Fabry Disease: Integrating Molecular Pathophysiology, Precision Diagnosis, and Artificial Intelligence Toward...

Fabry disease is a rare X-linked lysosomal storage disorder caused by pathogenic variants in the GLA gene, resulting in deficient α-galactosidase A activity and progressive accumulation of globotriaosylceramide (Gb3) and globotriaosylsphingosine (lyso-Gb3). Although lysosomal substrate storage represents the primary molecular defect, accumulating evidence indicates that disease progression is driven by interconnected mechanisms, including chronic inflammation, oxidative stress, endothelial dysfunction, and impaired autophagy, leading to progressive multisystem involvement. The marked clinical heterogeneity of Fabry disease, together with nonspecific early manifestations, frequently delays diagnosis and complicates patient stratification and therapeutic decision-making. While advances in biomarkers, genetic testing, and imaging have improved disease recognition, current diagnostic approaches remain insufficient to fully capture disease complexity. Precision medicine is therefore emerging as a promising strategy through the integration of clinical, molecular, imaging, and multi-omics data. In this context, artificial intelligence (AI) offers novel opportunities for early diagnosis, biomarker discovery, risk stratification, and prediction of therapeutic response. This review provides an integrated overview of the molecular mechanisms, inflammatory pathways, clinical manifestations, and precision diagnostic strategies underlying Fabry disease, highlighting how AI-driven approaches may accelerate the transition toward more accurate, personalized, and predictive disease management.