- Dr Michelle Lupton (QIMR)
- Prof Nick Martin (QIMR)
Dementia is the greatest cause of disability in Australians over the age of 65 years. In the absence of a significant medical breakthrough, more than $6.4 million Australians will be diagnosed with dementia in the next 40 years. The most common form of dementia is Alzheimer’s disease (AD), accounting for 60-80% of cases. The pathogenic process of AD begins decades prior to the clinical onset, so it is likely that treatments need to begin early in the disease process to be of benefit. Therefore there is an urgent requirement for the investigation of the AD process at the earliest stage, before clinical symptoms. Aside from the use of extensive longitudinal studies, prodromal changes are difficult to investigate. This project will use known genetic risk factors to identify those at a high risk of developing AD, where a high proportion of individuals will be in a prodromal stage of AD. Data will be available from the PISA (Prospective Imaging Study of Aging) Study (Lupton et al. 2020). There will be opportunity to investigate genetic risk factors for AD in healthy individuals and test for associations with extensive phenotypic data including co-morbid conditions and traits, neuroimaging, cognition, and blood based methylation markers. Significant associations will identify disease markers that represent early prodromal brain changes before the clinical onset of AD.
Lupton et al. A prospective cohort study of prodromal Alzheimer′s disease: Prospective Imaging Study of Ageing: Genes, Brain and Behaviour (PISA) medRxiv 2020.05.04.20091140; doi: https://doi.org/10.1101/2020.05.04.20091140
Approaches/skills and techniques
You will work within the Genetic Epidemiology group at QIMR Berghofer, and collaborate with other groups who work within the PISA study in the different data streams. The project will involve genetic association analysis and the use of Polygenic Risk Scores (PRS) techniques. There will also be the opportunity to work with different streams including; neuropsychology, neuroimaging, medical records, and DNA methylation array data. Students will develop skills in working with complex datasets, statistics and bioinformatics.
This work will provide: 1) important insights into mechanisms of AD development throughout the life span; 2) the opportunity to investigate prodromal markers, and allow selection of individuals for early treatment strategies.
Required skills and experience
Our ideal candidate will have an interest in working in a dry lab environment. Experience in statistical analysis is required and prior experience in working in genetic epidemiology, psychology or neuroimaging would be optimal.