Twin registries serve as foundational infrastructures for behavioral and medical genetics, epidemiology, public health, and increasingly for molecular genetic research as contributors to large consortia and register-based science. Several earlier papers, including multiple previous special issues of Twin Research and Human Genetics (THRG), have documented the global landscape of twin registries, tracing their growth and scientific impact (Box 1).
The first of these special issues, published in 1998, asked a simple question — ‘What’s out there?’ — and provided the first systematic overview of European twin registries (Boomsma, Reference Boomsma1998). A subsequent special issue extended this effort to the global level by cataloguing 36 twin registries worldwide and highlighting their diversity in design and scientific focus (Busjahn, Reference Busjahn2002). By 2006, twin registries were described as an ‘ongoing success story,’ reflecting rapid growth to more than 50 registries, broader phenotyping, and increasing international collaboration (Busjahn & Hur, Reference Busjahn and Hur2006).
An important intermediate milestone was the review by van Dongen et al. (Reference van Dongen, Slagboom, Draisma, Martin and Boomsma2012), which positioned twin registries at the forefront of the emerging omics era and demonstrated how classical twin designs could be integrated with genomic, epigenomic, transcriptomic, and metabolomic data to disentangle genetic, environmental, and stochastic sources of biological variation.
A further major step forward in twin research was marked by a special issue introduced by Hur and Craig (Reference Hur and Craig2013), which synthesized contributions from 71 twin registries and highlighted the growing importance of large national registries, particularly in Northern Europe, many of which had already been integrated or had the potential to be integrated with national demographic and health registers. This issue further demonstrated how twin registries were evolving from survey-based cohorts into infrastructures supporting molecular genetic research, alongside investigations of gene–environment interplay. At the same time, it drew attention to the growing geographical reach of twin research, including new or expanding cohorts in underrepresented regions, and called for multinational analyses that move beyond population-specific findings. It spotted novel cohorts in underrepresented regions like Cuba, Russia, Kyrgyzstan, African countries (Guinea-Bissau, Nigeria), and U.S. African-American studies, while advocating multinational analyses beyond population-specific variance.
This transition towards molecular research infrastructures was further reflected by Odintsova et al. (Reference Odintsova, Willemsen, Dolan, Hottenga, Martin, Slagboom, Ordoñana and Boomsma2018), who highlighted the value of twin registries as platforms for biomarker and multi-omics research and discussed methodological challenges associated with high-dimensional molecular data. The article also emphasized how collaboration and data sharing across registries could facilitate large-scale genetic and omics studies extending beyond individual cohorts.
This trajectory was reaffirmed and extended in the subsequent overview by Hur et al. (Reference Hur, Bogl, Ordoñana, Taylor, Hart, Tuvblad, Ystrom, Dalgård, Skytthe and Willemsen2019), which consolidated evidence that twin registries had become indispensable resources across disciplines — from psychology and education to medicine, pharmacology, and epidemiology. That review emphasized how large sample sizes, longitudinal follow-up, biospecimen collection, and innovative recruitment strategies enable registries to contribute to international consortia and high-impact meta-analyses. A prominent example is the CODATwins collaboration, which has brought together data from more than one million twins worldwide to study traits such as educational attainment, height, weight, and body mass index (Silventoinen et al., Reference Silventoinen, Jelenkovic, Yokoyama, Sund, Sugawara, Tanaka, Matsumoto, Bogl, Freitas, Maia, Hjelmborg, Aaltonen, Piirtola, Latvala, Calais-Ferreira, Oliveira, Ferreira, Ji, Ning and Kaprio2019).
This global perspective was further reinforced by Hur et al. (Reference Hur, Odintsova, Ordonana, Silventoinen, Willemsen, Harris, Segal, Tarnoki and Tarnoki2022) as a chapter in the book Twin Research for Everyone: From Biology to Health, Epigenetics, and Psychology, which documented twin registries across 26 countries and six continents, collectively representing over 1.3 million twins and family members.
