Alzheimer’s disease (AD) results from the complex interplay between genetic and epigenetic factors, environmental exposure, lifestyle and ageing. Recent genome-wide association studies (GWAS) have revealed several genetic loci associated with increased AD susceptibility. As the number of implicated loci grows, characterising their function in selectively vulnerable cell populations has become both a priority and a challenge.
This project seeks to recapitulate some of the in vivo interactions that drive AD by applying a set of parallel ‘omics’ approaches (total RNA-Seq, genome-wide genotyping and genome-wide DNA methylation profiling) to post-mortem pyramidal neurons from the middle temporal gyrus, a brain region that displays early pathology in end-stage AD cases. The ultimate goal is to advance our understanding of the molecular events that drive Alzheimer’s neurodegeneration and to highlight potential targets for precision therapies.
The student will apply statistical and computational methods to identify methylation- and expression-QTLs in Alzheimer’s neurons. Also, Bayesian Network (BN) construction and relative likelihood modeling will be used to dissect the mechanistic (causality, mediation, activation and inhibition) and directional relationships between DNA methylation and gene expression data at gene-level.
This project is suitable for a student who is interested in bioinformatics, functional genomics and epigenetics.