Integrated Transcriptomic and Neuroimaging Brain Model Decodes Biological Mechanisms in Aging and Alzheimer’s Disease

Abstract

SummaryBoth healthy aging and Alzheimer’s disease (AD) are characterized by concurrent alterations in several biological factors. However, generative brain models of aging and AD are limited in incorporating the measures of these biological factors at different spatial resolutions. Here, we propose a personalized bottom-up spatiotemporal brain model which accounts for the direct interplay between hundreds of RNA transcripts and multiple macroscopic neuroimaging modalities (PET, MRI). In normal elderly and AD participants, the model identifies top genes modulating tau and amyloid-β burdens, vascular flow, glucose metabolism, functional activity, and atrophy to drive cognitive decline. The results also revealed that AD and healthy aging share specific biological mechanisms, even though AD is a separate entity with considerably more altered pathways. Overall, this personalized model offers novel insights into the multiscale alterations in the elderly brain, with important implications for identifying effective genetic targets for extending healthy aging and treating AD progression.Highlights- A multiscale model integrating gene expression and neuroimaging identifies causal genes driving healthy aging and Alzheimer’s disease progression.- The specific neuroimaging modalities modulated by the causal genes are revealed.- Healthy aging and Alzheimer’s disease share specific biological pathways even though Alzheimer’s disease has more altered pathways.