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ABSTRACTObjectivesGeneration Scotland: Scottish Family Health Study (GS:SFHS) is a family-based genetic epidemiology study of ~24,000 volunteers from ~7000 families recruited across Scotland between 2006 and 2011 with the capacity for follow-up through record linkage and re-contact.
ApproachParticipants completed a demographic, health and lifestyle questionnaire and provided biological samples including DNA, and 90% underwent detailed clinical assessment, including anthropometric, cardiovascular, respiratory, cognition and mental health. The biological samples, phenotype and genotype data collected form a resource with broad consent for academic and commercial research on the genetics of health, disease and quantitative traits of current and projected public health importance. Features include the family-based recruitment; breadth and depth of phenotype information, with detailed data on cognition, personality and mental health. GWAS and exome genotype data is available on most of the cohort. These features maximise the power of the resource to identify, replicate or control for genetic factors associated with a wide spectrum of illnesses and risk factors. By linkage to routine NHS hospital, lab tests, prescribing and dental records this has become a longitudinal dataset, using the Scottish Community Health Index (CHI).
Results Researchers are now able to use the dataset to find prevalent and incidental disease cases, and healthy controls, to test research hypotheses on a stratified population. They can also do targeted recruitment of participants to new studies, utilising the NHS CHI register for up to date contact details. There are 6 published papers on a variety of conditions and currently around 10 ongoing studies based on our record linkage capabilities.
ConclusionWe have thoroughly tested the linkage process and plan to extend it to include primary care data (GP records) in the next year. There are current or planned collaborations looking into heart disease, diabetes, breast and colon cancers, depression, neuropathic pain, Alzheimer's disease and dementia. Generation Scotland is also a contributor to major international consortia. The resources are available to academic and commercial researchers through a managed access process.

Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based genetic epidemiology study of ~24,000 volunteers from ~7000 families recruited across Scotland between 2006 and 2011 with the capacity for follow-up through record linkage and re-contact. Broad consent was obtained for linkage to "medical records" for 98% of the cohort.
Participants completed a questionnaire, provided samples, and underwent clinical assessment. The samples and data collected form a resource with consent for research on the genetics of health, becoming a longitudinal dataset by linkage to routine NHS hospital, maternity, lab test, prescribing, dentistry and mortality data.
Researchers can use the linked datasets to test research hypotheses on a stratified population and target recruitment to new studies. We have established and validated EHR linkage, overcoming technical and governance issues in the process. We plan to collaborate with UK Biobank, creating a combined cohort of over 50,000 people in Scotland, and using the SHARE register to obtain new research samples from routine NHS tests.
We will extend linkage to include primary care data and scanned images in the next year. The resources are available to academic and commercial researchers through a managed access process.

ObjectivesWe started a family-based genetic epidemiology study in 2006-11 which recruited ~24,000 adult volunteers from ~7000 families across Scotland with consent for follow-up through medical record linkage and re-contact. In 2022-23 we are recruiting another 20,000, with consent extended to administrative records, with age range now 12+.
MethodsOriginal volunteers completed a demographic, health and lifestyle questionnaire, provided biological samples, and underwent detailed clinical assessment. The samples, phenotype and genotype data form a resource for research on the genetics of conditions of public health importance. This has become a longitudinal dataset by linkage to routine NHS hospital, maternity, lab test, prescriptions, dentistry, mortality, imaging, cancer screening, GP data records, Covid-19 testing and vaccinations, as well as follow-up questionnaires. The new wave of recruitment is all online and can be done on a smartphone, with DNA from saliva collected by post. Teenagers aged 12-15 can join with parental consent.
Results GWAS has been done on quantitative traits and biomarkers, with DNA methylation data and proteomics available for most of the cohort. Our "CovidLife" surveys collected data on effects of the pandemic.
Researchers can find prevalent and incident disease cases and controls, to test research hypotheses on a stratified population. They can also do targeted recruitment of participants to new studies, including recall by genotype. We have established and validated E-HR linkage with the NHS Scotland CHI Register,,overcoming technical and governance issues in the process. We contribute to major international consortia, with collaborators from institutions worldwide, both academic and commercial. Recruits are asked to give consent to linkage to other administrative data, and reuse of samples from routine NHS tests for medical research.
Conclusion We plan to extend the linkage process to include other administrative data from national datasets as and when approvals are obtained. New types of data can also be collected by online questionnaires. The Research Tissue Bank resources are available to academic and commercial researchers through a managed access process.

