UK Biobank: Current status and what it means for epidemiology

Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies

Prospective Studies Collaboration (2009) · The Lancet · doi:10.1016/s0140-6736(09)60318-4 · Cited by 4,807 · see citing works

The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine

Elliott, P., Peakman, T. C., & Biobank, O. B. O. U. (2008) · International Journal of Epidemiology · doi:10.1093/ije/dym276 · Cited by 996 · see citing works

The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition

Ríboli, E. (1997) · International Journal of Epidemiology · doi:10.1093/ije/26.suppl_1.s6 · Cited by 944 · see citing works

Underestimation of Risk Associations Due to Regression Dilution in Long-term Follow-up of Prospective Studies

Clarke, R., Shipley, M. J., Lewington, S., Youngman, L. D., Collins, R., Marmot, M. G., & Peto, R. (1999) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a010013 · Cited by 879 · see citing works

Development and evaluation of the Oxford WebQ, a low-cost, web-based method for assessment of previous 24 h dietary intakes in large-scale prospective studies

Liu, B. C., Young, H., Crowe, F. L., Benson, V. S., Spencer, E. A., Key, T. J., Appleby, P. N., & Beral, V. (2011) · Public Health Nutrition · doi:10.1017/s1368980011000942 · Cited by 572 · see citing works

Cohort studies: marching towards outcomes

Grimes, D. A., & Schulz, K. F. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07500-1 · Cited by 491 · see citing works

The EPIC Project: Rationale and study design

Ríboli, E., & Kaaks, R. (1997) · International Journal of Epidemiology · Cited by 475 · see citing works

UK Biobank: bank on it

Palmer, L. J. (2007) · The Lancet · doi:10.1016/s0140-6736(07)60924-6 · Cited by 377 · see citing works

Genes, environment and the value of prospective cohort studies

Manolio, T. A., Wilson, J., & Collins, F. S. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1919 · Cited by 317 · see citing works

Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology

Burton, P. R., Hansell, A., Fortier, I., Manolio, T. A., Khoury, M. J., Little, J., & Elliott, P. (2008) · International Journal of Epidemiology · doi:10.1093/ije/dyn147 · Cited by 258 · see citing works

Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies

Fortier, I., Burton, P. R., Robson, P. J., Ferretti, V., Little, J., L’Heureux, F., Deschênes, M., Knoppers, B. M., Doiron, D., Keers, J. C., et al. (2010) · International Journal of Epidemiology · doi:10.1093/ije/dyq139 · Cited by 176 · see citing works

The Million Women Study: design and characteristics of the study population

The Million Women Study Collaborative Group (1999) · Breast Cancer Research · doi:10.1186/bcr16 · Cited by 122 · see citing works

The Framingham Heart Study: review of epidemiological design and data, limitations and prospects.

Mw, H. (1984) · PubMed · Cited by 24 · see citing works

Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population

Fry, A., Littlejohns, T. J., Sudlow, C., Doherty, N., Adamska, L., Sprosen, T., Collins, R., & Allen, N. E. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx246 · Cited by 3,979 · see citing works

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020 · see citing works

Million Veteran Program: A mega-biobank to study genetic influences on health and disease

Gaziano, J. M., Concato, J., Brophy, M., Fiore, L., Pyarajan, S., Breeling, J., Whitbourne, S., Deen, J., Shannon, C., Humphries, D., et al. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.09.016 · Cited by 1,055 · see citing works

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Ritchie, S. J., Cox, S. R., Shen, X., Lombardo, M. V., Reus, L. M., Alloza, C., Harris, M. A., Alderson, H. L., Hunter, S., Neilson, E., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy109 · Cited by 855 · see citing works

Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

Batty, G. D., Gale, C. R., Kivimäki, M., Deary, I. J., & Bell, S. (2020) · BMJ · doi:10.1136/bmj.m131 · Cited by 635 · see citing works

Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety

Huckvale, K., Venkatesh, S., & Christensen, H. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0166-1 · Cited by 433 · see citing works

Genome-wide association study meta-analysis of the alcohol use disorders identification test (AUDIT) in two population-based cohorts

Sanchez-Roige, S., Palmer, A. A., Fontanillas, P., Elson, S. L., the 23andMe Research Team, T. S. U. D. W. G. O. T. P. G. C., Adams, M. J., Howard, D. M., Edenberg, H. J., Davies, G., Crist, R. C., et al. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.18040369 · Cited by 430 · see citing works

UK Biobank: Opportunities for cardiovascular research

Littlejohns, T. J., Sudlow, C., Allen, N. E., & Collins, R. (2019) · European Heart Journal · doi:10.1093/eurheartj/ehx254 · Cited by 270 · see citing works

Associations between chronotype, morbidity and mortality in the UK Biobank cohort

Knutson, K. L., & von Schantz, M. (2018) · Chronobiology International · doi:10.1080/07420528.2018.1454458 · Cited by 275 · see citing works

Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease

Walmsley, R., Chan, S., Smith-Byrne, K., Ramakrishnan, R., Woodward, M., Rahimi, K., Dwyer, T., Bennett, D., & Doherty, A. (2022) · British Journal of Sports Medicine · doi:10.1136/bjsports-2021-104050 · Cited by 238 · see citing works

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis

Xu, X., Li, J., Zhu, Z., Zhao, L., Wang, H., Song, C., Chen, Y., Zhao, Q., Yang, J., & Pei, Y. (2024) · Bioengineering · doi:10.3390/bioengineering11030219 · Cited by 242 · see citing works

Association of Body Mass Index With Cardiometabolic Disease in the UK Biobank: A Mendelian Randomization Study

