Optimising neuroimaging biomarkers of brain ageing to identify genetic and environmental risk factors for poor brain health
Principal Investigator: Dr James Cole
Approved Research ID: 40933
Approval date: September 10th 2018
As people age, cognitive problems including poorer concentration and memory, shortened attention span and slower reactions are common. The risk of dementia-related diseases, such as Alzheimer's, also increases with age. This happens because ageing affects both the structure and the function of the brain, so-called 'brain ageing'. However, brain ageing does not affect everyone the same way. Some people experience age-related cognitive problems much earlier than others, and the age dementia develops varies widely. Using magnetic resonance imaging (MRI) brain scans, we have developed a method of predicting whether someone's brain appears younger or older than would be expected at their age. Our previous work showed how this brain-predicted age difference (brain-PAD) relates to cognitive performance, physical health and can help predict how long older adults will live. Different health conditions, such as HIV, brain injuries and epilepsy also affect brain-PAD scores. Our aim here is to generate brain-PAD scores for the UK Biobank participants. Firstly, we will improve how well we can predict brain-age, using new statistical techniques to optimise neuroimaging data analysis. Then, we will see how brain-PAD relates to measures of current cognitive performance and physical health in UK Biobank participants. Next, we will test whether genetic differences are related to brain-PAD before finally, we will examine whether environmental factors, such as dietary habits, where people live, how much exercise they do, also impacts brain-PAD. Once we have identified factors that may affect brain health during ageing, we will analyse different datasets, available at King's College London, to see if these results can be repeated. This study will last for 30 months and will analyse all available UK Biobank neuroimaging data. The study will result in several outcomes that may impact public health. Firstly, we will produce an improved statistical method for estimating brain-PAD and share these data to all other UK Biobank researchers. Secondly, we will provide further evidence that brain-PAD is related to measures of brain and physical health. Thirdly, we hope to identify new genetic and environmental factors that may predispose people to suffer from cognitive changes and neurodegenerative diseases as they age. This will help improve our understanding of what causes poorer brain ageing and could provide new ideas for treatments. Finally, our study will show how MRI can be used to screen for individual people who may be at greater risk of poorer brain health as they age.