AbstractThe aim of the research in this thesis was to discover and validate blood biomarkers of early Alzheimer's Disease (AD). Existing and novel datasets from cohort studies were used for discovery and to attempt validation of previously reported biomarkers. For example, this thesis presents the first study to investigate associations between brain amyloid and blood metabolites. Further, this thesis presents the first study to combine more than one modality of blood biomarker in AD research and the first study to use a Bayesian methodology in this field.
This thesis begins by aiming to validate candidate protein markers of brain amyloid burden in a novel proteomics dataset. Secondly, pathway-based methods are used to investigate the use of gene expression measurements as a potential biomarker of AD diagnosis. In the fourth chapter I generated a novel metabolomics dataset to investigate associations between blood metabolites and brain amyloid burden. A panel is found that predicts dichotomized amyloid burden with reasonable accuracy. The accuracy is improved by the inclusion of a candidate protein in the model.
The fifth chapter of this thesis is focused on the use of a Bayesian methodology to predict measurements of amyloid using a variety of omics data. The Bayesian methodology allows incorporation of historical information by placing informative priors on demographic variables. No improvement is seen over demographics alone. The final chapter of this thesis aims to predict amyloid and tau burden using a polygenic risk score and levels of tau in blood. I have also considered a combined amyloid and tau pathology endpoint. The blood markers considered here do not improve predictive ability over demographics alone.
Much of the work in this thesis highlights the importance of demographic factors in the diagnosis of early AD. The metabolite discovery work shows an improvement in predictive ability over demographics alone and warrants further investigation and replication. The other chapters of this thesis highlight that (in the settings investigated so far) blood measurements add minimal information above demographics alone.
|Date of Award
|Steven Kiddle (Supervisor) & Richard Dobson (Supervisor)