The Danish Twin Registry: An Updated Overview
Dorthe Almind Pedersen1,2, Lisbeth Aagaard Larsen1,2, Marianne Nygaard1,2
1The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Summary
The Danish Twin Registry (DTR) is a large, historic resource with over 175,000 twins. It offers valuable data from surveys, biobanks, and national registers for diverse twin research.
Area of Science:
- Epidemiology
- Genetics
- Biostatistics
Background:
- Established in the 1950s, the Danish Twin Registry (DTR) is the oldest nationwide twin register.
- It has expanded to include twins born up to 2009, now comprising over 175,000 individuals across 140 birth cohorts.
- The DTR is among the world's largest twin registries, offering a unique research infrastructure.
Purpose of the Study:
- To provide an updated overview of the data resources available within the Danish Twin Registry.
- To detail the registry's establishment, ascertainment methods, and cohort composition.
- To highlight the integration of survey data, biobank information, and national register linkages for comprehensive twin studies.
Main Methods:
- Review of the Danish Twin Registry's historical establishment and ascertainment strategies.
- Description of major surveys conducted since 1994 and the DTR biobank, including molecular data.
- Explanation of data linkage with Danish national registers at Statistics Denmark.
Main Results:
- The DTR contains extensive data on over 175,000 twins from 1870-2009.
- A biobank with biological samples and molecular data is available, alongside repeated measurements.
- Successful linkage with Danish national registers provides a rich resource for epidemiological and genetic research.
Conclusions:
- The Danish Twin Registry is a premier, comprehensive resource for a wide array of twin studies.
- Its long history, large cohort size, and integrated data streams offer unparalleled opportunities for research.
- The DTR facilitates advanced research in genetics, epidemiology, and public health through its unique data infrastructure.
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