(199e) Developing Novel Tools Toward β-Amyloid-Neuron Interaction Discovery

β-amyloid(Aβ) is the primary protein component of senile plaques associated with Alzheimer’s disease (AD) histopathology. Because of Aβ’s longstanding implication in the initiating events leading to AD pathology in in vitro and in vivo experimental preparations, it is commonly considered the causative agent of AD.  Yet, though well studied, there still exists a lack of consensus concerning Aβ’s interactions with neurons and resulting alterations in neuronal signaling. We hypothesize that this lack of consensus is due to an incomplete framework for interpreting experimental data arising from a complex, networked system. In order to evaluate this hypothesis, we are using a genetic algorithm-based computational tool, CellNOptR, to infer Aβ-induced network topologies from a hippocampal neuronal signaling network that most closely fit literature-derived experimental data. In particular, we will present a statistical analysis of multiple Aβ-induced topologies generated via optimization of a prior knowledge network and literature-derived experimental data. Through the use of CellNOptR and subsequent statistical analysis on resulting network topologies, we can discriminate between different hypotheses of Aβ-neuron interactions. Our primary motivation in developing this methodology is (1) to synergize current knowledge of Aβ-neuron interactions towards creating working models for this system and (2) to expand our toolkit for addressing complex signaling phenomena in disease systems.