Accelerated MRI-predicted brain ageing and its associations with cardiometabolic and brain disorders
| Autor: | Ioanna Tzoulaki, Paul Elliott, Abbas Dehghan, Yannis Panagakis, Paul M. Matthews, Sarah Filippi, Arinbjörn Kolbeinsson |
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| Přispěvatelé: | Health Data Research Uk, Medical Research Council (MRC), UK DRI Ltd, Imperial College Healthcare NHS Trust- BRC Funding |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Aging Quantitative Trait Loci lcsh:Medicine Hippocampus Neuroimaging Disease Insular cortex Amygdala Article 03 medical and health sciences 0302 clinical medicine Metabolic Diseases Machine learning medicine Humans Dementia lcsh:Science Brain Diseases Multidisciplinary Cognitive ageing business.industry lcsh:R Brain Cognition Mendelian Randomization Analysis medicine.disease Magnetic Resonance Imaging 030104 developmental biology medicine.anatomical_structure Risk factors Cardiovascular Diseases Ageing lcsh:Q Neural Networks Computer business Body mass index 030217 neurology & neurosurgery Clinical psychology |
| Zdroj: | Scientific Reports, Vol 10, Iss 1, Pp 1-9 (2020) Scientific Reports |
| ISSN: | 2045-2322 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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