The Scottish Family Health Study
The Scottish Family Health Study (GS:SFHS) is a collection of genetic, medical, family history and lifestyle information from over 24,000 volunteers. This is an excellent resource for conducting studies on how our genes and the environment combine to affect our chance of getting common diseases.
The Scottish Family Health Study (GS:SFHS) is an intensively phenotyped, family-based cohort for the study of the genetic basis of common complex diseases and response to treatments. Recruitment began early in 2006 and was completed in 2011. The cohort includes just over 24,000 participants, with most consenting to record linkage and recontact.
Each participant gave blood or saliva samples (for processing, biochemistry and cryopreservation) and a urine sample. The blood or saliva samples were processed to DNA and extensive genotyping was carried out on over 20,000 participants by 2015.
Please see the following references for a description of the methods used for data collection:
- Smith, B. H., Campbell, A., Linksted, P., Fitzpatrick, B., Jackson, C., Kerr, S. M., … Morris, A. D. (2013). Cohort Profile: Generation Scotland: Scottish Family Health Study (GS:SFHS). The study, its participants and their potential for genetic research on health and illness. International Journal of Epidemiology, 42(3), 689-700.
- Smith, B. H., Campbell, H., Blackwood, D., Connell, J., Connor, M., Deary, I. J., … Morris, A. D. (2006). Generation Scotland: the Scottish Family Health Study; a new resource for researching genes and heritability. BMC Medical Genetics, 7, 74.
To help design studies, a data dictionary for GS:SFHS is available.
GS summary data can be viewed on the Data Portal, which is accessible by logging into an online GS Access User Account.
- Demographic details
- Occupational history
- Lifestyle – smoking, alcohol, diet and exercise
- Personal and family medical history, age at menarche and menopause
- Rose angina questionnaire
- Musculoskeletal questions – including Chronic Pain Grade, history of fractures
- Current drug history, including prescribed and non-prescribed medications, HRT use
- Height, weight, waist-hip ratio
- Blood pressure x 2 (Omron BP Monitor), resting pulse
- Ankle brachial pressure index (ABPI)
- Spirometry - FEV1, FVC, FEF
- Bioimpedance (% body fat)
Cognitive function measurements
- Eysenck Personality Questionnaire Revised Short Form
- Logical Memory from the Wechsler Memory Scale III
- Digit Symbol from the Wechsler Adult Intelligence Scale III
- Verbal Fluency
- Mill Hill Vocabulary Scale
- General Health Questionnaire – 28
Mental health measurements
- SCID Brief screening interview for major depression
- SPQ-B Personality Questionnaire
- MDQ Mood Questionnaire
- Total cholesterol
- HDL cholesterol
Generation Scotland has worked with a number of collaborators on generating genetic data on its resource, in particular with the MRC Institute of Genetics and Molecular Medicine Quantitative Trait Locus (QTL) group.
DNA from over 20,000 GS:SFHS participants has been analysed by high density genome-wide chip genotyping, Illumina OmniExpress SNP GWAS (700k) and exome chip (250K), with low failure and high call rates. QC analyses were performed, data cleaned using quality scores and proportions typed. Sample identity was verified against recorded gender and pedigree and data checked for unknown relationships based on estimated identity-by-descent. Population stratification was assessed by analysis of principal components and imputing all data to the 1000 Genome data set.
The quality of the checked data was assessed by GWAS analysis on anthropometric and lipid phenotypic quantitative traits. Family relationships were corrected for using a polygenic kinship matrix and for population stratification using principal component analysis. These results are being compared with those in published meta-analyses and the genome-wide data are being used by the QTL group in a range of research projects involving both international consortia and local experts. For example, cognition research is being led by colleagues at the University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology and a wide range of phenotypes is being analysed in collaboration with the CHARGE consortium. Methylation data is currently being analysed on a subset of 5,000 samples.
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