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Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Miller, Karla L.; Alfaro-Almagro, Fidel; Bangerter, Neal K.; Thomas, David L.; Yacoub, Essa; Xu, Junqian; Bartsch, Andreas J.; Jbabdi, Saad; Sotiropoulos, Stamatios N.; Andersson, Jesper L.R.; Griffanti, Ludovica; Douaud, Gwena�lle; Okell, Thomas W.; Weale, Peter; Dragonu, Iulius; Garratt, Steve; Hudson, Sarah; Collins, Rory; Jenkinson, Mark; Matthews, Paul M.; Smith, Stephen M.

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Authors

Karla L. Miller

Fidel Alfaro-Almagro

Neal K. Bangerter

David L. Thomas

Essa Yacoub

Junqian Xu

Andreas J. Bartsch

Saad Jbabdi

Jesper L.R. Andersson

Ludovica Griffanti

Gwena�lle Douaud

Thomas W. Okell

Peter Weale

Iulius Dragonu

Steve Garratt

Sarah Hudson

Rory Collins

Mark Jenkinson

Paul M. Matthews

Stephen M. Smith



Abstract

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.

Citation

Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., …Smith, S. M. (2016). Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nature Neuroscience, 19(11), https://doi.org/10.1038/nn.4393

Journal Article Type Article
Acceptance Date Aug 25, 2016
Publication Date Sep 19, 2016
Deposit Date Apr 5, 2018
Publicly Available Date Apr 5, 2018
Journal Nature Neuroscience
Print ISSN 1097-6256
Electronic ISSN 1546-1726
Publisher Nature Publishing Group
Peer Reviewed Peer Reviewed
Volume 19
Issue 11
DOI https://doi.org/10.1038/nn.4393
Keywords Cognitive ageing; Neurological disorders; Predictive markers
Public URL https://nottingham-repository.worktribe.com/output/817017
Publisher URL https://www.nature.com/articles/nn.4393
Contract Date Apr 5, 2018

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