American Journal for Young Scientists · ISSN 3068-9015
Coupled Calcium–Metabolism Dynamics and Lysosomal Dysfunction in Alzheimer’s Disease: A Computational and Transcriptomic Analysis
Authors: Jayanth Veerappa, Veda Kolkur
Published: March 5, 2026
Category: Computational Neuroscience
Abstract
Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder arising from the convergence of mitochondrial dysfunction, oxidative stress, lysosomal impairment, and genetic predisposition. Here, we combine computational modeling with experimental data to uncover how disruptions in calcium and energy homeostasis contribute to disease progression. We extend the Brusselator model which is traditionally used to describe oscillatory chemical reactions to represent the Krebs Cycle, calcium influx, and insulin resistance. This nonlinear framework captures how sustained calcium overload and age-related metabolic drift lead to attenuated oscillations in the cellular energy cycle, mirroring metabolic collapse observed in AD neurons. Complementing the model, we analyzed human-derived datasets stratified by diagnosis (Control, Mild Cognitive Impairment, Early AD, Late AD). Lysosomal measurements revealed a progressive increase in lysosome number per cell from 72.3 to 104.5 and a corresponding rise in lysosomal pH from 4.49 to 5.46, consistent with impaired acidification and defective autophagy. Furthermore, a Random Forest classifier trained on gene expression profiles of key mitochondrial and lysosomal genes achieved 87% accuracy in distinguishing between diagnostic groups which reveals the predictive power of molecular signatures associated with cellular energy dysregulation and identifies potential molecular biomarkers for early AD detection.