Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research.

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.

Cohort profile of the Young-HUNT Study, Norway: a population-based study of adolescents.

The Young-HUNT Study is the adolescent part (13-19 years) of HUNT, the Nord-Trøndelag Health Study, Norway. Three cross-sectional surveys have been conducted: Young-HUNT1 (1995-97), Young-HUNT2 (2000-01) and Young-HUNT3 (2006-08). Major public health issues, including somatic and mental health, quality of life and health behaviours are covered. Young-HUNT was performed in schools visited by trained nurses. Data collection included self-reported questionnaires, structured interviews, clinical measurements and, in Young-HUNT3, buccal smears. The total response rates varied from 90% to 83% and the Young-HUNT database includes 17 820 teenagers. Some Young-HUNT1 participants constitute the baseline for two follow-up studies: a 4-year follow-up through adolescence to Young-HUNT2 and an 11-year follow-up into young adulthood to the adult HUNT3. Longitudinal data are also obtained by linkage of data from Young-HUNT to different national health registers. Linkage to family registers allows the possibility of studying genetic and environmental interactions through generations. Presently 20 PhD students are working with the data, 11 Young-HUNT based PhD theses have been completed and more than 50 scientific papers published.

The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms.

BACKGROUND: Population based studies are important for prevalence, incidence and association studies, but their external validity might be threatened by decreasing participation rates. The 50 807 participants in the third survey of the HUNT Study (HUNT3, 2006-08), represented 54% of the invited, necessitating a nonparticipation study. METHODS: Questionnaire data from HUNT3 were compared with data collected from several sources: a short questionnaire to nonparticipants, anonymous data on specific diagnoses and prescribed medication extracted from randomly selected general practices, registry data from Statistics Norway on socioeconomic factors and mortality, and from the Norwegian Prescription Database on drug consumption. RESULTS: Participation rates for HUNT3 depended on age, sex and type of symptoms and diseases, but only small changes were found in the overall prevalence estimates when including data from 6922 nonparticipants. Among nonparticipants, the prevalences of cardiovascular diseases, diabetes mellitus and psychiatric disorders were higher both in nonparticipant data and data extracted from general practice, compared to that reported by participants, whilst the opposite pattern was found, at least among persons younger than 80 years, for urine incontinence, musculoskeletal pain and headache. Registry data showed that the nonparticipants had lower socioeconomic status and a higher mortality than participants. CONCLUSION: Nonparticipants had lower socioeconomic status, higher mortality and showed higher prevalences of several chronic diseases, whilst opposite patterns were found for common problems like musculoskeletal pain, urine incontinence and headache. The impact on associations should be analyzed for each diagnosis, and data making such analyses possible are provided in the present paper.