Background Generation Scotland is a family-based genetic epidemiology study of ~24,000 volunteers from ~7000 families recruited across Scotland with the capacity for follow-up through record linkage and re-contact. Broad consent was obtained for linkage to "medical records" for 98% of the cohort. This created a resource for investigation of the genetics of common conditions, available to researchers worldwide.
Methods Participants completed a demographic, health and lifestyle questionnaire, provided samples, and underwent detailed clinical assessment. The samples and data collected form a resource with broad consent for research on the genetics of conditions of current and projected public health importance. This has become a longitudinal dataset by linkage to routine NHS hospital, maternity, lab tests, prescribing, dentistry, and mortality data.
Results Researchers can use the linked datasets to find prevalent and incident disease cases, and healthy controls, in a stratified population. They can also do targeted recruitment of participants to new studies, including recall by genotype. We have established and validated EHR linkage, overcoming technical and governance issues in the process. Using consented data avoids some limitations of safe havens for analysis.
Genome-wide association studies (GWAS) have been done on a wide range of quantitative traits and biomarker measurements. Generation Scotland is a contributor to major international consortia and has collaborated with Dementia Platforms UK and Health Data Research UK to make the resources more widely known. There have been over 300 research collaborations, and GS data has contributed to 200 publications, with more in the pipeline.
Conclusions Generation Scotland has thoroughly tested the linkage process and is extending it to include primary care data and scanned images, with plans to collect more samples and data. The resources are available to academic and commercial researchers through a managed access process (www.generationscotland.org).

ObjectivesGeneration Scotland (GS) is a family-based genetic epidemiology study of around 24,000 volunteers from 7000 families recruited across Scotland between 2006 and 2011 with follow-up through record linkage and re-contact. Broad consent was obtained for linkage to medical records for 98% of the cohort. Recruitment has recommenced in 2022.
ApproachParticipants completed a demographic, health and lifestyle questionnaire, provided biological samples, and underwent detailed clinical assessment. The samples, phenotype and genotype data form a resource with broad consent for health-related research of current and projected public health importance.
This has become a longitudinal dataset by linkage to routine NHS hospital, maternity, lab test, prescriptions, dentistry, mortality, cancer screening, GP data records, Covid-19 testing and vaccinations. Genome-wide association studies (GWAS) have been done on quantitative traits and biomarkers, with DNA methylation data and proteomics available for most of the cohort. Our "CovidLife" surveys collected data on the effects of the pandemic.
ResultsResearchers can use the linked datasets to ascertain prevalent and incident disease cases and controls to test a wide range of research hypotheses. They can also recruit participants to new studies, including recall by genotype, utilising the NHS Scotland Community Health Index (CHI) Register for current contact details. We have established and validated electronic health record linkage, overcoming technical and governance issues in the process. Using consented data avoids some limitations of safe havens for analysis.
GS is a contributor to major international consortia, with collaborators from many institutions worldwide, both academic and commercial. New recruits are now asked to give consent to linkage to other administrative data, and reuse of samples from routine NHS tests for medical research.
ConclusionGS is now extending linkages to include radiology and health-relevant administrative data (e.g. education); and reopening recruitment to double the cohort size, including teenagers age 12+, collecting new data online and using remote sample collection.
GS resources are available to academic and commercial researchers through a managed access process (www.generationscotland.org).

