| Literature DB >> 25826379 |
Cathie Sudlow1, John Gallacher2, Naomi Allen3, Valerie Beral4, Paul Burton5, John Danesh6, Paul Downey7, Paul Elliott7, Jane Green4, Martin Landray4, Bette Liu8, Paul Matthews7, Giok Ong9, Jill Pell10, Alan Silman11, Alan Young4, Tim Sprosen4, Tim Peakman12, Rory Collins3.
Abstract
Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.Entities:
Mesh:
Year: 2015 PMID: 25826379 PMCID: PMC4380465 DOI: 10.1371/journal.pmed.1001779
Source DB: PubMed Journal: PLoS Med ISSN: 1549-1277 Impact factor: 11.069
Approximate numbers of incident cases of some exemplar conditions expected to accrue during the first 20 years of follow-up in UK Biobank.
| Condition | 2012 | 2017 | 2022 | 2027 |
|---|---|---|---|---|
| Diabetes mellitus | 10,000 | 25,000 | 40,000 | 68,000 |
| MI and coronary death | 7,000 | 17,000 | 28,000 | 47,000 |
| Stroke | 2,000 | 5,000 | 9,000 | 20,000 |
| COPD | 3,000 | 8,000 | 14,000 | 25,000 |
| Breast cancer (female) | 2,500 | 6,000 | 10,000 | 16,000 |
| Colorectal cancer | 1,500 | 3,500 | 7,000 | 14,000 |
| Prostate cancer | 1,500 | 3,500 | 7,000 | 14,000 |
| Lung cancer | 800 | 2,000 | 4,000 | 8,000 |
| Hip fracture | 800 | 2,500 | 6,000 | 17,000 |
| Rheumatoid arthritis | 800 | 2,000 | 3,000 | 5,000 |
| Alzheimer’s disease | 800 | 3,000 | 9,000 | 30,000 |
| Parkinson’s disease | 1000 | 3,000 | 6,000 | 14,000 |
Based on UK age- and sex-specific rates with adjustment for healthy cohort effects and losses to follow-up [6].
MI: myocardial infarction; COPD: chronic obstructive pulmonary disease or chronic bronchitis/emphysema
Data collected at the baseline assessment.
| Questionnaire and interview | |
|---|---|
| Sociodemographic | Social class; ethnicity; employment status; marital status; education; income; car ownership |
| Family history and early life exposures | Family history of major diseases; birth weight; breast feeding; maternal smoking; childhood body size; residence at birth |
| Psychosocial factors | Neurosis; depression (including bi-polar spectrum disorder); social support |
| Environmental factors | Current address; current (or last) occupation; domestic heating and cooking fuel; housing; means of travel; shift work; mobile phone use; sun exposure |
| Lifestyle | Smoking; alcohol consumption; physical activity; diet; sleep |
| Health status | Medical history; medications; disability; hearing; sight; sexual and reproductive history |
| Hearing threshold | Speech reception threshold |
| Cognitive function | Pairs matching; reaction time; prospective memory |
* assessed in 170,000 participants;
† assessed in 50,000 participants;
‡measured in one heel for 170,000 participants and in both heels for 320,000 participants;
¶ measured in 170,000 participants;
§ measured in 100,000 participants
Current and planned future data available in the UK Biobank resource.
| Data type | Number of participants | Details | Date of data acquisition | Date first available for research |
|---|---|---|---|---|
|
| Whole cohort | Questionnaire, physical measures, samples (see | 2006–2010 | Q2 2012 |
|
| 20,000–25,000 | As above every few years, to allow correction for regression dilution due to measurement error and within person fluctuations in exposure levels [ | 2013– | Q3 2013 |
|
| Whole cohort | Biomarkers with known disease associations (e.g., lipids for vascular disease), diagnostic value (e.g., HbA1c for diabetes), or ability to characterize phenotypes not otherwise well assessed (e.g., renal and liver function tests). | 2014–2015 | 2015 |
|
| Whole cohort | Dense genotyping chip with >800,000 markers including: approximately 250,000 SNPs in a whole-genome array; approximately 200,000 markers covering CNV, loss of function, insertions, deletions, and previously identified risk factor or disease associations; approximately 150,000 exome markers covering a high proportion of non-synonymous coding variants with allele frequency >0.02%. | 2013–2015 | 2015 |
|
| 210,000 | Automatically coded dietary recall questionnaire, providing estimates of nutrient intake. 80,000 respondents completed it ≥ three times. | 2011–2012 | Q2 2013 |
|
| 350,000 to be approached | Participants invited by email to provide additional information via Web questionnaires about exposures (e.g., occupation) and health outcomes (cognitive function, depression) that are not readily identified from health record linkages. | 2014– | 2015 |
|
| 100,000 | Wrist-worn tri-axial accelerometers record information on type, intensity, and duration of physical activity. | 2013–2015 | 2015 |
|
| 100,000 | MRI brain, heart, and abdomen (for lipid distribution); ultrasound of carotid arteries; whole body DXA scan of bones and joints | Pilot phase: 2014–2015 Main phase: 2016–2019 | 2015 |
|
| Whole cohort | |||
| Death registrations | ICD-coded cause specific mortality | 2006– | Q2 2013 | |
| Cancer registrations | ICD-coded cancer diagnoses | 1971– | Q2 2013 | |
| Hospital inpatient episodes | ICD-coded diagnoses, OPCS-coded procedures | 1997– | Q4 2013 | |
| Hospital outpatient episodes | Limited ICD and OPCS coding | 2003– | 2015 | |
| Primary care | Read-coded information including diagnoses, measurements, referrals, prescriptions | Variable | 2015 | |
| Other | UK Biobank will obtain data from national mental health care, residential history, laboratory and disease audit datasets and is considering the value of further linkages (e.g., imaging, cancer screening, dental). | Variable | Not yet determined | |
|
| Whole cohort | Expert-led confirmation and subclassification of outcomes in a range of disease areas, including cancer, diabetes, heart disease, stroke, mental health, musculoskeletal, respiratory, neurodegenerative, and ocular disorders. | 2015 | |
Hb: haemoglobin; SNPs: single nucleotide polymorphisms; CNV: copy number variations; MRI: magnetic resonance imaging; DXA: dual-energy X-ray absorptiometry; ICD: International Classification of Diseases; OPCS: Office of Population Censuses and Surveys Classification of Interventions and Procedures
‡ Future dates are estimated. Data available may be all or part of the relevant dataset.
* available from an earlier date from health record systems in Scotland