Alzheimer’s disease (AD) results from the complex interplay between genetic and epigenetic factors, environmental exposure, lifestyle and aging. AD is characterized by a progressive pattern of cognitive and functional impairment.. This project is aimed at advancing our understanding of the genetic basis of normal cognitive ability in the population as well as the genetic and environmental factors that lead to Alzheimer’s disease and other dementias.
The student with apply state-of-the-art genome-wide and phenome-wide analysis methods to data from electronic health records, genetic profiles, lifestyle surveys and cognitive tests in large datasets such as the UK Biobank, the Genetic Epidemiology Research on Aging (GERA) cohort, and studies of the Queensland Twin Registry. The overarching goal is to understand the relationship between genetic and environmental risk factors that predispose some individuals to develop AD, and to uncover the aetiology of co-morbid conditions and potential biomarkers for outcome prediction.
An example of a potential project might be to correlate cognitive test results with polygenic risk for AD or Parkinson’s disease. Another example could involve looking at neuroimaging traits in a stratified manner according to AD relative genetic risk. Given that the project involves applying a wide variety of statistical and computational methods, this project is suitable for students who have strong quantitative foundations and an interest in using statistics and programming to answer scientific questions in biomedicine. The student will also be encouraged to pursue his/her own interests