Generation Scotland - Using Electronic Health Records for Research

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.

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Cohort Profile: Stratifying Resilience and Depression Longitudinally (STRADL): a questionnaire follow-up of Generation Scotland: Scottish Family Health Study (GS:SFHS)

International Journal of Epidemiology ◽

10.1093/ije/dyx115 ◽

2017 ◽

Vol 47 (1) ◽

pp. 13-14g ◽

Cited By ~ 32

Author(s):

L B Navrady ◽

M K Wolters ◽

D J MacIntyre ◽

T-K Clarke ◽

A I Campbell ◽

...

Keyword(s):

Family Health ◽

Health Study ◽

Generation Scotland

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Generation Scotland - Using Electronic Health Records for Research

International Journal for Population Data Science ◽

10.23889/ijpds.v4i3.1174 ◽

2019 ◽

Vol 4 (3) ◽

Author(s):

Archie Campbell ◽

Rachel Edwards ◽

David Porteous

Keyword(s):

Association Studies ◽

Mortality Data ◽

Genome Wide Association Studies ◽

Broad Consent ◽

Public Health Importance ◽

Generation Scotland ◽

Wide Range ◽

Lifestyle Questionnaire ◽

Scanned Images ◽

Family Based

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).

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Generation Scotland: using data linkage for longitudinal studies

International Journal for Population Data Science ◽

10.23889/ijpds.v1i1.82 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Archie Campbell

Keyword(s):

Mental Health ◽

Biological Samples ◽

Record Linkage ◽

Wide Spectrum ◽

Family Health ◽

Health Study ◽

Genotype Data ◽

Public Health Importance ◽

Generation Scotland ◽

Family Based

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.

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1461-P: Cardiac Troponin T and Troponin I and Incident Diabetes in the General Population: Generation Scotland Scottish Family Health Study

Diabetes ◽

10.2337/db19-1461-p ◽

2019 ◽

Vol 68 (Supplement 1) ◽

pp. 1461-P

Author(s):

PAUL WELSH ◽

DAVID PREISS ◽

ARCHIE CAMPBELL ◽

DAVID J. PORTEOUS ◽

NICHOLAS L. MILLS ◽

...

Keyword(s):

General Population ◽

Cardiac Troponin ◽

Troponin I ◽

Troponin T ◽

Family Health ◽

Incident Diabetes ◽

Health Study ◽

Cardiac Troponin T ◽

Generation Scotland

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Phenotypic and genetic analysis of cognitive performance in Major Depressive Disorder in the Generation Scotland: Scottish Family Health Study

Translational Psychiatry ◽

10.1038/s41398-018-0111-0 ◽

2018 ◽

Vol 8 (1) ◽

Cited By ~ 3

Author(s):

Joeri J. Meijsen ◽

Archie Campbell ◽

Caroline Hayward ◽

David J. Porteous ◽

Ian J. Deary ◽

...

Keyword(s):

Major Depressive Disorder ◽

Genetic Analysis ◽

Depressive Disorder ◽

Cognitive Performance ◽

Family Health ◽

Health Study ◽

Major Depressive ◽

Generation Scotland

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536. Cognitive Performance in Major Depressive Disorder in Generation Scotland: The Scottish Family Health Study (GS:SFHS)

Biological Psychiatry ◽

10.1016/j.biopsych.2017.02.1144 ◽

2017 ◽

Vol 81 (10) ◽

pp. S217

Author(s):

Joeri Meijsen ◽

Archie Campbell ◽

Andrew McIntosh ◽

David Porteous ◽

Ian Deary ◽

...

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Cognitive Performance ◽

Family Health ◽

Health Study ◽

Major Depressive ◽

Generation Scotland

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Intelligence and neuroticism in relation to depression and psychological distress: evidence of interaction using data from Generation Scotland: Scottish Family Health Study and UK Biobank

10.1101/039545 ◽

2016 ◽

Cited By ~ 1

Author(s):

LB Navrady ◽

SJ Ritchie ◽

SWY Chan ◽

DM Kerr ◽

MJ Adams ◽

...

Keyword(s):

Psychological Distress ◽

Significant Interaction ◽

Protective Factor ◽

Short Form ◽

Family Health ◽

Population Based ◽

Depressive Illness ◽

Health Study ◽

Uk Biobank ◽

Generation Scotland

ABSTRACTBackgroundNeuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined.MethodsAssociations and interactions between neuroticism and general intelligence (g) on MDD and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, N=19,200) and UK Biobank (N=90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS.ResultsNeuroticism was associated with MDD and psychological distress in both samples. A significant interaction between neuroticism and g in predicting MDD status was found in UK Biobank (OR = 0.96, p < .01), suggesting that higher g ameliorated the adverse effects of neuroticism on the likelihood of having MDD. This interaction was not found in GS:SFHS. In both samples, higher neuroticism and lower intelligence were associated with increased psychological distress. A significant interaction was also found in both cohorts (GS:SFHS: ß = -0.05, p < .01; UK Biobank: ß = -0.02, p < .01), such that intelligence protected against the deleterious effect of neuroticism on psychological distress.ConclusionsFrom two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on risk for depressive illness and psychological distress.

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Generation Scotland participant survey on data collection

Wellcome Open Research ◽

10.12688/wellcomeopenres.15354.2 ◽

2019 ◽

Vol 4 ◽

pp. 111 ◽

Cited By ~ 1

Author(s):

Rachel Edwards ◽

Archie Campbell ◽

David Porteous

Keyword(s):

Data Collection ◽

Online Survey ◽

Family Health ◽

Dried Blood Spots ◽

Health Study ◽

Health Determinants ◽

Sample Collection ◽

Generation Scotland ◽

High Level ◽

Remote Data

Background: Generation Scotland (GS) is a population and family-based study of genetic and environmental health determinants. Recruitment to the Scottish Family Health Study component of GS took place between 2006-2011. Participants were aged 18 or over and consented to genetic studies, linkage to health records and recontact. Several recontact exercises have been successfully conducted aimed at a) recruitment to embedded or partner studies and b) the collection of additional data. As the cohort matures in age, we were interested in surveying attitudes to potential new approaches to data collection and recruitment. Methods: A ten-question online survey was sent to those participants who provided an email address. Results: We report a high level of positive responses to encouraging relatives to participate, to remote data and sample collection and for research access to stored newborn dried blood spots. Conclusions: The majority of current and prospective GS participants are likely to respond positively to future requests for remote data and sample collection.

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