Genetic and environmental determinants of brain function in health and disease
Approved Research ID: 78867
Approval date: April 29th 2022
Brain disorders - such as dementia, Parkinson's Disease, and Multiple Sclerosis - are among the biggest causes of disability and mortality among older adults. Although these disorders have different sets of causes, they are all incurable, long-term diseases with a substantial human and economic impact on the health and social care systems. In particular, age-related disorders like dementia are becoming more common as the population ages.
We do not understand why some people get these diseases and others don't. Although lots is known about the influences of genetic and environmental factors on the risk of developing these diseases, there are no effective treatments available for prevention.
A widely-held view is that a number of these diseases represent an acceleration of normal brain ageing. Understanding brain ageing in healthy people may therefore shed light on why some people develop brain disorders.
We aim to use UK Biobank to further our understanding of healthy brain ageing, extend these findings to brain diseases, and develop these insights into improvements in disease prediction, treatment, and prevention.
Our specific aims are as follows:
To assess all 'environmental' factors within UK Biobank to determine whether they are associated with selected brain diseases. We will then use statistical techniques to work out whether these are merely associations, or whether they might be causally influencing the risk of brain disease. If we find potential causal risk factors for brain diseases, we hope to be able to make a case for trials/public health interventions.
To determine how genetic and environmental factors influences brain structure in health and disease. We will look for associations between specific DNA variants and brain diseases, measures of brain function in health , and we will explore the similarities and differences between these relationships.
To see how effectively genetic information can be used to predict the subsequent development of brain diseases.
To assess whether the effect of some risk factors depends on an individual's genetics. This is important as specific interventions, e.g. better treatment of high blood pressure, may be more effective in individuals with a particular set of DNA variants that enhance the harmful effects of high blood pressure.
To extend our findings across diverse ancestral and ethnic backgrounds.