Methylation-based biomarkers for Alzheimer’s disease

This project is suitable for Honours, Masters, MPhil, MD or PhD students. For those with experience in coding and statistics, and an interest in dementia, DNA methylation analysis, genetic epidemiology, and bioinformatics.

Background

DNA methylation (DNAm) patterns derived from blood samples correlate strongly with chronological age, thereby referred to as the ‘epigenetic clock’. Epigenetic clocks are also associated with differences in physical and cognitive fitness. Epigenetic changes in Alzheimer’s disease (AD) affected brain regions have been shown to associate with AD pathogenesis, and significant differences in DNAm patterns are identified in the blood between AD cases and controls. Therefore there is great potential for epigenetic patterns to be diagnostic markers for prodromal AD.

Aims

Test whether the ‘epigenetic clock’ associated with ageing also associates with genetic risk of AD and prodromal dementia phenotypes. Data from this project will also contribute to a large international consortia carrying out world leading collaborative analysis on the genetics of DNA Methylation.

Method

The student will carry out data analysis using an existing genome-wide array-based methylation dataset, including working with specialised software in a Linux environment. Building on current work in PISA (the Prospective Study of Aging, Genes, Brain and Behaviour). Association analysis will be carried out with dementia-related phenotypes such as neuroimaging and cognitive data.

Project Potential

This study will identify DNA methylation patterns from the entire genome, in the blood which associate with dementia related phenotypes, and future decline in a population at high risk of AD. These could be used as an accessible AD biomarker, allowing the use of early treatment, and enabling monitoring of disease progression.