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TwinsUK

Population Size

15,000

People

Years

1992

Associated BioSamples

Core biopsy

DNA

...see more

Geographic coverage

United Kingdom

Lead time

Not applicable

Summary

TwinsUK follows the lives of adult twins to understand how genetic variation relates to health and ageing. Over 30 years, collected data comprises self-reported, physical and cognitive measures, biochemical measures, 'omics and a wealth of biosamples.

Documentation

The TwinsUK cohort (https://twinsuk.ac.uk/),

set up in 1992, is a major volunteer-based genomic epidemiology resource with longitudinal deep genomic and phenomics data from over 15,000 adult twins (18+) from across the UK who are highly engaged and recallable. The cohort is predominantly female (80%) for historical reasons. It is one of the most deeply characterised adult twin cohort in the world, providing a rich platform for scientists to research health and ageing longitudinally. There are over 700,000 biological samples stored and data collected on twins with repeat measures at multiple timepoints. Extremely large datasets (billions of data points) have been generated for each TwinsUK participant over 30 years, including phenotypes from questionnaires, multiple clinical visits, and record linkage, and genetic and ‘omic data from biological samples. TwinsUK ensures derived datasets from raw data are returned by collaborators to enhance the resource. TwinsUK also holds a wide range of laboratory samples, including plasma, serum, DNA, faecal microbiome and tissue (skin, fat, colonic biopsies) within HTA-regulated facilities at King's College London.

More recently, postal and at-home collection strategies have allowed sample collections from frail twins, our whole cohort for COVID-19 studies, and for new twin recruits. The cohort is recallable either on a four-year longitudinal sweep visit or, based on diagnosis or genotype.

More than 1,000 data access collaborations and 250,000 samples have been shared with external researchers, resulting in over 800 publications since 2012.

TwinsUK is now working to link to twins’ official health, education and environmental records for health research purposes, which will further enhance the resource, education and environmental records for health research purposes, which will further enhance the resource.

Dataset type
Health and disease
Dataset sub-type
Not applicable
Dataset population size
15,000
Associated media

Keywords

Cohort, Fit and well, UKCRC Tissue Directory, Alleviate, COVID-19, UK Longitudinal Linkage Collaboration, UK LLC, Self-Reported Data, Physical Measures, Cognitive Measures, Biochemical Measures, Omics, Genetic, BioBank, Twin, Heritability

Observations

Observed Node
Disambiguating Description
Measured Value
Measured Property
Observation Date

Persons

Volunteer adults females and males (predominantly females) living in UK at time of recruitment. The dataset includes single twins, twin pairs and triplets (identical and non-identical).

15000

Count

31 Dec 2021

Provenance

Purpose of dataset collection
Study
Collection source setting
Clinic, Home
Patient pathway description
Fit and well
Image contrast
Not stated
Biological sample availability
Core biopsy, DNA, Faeces, Immortalized cell lines, Peripheral blood cells, Plasma, RNA, Saliva, Serum, Swabs, Tissue, Urine, Whole blood, Other

Details

Publishing frequency
Irregular
Version
8.0.0
Modified

08/10/2024

Citation Requirements
TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Global Ltd and the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.

Coverage

Start date

01/01/1992

Time lag
Variable
Geographic coverage
United Kingdom
Minimum age range
18
Maximum age range
100
Follow-up
Other

Accessibility

Language
en
Controlled vocabulary
LOCAL
Format
MS Excel, CSV, SPSS, Stata, R

Data Access Request

Dataset pipeline status
Not available
Time to dataset access
Not applicable
Access request cost
TwinsUK operate on a cost recovery basis regarding data provision. Current application costs for data are as follows: £1140 – for basic and published datasets £1620 – for omics data £570 – for Data Access amendments Please note: Requests for samples, new data collections and non-standard and complex data access proposals will be subject to bespoke costs https://twinsuk.ac.uk/resources-for-researchers/our-data/
Access method category
Direct access
Access service description

To access access the TwinsUK data or if you are interested in proposing a collaboration with us, please first read through the Data Access Policy Document which will give you the necessary background information.

You will then need to complete a “Data Access Proposal Form” and email the completed form to the Data Access Manager Victoria Vazquez for consideration by the Department of Twin Research Executive Committee (TREC). We encourage collaboration either on the analysis of these phenotypes or on novel phenotypes.

The proposal should specify the data and/or samples required clearly. Individual variables need to be listed with an appropriate justification describing the aims/hypothesis of the project for which the data is requested.

No attempt should be made to link or combine the data provided under this agreement to other information or archived data available for the data sets provided, even if access to that data has been formally granted to you, or it is freely available without restriction, unless specific permission to do so has been received from the TwinsUK TREC.

Please be aware that our governance does not allow extensive, untargeted AI data requests and therefore we will not be able to support these applications.

There may be costs associated for your request to be fulfilled.

Jurisdiction
GB-ENG, GB-GBN
Data use limitation
General research use
Data use requirements
Not for profit use, Project-specific restrictions, Return to database or resource, User-specific restriction
Data Controller
King's College London
Data Processor
King's College London

Dataset Types: Health and disease


Collection Sources: No collection sources listed