Identifying rare variants in schizophrenia with long range phasing of Norwegian population

Schizophrenia is a serious psychiatric disorder with increased morbidity and mortality. Although there have been few improvements in the treatment of schizophrenia in the last two decades, research on the genetic causes has made important progress and provided new insights into the etiology of schizophrenia. There is now evidence that there are many genetic variants (polygenic architecture) associated with schizophrenia. These associated genetic variants imply biological disease processes related to neurodevelopment, neuronal origin, synaptic function, and immune system in the pathogenesis of schizophrenia. It is expected that rare risk gene variants will increase insight into disease mechanisms. Mathematical models also suggest genetic overlap between schizophrenia and mental and behavioral traits and cognitive characteristics, a scenario that has implications for understanding epidemiology, the clinical picture, and may contribute to psychiatric nosology. In the project, we expect further genetic findings that will lead to better insight into disease mechanisms, and new opportunities for personalized treatment.

Prosjektet brukte data fra norske, nordiske og internasjonale biobanker og helseregistre til å studere genetisk variasjon og arvelighet ved schizofreni og relaterte psykiske lidelser. I tillegg ble pasienter fra sykehus rekruttert og undersøkt grundig. Prosjektet har identifisere genetiske risikofaktorer for schizofreni og psykiske lidelser, og skaffet mer innsikt i sykdomsmekanismene. Prosjektet har også bidratt til at et stort antall av norske kohorter har blitt genotypet, data som kan brukes av andre forskere. Prosjektet har også bidratt til å utvikle avanserte biostatistiske metoder for å utnytte det store potensialet i Nordiske studier. Dette har bidratt til infrastruktur som kan benyttes av en rekke forskere i Norden, og har ledet til flere Europeiske og Nordiske prosjekter, blant annet H2020. Videre kan funn og metoder bidra til utvikling av presisjonsmedisin (persontilpasset behandling) innen psykiske lidelser.

Schizophrenia and other mental disorders are recognized as leading causes of morbidity globally, and are among the most costly disorders to affect humans. Identifying the underlying pathophysiology is imperative and can lead to major health benefits, through better treatment and prevention strategies. The heritability is high, but most of the genetic factors are unknown, and few rare variants have yet been identified. The current project combines analytical results from Norwegian human biobank material and data from health registries, as well as hospital samples, to develop knowledge about genetic risk factors and causes, to identify the underlying disease mechanisms of schizophrenia, which is a complex human disease. We have genotypes from n=85 000 Norwegians, which will be used for discovery of rare gene variants associated with schizophrenia, in collaboration with Nordic partners, building on the similarities in genetic background. The project is based on collaboration between Norwegian universities, hospitals and the Institute of Public Health, and Nordic partners including Industry. Further, it builds on novel biostatistical and bioinformatics methodology, and the strong expertise in the field from the current partners. The project is made possible through a tight collaboration between Icelandic and Norwegian research groups, which are leaders in genetics of mental illness, as well as in bioinformatics and biostatistics. They have complementary expertise in molecular genetics, big data analysis, and clinical and brain imaging in schizophrenia, leading to synergy. The project will facilitate the development of new knowledge as well as excellent research environments, with a long-term potential for future studies based on Scandinavian biobank material and registry datasets. Although the project focuses on schizophrenia, the methods and infrastructure can be used for other complex human diseases, and for more samples from additional studies.