ABSTRACT
BackgroundElectronic health records provides unprecedented opportunity for their re-use in genetic epidemiological research. However, electronic health records data from clinical settings, such as dental practices may be inaccurate or of insufficient granularity to be of use in research. In this study, we wish to determine the utility of National Health Service (NHS) electronic dental treatment records in genetic epidemiological research.
ObjectiveTo estimate the heritability of periodontal disease using NHS electronic dental treatment records linked to health and non-health data within the Generation Scotland: Scottish Family Health Study (GS:SFHS).
ApproachWe linked 852,355 NHS Scotland electronic dental treatment records from April 2000 to July 2015 to 20,626 participants within the GS:SFHS with pedigree, genomic, sociodemographic and clinical data. We then conducted a proof-of-principle genetic epidemiological analysis using periodontal (gum) disease treatment records. The data set analysed, consisted of 160,508 dental treatment records from 13,717 study participants; 3,387 of which were periodontal treatment records (from 2,192 study participants). We adjusted for the effects of previous treatment record, interval since last treatment, age, sex, treatment year, and treatment month, Scottish index of multiple deprivation, alcohol consumption, diabetes diagnosis, and smoking status in a linear model in the statistical software ASReml. We then calculated the mean risk of periodontal disease for each study participant based on residuals extracted from the aforementioned model. Genome-complex trait analysis (GCTA; with correction for population stratification) was used to estimate the pedigree and genomic based heritability of periodontal disease.
ResultsWe estimate the familial heritability of periodontal (gum) disease at 10.42% (95% confidence interval 5.97-14.88%). The genomic component did not contribute significantly to the heritability estimate.
Conclusionwe have demonstrated the usefulness of electronic dental treatment records in population based genetic epidemiological research .This study has also, to the best of our knowledge provided the first population based estimates of the genetic parameters for periodontal disease; confirming its familial nature. This invaluable and unique data resource will allow the acceleration of oral health research in Scotland and the exploration of research questions that could not be considered previously.

IntroductionHeritability (proportion of trait variation attributable to genetic factors) is not a fixed property. It can vary across different social settings and environments. Exploration of gene-environment interaction has been limited by lack of large sample sizes. Biobanks linked to electronic health records pose a solution to this sample size problem.
Objectives and ApproachSocial inequalities in periodontal health have been well documented in the dental scientific literature. However, gene-socioeconomic status interaction has yet to be examined. We identified 2,192 cases and 11,525 controls from linked electronic periodontal treatment records within the Generation Scotland: Scottish Family Health Study (GS: SFHS) (www.generationscotland.org). The measure of socioeconomic status used was the Scottish Index of Multiple Deprivation. The objective of this study was to investigate the gene-socioeconomic status interaction within this data. A reaction norm model was used to evaluate the presence of a gene-socioeconomic status interaction in the statistical software ASReml.
ResultsWe estimated the heritability of periodontal disease at 10.42% (95% confidence interval 5.97-14.88%). Socioeconomic status modified the heritability of periodontal disease. The heritability of was 13.37%, 0.14% and 11.70% in areas of high, moderate and low deprivation respectively; indicating the occurrence of a gene-socioeconomic status interaction with periodontal disease. These results indicate that socioeconomic status explains a large portion of genetic variation in periodontal disease risk. This information suggests that effective intervention and prevention programs for periodontal disease should involve socioeconomic aspects in their planning, implementations and evaluation. For instance, interventions targeted to reduce smoking in more deprived subjects with a genetic predisposition to periodontal disease could enhance the effect of health promotion strategies in reducing risk.
Conclusion/ImplicationsThis study presents contemporary evidence in a large population based cohort that gene-socioeconomic interaction leads to the progression of periodontal disease. This information may lead to the development of better preventative strategies for clinical dentistry.

ObjectivesGeneration Scotland (GS) is a family-based genetic epidemiology study. Initial recruitment between 2006-11 recruited ~24,000 adults from ~7000 families across Scotland with consent for medical record linkage and re-contact. In 2022 we began recruiting another 20,000, with consent extended to administrative records, with age range now 12+.
MethodsOriginal volunteers completed a baseline questionnaire, provided biological samples and underwent clinical assessment. The samples, phenotype and genotype (including methylation) data are linked to routine NHS hospital, maternity, lab test, prescriptions, dentistry, mortality, imaging, cancer screening, GP data records, Covid-19 testing and vaccinations, and follow-up questionnaires. The new wave of recruitment is all online and can be done on a smartphone, with DNA from saliva collected by post. Teenagers aged 12-15 can join with parental consent.
ResultsResearchers can find prevalent and incident disease cases and controls, to test research hypotheses on a stratified population. GS is a vanguard cohort testing emerging linkage opportunities in Scotland – including neonatal bloodspots and medical imaging reports. GS has established and validated E-HR linkage with the NHS Scotland CHI Register, overcoming technical and governance issues in the process. We contribute to major international consortia, with collaborators from institutions worldwide, both academic and commercial.
ConclusionWe plan to extend the linkage process to include other administrative data from national datasets as and when approvals are obtained. New types of data can also be collected by online questionnaires. The Research Tissue Bank resources are available to academic and commercial researchers through a managed access process.

