Introduction of UK Biobank data application_Chinese Journal of Evidence-Based Medicine

Authors：

HUANG Xiaxuan ^1,2 , HUANG Tao ² , YANG Rui ² , YUAN Shiqi ^1,2 , HE Ningxia ² ,  XU Anding ¹ , LV Jun ^2,3

1. Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, P. R. China;
2. Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510630, P. R. China;
3. Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou 510632, P. R. China;

Corresponding author：

XU Anding, Email: tlil@jnu.edu.cn

Keywords：

UK Biobank; Database; Imaging; Genomics; Artificial intelligence

DOI：

10.7507/1672-2531.202204162

Video：

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UK Biobank is an extensive biomedical database and research resource. It contains in-depth genetic and health information from 500 000 UK subjects, comprising a wealth of basic structured data, high-throughput genomic and genetic data, and multimodal imaging data. However, difficulties in accessing the large amount of data mean that the database has not been widely used in China. We first introduced the health-related structural data, genetic data, and imaging data in the UK Biobank. We then described methods for using different types of data downloaded from UK Biobank, and explored recent research based on these data. We also discussed classic research focusing on applying artificial intelligence technology to UK Biobank data. Finally, we predicted future research trends in the utilization of UK Biobank data in areas such as anatomy, physiology, genetic variation, and phenotypic characteristics.

Citation： HUANG Xiaxuan, HUANG Tao, YANG Rui, YUAN Shiqi, HE Ningxia, XU Anding, LV Jun. Introduction of UK Biobank data application. Chinese Journal of Evidence-Based Medicine, 2022, 22(9): 1099-1107. doi: 10.7507/1672-2531.202204162 Copy

1.	UK Biobank (2006). Protocol for a large-scale prospective epidemiological resource. Available at: www.ukbiobank.ac.uk/resources/.
2.	Ollier W, Sprosen T, Peakman T. UK Biobank: from concept to reality. Pharmacogenomics, 2005, 6(6): 639-646.
3.	Littlejohns TJ, Holliday J, Gibson LM, et al. The UK Biobank imaging enhancement of 100, 000 participants: rationale, data collection, management and future directions. Nat Commun, 2020, 11(1): 2624.
4.	Miller KL, Alfaro-Almagro F, Bangerter NK, et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci, 2016, 19(11): 1523-1536.
5.	穆琳, 裴昀, 冬冬. 深度学习在骨关节医学影像中的研究及应用进展. 临床放射学杂志, 2020, 39(8): 1666-1669.
6.	万艳丽, 雷行云, 王岩, 等. 基于层次化深度学习的海量医学影像组织与检索研究. 医学信息学杂志, 2015, 36(5): 46-51.
7.	McIntosh AM, Stewart R, John A, et al. Data science for mental health: a UK perspective on a global challenge. Lancet Psychiatry, 2016, 3(10): 993-998.
8.	Wilkinson T, Schnier C, Bush K, et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur J Epidemiol, 2019, 34(6): 557-565.
9.	The UK Biobank. Genotyping and quality control of UK Biobank, a Large-Scale, extensively phenotyped prospective resource. Available at: https://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/genotyping_qc.pdf.
10.	The UK Biobank. UK Biobank Axiom Array Content Summary. Available at: https://tools.thermofisher.cn/content/sfs/brochures/uk_axiom_biobank_contentsummary_brochure.pdf.
11.	Bycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature, 2018, 562(7726): 203-209.
12.	Tyrrell J, Jones SE, Beaumont R, et al. Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank. BMJ, 2016, 352: i582.
13.	Van Hout CV, Tachmazidou I, Backman JD, et al. Exome sequencing and characterization of 49, 960 individuals in the UK Biobank. Nature, 2020, 586(7831): 749-756.
14.	Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med, 2015, 12(3): e1001779.
15.	Hanscombe KB, Coleman JRI, Traylor M, et al. ukbtools: an R package to manage and query UK Biobank data. PLoS One, 2019, 14(5): e0214311.
16.	Smith SM, Elliott LT, Alfaro-Almagro F, et al. Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations. Elife, 2020, 9: e52677.
17.	Cox SR, Lyall DM, Ritchie SJ, et al. Associations between vascular risk factors and brain MRI indices in UK Biobank. Eur Heart J, 2019, 40(28): 2290-2300.
18.	林岚, 熊敏, 吴水才. 英国生物银行在神经影像领域应用的研究综述. 生物医学工程学杂志, 2021, 38(3): 594-601.
19.	Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol, 2017, 186(9): 1026-1034.
20.	Bycroft C, Freeman C, Petkova D, et al. Genome-wide genetic data on ~500, 000 UK Biobank participants. 2017. DOI: 10.1101/166298.
21.	Daghlas I, Dashti HS, Lane J, et al. Sleep duration and myocardial infarction. J Am Coll Cardiol, 2019, 74(10): 1304-1314.
22.	Suinesiaputra A, Sanghvi MM, Aung N, et al. Fully-automated left ventricular mass and volume MRI analysis in the UK Biobank population cohort: evaluation of initial results. Int J Cardiovasc Imaging, 2018, 34(2): 281-291.
23.	Willetts M, Hollowell S, Aslett L, et al. Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96, 220 UK Biobank participants. Sci Rep, 2018, 8(1): 7961.
24.	Khera AV, Chaffin M, Aragam KG, et al. Genome-wide polygenic score to identify a monogenic risk-equivalent for coronary disease. 2017. DOI: 10.1101/218388.
25.	Buchanan CR, Bastin ME, Ritchie SJ, et al. The effect of network thresholding and weighting on structural brain networks in the UK Biobank. Neuroimage, 2020, 211: 116443.
26.	李莉, 黄韬, 王新宇, 等. 胸腔X射线影像数据库——MIMIC-CXR数据探索. 中国循证心血管医学杂志, 2021, 13(6): 653-656,660.
27.	Elliott LT, Sharp K, Alfaro-Almagro F, et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature, 2018, 562(7726): 210-216.
28.	Hassan L, Peek N, Lovell K, et al. Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank. Mol Psychiatry, 2022, 27(2): 1248-1255.

