TwinsUK

TwinsUK provides a longitudinal multi-omics and phenotypic dataset from a large cohort of adult twins to enable research into genetic, environmental, and lifestyle determinants of complex diseases and healthy aging.

Key Features:

• Cohort composition: More than 14,000 volunteer twins (including mixed pairs, singletons, and triplets) with an additional registry of over 1,800 parents and siblings.
• Demographics: Cohort is predominantly female (82%) with a mean age of 59 years.
• Longitudinal phenotyping: Repeated questionnaire responses and physical and cognitive assessments across more than 8,500 subjects, including four comprehensive clinical phenotyping visits.
• Clinical and exposure data: Detailed longitudinal characterization of clinical, biochemical, behavioral, dietary, and socioeconomic factors.
• Omics modalities: Genome-wide scans of single-nucleotide variants, next-generation sequencing, exome sequencing, gene expression arrays, RNA sequencing, metabolomics, microbiomics, epigenetic markers, and telomere length measures.
• Diverse sample types: Biological samples collected across participants enabling integration of multiple omics datasets.
• Data integration potential: Combined genetic, environmental, and lifestyle measures to support integrative analyses of health outcomes.

Scientific Applications:

• Genetic epidemiology: Analysis of genetic influences on complex diseases using genome-wide SNV scans, exome, and sequencing data.
• Environment and lifestyle studies: Investigation of environmental, dietary, and behavioral impacts using metabolomics, microbiomics, and questionnaire data.
• Healthy aging research: Longitudinal assessment of aging-related traits, including telomere length measures and repeated clinical phenotyping.
• Biomarker discovery and molecular epidemiology: Identification of biochemical, gene-expression, and epigenetic biomarkers for disease and health trajectories.

Methodology:

Data generation methods explicitly include genome-wide single-nucleotide variant scans, next-generation sequencing including exome sequencing, gene expression arrays and RNA sequencing, metabolomics, microbiomics, epigenetic assays, telomere length measurement, and repeated questionnaire-based and clinical phenotyping.