BackgroundGeneration Scotland (GS) is large family-based cohort study established as a resource for research into the genetic and environmental determinants of physical and mental health. Participants completed a baseline questionnaire and clinic visit in 2006-2011.
24,084 Participants
5,501 Families

NHS data linkage 22,402 (93%)
Genotype array data 20,026 (83%)
DNA methylation data 18,876 (78%)

In 2019 funding was obtained to expand the existing GS cohort. By 2025 NextGenScot aims to:

Recruit 20,000 new participants online
Expand eligibility to 12-17 year olds
Collect saliva samples by post for genotyping
Linkage to NHS and other administrative data

Details on how to join at www.gen.scot
Participants consented to linkage to NHS Scotland medical records which offer longitudinal phenotype information. Linkage is conducted using the Community Health Index (CHI).
IntroductionGS receives 30-40 requests for access to data and/or samples every year, and has been included in over 380 publications. Research proposals are subject to review by the GS Access Committee. Details of the application process terms and conditions for access are available on the GS website, and now on the new research access website.
The previous GS access process was based on an application form in Word, downloaded from the main GS website. We are replacing this with a new online research access system, adhering to transparency standards1, helped by HDR Alliance Transparency funding.
After researchers publish their results, a link to the publication and a lay summary is currently posted on the GS website, with a spreadsheet listing papers. We will now make this information available and searchable for researchers, participants and the public on the new research access website.
MethodsWe are developing a website, using in-house staff, with HDR Alliance Transparency contributing to their salaries. The system coding uses Django (a Python tool) linked to a MySQL database, a platform widely used for such projects, enabling faster development in a secure environment.
Transparent access to GS data for registered users

View summary of data available
Query the summary data to see if it fits research requirements
Select data requested from data dictionaries
Get a detailed quote for access charges
Complete application form showing the project complies with the Five Safes2
Upload supporting documentation (e.g. protocol, DPIA, ethics, etc)
Track progress of their application review, approval and delivery
Researchers will be required to submit a lay summary of their application

GS participants, researchers and the public can view:

List of approved applications with lay summaries
Summaries of ongoing projects which will link to eventual publications
Searchable list of publications

ResultThe new system is undergoing internal testing, using data imported from previous and ongoing access requests (May 2024). We will then pilot it with selected external researchers and GS participants (June 2024), with a plan to launch it for public access in July/August 2024.
The GS Access Committee and admin team will be able to streamline the review and approval process, giving an improved turnaround time.
ConclusionsWe were already planning to develop a new online application system, but the Transparency grant funding has enabled us to extend the functionality beyond a simple form-filling system. The new access website will give researchers more information about the application process, the data and samples available, see what other research has been approved in their area of interest, and track the progress of their project from enquiry through to publication.
By adding a participant/public access area, with lay summaries of projects and publications, GS participants will be able to see how their data is being used for public benefit, as can potential new volunteers or other interested parties.
NotesThe URL for the new website is www.gsaccess.orgThe main GS website is at www.generationscotland.org
References

Transparency Standards https://zenodo.org/record/8262453
Five Safes https://ukdataservice.ac.uk/help/secure-lab/what-is-the-five-safes-framework/

