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Insights into the Value of Lyso-Gb1 as a Predictive Biomarker in Treatment-Naïve Patients with Gaucher Disease Type 1 in the LYSO-PROOF Study

Authors :
Filipa Curado
Sabine Rösner
Susanne Zielke
Gina Westphal
Ulrike Grittner
Volha Skrahina
Mohammed Alasel
Ahmad Mehmood Malik
Christian Beetz
Tobias Böttcher
Gal Barel
Ashish Prasad Sah
Tama Dinur
Nadeem Anjum
Quidad Ichraf
Yamna Kriouile
Zahra Hadipour
Fatemeh Hadipour
Shoshana Revel-Vilk
Claudia Cozma
Jörg Hartkamp
Huma Cheema
Ari Zimran
Peter Bauer
Arndt Rolfs
Source :
Diagnostics, Vol 13, Iss 17, p 2812 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Gaucher disease (GD) is a rare autosomal recessive disorder arising from bi-allelic variants in the GBA1 gene, encoding glucocerebrosidase. Deficiency of this enzyme leads to progressive accumulation of the sphingolipid glucosylsphingosine (lyso-Gb1). The international, multicenter, observational “Lyso-Gb1 as a Long-term Prognostic Biomarker in Gaucher Disease”—LYSO-PROOF study succeeded in enrolling a cohort of 160 treatment-naïve GD patients from diverse geographic regions and evaluated the potential of lyso-Gb1 as a specific biomarker for GD. Using genotypes based on established classifications for clinical presentation, patients were stratified into type 1 GD (n = 114) and further subdivided into mild (n = 66) and severe type 1 GD (n = 48). Due to having previously unreported genotypes, 46 patients could not be classified. Though lyso-Gb1 values at enrollment were widely distributed, they displayed a moderate and statistically highly significant correlation with disease severity measured by the GD-DS3 scoring system in all GD patients (r = 0.602, p < 0.0001). These findings support the utility of lyso-Gb1 as a sensitive biomarker for GD and indicate that it could help to predict the clinical course of patients with undescribed genotypes to improve personalized care in the future.

Details

Language :
English
ISSN :
20754418
Volume :
13
Issue :
17
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.8bc45cefc4f4454f8ba12c3c3714514a
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics13172812