Genetic and phenotypic architecture of the ontogenetic determinants of severe mental illness

Severe mental disorders are among the largest contributors to personal despair, reduced function, and disability worldwide. Psychotic disorders, including schizophrenia and bipolar disorders are heritable illnesses that often manifest during adolescence and early adulthood. Identifying why some people develop severe mental illness is crucial to identify individuals who might be at high risk and who would benefit from early interventions, and for developing targeted and effective treatments. Large-scale and coordinated international efforts in psychiatric research have started to reveal brain abnormalities in patients with severe mental disorders, and also some of the genetic and environmental risk factors. Recent research has shown that the clinical manifestations of psychotic symptoms are associated with aberrant development of brain networks in early years. However, causal models combining cognitive, neurobiological, environmental and genetic information are still lacking. In this large-scale multi-disciplinary and translational project, we have enhanced our understanding by combining information from different levels of enquiry. We have identified and described structural and functional brain differences associated with psychotic symptoms, their developmental profiles and genetic modifiers. We have aimed to disentangle the specific brain patterns that best discriminate between individuals with severe mental illness and healthy control individuals, and to determine their developmental patterns and genetic associations. Lastly, we have used advanced statistical methods which allowed us to get a better understanding of the common and unique determinants of individual differences in brain function and the development of mental illness, focussing on genetic and environmental risk factors. In the first periods we developed and tested methods for investigating brain networks using advanced brain imaging, and have, among other results, reported that children and adolescent with increased symptoms of mental disorders show delayed brain network development compared to individuals with less symptoms. Further, we have investigated if this delayed development can be attributed to genetic variability, and reported that similar brain network patterns can be identified in adult patients with mental disorders. In the latter phase we have identified a larger part of the genetic variability related to individual differences in neurodevelopmental patterns and aberrations relate to risk for mental disorders. We have developed and applied novel techniques for large-scale imaging genetics analysis in large population based cohorts.

Prosjektet har gitt ny kunnskap om hjernen hos pasienter med schizofreni og bipolar lidelse. Arbeidet har ført til informasjon om hvordan gener og miljø påvirker hjernen i ungdomsårene, og at hjernens utvikling er knyttet til risiko for psykiske lidelser. Dette er nyttig for å lage modeller for å predikere sykdom og utvikle målrettede tiltak på system- og individnivå. I tillegg til å påvise gruppeforskjeller, har vi vist at slike effekter kan skjule stor variasjon. Noen pasienter viser betydelige avvik i hjernen sammenlignet med en normalgruppe, viser andre pasienter ingen eller svært små avvik. Dette er i tråd med kliniske observasjoner om stor variasjon i symptomer og prognose. I tillegg til å være et viktig supplement til gruppestudier, gir slike individuelle tilnærminger mulighet til å vurdere informasjon om enkeltpersoner, som er nødvendig for å utvikle modeller for prediksjon av sykdom og effekter av behandling, og for å utvikle målrettet og persontilpasset behandling.

The prototypical manifestation of psychosis including delusions, hallucinations, and social withdrawal emerge during adolescence, and has remained remarkably stable over the past century, both in terms of prevalence and disability. Despite major health, social, and economic consequences, research designed to identify mechanisms has not succeeded, and the pathophysiology remains elusive. The lack of models integrating clinical, cognitive, biological, and genetic mechanisms has delayed targeted interventions, and the emphasis on adult patients has provided a static apprehension of the truly dynamic mechanisms. We propose a novel perspective building on neurodevelopmental characteristics, and the joint sample size of >10,000 yields an unprecedented opportunity to identify the dynamic determinants of mental disorders towards personalized interventions. Our unique approach includes state-of-the art technology and tools for data integration, and builds on the joint efforts of a cross-disciplinary international team. Anecdotal observations and statistical evidence have suggested overlap between a range of traits and disorders. Novel biostatistical tools have finally enabled us to quantify the genetic correlations between traits using high-density genotype data, which have created an avenue for genetic dissection of complex traits, allowing for new discoveries and hypotheses. These methods provide a biostatistical platform for challenging historical conventions, paving the way toward a new nosology of complex disorders. We leverage these exciting new developments to propose a genetically informed hierarchical clustering of brain imaging and clinical traits, with a particular emphasis on neurodevelopmental markers. In addition to improving current brain-based models of mental illness, our genetic dissection provides novel clues about the fundamental architecture of the brain, the dynamic lifespan alterations, and the perturbations underlying neurodevelopmental disorders.