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Abstract
Medical imaging provides numerous insights into the subclinical changes that precede serious diseases such as heart disease and dementia. However, most imaging research either describes a single organ system or draws on clinical cohorts with small sample sizes. In this study, we use state-of-the-art multi-organ magnetic resonance imaging phenotypes to investigate cross-sectional relationships across the heart-brain-liver axis in 30,444 UK Biobank participants. Despite controlling for an extensive range of demographic and clinical covariates, we find significant associations between imaging-derived phenotypes of the heart (left ventricular structure, function and aortic distensibility), brain (brain volumes, white matter hyperintensities and white matter microstructure), and liver (liver fat, liver iron and fibroinflammation). Simultaneous three-organ modelling identifies differentially important pathways across the heart-brain-liver axis with evidence of both direct and indirect associations. This study describes a potentially cumulative burden of multiple-organ dysfunction and provides essential insight into multi-organ disease prevention.
While heart disease, dementia and liver disease often co-occur, multi-organ imaging is needed for deeper elucidation of these cross-organ links. Here, the authors use image-derived phenotypes to describe underlying associations between heart, brain and liver health in a large population cohort.
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1 Oxford University Hospitals NHS Foundation Trust, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford, UK (GRID:grid.410556.3) (ISNI:0000 0001 0440 1440)
2 Queen Mary University of London, Charterhouse Square, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, UK (GRID:grid.4868.2) (ISNI:0000 0001 2171 1133); Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London, UK (GRID:grid.416353.6) (ISNI:0000 0000 9244 0345)
3 University of Oxford, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); University of Oxford, Department of Experimental Psychology, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
4 Perspectum Ltd, Gemini One, Oxford, UK (GRID:grid.410556.3)
5 University of Oxford, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); University of Oxford, Department of Experimental Psychology, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); University of Oxford, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
6 University of Oxford, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); University of Oxford, Nuffield Department of Population Health, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
7 Queen Mary University of London, Charterhouse Square, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, UK (GRID:grid.4868.2) (ISNI:0000 0001 2171 1133); Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London, UK (GRID:grid.416353.6) (ISNI:0000 0000 9244 0345); Health Data Research UK, London, UK (GRID:grid.507332.0) (ISNI:0000 0004 9548 940X); The Alan Turing Institute, London, UK (GRID:grid.499548.d) (ISNI:0000 0004 5903 3632)