Environmental Risk Factors and Gene-environment Interactions

A prevailing model for the development of mental disorders is the neurodevelopmental model. According to this model, exposures during fetal development or early childhood lead to a developmental trajectory that results in psychopathology recognized years later. Furthermore, early exposures may interact with stressors and other exposures later in life, and all of these factors may interact with genetic variants affecting vulnerability and resilience. It is also plausible that similar developmental trajectories may lead to different psychiatric outcomes, but cross-disorder similarities and differences are not well understood.

Empirical testing of the many facets of this model requires detailed information about exposures and events over the life course, including genetic and other biological data. Also, in order to obtain sufficient statistical power and to avoid bias, it is necessary to have access to these data in large population-based study cohorts. The iPSYCH programme currently represents one of the very few possibilities in the World to access such data.

In this work package, we systematically asses the similarities and differences in environmental risk factors among autism, attention deficit hyperactive disorder (ADHD), schizophrenia, bipolar disorder and depression. We assess how these effects interact with genetic background, and, in addition, we develop analytical tools required to test for genotype x environment interactions that constitute risk factors.  

Register-based studies

A number of early environmental risk factors have already been identified for mental disorders, especially schizophrenia. They include obstetric complications, paternal age, urbanicity at place of birth and social adversity. This knowledge is based on information extracted from registers. Using the total Danish population as a dynamic cohort we compare known and suspected environmental risk factors among disorders, and individual and familial comorbidity of the five disorders are examined across the general Danish population. In addition, we use the identified risk factors at the individual level as predictors of course and outcomes such as readmissions, adherence to treatment, physical illness and mortality. Social and occupational dimensions of outcome are studied, as well (see also WP1).

Biological risk factor data

Biological factors measured in neonatal blood spots can include levels of inflammatory markers, vitamin D, food-related antigens and auto-antibodies, as well as hormones and environmental pollutants. Our collaborators at Statens Serum Institut, Denmark are continuously developing the panel of factors that can be measured. We expect to apply the measurements of biological factors to large numbers (thousands) of cases and carefully selected controls from the total Danish population.

G x E analyses

The combination of the rich longitudinal data on risk factors and the comprehensive genetic data generated in WP2, made available in large population-based samples, represents one of the truly unique features of iPSYCH. To combine the longitudinal risk factor data and genetic data, we apply both (1) a hypothesis-driven approach, for example linking vitamin D to genes in relevant pathways and (2) Gene-Environment Wide Interaction Study (GEWIS) strategies. We do this in order to identify important interactions and to better interpret genetic and environmental associations while taking confounding/genetic stratification into account.