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Predicting the development of anti-drug antibodies against recombinant alpha-galactosidase A in male patients with classical Fabry disease

Please always quote using this URN: urn:nbn:de:bvb:20-opus-285687
  • Fabry Disease (FD) is a rare, X-linked, lysosomal storage disease that mainly causes renal, cardiac and cerebral complications. Enzyme replacement therapy (ERT) with recombinant alpha-galactosidase A is available, but approximately 50% of male patients with classical FD develop inhibiting anti-drug antibodies (iADAs) that lead to reduced biochemical responses and an accelerated loss of renal function. Once immunization has occurred, iADAs tend to persist and tolerization is hard to achieve. Here we developed a pre-treatment prediction model forFabry Disease (FD) is a rare, X-linked, lysosomal storage disease that mainly causes renal, cardiac and cerebral complications. Enzyme replacement therapy (ERT) with recombinant alpha-galactosidase A is available, but approximately 50% of male patients with classical FD develop inhibiting anti-drug antibodies (iADAs) that lead to reduced biochemical responses and an accelerated loss of renal function. Once immunization has occurred, iADAs tend to persist and tolerization is hard to achieve. Here we developed a pre-treatment prediction model for iADA development in FD using existing data from 120 classical male FD patients from three European centers, treated with ERT. We found that nonsense and frameshift mutations in the α-galactosidase A gene (p = 0.05), higher plasma lysoGb3 at baseline (p < 0.001) and agalsidase beta as first treatment (p = 0.006) were significantly associated with iADA development. Prediction performance of a Random Forest model, using multiple variables (AUC-ROC: 0.77) was compared to a logistic regression (LR) model using the three significantly associated variables (AUC-ROC: 0.77). The LR model can be used to determine iADA risk in individual FD patients prior to treatment initiation. This helps to determine in which patients adjusted treatment and/or immunomodulatory regimes may be considered to minimize iADA development risk.show moreshow less

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Metadaten
Author: Sanne J. van der Veen, Wytze J. Vlietstra, Laura van Dussen, André B.P. van Kuilenburg, Marcel G. W. Dijkgraaf, Malte Lenders, Eva Brand, Christoph Wanner, Derralynn Hughes, Perry M. Elliott, Carla E. M. Hollak, Mirjam Langeveld
URN:urn:nbn:de:bvb:20-opus-285687
Document Type:Journal article
Faculties:Medizinische Fakultät / Medizinische Klinik und Poliklinik I
Language:English
Parent Title (English):International Journal of Molecular Sciences
ISSN:1422-0067
Year of Completion:2020
Volume:21
Issue:16
Article Number:5784
Source:International Journal of Molecular Sciences (2020) 21:16, 5784. https://doi.org/10.3390/ijms21165784
DOI:https://doi.org/10.3390/ijms21165784
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:Fabry disease; anti-drug antibodies; enzyme replacement therapy; prediction model
Release Date:2023/06/14
Date of first Publication:2020/08/12
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International