Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease driven by interacting molecular dysfunctions across motor neurons, skeletal muscle, glial cells, Schwann cells, endothelial cells, and immune components of the neuromuscular junction. In this study, the authors employ a systematic bioinformatics and systems biology methodology to construct a multi-layered molecular systems architecture that captures these interactions in a unified framework. The architecture organizes genetic triggers, cellular components, molecular pathways, and biological processes—such as neuronal degeneration, muscle atrophy, and neuroinflammation—into a coherent, visual, and computationally actionable model. The analysis reveals how dysregulation across pathways including ER stress, mitophagy, agrin signaling, IL-6 signaling, inflammasome activation, and glutamate excitotoxicity converge to drive ALS pathogenesis. By explicitly mapping cross-talk between molecular subsystems, the study exposes why reductionist, single-target therapies have repeatedly failed in ALS. This systems architecture provides a foundational framework for identifying combination therapeutic targets, developing predictive in-silico models, and advancing precision approaches to ALS drug discovery and clinical strategy.
