Professor IJ Deary
University of Edinburgh
Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III
Neurodegenerative disease in general
Studying the changes in brain structure that accompany older age may be useful for understanding cognitive ageing and reducing the risk of dementia in the elderly. We seek funds to acquire a 3rd wave of brain MRI and a 2nd wave of carotid Doppler ultrasound data from the Lothian Birth Cohort 1936, a large group of relatively healthy subjects in their late seventies. This cohort has a wide range of phenotypic data available from older age (at 70, 73, 76; 79 to be done) including cognitive, genetic, epigenetic, lifestyle, etc. Uniquely, they also have a measure of childhood intelligence from age 11. These subjects have already undergone brain MRI at ages 73 and 76, and vascular imaging at age 73. Repeat brain MRI and ultrasound scanning at age 79 will provide multi-time-point longitudinal imaging data across the eighth decade of life. This will be used to investigate associations between older age brain structure, vascular, genetic and other risk factors, and cognitive ability across the life course.
This 3rd wave of brain MRI will be undertaken on the same GE 1.5T clinical scanner as used in the first two examinations. The imaging protocol will consist of structural, diffusion tensor (DT), magnetization transfer (MT) and quantitative T1-mapping sequences. The structural scans will be analyzed to provide measures of brain atrophy, cortical thickness and white matter hyperintensity volume. The DT, MT and T1 data will be used to segment a range of major white matter tracts and provide measures of the integrity of these structures.
These imaging data will be analyzed using methods such as structural equation and longitudinal latent growth curve modelling to examine associations, both cross-sectionally and longitudinally, with cognitive, genetic, epigenetic, lifestyle, and other phenotypic data to provide insights into the factors driving non-pathological cognitive ageing. The carotid Doppler ultrasound data will be used as outcome and predictor variables.