Evolution of overviews on Twin Registries
1998 — Mapping the field in Europe (Boomsma, Reference Boomsma1998)
The overview provided the first systematic mapping of European twin registries, describing 16 population-based and volunteer registries across nine countries and establishing their collective value as a major resource for genetic-epidemiological research.
2002 – Mapping the field worldwide (Busjahn, Reference Busjahn2002)
TRHG special issue focused on identifying and cataloguing existing twin registries worldwide. Its main contribution was descriptive: documenting what registries existed, where they were located, and how they differed in design, size, and phenotypic focus. The emphasis was on visibility and recognition of twin registries as a global research resource.
2006 — Growth and consolidation (Busjahn & Hur, Reference Busjahn and Hur2006)
TRHG special issue highlighted expansion and maturation. It documented the rapid increase in the number of registries, broader recruitment strategies, richer phenotyping, and the emergence of sustained infrastructures. Increasing international collaboration and the transition from small, project-based cohorts to long-term registries were key themes.
2012 — Development of omics (van Dongen et al., Reference van Dongen, Slagboom, Draisma, Martin and Boomsma2012)
This review positioned twin registries at the forefront of the emerging omics era, demonstrating how classical twin designs could be integrated with genomics, epigenomics, transcriptomics, and metabolomics to disentangle genetic, environmental, and stochastic sources of biological variation, and highlighting twins as a powerful framework for studying molecular mechanisms underlying complex traits and disease. Overviewed 17 registries.
2013 — Scale, diversity, and molecular transition (Hur & Craig, Reference Hur and Craig2013)
TRHG special issue marked a shift toward scale and scientific breadth. It showcased large registries, particularly in Europe, and documented the growing integration of molecular data, including genetics and early epigenetic work. The issue emphasized expanding geographic diversity of twin registries, the results of cross-national analyses, and the value of the study of gene–environment interplay.
2018 — Establishing a twin register for biomarker and omics research (Odintsova et al., Reference Odintsova, Willemsen, Dolan, Hottenga, Martin, Slagboom, Ordoñana and Boomsma2018)
This article highlighted the value of twin registries as infrastructures for behavioral genetic, epidemiological, biomarker, and multi-omics research and discussed methodological challenges associated with high-dimensional molecular data. It further illustrated how collaboration and data sharing across registries can facilitate large-scale genetic and omics studies that extend beyond individual cohorts.
2019 — Integration and consortia science (Hur et al., Reference Hur, Bogl, Ordoñana, Taylor, Hart, Tuvblad, Ystrom, Dalgård, Skytthe and Willemsen2019)
TRHG special issue emphasized integration across registries and disciplines. Twin registries were positioned as indispensable infrastructures for large-scale consortia, longitudinal research, and biosample-based studies. Harmonization, meta-analysis, and participation in global collaborations such as CODATwins were central themes of the special Issue.
2026 — Record linkage and linkage-enabled infrastructures (current Special Issue)
The current TRHG special Issue reflects the next stage of evolution in twin registries: systematic record linkage and dataset expansion. Its focus is on linking twin registries to national population databases, health and administrative registers, and biobanks, enabling life-course, multi-source, and multi-omics research at unprecedented scale. Legal, ethical, and governance frameworks for linked data, as well as emerging registries adopting linkage-first designs, are central to this issue. The Special Issue overviews twin registers and cohorts, consortiums, and studies with record linkage experience.
Together, these reviews chart the transformation of twin registries from descriptive national cohorts into globally connected research infrastructures capable of addressing complex biological, behavioral, and social questions at scale. Collectively, they demonstrate that the natural progression of twin registries is toward integration with broader health, demographic, social, and molecular data infrastructure through record linkage. This evolution has set the stage for the next generation of twin research, in which linked data ecosystems enable longitudinal, multi-source, and multi-omics investigations that would not be possible within stand-alone registries.
