particularly important for the investigation of major depression, one of the most common psychiatric disorders. In contrast to other disorders no risk gene could be identified yet. Nevertheless, the knowledge about the biological mechanisms in psychiatric disorders and risk profiles can provide the chance for early interventions.
We aim to combine different biological layers (e.g. genetics, gene-expression, metabolome or brain imaging) and to further investigate our results in other WGs. By this we can for example identify the effect of genetic variants on brain structure (WG brain imaging; Van der Auwera et al., 2015) or on metabolome profiles (WG metabolomics).