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Development of a newborn screening tool for mucopolysaccharidosis type I based on bivariate normal limits: Using glycosaminoglycan and alpha‐L‐iduronidase determinations on dried blood spots to predict symptoms

Authors :
Thomas J. Langan
Kabir Jalal
Amy L. Barczykowski
Randy L. Carter
Molly Stapleton
Kenji Orii
Toshiyuki Fukao
Hironori Kobayashi
Seiji Yamaguchi
Shunji Tomatsu
Source :
JIMD Reports, Vol 52, Iss 1, Pp 35-42 (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Abstract Purpose Current newborn screening (NBS) for mucopolysaccharidosis type I (MPSI) has very high false positive rates and low positive predictive values (PPVs). To improve the accuracy of presymptomatic prediction for MPSI, we propose an NBS tool based on known biomarkers, alpha‐L‐iduronidase enzyme activity (IDUA) and level of the glycosaminoglycan (GAG) heparan sulfate (HS). Methods We developed the NBS tool using measures from dried blood spots (DBS) of 5000 normal newborns from Gifu Prefecture, Japan. The tool's predictive accuracy was tested on the newborn DBS from these infants and from seven patients who were known to have early‐onset MPSI (Hurler's syndrome). Bivariate analyses of the standardized natural logarithms of IDUA and HS levels were employed to develop the tool. Results Every case of early‐onset MPSI was predicted correctly by the tool. No normal newborn was incorrectly identified as having early‐onset MPSI, whereas 12 normal newborns were so incorrectly identified by the Gifu NBS protocol. The PPV was estimated to be 99.9%. Conclusions Bivariate analysis of IDUA with HS in newborn DBS can accurately predict early MPSI symptoms, control false positive rates, and enhance presymptomatic treatment. This bivariate analysis‐based approach, which was developed for Krabbe disease, can be extended to additional screened disorders.

Details

Language :
English
ISSN :
21928312
Volume :
52
Issue :
1
Database :
Directory of Open Access Journals
Journal :
JIMD Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.419e1a9be84711aacdc66fabfc4e7d
Document Type :
article
Full Text :
https://doi.org/10.1002/jmd2.12093