From Mapping to the Analysis of Record linkage
The current Special Issue of TRHG focuses on a transformation in twin research: the expanding use of record linkage to population databases, biobanks, and multi-disciplinary research infrastructures. Twin registries and research resources have entered an era characterized by large-scale biobanking, multi-omics data generation, linkage to national administrative data and systematic data harmonization in the framework of large-scale collaborations and meta-analyses (Odintsova et al., Reference Odintsova, Willemsen, Dolan, Hottenga, Martin, Slagboom, Ordoñana and Boomsma2018).
Record linkage substantially extends the scientific value of existing research resources by integrating complementary information across cohorts, administrative and health registers, biobanks, and other population-based data sources. Such integration can improve data completeness, extend longitudinal follow-up, and support more informative epidemiological designs without relying exclusively on repeated primary data collection (Ong et al., Reference Ong, Voong, Kwan, Reno, Crume, Grannis, Hill, Silvasstar, Schilling and Kahn2023; Roos et al., Reference Roos, Wall-Wieler, Burchill, Hamm, Hamad and Lix2022). For twin research, linking deeply phenotyped and genetically informative cohorts to population-level data creates particularly powerful opportunities to study health and behavior across the life course. However, realizing these opportunities depends on accurate linkage methods, interoperable data infrastructures, data access, and appropriate ethical, legal, and governance frameworks. Differences in identifiers, data standards, legal frameworks, and privacy requirements continue to limit linkage within and across countries, while linkage errors may introduce bias into subsequent analyses (Intemann et al., Reference Intemann, Kaulke, Kipker, Lettieri, Stallmann, Schmidt, Bialke, Hampf, Stahl, Lablans, Kraywinkel, Bartholomäus, Näher, Tremper, Lambarki, March, Prasser, Haber, Drepper and Ahrens2025; Ong et al., Reference Ong, Voong, Kwan, Reno, Crume, Grannis, Hill, Silvasstar, Schilling and Kahn2023). Advances in privacy-preserving linkage and secure federated infrastructures may help overcome some of these barriers while maintaining data protection and public trust.
This Special Issue brings together 20 contributions describing twin research resources, including two global overviews, and resources with realized or developing record linkage. Spanning 13 countries and two multinational initiatives, these contributions reflect the broad geographical scope and diverse stages of implementation of record linkage in contemporary twin research. Table 1 summarizes the twin research resources included in this Special Issue, their record linkage characteristics, linked data sources, coverage, and associated ethical and legal frameworks.
Overview of twin research resources included in this Special Issue and their record linkage characteristics
Long description
A table with 20 rows and 8 columns summarizing twin research resources. The columns are Country, Did, N 1, Bucket, Linked data sources, Coverage, Ethical and legal frameworks, and Record linkage status. The rows are as follows: Row 1: Country, Denmark; Did, 9; N 1, 28.221196; Bucket, bucket_underscore_2; Linked data sources, Population and anthropometric data, hospital admissions, hospital outpatient visits, pharmacy, psychiatric, psychiatric inpatient and outpatient, causes of death, education, employment, income, and social welfare benefits; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 2: Country, Sweden; Did, 10; N 1, 163.712372; Bucket, bucket_underscore_2; Linked data sources, Multiple databases and health and body measures; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 3: Country, Finland; Did, 11; N 1, 40.355556; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 4: Country, Norway; Did, 12; N 1, 22.222222; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 5: Country, Netherlands; Did, 13; N 1, 24.691358; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 6: Country, United Kingdom; Did, 14; N 1, 15.923077; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 7: Country, Australia; Did, 15; N 1, 8.571429; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 8: Country, United States; Did, 16; N 1, 7.575758; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 9: Country, Italy; Did, 17; N 1, 1.388889; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 10: Country, Spain; Did, 18; N 1, 0.694444; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 11: Country, Belgium; Did, 19; N 1, 0.444444; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 12: Country, France; Did, 20; N 1, 0.277778; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 13: Country, Germany; Did, 21; N 1, 0.222222; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 14: Country, Switzerland; Did, 22; N 1, 0.166667; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 15: Country, Iceland; Did, 23; N 1, 0.111111; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 16: Country, Brazil; Did, 24; N 1, 0.055556; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 17: Country, South Africa; Did, 25; N 1, 0.027778; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 18: Country, Japan; Did, 26; N 1, 0.027778; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 19: Country, China; Did, 27; N 1, 0.027778; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized. Row 20: Country, International; Did, 28; N 1, 0.027778; Bucket, bucket_underscore_2; Linked data sources, Multiple databases; Coverage, Nationwide; Ethical and legal frameworks, Fully approved; Record linkage status, Realized.
