Personalized prevention of dementia - integrating lifestyle, biomarkers and genomics.
Approved Research ID: 66214
Approval date: October 26th 2021
Worldwide around 50 million people now live with dementia, a number projected to triple by 2050 due to rapid global demographic changes, making dementia a major health and socioeconomic challenge. The Lancet Commission report now states that 40% of dementia is preventable. In the light of repeated failures of novel drug approaches to treating established dementia, preventive strategies become paramount.
The present proposal aims to bring personalized risk prediction to a higher level by taking advantage of high-quality data from large-scale studies of general populations. Collectively, these high-quality data will be used in genetic and non-genetic versions of risk scores as well as in meaningful subtypes of dementia. We anticipate to greatly improve risk prediction and thus personalized prevention for those with highest baseline risk, likely to benefit the most from an early intensive intervention.
By integrating robust risk prediction, genomics, and understanding of causal factors, this proposal will create an evidence base to guide the implementation of personalized prevention for risk reduction of dementia both at the individual level and for public health in general. The proposal has the potential to generate new insights and tools helping us to reach the 40% reduction in dementia anticipated to be preventable.