Systematic modeling and prediction of cell-type-specific and spatiotemporal crosstalk pathways in Alzheimer's Disease

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Abstract Alzheimer’s disease (AD) affects more than 50 million people worldwide but there is no clear therapeutic option for the patients. For last two decades, AD research has been focusing on a neuron-centric biochemical process that leads to synaptic deficits and neuronal degeneration. However, recent failures in clinical trials clearly demonstrate a gap in knowledge in our current understanding of AD pathogenesis and call for studies that lead to unbiased and holistic understanding of disease pathways in different types of brain cells. This project aims to tackle this important and urgent issue by combining a computational systems biology platform Single-Cell Resolution Brain Interactome (SCRBI) Explorer, 3D human Alzheimer’s-in-a-dish models, and the publicly available multiple-omics AD databases through NIH-funded AMP-AD portal. We will expand the knowledge base of SCRBI Explorer to handle single cell transcriptomic and multiple omics profiles from 3D cell models and human brain tissues, which can detect on multiple layers of neuron-glia and glia-glia crosstalk pathways via ligand-receptor interactions, cytokine/chemokine signaling, intracellular signaling activities, and transcriptional activation. The central hypothesis is that the combined use of multi-cellular systems biology modeling and 3D human AD cellular models will identify AD-specific neuron-glia and glia-glia crosstalk pathways, which would provide novel therapeutic targets for drug repositioning. We will test this hypothesis by pursuing three specific aims: 1) Develop a multi-cellular crosstalk model to uncover altered neuron-glia and glia-glia crosstalk pathways in AD, 2) identify and validate AD-specific neuron-glia and glia-glia crosstalk pathways that are enriched in 3D human AD cellular models and human AD brain cells, and 3) evaluate the therapeutic potential of neuron-glia and glia-glia crosstalk using 3D human neural cell culture models of AD. The potential impact of this proposal is high because the proposed study, if successful, will provide a unique integrated bioinformatics tool to unbiasedly identify neuron-glia and glia-glia crosstalk pathways in AD and even other neurodegenerative diseases. More importantly, it will provide novel therapeutic targets based on altered neuron-glia interaction pathways in AD and open up a new vista for drug repositioning targeting cell-cell interactions in the brain of AD patients.