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BEHANDLING-God og treffsikker diagnostikk, behandling og rehabilitering

National training initiative to make better use of biobanks and health registry data

Alternativ tittel: Nasjonalt treningsinitiativ for bedre utnyttelse av biobanker og helseregistre

Tildelt: kr 12,5 mill.

Den høye kvaliteten på norske befolkningsbiobanker og helseregistre legger til rette for svært gode forskningsmuligheter. I dette prosjektet har vi koblet helseopplysninger fra to store norske helseundersøkelser med opplysninger fra norske helseregistre for bedre å forstå risiko for sykdom og sykdomsforløp. Vi har inngående studert sammenhengen mellom arv og miljø ved å koble helsedata med genetisk informasjon fra ca. 70,000 deltakere fra Helseundersøkelsen i Trøndelag (HUNT), ca 35 000 deltagere i Tromsøundersøkelsen. For å kunne utnytte den omfattende informasjonen som ligger i denne typen storskala datasett på best mulig måte, trenger vi gode og tilpassede statistiske metoder og modeller. En viktig del av prosjektet har derfor vært å utvikle både mer treffsikre metoder og gode analyse-"pipelines". Så langt har vi sett spesielt på statistiske metoder som kan kompensere for en høy grad av slektskap og ubalanse mellom antall case (syke) og kontroller i såkalte genomvide assosiasjonsstudier (GWAS). Dette har vært en spesiell utfordring for HUNT og i 2018 kunne vi publisere en ny metode for GWAS-analyser, SAIGE (Zhou et al, Nature Genetics 2018), som løste disse utfordringene. Vi har etablert et nasjonalt nettverk gjennom en strategisk fordeling av vitenskapelige stillinger blant partnerinstitusjonene for forskere innen biostatistikk og bioinformatikk og som også har kunnet bygge egne, selvstendige forskningskarrierer. Vi har også lagt til rette for hospitering og faglig utveksling for å hjelpe unge forskere til å møte nye miljø og faglige utfordringer på en best mulig måte. I takt med det stadig økte tilfanget av helseopplysninger og personsensitive data er det viktig å ivareta deltakernes personvern og integritet på best mulig måte. En viktig del av prosjektet og treningen hat også vært å bygge opp kompetanse rundt etiske spørsmål knyttet til forskning på biobanker og helseregistre og hva som kreves for å fremme sikker lagring og håndtering av sensitive data.

Our first goal has been to better understand the biology within four important disease domains (cardiovascular disease; neurological disease; dermatological disease and cancer) and to use this information to provide new insights into biological mechanisms that have the potential to catalyze breakthroughs in prevention, treatment, and diagnosis of disease. Our second goal has been to develop new statistical methods specifically tailored to the needs presented by the ever increasing digital information stored in biobanks and health registries. Our third goal has been to train a cross-institutional team of outstanding postdoctoral fellows within the interface of applied and methodologically driven biostatistics and bioinformatics, genomics, medicine, epidemiology and ethics to meet the demands of an increasingly complex field of population based genomics and the new era of precision medicine. This project has made it possible to build national analytical expertise associated with the use of genetic data and other omics data from HUNT and the Tromsø survey , through the establishment of cross-border collaboration, both nationally and internationally. This formed the basis for a K.G. Jebsen Center for Genetic Epidemiology, established at NTNU in 2016. •The K.G. Jebsen Center for Genetic Epidemiology (NTNU), holds a strong analytical environment of bioinformaticians, biostatisticians and expertise in genetic statistics which has functioned as a hub for this work and contributed with expertise in data handling and analysis in a number of large-scale research projects data analysis and multi-omics integration have been central, e.g. as participants in larger international consortia. The establishment of HUNT Cloud has been a crucial resource in this work. Competence environments have also been established at the collaborative institutions, such as, for example. UiT and UiO/OUS. We have worked broadly with a number of disease categories which have provided new insight into various clinical diseases and the use of data from health registers. • The project has contributed to a clear increase in research output in the research environments involved What potential social effects can the project have in the future? • It is difficult to measure the social effect directly, but these are competence environments which will be central to the work with personalized medicine, and which will be able to contribute actively towards the new strategy where integration between population studies and clinical environments will be an important investment. • The Research Council has spent significant amounts on biobanks and partly also funding genetic analyzes directly. This will be able to get the desired "return" in future research through the expertise that has been developed and strengthened in this project.

We present an ambitious but realistic three year proposal to leverage existing digital biologic information from three of the largest prospective cohort studies in Norway, enriched with linkages to a comprehensive list of health registries, to better understand the biology for health and disease within diverse disease domains. We will build national methodological competence and capacity in the analysis of large-scale biobanks and health registries by focusing on relevant methodological developments. We will investigate complex ethical questions on the horizon, such as gene-based follow up of participants, in order to secure that the interest of large-scale biobank research and the participants are harmonious and compatible with an ethical commitment to the principle of reciprocity. We will expand our strong interdisciplinary research team within our three partner universities in Norway, and continue to collaborate with world leaders in biostatistics and bioinformatics. We will use this foundation to mentor and train six postdoctoral fellows at the multidisciplinary interface of applied and methodologically driven biostatistics and bioinformatics to meet the increasing complexity of the new era of precision medicine. Our proposal is in compliance with the overarching strategies of the partner universities to build strong statistical and bioinformatics expertise and capacity, and the proposal will be in synergy with our ongoing RCN and NIH supported efforts.

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BEHANDLING-God og treffsikker diagnostikk, behandling og rehabilitering