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<p>Fabry disease is an X-linked lysosomal storage disorder caused by α-galactosidase A deficiency, leading to progressive accumulation of Gb3 and lyso-Gb3 and a complex multisystem phenotype extending beyond substrate storage. Cardiovascular involvement remains the leading cause of morbidity and mortality, yet early detection and risk stratification remain challenging. In this context, a new proteomic study leveraging high-throughput proximity extension assays and machine learning has defined a cardiovascular risk signature in Fabry disease. Differential expression analysis identified widespread proteomic remodeling involving inflammatory signaling, extracellular matrix organization, angiogenesis, and metabolic pathways, supporting a systems-level view of disease pathogenesis. A 10-protein biosignature integrating markers of mitochondrial stress, lysosomal function, vascular remodeling, and immune activation demonstrated the ability to discriminate patients with cardiovascular involvement. Notably, proteins such as GDF15, NT-proBNP, NOS1, CTSF, and TNFRSF11B highlight the interplay between mitochondrial dysfunction, lysosomal impairment, and vascular inflammation. These findings suggest that Fabry cardiomyopathy reflects coordinated dysregulation across metabolic and inflammatory networks and that multi-protein signatures may improve precision phenotyping and cardiovascular risk prediction beyond conventional biomarkers.</p>

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A proteomic atlas phenotyping Fabry disease identifies a precise cardiovascular risk signature that integrates mitochondrial and lysosomal pathways

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • Gaetano Santulli,
  • Shivangi Pande,
  • Fahimeh Varzideh

摘要

Fabry disease is an X-linked lysosomal storage disorder caused by α-galactosidase A deficiency, leading to progressive accumulation of Gb3 and lyso-Gb3 and a complex multisystem phenotype extending beyond substrate storage. Cardiovascular involvement remains the leading cause of morbidity and mortality, yet early detection and risk stratification remain challenging. In this context, a new proteomic study leveraging high-throughput proximity extension assays and machine learning has defined a cardiovascular risk signature in Fabry disease. Differential expression analysis identified widespread proteomic remodeling involving inflammatory signaling, extracellular matrix organization, angiogenesis, and metabolic pathways, supporting a systems-level view of disease pathogenesis. A 10-protein biosignature integrating markers of mitochondrial stress, lysosomal function, vascular remodeling, and immune activation demonstrated the ability to discriminate patients with cardiovascular involvement. Notably, proteins such as GDF15, NT-proBNP, NOS1, CTSF, and TNFRSF11B highlight the interplay between mitochondrial dysfunction, lysosomal impairment, and vascular inflammation. These findings suggest that Fabry cardiomyopathy reflects coordinated dysregulation across metabolic and inflammatory networks and that multi-protein signatures may improve precision phenotyping and cardiovascular risk prediction beyond conventional biomarkers.