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Population-Level Data Linkages in Worldwide Twin Research Resources
Veronika V Odintsova1, Dmitry V Kuznetsov2, Dorret I Boomsma1
1Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, the Netherlands.
Abstract:
Twin registries are foundational resources for research in behavioral and medical genetics, epidemiology, and public health. Over several decades, successive international reviews have documented their expansion in number, geographical coverage, phenotypic scope, molecular profiling, and participation in large-scale collaborations. This overview first traces this development through previous global overviews of twin registries and then examines record linkage as an increasingly important feature of contemporary twin research. Drawing on diverse twin registries, twin cohorts, multi-cohort resources, and international consortia, we describe how twin data are linked to population and administrative registers, health and educational records, biobanks, and environmental and geospatial data. Microdata linkage connects individual-level twin phenotypes with longitudinal administrative, clinical, educational, and molecular information, extending follow-up and supporting life-course analyses. Macrodata linkage incorporates contextual information on neighborhood environments, socioeconomic conditions, and policy settings, enabling individual and familial differences to be studied within broader social and environmental contexts. Comparison across resources demonstrates substantial variation in the scope and implementation of record linkage, from established national linkage systems to partial, domain-specific, and planned linkages, shaped by differences in legal frameworks, consent models, data governance, and secure access infrastructures. By placing current record linkage practices within the historical development of twin research resources, this overview shows how linkage extends the classical twin design through longitudinal, multi-domain, and contextual data, broadening its potential for research on health, behavior, and development across the life course.
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