2a.To examine how CeVD, tau, and amyloid impact longitudinal brain structural and functional integrity and cognitive decline in elderly at-risk for cognitive decline or dementia.
We hypothesize that CeVD and AD have distinct influence on brain, retina and blood markers of neurodegeneration and cerebrovascular burden, reflecting complex underlying disease interactions that will be revealed in a longitudinal study. Further, we hypothesize that these multimodal measures at baseline coupled with polygenic scores could identify high risk individuals (diagnostic) and predict future disease progression (prognostic) or response to intervention in Theme 1. To test these hypotheses, we will elucidate the cognitive trajectories of elderly at risk for cognitive decline or dementia with or without CeVD or AD changes (i.e. tau or amyloid) so that the interactions of these two disease processes (CeVD and AD) on brain integrity and cognition can be better defined. One aim of this theme is to characterize differential trajectories of multimodal neuroimaging measures of neurodegeneration and vascular burden longitudinally in 1200 older individuals with normal cognition or mild cognitive impairment (600 in the intervention arm and 600 in the control arm) over 2 years. A subset of 400 individuals will be examined at year 4. There will be close interactions with Theme 1 and Theme 3.
2b.To carry out exploratory studies
This is to evaluate whether correlations between polygenic risk scores (PRS) and disease progression (either clinical or from multimodal measures) seen in Western populations are informative in the local Asian population based on the newly recruited 1200 elderly atrisk for cognitive impairment. Moreover, discovery of Asian vascular PRS will be performed based on the existing blood samples of 1200 patients from the Memory Aging & Cognition Centre (MACC) at National University of Singapore (NUS) (N=700) and National Neuroscience Institute (N=500). The third and fourth aims of this theme (2c & 2d) are to develop novel blood and brain/retinal imaging biomarkers of neuroinflammation, vascular disease and neurodegeneration, to determine whether they are informative with respect to disease phenotype (especially early stage) or progression. Lastly, we will evaluate the prognostic values of the brain, PRS, retinal and blood markers (individual and combined) using state-of-art machine learning approaches (2e) for cognitive decline and intervention outcomes (Theme 1).
