< Back to previous page

Project

Can we predict rate of cognitive decline in Alzheimer's disease based on genetic modifiers of differential gene expression in the default mode network?

Due to increased life expectancy, the number of people suffering from dementia is growing. Alzheimer's disease (AD), the most common form of dementia, is still incurable. Clinical trials with amyloid B (AB plaques as clearing targets have failed to show major improvements, resulting in pharmaceutical companies, such as Pfizer, to reduce investments into AD treatments. This emphasizes that studies on other mechanisms related to underlying pathophysiology of the disease are urgently needed. Moreover, although AB is an early biomarker for AD, it does not have any prognostic value to predict age at onset (AAO) or rate of cognitive decline. We hope to provide proof that altered functional connectivity in the default mode network (DMN), caused by synaptic degeneration, is linked with cognitive decline. This hypothesis will be challenged by studying DMN brain regions with a combined genomics and transcriptomics approach in order to find clear underlying genetic modifiers of altered gene expression. These modifiers will allow construction of a polygenic risk score (PRS) that can predict AAO and rate of decline. Outcomes of this PhD project will provide an insight into the processes contributing to network disruption, possibly delivering new druggable targets as well as prognostic markers for early diagnosis of AD.
Date:1 Oct 2018 →  30 Sep 2020
Keywords:ALZHEIMER'S DISEASE
Disciplines:Genetics, Systems biology, Molecular and cell biology