Lyall, D. M., Celis-Morales, C., Ward, J., Iliodromiti, S., Anderson, J. J., Gill, J. M. R., Smith, D. J., Ntuk, U. E., Mackay, D. F., Holmes, M. V., et al. (2017) · JAMA Cardiology · doi:10.1001/jamacardio.2016.5804 · Cited by 235 · see citing works

Ethnic-specific obesity cutoffs for diabetes risk: cross-sectional study of 490,288 UK biobank participants

Ntuk, U. E., Gill, J. M. R., Mackay, D. F., Sattar, N., & Pell, J. P. (2014) · Diabetes Care · doi:10.2337/dc13-2966 · Cited by 220 · see citing works

Big data in digital healthcare: lessons learnt and recommendations for general practice

Agrawal, R., & Prabakaran, S. (2020) · Heredity · doi:10.1038/s41437-020-0303-2 · Cited by 218 · see citing works

Vigorous physical activity, incident heart disease, and cancer: how little is enough?

Ahmadi, M. N., Clare, P. J., Katzmarzyk, P. T., del Pozo Cruz, B., Lee, I. M., & Stamatakis, E. (2022) · European Heart Journal · doi:10.1093/eurheartj/ehac572 · Cited by 175 · see citing works

Imprint of assortative mating on the human genome

Yengo, L., Robinson, M. R., Keller, M. C., Kemper, K. E., Yang, Y., Trzaskowski, M., Gratten, J., Turley, P., Cesarini, D., Benjamin, D. J., et al. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0476-3 · Cited by 148 · see citing works

Smoking, screen-based sedentary behavior, and diet associated with habitual sleep duration and chronotype: data from the UK Biobank

Patterson, F., Malone, S. K., Lozano, A., Grandner, M. A., & Hanlon, A. L. (2016) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9797-5 · Cited by 144 · see citing works

Role of brain imaging in disorders of brain–gut interaction: a Rome Working Team Report

Mayer, E. A., Labus, J., Aziz, Q., Tracey, I., Kilpatrick, L., Elsenbruch, S., Schweinhardt, P., Van Oudenhove, L., & Borsook, D. (2019) · Gut · doi:10.1136/gutjnl-2019-318308 · Cited by 138 · see citing works

Central adiposity and the overweight risk paradox in aging: follow-up of 130,473 UK Biobank participants

Bowman, K., Atkins, J. L., Delgado, J., Kos, K., Kuchel, G. A., Ble, A., Ferrucci, L., & Melzer, D. (2017) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.147157 · Cited by 100 · see citing works

The limitations of large-scale volunteer databases to address inequalities and global challenges in health and aging

Brayne, C., & Moffitt, T. E. (2022) · Nature Aging · doi:10.1038/s43587-022-00277-x · Cited by 89 · see citing works

Endogenous hormones and risk of invasive breast cancer in pre- and post-menopausal women: findings from the UK Biobank

Tin Tin, S., Reeves, G. K., & Key, T. J. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01392-z · Cited by 71 · see citing works

Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health

Ruth, K. S., Beaumont, R. N., Tyrrell, J., Jones, S. E., Tuke, M. A., Yaghootkar, H., Wood, A. R., Freathy, R. M., Weedon, M. N., Frayling, T. M., et al. (2016) · Human Reproduction · doi:10.1093/humrep/dev318 · Cited by 70 · see citing works

Heaviness, health and happiness: a cross-sectional study of 163066 UK Biobank participants

Ul-Haq, Z., Mackay, D. F., Martin, D., Smith, D. J., Gill, J. M. R., Nicholl, B. I., Cullen, B., Evans, J., Roberts, B., Deary, I. J., et al. (2014) · Journal of Epidemiology and Community Health · doi:10.1136/jech-2013-203077 · Cited by 30 · see citing works

Reallocating time from device-measured sleep, sedentary behaviour or light physical activity to moderate-to-vigorous physical activity is associated with lower cardiovascular disease risk

Walmsley, R., Chan, S., Smith-Byrne, K., Ramakrishnan, R., Woodward, M., Rahimi, K., Dwyer, T., Bennett, D., & Doherty, A. (2020) · doi:10.1101/2020.11.10.20227769 · Cited by 12 · see citing works

Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,932)

Sanchez-Roige, S., Palmer, A. A., Fontanillas, P., Elson, S. L., The 23andMe Research Team, Substance Use Disorder Working Group of the Psychiatric Genomics Consortium, Adams, M. J., Howard, D. M., Edenberg, H. J., Davies, G., et al. (2018) · doi:10.1101/275917 · Cited by 14 · see citing works

Integrating biomedical and clinical data with BioBank Japan

Tanaka, T., Nagata, Y., & Takemoto, A. (2022) · Nature Cardiovascular Research · doi:10.1038/s44161-022-00105-w · Cited by 3 · see citing works

Russian National Association of Biobanks and Biobanking Specialists — a tool for integrating Russian biobanks and increasing the efficiency of biomedical research Drapkina O. M.

Drapkina, O. M. (2020) · CARDIOVASCULAR THERAPY AND PREVENTION · doi:10.15829/1728-8800-2020-2757 · Cited by 11 · see citing works

Types of Biobanks

Gramatiuk, S., & Huppertz, B. (2022) · Springer eBooks · doi:10.1007/978-3-030-87637-1_3 · Cited by 3 · see citing works

The Significance of Biobanking in the Sustainability of Biomedical Research: A Review

Zohouri, M., & Ghaderi, A. A. (2020) · Iranian Biomedical Journal · doi:10.29252/ibj.24.4.206 · Cited by 18 · see citing works

MGA Biobank - A Multispecialistic Project Biobank in Slovakia

Hirjakova, P. (2023) · Biomedical Journal of Scientific & Technical Research · doi:10.26717/bjstr.2023.51.008052