1. UK Biobank (2006). Protocol for a large-scale prospective epidemiological resource. Available at: www.ukbiobank.ac.uk/resources/.
2. Ollier W, Sprosen T, Peakman T. UK Biobank: from concept to reality. Pharmacogenomics, 2005, 6(6): 639-646.
3. Littlejohns TJ, Holliday J, Gibson LM, et al. The UK Biobank imaging enhancement of 100, 000 participants: rationale, data collection, management and future directions. Nat Commun, 2020, 11(1): 2624.
4. Miller KL, Alfaro-Almagro F, Bangerter NK, et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci, 2016, 19(11): 1523-1536.
5. 穆琳, 裴昀, 冬冬. 深度学习在骨关节医学影像中的研究及应用进展. 临床放射学杂志, 2020, 39(8): 1666-1669.
6. 万艳丽, 雷行云, 王岩, 等. 基于层次化深度学习的海量医学影像组织与检索研究. 医学信息学杂志, 2015, 36(5): 46-51.
7. McIntosh AM, Stewart R, John A, et al. Data science for mental health: a UK perspective on a global challenge. Lancet Psychiatry, 2016, 3(10): 993-998.
8. Wilkinson T, Schnier C, Bush K, et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur J Epidemiol, 2019, 34(6): 557-565.
9. The UK Biobank. Genotyping and quality control of UK Biobank, a Large-Scale, extensively phenotyped prospective resource. Available at: https://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/genotyping_qc.pdf.
10. The UK Biobank. UK Biobank Axiom Array Content Summary. Available at: https://tools.thermofisher.cn/content/sfs/brochures/uk_axiom_biobank_contentsummary_brochure.pdf.
11. Bycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature, 2018, 562(7726): 203-209.
12. Tyrrell J, Jones SE, Beaumont R, et al. Height, body mass index, and socioeconomic status: mendelian randomisation study in UK Biobank. BMJ, 2016, 352: i582.
13. Van Hout CV, Tachmazidou I, Backman JD, et al. Exome sequencing and characterization of 49, 960 individuals in the UK Biobank. Nature, 2020, 586(7831): 749-756.
14. Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med, 2015, 12(3): e1001779.
15. Hanscombe KB, Coleman JRI, Traylor M, et al. ukbtools: an R package to manage and query UK Biobank data. PLoS One, 2019, 14(5): e0214311.
16. Smith SM, Elliott LT, Alfaro-Almagro F, et al. Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations. Elife, 2020, 9: e52677.
17. Cox SR, Lyall DM, Ritchie SJ, et al. Associations between vascular risk factors and brain MRI indices in UK Biobank. Eur Heart J, 2019, 40(28): 2290-2300.
18. 林岚, 熊敏, 吴水才. 英国生物银行在神经影像领域应用的研究综述. 生物医学工程学杂志, 2021, 38(3): 594-601.
19. Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol, 2017, 186(9): 1026-1034.
20. Bycroft C, Freeman C, Petkova D, et al. Genome-wide genetic data on ~500, 000 UK Biobank participants. 2017. DOI: 10.1101/166298.
21. Daghlas I, Dashti HS, Lane J, et al. Sleep duration and myocardial infarction. J Am Coll Cardiol, 2019, 74(10): 1304-1314.
22. Suinesiaputra A, Sanghvi MM, Aung N, et al. Fully-automated left ventricular mass and volume MRI analysis in the UK Biobank population cohort: evaluation of initial results. Int J Cardiovasc Imaging, 2018, 34(2): 281-291.
23. Willetts M, Hollowell S, Aslett L, et al. Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96, 220 UK Biobank participants. Sci Rep, 2018, 8(1): 7961.
24. Khera AV, Chaffin M, Aragam KG, et al. Genome-wide polygenic score to identify a monogenic risk-equivalent for coronary disease. 2017. DOI: 10.1101/218388.
25. Buchanan CR, Bastin ME, Ritchie SJ, et al. The effect of network thresholding and weighting on structural brain networks in the UK Biobank. Neuroimage, 2020, 211: 116443.
26. 李莉, 黄韬, 王新宇, 等. 胸腔X射线影像数据库——MIMIC-CXR数据探索. 中国循证心血管医学杂志, 2021, 13(6): 653-656,660.
27. Elliott LT, Sharp K, Alfaro-Almagro F, et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature, 2018, 562(7726): 210-216.
28. Hassan L, Peek N, Lovell K, et al. Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank. Mol Psychiatry, 2022, 27(2): 1248-1255.

Chinese Journal of Evidence-Based Medicine

Introduction of UK Biobank data application

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