The role of neuronal hyperexcitability and proteostasis in alzheimer's disease - key prodromal events in alzheimer's disease (ad) revolve on altered electrical signals and buildup of garbage…

The role of neuronal hyperexcitability and proteostasis in alzheimer's disease - key prodromal events in alzheimer's disease (ad) revolve on altered electrical signals and buildup of garbage proteins in vulnerable areas before signs of ad (locus coeruleus, LC)) and as disease progresses to brain regions that govern memory (hippocampus, HPC) as disease severity increases. This study bridges the potential lifespan of disease progression using a mouse model of ad pathology to examine how modifications in brain activity can lead to disease. The LC, while not traditionally associated with ad, is the site of some of the earliest pathology in ad, as early as people in their 20S. IT is also an area regulating flight or fight response and arousal. In ad, the hyperexcitation or unregulated arousal (hyperarousal) may be a key event in moving the disease from areas like the LC, or another area with early pathology, the entorhinal cortex (EC) to the hippocampus or other cortical regions that are more commonly associated with alzheimer's. In ad, the accumulation of aggregated proteins due to altered cellular processes, specifically, the regulation of protein life cycle (proteostasis) and dysfunction of autophagic-lysosomal and ubiquitin-proteasomal systems is a key feature of neuropathology. These processes are responsible for clearing the garbage in cells and declines with age and is accelerated in disease. While we know loss of proteostasis can impair cellular function, how IT can impede neuronal activity has not been well advanced. In this application, we propose that a primary event early on is the alteration of neural networks in the LC (and EC), leads to the pathological hallmarks of ad including hippocampal pathology. Demonstrating hyperactivation and proteostasis deficits in the LC as instigators of hippocampal pathology, particularly, selective neuronal loss provides mechanistic insight as to why these are key neural network changes in disease. To model alzheimer's pathology, we focus on the LC and HPC to identify how these regions are disrupted when proteostasis slows down and how hyperexcitation impacts these functions. We will track early electrophysiological changes in the LC and HPC when proteins like beta-amyloid (a) and TAU start accumulating and assess hyperarousal/excitation using electrophysiological measurements. Over time, hyperexcitation reduces clearance of aberrant proteins resulting in a positive feedback loop of proteostasis loss and hyperarousal, and cascade to hippocampus and memory loss. We identify the type of neurons that are most vulnerable to hyperexcitation/arousal-proteostasis changes in this network, destabilizing excitatory-inhibitory homeostasis. Finally, we test if dampening hyperexcitation or proteostasis restoration improves cognitive function and reverses pathological changes in our model. Our goal is to use observations from all the paradigms to identify if these biological changes and pathological spread of disease can be analyzed using computational tools to predict the patterns and events leading to ad and to test if we can use as a disease risk score.