Deckers, K. et al. Coronary heart disease and risk for cognitive impairment or dementia: Systematic review and meta-analysis. PLoS ONE 12, e0184244 (2017).
Article
Google Scholar
Stahl, E. P. et al. Nonalcoholic Fatty Liver Disease and the Heart: JACC State-of-the-Art Review. J. Am. Coll. Cardiol. 73, 948–963 (2019).
Article
Google Scholar
Butterworth, R. F. The liver–brain axis in liver failure: neuroinflammation and encephalopathy. Nat. Rev. Gastroenterol. Hepatol. 10, 522–528 (2013).
Article
CAS
Google Scholar
Anstee, Q. M., Targher, G. & Day, C. P. Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis. Nat. Rev. Gastroenterol. Hepatol. 10, 330–344 (2013).
Article
CAS
Google Scholar
Iadecola, C. & Gottesman, R. F. Neurovascular and Cognitive Dysfunction in Hypertension: Epidemiology, Pathobiology, and Treatment. Circ. Res. 124, 1025–1044 (2019).
Article
CAS
Google Scholar
Lee, L., Pandey, A., Maron, B. & Loscalzo, J. Network medicine in Cardiovascular Research. Cardiovasc. Res. 117, 2186–2202 (2021).
Article
CAS
Google Scholar
Targher, G., Tilg, H. & Byrne, C. D. Non-alcoholic fatty liver disease: a multisystem disease requiring a multidisciplinary and holistic approach. Lancet Gastroenterol. Hepatol. 6, 578–588 (2021).
Article
Google Scholar
Qiu, C. & Fratiglioni, L. A major role for cardiovascular burden in age-related cognitive decline. Nat. Rev. Cardiol. 12, 267–277 (2015).
Article
Google Scholar
Lombardi, R., Fargion, S. & Fracanzani, A. L. Brain involvement in non-alcoholic fatty liver disease (NAFLD): A systematic review. Dig. Liver Dis. 51, 1214–1222 (2019).
Article
Google Scholar
Ismaiel, A. & Dumitraşcu, D. L. Cardiovascular Risk in Fatty Liver Disease: The Liver-Heart Axis—Literature Review. Front. Med. 6, 202 (2019).
Article
Google Scholar
Jokinen, H. et al. Global Burden of Small Vessel Disease-Related Brain Changes on MRI Predicts Cognitive and Functional Decline. Stroke 51, 170–178 (2020).
Article
Google Scholar
Nwabuo, C. C. et al. Left ventricular global function index predicts incident heart failure and cardiovascular disease in young adults: The coronary artery risk development in young adults (CARDIA) study. Eur. Heart J. Cardiovasc. Imaging 20, 533–540 (2019).
Article
Google Scholar
Jayaswal, A. N. A. et al. Prognostic value of multiparametric magnetic resonance imaging, transient elastography and blood-based fibrosis markers in patients with chronic liver disease. Liver Int 40, 3071–3082 (2020).
Article
CAS
Google Scholar
Mojtahed, A. et al. Reference range of liver corrected T1 values in a population at low risk for fatty liver disease—a UK Biobank sub-study, with an appendix of interesting cases. Abdom. Radiol. 44, 72–84 (2019).
Article
CAS
Google Scholar
Beller, E. et al. Hepatic fat is superior to BMI, visceral and pancreatic fat as a potential risk biomarker for neurodegenerative disease. Eur. Radiol. 29, 6662–6670 (2019).
Article
Google Scholar
Weinstein, G. et al. Association of nonalcoholic fatty liver disease with lower brain volume in healthy middle-aged adults in the Framingham Study. JAMA Neurol. 75, 97–104 (2018).
Article
Google Scholar
Gurholt, T. P. et al. Population-based body–brain mapping links brain morphology with anthropometrics and body composition. Transl. Psychiatry 11, 295 (2021).
Article
Google Scholar
VanWagner, L. B. et al. Nonalcoholic fatty liver disease and measures of early brain health in middle-aged adults: The CARDIA study. Obesity 25, 642–651 (2017).
Article
CAS
Google Scholar
Rovira, A. et al. Decreased white matter lesion volume and improved cognitive function after liver transplantation. Hepatology 46, 1485–1490 (2007).
Article
Google Scholar
Jang, H. et al. Non-alcoholic fatty liver disease and cerebral small vessel disease in Korean cognitively normal individuals. Sci. Rep. 9, 1814 (2019).
Article
ADS
Google Scholar
Petta, S. et al. The Presence of White Matter Lesions Is Associated With the Fibrosis Severity of Nonalcoholic Fatty Liver Disease. Med. (Baltim.) 95, e3446 (2016).
