Accelerated MRI-predicted brain ageing and its associations with cardiometabolic and brain disorders
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Brain structure in later life reflects both influences of intrinsic aging and those of lifestyle, environment and disease. We developed a deep neural network model trained on brain MRI scans of healthy people to predict “healthy” brain age. Brain regions most informative for the prediction included the cerebellum, hippocampus, amygdala and insular cortex. We then applied this model to data from an independent group of people not stratified for health. A phenome-wide association analysis of over 1,410 traits in the UK Biobank with differences between the predicted and chronological ages for the second group identified significant associations with over 40 traits including diseases (e.g., type I and type II diabetes), disease risk factors (e.g., increased diastolic blood pressure and body mass index), and poorer cognitive function. These observations highlight relationships between brain and systemic health and have implications for understanding contributions of the latter to late life dementia risk.
Date Issued
2020-11-17
Date Acceptance
2020-10-19
Citation
Scientific Reports, 2020, 10
ISSN
2045-2322
Publisher
Nature Publishing Group
Journal / Book Title
Scientific Reports
Volume
10
Copyright Statement
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Sponsor
Health Data Research Uk
Medical Research Council (MRC)
UK DRI Ltd
UK DRI Ltd
UK DRI Ltd
Medical Research Council (MRC)
Health Data Research Uk
Imperial College Healthcare NHS Trust- BRC Funding
Grant Number
Health Data Research UK
HQR00720
N/A
N/A
4050641385
4050641385
2349756
RDF03
Publication Status
Published
Article Number
ARTN 19940