Cardiac Phenotypes in Fabry Disease: Genetic Variability and Clinical Severity Staging Correlation in a Reference Center Cohort

法布里病心脏表型:参考中心队列中遗传变异性和临床严重程度分期的相关性

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Abstract

BACKGROUND/OBJECTIVES: Anderson-Fabry disease (AFD) presents with a wide spectrum of clinical manifestations, influenced by the underlying GLA genotype. While classical variants are typically associated with early-onset, multisystemic involvement, late-onset mutations and variants of uncertain significance (VUS) often display predominantly cardiac phenotypes. This study aimed to explore the relationship between GLA variant class, cardiovascular severity, and clinical outcomes using validated staging systems and real-world data. METHODS: In this single-centre retrospective study, we evaluated 42 patients with genetically confirmed AFD, stratified into classical, late-onset, and VUS categories. Cardiovascular involvement was assessed using three standardized staging tools-Del Franco, Meucci, and MSSI-and correlated with the occurrence and burden of major adverse cardiovascular events (MACE). Multivariable analyses were performed to adjust for age, sex, and treatment status. RESULTS: Classical variants were strongly associated with more advanced cardiac staging (Del Franco, Meucci) and higher MSSI scores, reflecting systemic disease severity. These patients experienced significantly more frequent and severe MACE (p = 0.022), confirming the prognostic relevance of genotypic stratification. In contrast, carriers of late-onset mutations and VUS exhibited milder phenotypes and lower event rates. Importantly, genotype remained an independent predictor of cardiovascular risk in adjusted models, suggesting a direct contribution to disease progression beyond demographic or therapeutic factors. CONCLUSIONS: This study highlights the role of GLA genotype in shaping cardiovascular risk and clinical trajectory in AFD. Integrating genetic classification with clinical staging provides a powerful, multimodal approach to risk stratification and supports the move toward genotype-informed, personalized management strategies in AFD.

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