Note: Ordered alphabetically by country
Abbreviations: ANPR, National Register of the Resident Population (Anagrafe Nazionale della Popolazione Residente); DASH, Data and Specimen Hub; FIONA, Finnish Intelligent Open Data Platform for Research; GECCO, Geoscience and Health Cohort Consortium; GDPR, General Data Protection Regulation; GIS, Geographic Information System; IRB, Institutional Review Board; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NHS, National Health Service (England); NIH, National Institutes of Health; ODISSEI, Open Data Infrastructure for Social Science and Economic Innovations (Netherlands); SINASC, Live Birth Information System (Sistema de Informações sobre Nascidos Vivos).
The Special Issue opens with two complementary global overviews of contemporary twin research resources. Kuznetsov and Odintsova (this issue) introduce Twin Registries Worldwide, a new online interactive resource hosted on the International Society for Twin Studies (ISTS) website (https://twinstudies.org/information/; also available with the direct link: https://ofnht3-dmitry-kuznetsov.shinyapps.io/version2904/), providing an up-to-date overview of twin registries worldwide, their characteristics, and their reported record linkage activities. Campbell et al. (this issue) present the first comprehensive review of twin cohorts using linked administrative data, examining how administrative data have been used to identify twins, establish and enrich twin cohorts, and support genetically informative research across multiple countries and disciplines. Together, these overview papers provide the broader context for the individual resources presented in this Special Issue.
The remaining contributions comprise 16 twin research resources with realized record linkage, including 11 national twin registries, one international consortium (Interplay of Genes and Environment across Multiple Studies [(IGEMS]), two national multi-cohort twin research resources (German Twin Registry [GERTRUD] and National Project on Achievement in Twins [NatPAT]), and two administrative register-based twin cohorts (from the Norwegian and Swedish Medical Birth Registers). The Special Issue also includes three twin research resources with planned or developing record linkage (University of Sao Paolo [USP] Twin Panel, Hungarian Twin Registry [HTR], and African Twin Registry [AfTR]). Taken together, these contributions illustrate the diversity of contemporary approaches to record linkage, ranging from long-established linkage infrastructures to newly established resources in which linkage is incorporated from the outset.
Across the contributions, record linkage is described at different levels of implementation and scope. Some resources report extensive or near-complete record linkage, covering most or all participants and, in several cases, spanning multiple data domains, including the Older Finnish Twin Cohort, German Twin Family Panel TwinLife, Netherlands Twin Register (NTR), Norwegian Twin Registry (NTR-Norway), Swedish Twin Registry (STR), the Norwegian Medical Birth Registers, the Swedish Medical Birth Registers, and Qatar Twin Registry (QTR). Others describe partial or domain-specific linkage, focused on particular regions, cohorts, or subsamples, including East Flanders Prospective Twin Survey (EFPTS), GERTRUD, Italian Twin Registry (ITR), Murcia Twin Registry (MTR), Twins Early Development Study (TEDS), Early Growth and Development Study (EGDS), NatPAT, and IGEMS.
To further contextualize these efforts, it is useful to distinguish between two complementary levels of linkage — macrodata and microdata — which differ in the scale and nature of the information integrated.
Macrodata linkage involves the integration of area-level or contextual datasets that are not uniquely identifying individuals but are linked via residential address, geographic location, or cohort- or country-level context. In twin studies, macrodata linkage is increasingly used to characterize environmental, socioeconomic, and policy contexts, enabling the analysis of spatial, temporal, and structural influences on health and behavior alongside individual-level genetic and phenotypic data. Across the Special Issue, macrodata linkage takes several forms, including address-based environmental and neighborhood exposures derived from Geographic Information Systems (GIS) and national monitoring systems (NTR, EFPTS, MTR, GERTRUD, German TwinLife), macro-level socioeconomic and inequality indicators used for cross-national or cross-regional comparisons (IGEMS, NatPAT), and policy-level contextual data capturing institutional environments (NatPAT, IGEMS).