Article
CAS
Google Scholar
Parisinos, C. A. et al. Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis. J. Hepatol. 73, 241–251 (2020).
Article
CAS
Google Scholar
Dekkers, I. A., Jansen, P. R. & Lamb, H. J. Obesity, Brain Volume, and White Matter Microstructure at MRI: A Cross-sectional UK Biobank Study. Radiology 291, 763–771 (2019).
Article
Google Scholar
Poitelon, Y., Kopec, A. M. & Belin, S. Myelin Fat Facts: An Overview of Lipids and Fatty Acid Metabolism. Cells 9, 812 (2020).
Article
CAS
Google Scholar
Pase, M. P. et al. Association of Aortic Stiffness with Cognition and Brain Aging in Young and Middle-Aged Adults: The Framingham Third Generation Cohort Study. Hypertension 67, 513–519 (2016).
Article
CAS
Google Scholar
Pase, M. P. et al. Vascular risk at younger ages most strongly associates with current and future brain volume. Neurology 91, e1479 (2018).
Article
Google Scholar
Singer, J., Trollor, J. N., Baune, B. T., Sachdev, P. S. & Smith, E. Arterial stiffness, the brain and cognition: A systematic review. Ageing Research Reviews 15, 16–27 (2014).
G, D. et al. Heart and Brain: Complex Relationships for Left Ventricular Dysfunction. Curr. Cardiol. Rep. 22, 72 (2020).
Article
Google Scholar
van Hout, M. J. P. et al. Associations between left ventricular function, vascular function and measures of cerebral small vessel disease: a cross-sectional magnetic resonance imaging study of the UK Biobank. Eur. Radiol. 31, 5068–5076 (2021).
Article
Google Scholar
Moore, E. E. et al. Increased Left Ventricular Mass Index Is Associated With Compromised White Matter Microstructure Among Older Adults. J. Am. Heart Assoc. 7, e009041 (2018).
Article
CAS
Google Scholar
Salerno, J. A. et al. Brain atrophy in hypertension: A volumetric magnetic resonance imaging study. Hypertension 20, 340–348 (1992).
Article
CAS
Google Scholar
Dickie, D. A. et al. Vascular risk factors and progression of white matter hyperintensities in the Lothian Birth Cohort 1936. Neurobiol. Aging 42, 116–123 (2016).
Article
Google Scholar
Suzuki, H. et al. Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension. PLoS ONE 12, e0187600 (2017).
Article
Google Scholar
Wassenaar, T. M., Yaffe, K., van der Werf, Y. D. & Sexton, C. E. Associations between modifiable risk factors and white matter of the aging brain: insights from diffusion tensor imaging studies. Neurobiol. Aging 80, 56–70 (2019).
Article
Google Scholar
Veldsman, M. et al. Cerebrovascular risk factors impact frontoparietal network integrity and executive function in healthy ageing. Nat. Commun. 11, 4340 (2020).
Article
ADS
CAS
Google Scholar
Tsao, C. W. et al. Left ventricular structure and risk of cardiovascular events: A framingham heart study cardiac magnetic resonance study. J. Am. Heart Assoc. 4, e002188 (2015).
Article
Google Scholar
Borges-Canha, M. et al. Association between nonalcoholic fatty liver disease and cardiac function and structure—a meta-analysis. Endocrine 66, 467–476 (2019).
Article
CAS
Google Scholar
Raisi-Estabragh, Z. et al. Left atrial structure and function are associated with cardiovascular outcomes independent of left ventricular measures: a UK Biobank CMR study. Eur. Heart J. – Cardiovasc. Imaging jeac119, https://doi.org/10.1093/EHJCI/JEAB266 (2021).
Littlejohns, T. J. et al. The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions. Nat. Commun. 11, 2624 (2020).
Article
ADS
CAS
Google Scholar
Miller, K. L. et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat. Neurosci. 19, 1523–1536 (2016).
Article
CAS
Google Scholar
Petersen, S. E. et al. UK Biobank’s cardiovascular magnetic resonance protocol. J. Cardiovasc. Magn. Reson. 18, 8 (2016).
Article
Google Scholar
Wilman, H. R. et al. Characterisation of liver fat in the UK Biobank cohort. PLoS ONE 12, e0172921 (2017).
Article
Google Scholar
McKay, A. et al. Measurement of liver iron by magnetic resonance imaging in the UK Biobank population. PLOS ONE 13, e0209340 (2018).
Article
Google Scholar
Bachtiar, V. et al. Repeatability and reproducibility of multiparametric magnetic resonance imaging of the liver. PloS One 14, e0214921 (2019).
