Alzheimer's disease (AD), in particular la?te onset AD, is the most common form of dementia, accounting for about two thirds of all the dementia cases, and its pathogenesis may start decades early before its actual clinic manifestation. The search for disease modifying treatments is the primary objective of most rigorous therapeutic research efforts on AD. However, AD is currently incurable and available therapies are only effective in partially alleviating selected AD clinical symptoms, but not its onset and/or progression. The unmet need for the timely development of potent therapies for AD has been constantly growing with the heavy burden on our healthcare system reaching a critical level. There is an urgent need to reinvigorate AD drug development by utilizing systems biology, especially network biology approaches which have the potential to present not only global landscape of pathway-pathway interactions but also detailed molecular interaction/regulation circuits underlying AD. Network biology approaches to integrate large-scale multi-omics data in AD have demonstrated that differentially regulated subnetworks in AD, which regulate diverse AD pathogenic phenotypes, often include a large number of key regulators. Therefore, drugs and drug combinations that can modulate such subnetworks as a whole are the most pertinent for therapeutic intervention and have better chance to be successful. In this application, we propose to develop novel molecular network based drug repositioning approaches to identify individual FDA approved drugs as well as their combinations that can potentially reverse molecular signatures and network states of AD. A large number of predicted drugs and drug combinations will be tested in multiple model systems including mouse brain primary cells, human iPSC derived brain cells and AD mouse models. This project will establish an integrative platform comprised of highly innovative systems and experimental biology components for rapid drug discovery for AD.
- This proposal aims to develop novel molecular network based drug repositioning approaches to identify FDA approved drugs and their combinations that can potentially reverse molecular signatures and network states of Alzheimer's disease (AD) derived from large-scale bulk-tissue and single cell transcriptomic data in AD. A number of predicted drugs and drug combinations will be validated using multiple model systems including mouse primary brain cells, human iPSC derived brain cells and AD mouse models.