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Preben Bo Mortensen group

at National Centre for Register-based Research, Aarhus University

Our group at the National Centre for Register-based Research (NCRR) has its main expertise in utilizing data from the numerous Danish registers for epidemiological research. An overriding hypothesis of our work is that environmental factors may contribute to the etiology of a broad range of disorders through their impact on neurodevelopment during fetal life, infancy and childhood. Also according to this hypothesis, these early exposures may interact with later risk factors such as social adversity or physical illness, as well as with genetic risk. Over the last decade we have therefore added genetic and other biological data to our studies, anticipating that a combination of biological, health and social data will allow the discovery of interacting genetic and environmental etiologies of mental disorders.

Because of this, and made possible by the generous funding from the Lundbeck Foundation and other sources, we can provide access to combinations of population based longitudinal data and genetic and other biological data that currently are unparalleled with respect to size of study populations and richness of content.

Within the iPSYCH initiative our research mainly focuses upon studies of risk factors for and the course and outcome of five mental disorders. We specifically focus upon Schizophrenia, Bipolar disorder, Depression, Autism Spectrum Disorders and ADHD, performing register-based research on large cohorts and population-based case-control studies on neonatal biomarkers, with particular emphasis on environmental risk factors and Gene-Environment interactions relevant to etiology course and outcome.

We also conduct or participate in studies aiming at developing population-based models for prediction of disease risk, course, somatic and psychiatric co-morbidities and outcome within a broader range of mental disorders, for example Anorexia Nervosa, OCD, Tourette’s Syndrome and Dementia.

The research of this group is, in its nature, interdisciplinary. For example we collaborate with groups of geneticists and experimental neurobiologists affiliated with other groups within iPSYCH, and have frequent interactions with researchers from, for example, Johns Hopkins School of Medicine and School of Public Health, the Broad Institute, University of North Carolina, Queensland Brain Institute, Karolinska Institutionen and many others.

As of October 2016 we are also privileged to welcome Professor John McGrath as Niels Bohr Professor, funded for 5 years by the Danish National Research foundation.

We hence provide a lively research environment with access to cutting edge techniques, ideas and people in the study of etiology, course and outcome of major mental disorders. 

Read more about Professor Preben Bo Mortensen.

Professor Preben Bo Mortensen at National Centre for Registre-based Research, Aarhus University
Professor Preben Bo Mortensen, Foto: AU Kommunikation

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.

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 ...

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 apply the measurements of biological factors to 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 iPSYCH, 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, linking environmental factors 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.

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