Data-driven stochastic model for quantifying the interplay between amyloid-beta and calcium levels in Alzheimer's disease

Abstract

The abnormal aggregation of extracellular amyloid-β (Formula presented.) in senile plaques resulting in calcium (Formula presented.) dyshomeostasis is one of the primary symptoms of Alzheimer's disease (AD). Significant research efforts have been devoted in the past to better understand the underlying molecular mechanisms driving (Formula presented.) deposition and (Formula presented.) dysregulation. Importantly, synaptic impairments, neuronal loss, and cognitive failure in AD patients are all related to the buildup of intraneuronal (Formula presented.) accumulation. Moreover, increasing evidence show a feed-forward loop between (Formula presented.) and (Formula presented.) levels, that is, (Formula presented.) disrupts neuronal (Formula presented.) levels, which in turn affects the formation of (Formula presented.). To better understand this interaction, we report a novel stochastic model where we analyze the positive feedback loop between (Formula presented.) and (Formula presented.) using ADNI data. A good therapeutic treatment plan for AD requires precise predictions. Stochastic models offer an appropriate framework for modeling AD since AD studies are observational in nature and involve regular patient visits. The etiology of AD may be described as a multi-state disease process using the approximate Bayesian computation method. So, utilizing ADNI data from (Formula presented.) -year visits for AD patients, we employ this method to investigate the interplay between (Formula presented.) and (Formula presented.) levels at various disease development phases. Incorporating the ADNI data in our physics-based Bayesian model, we discovered that a sufficiently large disruption in either (Formula presented.) metabolism or intracellular (Formula presented.) homeostasis causes the relative growth rate in both (Formula presented.) and (Formula presented.), which corresponds to the development of AD. The imbalance of (Formula presented.) ions causes (Formula presented.) disorders by directly or indirectly affecting a variety of cellular and subcellular processes, and the altered homeostasis may worsen the abnormalities of (Formula presented.) ion transportation and deposition. This suggests that altering the (Formula presented.) balance or the balance between (Formula presented.) and (Formula presented.) by chelating them may be able to reduce disorders associated with AD and open up new research possibilities for AD therapy.