Microdata linkage refers to the integration of individual-level records across datasets, typically enabled by unique personal identifiers or secure pseudonymization procedures. In twin research, microdata linkage allows survey-based phenotypes to be complemented with administrative, clinical, educational, and biobank data, supporting longitudinal follow-up, reducing attrition bias, and enabling analyses that combine genetically informative designs with detailed life-course information. Among the contributions in this Special Issue, linked microdata sources include demographic and population registers (EGDS, EFPTS, NTR, MTR, NTR-Norway, STR, Older Finnish Twin Cohort), socioeconomic and administrative registers (NatPAT, EFPTS, NTR, MTR, Older Finnish Twin Cohort), education data systems (NatPAT, MTR, Older Finnish Twin Cohort), health and clinical datasets (TEDS, EFPTS, NTR, STR, Older Finnish Twin Cohort), and pathology registries and biobanks (QTR, NTR, STR). In addition, some resources link less conventional administrative datasets, such as criminal records (Older Finnish Twin Cohort) or animal ownership registries (STR).
Growing demands for larger sample sizes, replication, and cross-country comparison have further accelerated efforts toward data harmonization and consortium-based research. This Special Issue highlights one such initiative — the IGEMS consortium — which illustrates both the scientific potential of harmonized twin data across cohorts and the organizational and methodological challenges of combining linked data across countries with heterogeneous data infrastructures. Similar challenges are discussed for harmonizing linked data across multiple twin studies at the national level in NatPAT.
Finally, two contributions illustrate how newly established twin research resources are being designed from the outset to interface with national infrastructures and biobanks. The QTR integrates twin recruitment with a national biobank and whole-genome sequencing program, embedding classical twin designs within a population-wide precision health framework. Similarly, the GERTRUD was established as a nationwide platform to enable harmonized multi-source data collection and address-based environmental linkage within a GDPR-compliant governance structure.
Taken together, the contributions in this Special Issue demonstrate that record linkage is becoming a core component of contemporary twin research. By extending classical twin designs with administrative, clinical, environmental, and molecular data, record linkage substantially broadens the scientific questions that twin studies can address across the life course.
Ethical and Legal Considerations in Record Linkage
Across the twin research resources represented in this Special Issue, ethical and legal considerations emerge as central determinants of how record linkage is permitted, implemented, governed, and expanded. Although regulatory frameworks differ across countries, common themes include ethical approval, participant consent, data protection, governance arrangements, and secure data access infrastructures.
Among the European resources, GDPR and related national data protection legislation form the principal regulatory framework for record linkage in STR, NTR, ITR, HTR, GERTRUD, IGEMS, and German TwinLife. The corresponding articles highlight how these regulations influence governance arrangements, consent procedures, and technical safeguards such as pseudonymization, trusted third parties, and controlled-access research environments. Several contributions also describe national secure research infrastructures supporting record linkage, including the FIONA (Finnish Intelligent Open data pLatform for Research) remote-access platform in Finland (Older Finnish Twin Cohort), ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations) in the Netherlands (NTR), and virtual research environments supporting secure data access and re-analysis (GERTRUD).
Outside Europe, governance is presented within national regulatory frameworks. The TEDS article describes linkage to National Health Service records within the UK governance framework, including participant consent, the NHS National Data Opt-Out mechanism, public involvement, and access through Trusted Research Environments. In the United States, the EGDS and NatPAT papers emphasize Institutional Review Board (IRB) approval, consent-based access, confidentiality protections for sensitive administrative data, and compliance with NIH data-sharing policies. The QTR article describes linkage with the Qatar Biobank and Qatar Genome Program under informed consent procedures and national governance frameworks for genomic data.