ObjectivesThere were two objectives to this study: 1) to gauge public opinion on the use of Guthrie card-derived blood samples for epidemiological and biological research; and 2) to evaluate the feasibility of recovering meaningful molecular data from these samples.
ApproachTo address the first objective, a 2-day Citizens' Jury was conducted in partnership with Ipsos MORI, comprising a diverse adult sample in terms of age, sex, working status and social grade (n=20). Jurors were asked whether research access to Guthrie card blood tests would be in the public interest. To address the second objective, DNA methylation (DNAm) was profiled from samples from 58 Generation Scotland participants, whose Guthrie cards had been stored from birth for between 32 and 38 years. Analyses were performed on Guthrie DNAm samples to determine whether previously-reported associations with perinatal maternal smoking behaviours were detectable.
ResultsThe Citizens' Jury yielded an overall positive response towards data sharing for health research. Concerns were raised about data protection and security, control and oversight, and commercial use. The overall verdict was that access to Guthrie card data would be in the public interest, conditional on the purpose of the research, regulated access procedures, ethical oversight and provision of opportunities for participants to opt out.
DNAm detection rates from Guthrie samples were lower than from samples stored in tubes. However, it was possible to confirm linkage to the correct individuals in Generation Scotland using DNAm-derived estimates of genotype and sex. A significant association was observed between a DNAm-based score for smoking and perinatal maternal smoking status derived from the baseline Generation Scotland questionnaire.
ConclusionWe showed that: 1) public support exists for using Guthrie samples in research, conditional on certain safeguards; 2) DNAm can be profiled from cards stored for up to 38 years and can predict maternal smoking behaviour. Guthrie cards are a potentially valuable resource for epidemiological studies and predicting health outcomes.

Acknowledgements: The authors thank all LBC study participants and research team members who have contributed, and continue to contribute, to the ongoing LBC study. The LBC1936 is supported by Age UK (Disconnected Mind programme) and the Medical Research Council [MR/M01311/1]. The LBC1921 is supported by the Biotechnology and Biological Sciences Research Council [SR176], the Chief Scientist Office [CZB/4/505; ETM/55] and the Medical Research Council [R42550]. Methylation typing was supported by the Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. This work was conducted in the Centre for Cognitive Ageing and Cognitive Epidemiology, which is supported by the Medical Research Council and Biotechnology and Biological Sciences Research Council [MR/K026992/1], and which supports Ian Deary. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award "STratifying Resilience and Depression Longitudinally" [(STRADL) 104036/Z/14/Z]) ; Peer reviewed ; Publisher PDF

This work was supported by a Alzheimer's Research UK Major Project grant (ARUK-PG2017B-10). Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team that includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, health-care assistants and nurses. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award "STratifying Resilience and Depression Longitudinally" [STRADL];104036/Z/14/Z). DNA methylation data collection was funded by the Wellcome Trust Strategic Award (10436/Z/14/Z). The research was conducted in the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and Medical Research Council (MRC) is gratefully acknowledged. CCACE supports I.J.D. with some additional support from the Dementias Platform UK (MR/L015382/1). A.M.M. and H.C.W. have received support from the Sackler Institute. ; Peer reviewed ; Publisher PDF

Variation in human cognitive ability is of consequence to a large number of health and social outcomes and is substantially heritable. Genetic linkage, genome-wide association, and copy number variant studies have investigated the contribution of genetic variation to individual differences in normal cognitive ability, but little research has considered the role of rare genetic variants. Exome sequencing studies have already met with success in discovering novel trait-gene associations for other complex traits. Here, we use exome sequencing to investigate the effects of rare variants on general cognitive ability. Unrelated Scottish individuals were selected for high scores on a general component of intelligence (g). The frequency of rare genetic variants (in n = 146) was compared with those from Scottish controls (total n = 486) who scored in the lower to middle range of the g distribution or on a proxy measure of g. Biological pathway analysis highlighted enrichment of the mitochondrial inner membrane component and apical part of cell gene ontology terms. Global burden analysis showed a greater total number of rare variants carried by high g cases versus controls, which is inconsistent with a mutation load hypothesis whereby mutations negatively affect g. The general finding of greater non-synonymous (vs. synonymous) variant effects is in line with evolutionary hypotheses for g. Given that this first sequencing study of high g was small, promising results were found, suggesting that the study of rare variants in larger samples would be worthwhile.

Generation Scotland has received core funding from the Chief Scientist Office of the Scottish Government Health DirectoratesCZD/16/6 and the Scottish Funding CouncilHR03006. We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants and nurses. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland and was funded by the UK's Medical Research Council. The Quantitative Trait Locus team at the Human Genetics Unit is funded by the Medical Research Council. REM, GD, DL, ML, DJP, PMV, and IJD undertook the work within The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (MR/K026992/1), part of the cross council Lifelong Health and Wellbeing Initiative. Funding from the BBSRC and MRC is gratefully acknowledged. REM is an Alzheimer's Research UK Fellow (ART-RF2010-2). ; Peer reviewed ; Publisher PDF