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.

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