Investigation of active kinome networks in Alzheimer's dementia.

Summary This is a revised R01 application from a team of established investigators who bring complementary expertise for a multi-omics, hypothesis generating, series of experiments that have the overarching goal of deepening understanding of the pathophysiology of Alzheimer’s dementia (AD). Taken together, the prevalence of this

devastating disorder, the paucity of efficacious treatments, and the very high failure rate of clinical trials for new AD treatments indicate a pressing need to better understand how this disease breaks the brain. We posit that measures of protein function, rather than gene expression, are needed to develop a more sophisticated

understanding of AD progression. Protein function can be measured in many ways. Genetic or pharmacological manipulation provides compelling insights for causal relationships between proteins. Such work relies on assumptions about biological function that are linear. However, the sum of the properties of

individual components may not model whole systems, and orchestration of complex systems may not be explained by individual components. This is particularly true for protein kinase signaling, where overlap, crosstalk, and reversibility of phosphorylation events makes for non-linear networks. In this proposal, we

embrace this complexity with a series of experiments designed to assess these typically non-linear networks. We plan to assess the serine/threonine subkinome using an unbiased protein kinase activity array approach. Combined with bioinformatics tools that yield protein kinase networks and nodes, we hypothesize that higher

order information regarding signaling networks in AD progression will yield novel insights about the disease. The biological substrates for this study will include postmortem brain from control, mild cognitive impairment (MCI), and AD subjects, as well as iPSC-derived neuronal, astrocyte, and microglia cultures from sporadic (late

onset) and familial AD cases. AD progression will be assessed with early, intermediate, and late timepoints in AD iPSC cultures, and by comparing control vs MCI and MCI vs AD postmortem samples. Deliverables include 1) identification of protein kinases networks and nodes associated with AD progression, 2) validation of protein

kinase nodes during AD progression between and across postmortem and iPSC substrates, and 3) advancement of validated protein kinase nodes for causal studies in human AD iPSCs. Effects of sex will be assessed as a secondary outcome, with equal numbers of male and female samples for each AD substrate.

LCMS datasets will be generated in parallel to kinome array datasets, permitting multi-omics integration. All datasets will be incorporated into an R-Shiny platform that integrates biological features of protein kinases. Importantly, the preliminary data for this proposal demonstrate that this project is low-risk, high reward, as we

have performed a series of rigorous studies that identify candidate protein kinase network nodes and carefully advance and validate a candidate node previously implicated in AD that has not been studied in human model systems. For these reasons, we believe that this project is highly impactful with a high probability of success.