Linking genetics, multi-omics and the life-course to disentangle the causal pathways involved in Alzheimer’s Disease

Worldwide, over 50 million people are estimated to be affected by dementia, making it an increasing threat to global health. Developing effective strategies that prevent, delay, or halt its development has proven challenging because dementia is complex and has a long preclinical phase. New disease-modifying drugs show clinical benefit in the early stages of Alzheimer’s disease (AD), the most common form of dementia; however, they have modest efficacy and potential side effects.

We therefore need to identify easily accessible and scalable markers that will help us to better identify individuals ‘at risk’ of developing dementia as early as possible, to enable their recruitment into suitable clinical trials and prompt treatment when available. We also need to understand more about the causes of dementia, to design effective therapeutic and preventive strategies.

During this talk I will showcase examples of how we have used deeply-phenotyped datasets with multi-omic data such as metabolomics and proteomics, along with clinical and lifestyle information, and applied systems biology and genetic epidemiology approaches, to improve early detection and to unravel causal pathways in dementia.

I will talk about some past and current projects, as well as our future research direction, which will hopefully instigate future collaborations.

Registration link:

https://hku.zoom.us/meeting/register/tJAlcOChqjIsG9dpYKBGvCCwtViSM4ESl11s