Psychotic disorders (schizophrenia, bipolar and severe depressive disorder) represent major societal challenges, with large unmet needs. Despite this, several factors that affect disease development and the neurobiological foundations are largely unknown. Recent findings suggest that there are a large number of genetic variants with little effect, which increase the vulnerability of the disorders. Furthermore, there appears to be a large overlap in genetic vulnerability across psychotic disorders and mental traits. This has led to the 'polygenic pleiotropy' model. We will examine this, especially if most associated gene variants are not unique to a psychotic disorder or mental traits, but affect vulnerability to a wider range of mental functions. PleioMent will use innovative analytical methods developed to examine the genetic architecture of mental phenotypes, such as psychosis.
The project has the following specific objectives: 1) to map the genetic vulnerability of psychotic disorders 2) to discover genetic variants associated with several mental traits and psychotic disorders, 3) to identify brain-related developmental pathways for psychotic disorders and interaction with stressors from the environment in a birth cohort (Moba) .
The project will apply analytical tools for big data analyses of huge amounts of genotype samples where the largest cohorts have information about mental traits in addition to diagnosis, and we will combine this with information about environmental factors (stress) and brain imaging from a large, well-described birth cohort (MoBa). We combine expertise on clinical features of the disorders, big data analyzes as well as genetics and brain imaging. We expect that the project, if successful, will provide unique, new insight into the processes during brain development that contribute to psychotic disorders. This could lead to a better understanding of the disorders, and thus the development of better treatment and new better medicines.
Psychotic disorders (schizohrenia, bipolar and depressive disorder), represent major societal challenges, with large unmet needs. In spite of this, factors that influence disease development and the neurobiological underpinnings are mainly unknown. Recent evidence supports extensive polygenic overlap across psychotic disorders and traits, leading to the polygenic pleiotropy model. This suggests that most associated genetic variants are not unique for a given mental trait or disorder, but influence susceptibility to a wide range of phenotypes. PleioMent will apply innovative methodology designed to test the hypothesis that the distinct genetic architecture of a mental phenotype is determined by the unique patterns of associations among a group of highly pleiotropic genetic variants with the following specific aims: 1) map the ‘polygenic pleiotropy’ architecture of mixed effects across psychotic phenotypes, 2) discover genetic loci associated with multiple brain-related traits and psychotic disorders with multivariate methods, 3) identify brain-related neurodevelopmental trajectories for psychotic disorders and interplay with environmental stressors in a prospective birth cohort
PleioMent will develop apply biostatistical tools based on mixture and multivariate models and integrate massive amounts of genotype data with sparse phenotypes enriched by the collection of new critical data (environmental stressors, brain imaging) from a large, deeply phenotyped prospective birth cohort (MoBa). We will apply our novel analytical framework to exploit unprecedented large samples and investigate the brain characteristics (multimodal MRI) of mental dysregulation risk in a longitudinal setting. If successful, this high risk – high gain approach will provide novel insight into the neurodevelopmental processes preceding the emergence of mental psychopathology and psychotic disorders.