Several contributions also draw attention to country-specific organizational challenges affecting record linkage. The TwinLife and GERTRUD articles discuss the absence of a universal personal identifier and the decentralized organization of data custodians in Germany, while the ITR article highlights legal barriers to accessing Italy’s National Population Register (ANPR). The EFPTS article notes regional constraints on administrative record linkage in Belgium. In contrast, the articles describing the Norwegian and Swedish Medical Birth Registers emphasize national agreements with statistical authorities, secure data environments, the use of anonymized administrative data, and, where appropriate, waiver of informed consent for register-based research.
The articles describing emerging resources (HTR, USP Twin Panel, and AfTR) emphasize that establishing appropriate ethical, legal, and governance frameworks is a prerequisite for future linkage with administrative databases, health records, and biobanks.
Overall, the contributions demonstrate that ethical approval, participant consent, data protection, secure research environments, and transparent governance have become fundamental components of contemporary record linkage in twin research. Although their implementation varies across jurisdictions, these frameworks aim to enable responsible use of linked data while protecting participant privacy and maintaining public trust.
Future Directions
Twin registries have evolved from relatively independent cohorts into interconnected research infrastructures that increasingly operate at the intersection of genetics, environment, and population-level data. Several converging developments now shape the future of twin research, most notably the growing demand for harmonization across registries, the expansion of data linkage with national resources, advances in environmental and exposome research, and the integration of artificial intelligence (AI) approaches. These trends redefine both the opportunities and responsibilities of twin registries worldwide.
Harmonization and Cross-Registry Collaboration
The increasing scale of genetic and epidemiological research has amplified the need for harmonized data across twin registries. Successful cross-cohort initiatives, such as IGEMS and other international consortia, demonstrate the scientific value of pooling twin data to address questions that exceed the statistical power or scope of individual cohorts (Hagenbeek et al., Reference Hagenbeek, Hirzinger, Breunig, Bruins, Kuznetsov, Schut, Odintsova and Boomsma2023; Myers & Bölte, Reference Myers and Bölte2022). Likewise, genomewide and epigenome-wide association studies based on twin and twin family samples now routinely extend beyond classical traits, reflecting the growing maturity and diversity of phenotyping within registries.
As twin registries continue to introduce new measures, many already draw on instruments used in other cohorts to facilitate comparability. Nevertheless, the need for harmonized approaches has never been greater. The expansion of biobanking and the availability of longitudinal physiological and molecular data — often processed using increasingly unified pipelines — contrast sharply with the heterogeneity that still characterizes behavioral and environmental measures. Without deliberate coordination, this heterogeneity risks limiting the interpretability and integrative potential of otherwise highly valuable datasets (Boomsma, Reference Boomsma2013; van Dongen et al., Reference van Dongen, Slagboom, Draisma, Martin and Boomsma2012).
Strategic collaboration across registries offers a path forward. The development and adoption of shared measurement tools and coordinated protocols can ensure that key phenotypes are assessed in comparable ways across cohorts. Importantly, harmonization does not imply uniformity at the expense of contextual specificity. On the contrary, harmonized designs enable the systematic investigation of cultural, cohort-specific, and regional effects, as well as the study of smaller or context-dependent effects that may form essential components of broader causal pathways (Røysamb & Tambs, Reference Røysamb and Tambs2016). Through such collaboration, twin registries can explain more variance and provide a more realistic representation of complex developmental and health-related phenomena.
Record Linkage and Life-Course Perspectives
A second major direction concerns the linkage of twin registry data with national statistical, health, and administrative records. As illustrated throughout this special issue, linked data from governmental and statistical registries represent a rapidly expanding and highly promising resource for behavioral and health research. These data offer longitudinal coverage, population-wide scope, and the ability to trace outcomes across the whole life course of individuals as well across generations. Access to such resources, however, is far from trivial. Record linkage requires sustained efforts to obtain approval from multiple stakeholders, including registry participants, governmental and statistical institutes, and, in some cases, third-party data custodians. Ethical governance, transparency, and participant trust are therefore central to the long-term success of linkage initiatives (Myers & Bölte, Reference Myers and Bölte2022).