Article
CAS
Google Scholar
Harrison, S. A. et al. Prospective evaluation of the prevalence of non-alcoholic fatty liver disease and steatohepatitis in a large middle-aged US cohort. J. Hepatol. 75, 284–291 (2021).
Article
Google Scholar
Smith, S. M., Alfaro-Almagro, F. & Miller, K. L. UK Biobank – Brain Imaging Documentation https://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/brain_mri.pdf (Date accessed: 29 October 2021) (2020).
Alfaro-Almagro, F. et al. Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank. NeuroImage 166, 400–424 (2018).
Article
Google Scholar
van den Heuvel, M. P. & Yeo, B. T. T. A Spotlight on Bridging Microscale and Macroscale Human Brain Architecture. Neuron 93, 1248–1251 (2017).
Article
Google Scholar
Smith, S. M. et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. NeuroImage 17, 479–489 (2002).
Article
Google Scholar
Prins, N. D. & Scheltens, P. White matter hyperintensities, cognitive impairment and dementia: an update. Nat. Rev. Neurol. 11, 157–165 (2015).
Article
Google Scholar
Debette, S., Schilling, S., Duperron, M. G., Larsson, S. C. & Markus, H. S. Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury: A Systematic Review and Meta-analysis. JAMA Neurol. 76, 81–94 (2019).
Article
Google Scholar
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A. & Alexander, D. C. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage 61, 1000–1016 (2012).
Article
Google Scholar
Taoka, T. et al. White matter microstructural changes in tuberous sclerosis: Evaluation by neurite orientation dispersion and density imaging (NODDI) and diffusion tensor images. Sci. Rep. 2020 101 10, 1–9 (2020).
Google Scholar
Venkatesh, A., Stark, S. M., Stark, C. E. L. & Bennett, I. J. Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging. Neurobiol. Aging 96, 12–21 ne to (2020).
Article
Google Scholar
Jones, D. K., Knösche, T. R. & Turner, R. White matter integrity, fiber count, and other fallacies: The do’s and don’ts of diffusion MRI. NeuroImage 73, 239–254 (2013).
Article
Google Scholar
Peterson, R. A. & Cavanaugh, J. E. Ordered quantile normalization: a semiparametric transformation built for the cross-validation era. J. Appl. Stat. 47, 2312–2327 (2020).
Article
MathSciNet
MATH
Google Scholar
Petersen, S. E. et al. Reference ranges for cardiac structure and function using cardiovascular magnetic resonance (CMR) in Caucasians from the UK Biobank population cohort. J. Cardiovasc. Magn. Reson. 19, 1–19 (2017).
Article
Google Scholar
Bai, W. et al. Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. J. Cardiovasc. Magn. Reson. 20, 1–12 (2018).
Article
Google Scholar
Raisi-Estabragh, Z. et al. Associations of cognitive performance with cardiovascular magnetic resonance phenotypes in the UK Biobank. Eur. Heart J. – Cardiovasc. Imaging jeab075 (2021).
Desai, M. Y. et al. LV Global Function Index Provides Incremental Prognostic Value Over LGE and LV GLS in HCM. JACC Cardiovasc. Imaging 13, 2052–2054 (2020).
Article
Google Scholar
Biasiolli, L. et al. Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data. PLOS ONE 14, e0212272 (2019).
Article
CAS
Google Scholar
Redheuil, A. et al. Proximal aortic distensibility is an independent predictor of all-cause mortality and incident CV events: The MESA study. J. Am. Coll. Cardiol. 64, 2619–2629 (2014).
Article
Google Scholar
Fawns-Ritchie, C. & Deary, I. J. Reliability and validity of the UK Biobank cognitive tests. PLOS ONE 15, e0231627 (2020).
Article
CAS
Google Scholar
Lyall, D. M. et al. Cognitive Test Scores in UK Biobank: Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants. PLOS ONE 11, e0154222 (2016).
Article
Google Scholar
Craig, C. L. et al. International Physical Activity Questionnaire: 12-Country Reliability and Validity. Med Sci. Sports Exerc 35, 1381–1395 (2003).
Article
Google Scholar
The IPAQ group. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ) – Short and Long Forms. https://biobank.ndph.ox.ac.uk/ukb/ukb/docs/ipaq_analysis.pdf (Date accessed: 21 October 2021) (2005).
Alfaro-Almagro, F. et al. Confound modelling in UK Biobank brain imaging. NeuroImage 224, 117002 (2021).
Article
Google Scholar
R. Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. in R Version 4.0.3 Vienna, Austria. URL https://www.R-project.org/ (2019).
RStudio Team. RStudio: Integrated Development Environment for R. (RStudio, PBC, Boston, MA, 2020). http://www.rstudio.com/.
Rosseel, Y. Lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).
Article
Google Scholar