Genetic Screens to Identify Targets that Regulate Amyloid Precursor Protein (APP)
Co-Principal InvestigatorsJuan Botas, PhD Baylor College of Medicine
Alzheimer disease (AD) is characterized by the deposition of amyloid plaques and the accumulation of neurofibrillary tangles (eg, tau tangles), These AD pathologies are the, products of amyloid precursor protein (APP) processing and tau hyperphosphorylation, respectively. Several studies demonstrate that reduction of APP is therapeutically beneficial in AD mouse models. This evidence prompted us to hypothesize that modest reduction in the levels of APP proteins would delay the onset and retard progression of AD. We plan to identify new therapeutic targets using an unbiased, high-throughput screen that employs two different assay systems in parallel (human neuronal cell lines and fruit flies expressing human APP).Our goal is to identify those proteins whose reduction results in lower levels of APP, and whether this reduction rescues neuronal degeneration in flies.
The major goal of this project is to discover new therapeutic targets for Alzheimer disease (AD). We propose a research program centered on genes and genetic networks that control amyloid precursor protein (APP) levels using innovative screens of the “druggable” genome. In Aim 1, we will employ two different assay systems in parallel (human neuronal cell lines and Drosophila, eg, fruit-flies expressing human APP) to identify those proteins whose reduction results in lower APP levels. This type of screening paradigm is novel and we have found this approach fruitful in other disease models. One system will use shRNAs [short hairpin RNAs] targeting the druggable human genes to find those whose reduction lowers APP levels in reporter lines. In parallel, we will perform a loss-of-function screen targeting the homologues of the same genes in Drosophila, looking for modifiers of APP-induced neuronal dysfunction. In Aim 2, shared hits from these screens will be prioritized based on: (1) existing genomic and transcriptomic data from human AD patients, (2) pathway enrichment analysis, and (3) availability of known chemical inhibitors. We will confirm the top modifiers in cells and then assess available inhibitory compounds on endogenous APP levels in cells. The top confirmed hits will then be further validated in primary neuronal cultures from wild-type and APP mice. By the end of this project, we will have a set of optimal candidate therapeutic targets ready for genetic knock-down in the mouse brain, as well as for use with known small-molecule inhibitors for further preclinical drug development in mouse models of AD. Assembly of the results into established regulatory pathways, together with validation using known small molecules, should greatly improve our understanding of the regulation of APP protein levels and accelerate the discovery of new therapeutic leads for the treatment of AD.