Unmasking cellular and molecular networks encoding risk and resilience in Alzheimer’s disease

ongoing

AlzheimerAlzheimer’s disease (AD) is a crucial problem in our society, raising the need for new therapeutic targets. Evidence suggests multiple non-neuronal cells are implicated in the systemic deficits of AD, but the complex cellular diversity in the brain hampers the investigation of specific cells and their interactions. Moreover, the course of the disease is highly variable, due to multiple risk factors, including aging and gender, which have overlapping molecular signatures with AD that might be further masking disease mechanisms. I propose to expand the resolution from tissues to cellular environments, and to untangle overlapping molecular signatures of gender and aging, in order to unmask molecular mechanism of AD. Technological advances in genomics and imaging, including the single nucleus RNA-sequencing methods developed by me, as well as my expertise in computational analysis and CRIPSR perturbations, provide a unique opportunity to address this challenge. I obtained preliminary results strongly suggesting that multiple cell types are indeed altered in AD brains of mice and humans, and that gender, aging, and AD have overlapping molecular features. I hypothesize that age-dependent cellular/molecular alterations are key drivers of cognitive decline, and that the dynamics of these alterations determine risk and resilience levels in individuals. We will test this hypothesis by: 1) Charting the cellular microenvironments and tissue topology of the human AD brain, to reveal cells, pathways, and cellular interactions driving AD; 2) Mapping the dynamic cellular/molecular trajectories in aging and AD in w.t. and AD mice, to untangle AD, aging, and gender dimorphism; and 3) Identifying regulators of cognitive resilience and decline in AD and aging, and connecting genes to function by detailed mechanistic investigations in vivo. Overall, our innovative proposal is expected to advance our understanding of AD mechanism, and the link to aging and gender dimorphism.