Approved research

Study circadian clock disruption in Alzheimer's disease (AD) and other dementias of aging

Lay summary

We aim to discover actigraphy signal patterns (or in combination with genetic and demographic factors) that are associated with Alzheimer's disease (AD) occurrence and progression. AD is a prevalent disease in the elderly and the mechanism is very complicated. So far, there is no good treatment for AD and different people seem to have different degeneration pathways. It is often too late to get diagnosed with AD through imaging tests, so we would like to have some alternative methods for early detection and progress tracking. Circadian clock disruption is a risk factor to AD and actigraphy data can reveal the changes. But we have to jointly consider other risk factors like genetics and demographics (age, gender) to make sure the outcome is not biased. We will develop advanced tensor factorization and associated deep learning pipelines for this research. Hopefully, the findings will contribute to the medical knowledge and advance scientific research for AD.