Importantly, analyses based solely on administrative or registry-based data, while powerful, are often fragmented and limited in their ability to illuminate underlying mechanisms. Their value increases substantially when linked to methodically collected historical behavioral, psychological, and biological data that are a defining feature of many twin registries. This combination enables researchers to study distal and cumulative effects, trace developmental trajectories, and better understand how early-life exposures shape mental health, wellbeing, and disease risk across the lifespan (Boomsma et al., Reference Boomsma, Busjahn and Peltonen2002; Davis et al., Reference Davis, Turkheimer, Finkel, Beam and Ryan2019). In this way, linkage transforms twin registries from isolated cohorts into truly life-course research infrastructures within macro-social context.
Environmental and Exposome Research
Alongside genetic and molecular advances, interest in the systematic characterization of environmental exposures — the exposome — continues to grow. Technological developments in smart sensing, wearable devices, and geographic information systems now allow environmental factors to be measured with unprecedented spatial and temporal resolution. These advances create new opportunities to examine subtle environmental changes and long-term exposure patterns in relation to health and behavior (Tarnoki et al., Reference Tarnoki, Tarnoki and Molnar2014).
Yet, in contrast to the relatively standardized pipelines available for genetic and omics data, environmental data lack uniform approaches to preprocessing, harmonization, and analysis. The integration of exposome data into twin research therefore presents the methodological challenges to handle. Developing standards for environmental data collection and processing will remain a priority, particularly if such data are to be meaningfully combined across cohorts and linked to molecular and phenotypic measures (Watanabe, Reference Watanabe2025).
AI, Machine Learning
The growth of biobanking and linked data within twin registries makes them well suited for the application of AI and machine learning techniques. Both supervised and unsupervised approaches offer opportunities for hypothesis-free discovery, including the identification of interaction effects across environments, genetic variants, and omics layers. Such approaches may reveal patterns that are difficult to detect using traditional hypothesis-driven methods.
At the same time, these methods introduce new challenges. The rapid expansion of the analytical search space does not automatically translate into increased statistical power, and the interpretation of complex, high-dimensional models remains difficult. Moreover, the extensive use of AI raises established and emerging ethical issues related to data privacy, security, ownership, storage, and governance — issues that are particularly salient in the context of linked population-level data (Myers & Bölte, Reference Myers and Bölte2022).
Conclusions
Taken together, these developments underscore the continued and evolving value of twin registries. Rather than being superseded by large population cohorts, twin studies are increasingly positioned as integrative frameworks that connect genomic, other omics, environmental twin and twin family data to national registries data, strengthening causal inference and life-course perspectives that are otherwise difficult to achieve (Hagenbeek et al., Reference Hagenbeek, Hirzinger, Breunig, Bruins, Kuznetsov, Schut, Odintsova and Boomsma2023; van Dongen et al., Reference van Dongen, Slagboom, Draisma, Martin and Boomsma2012). Recent applications, including the study of infectious disease susceptibility and host response, further highlight the unique contribution of twin designs to emerging global health challenges (Smatti et al., Reference Smatti, Yassine, Mbarek and Boomsma2025). Addressing the challenges of harmonization, linkage, sustainability, and ethical governance will be essential to ensure that twin registries remain at the forefront of biomedical, behavioral, and population research in the decades to come.
Multiple overviews and special issues together form a multi-volume chronology of the development of global twin registries. The earlier issues documented the existence and scale of twin-family resources worldwide. The present issue documents how those registries were enriched through biobanking, record linkage, legally structured platforms for population science. These developments position twin registries as uniquely valuable global resource for addressing major scientific and societal questions in the coming decades.
Acknowledgements
We acknowledge the Royal Dutch Academy of Arts and Sciences (KNAW) Academy Professor Award (PAH/6635).
Funding Statement
Open access funding provided by Vrije Universiteit Amsterdam.
Open access
