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Synergistic use of glycomics and single-molecule molecular inversion probes for identification of congenital disorders of glycosylation type-1.

Authors :
Abu Bakar N
Ashikov A
Brum JM
Smeets R
Kersten M
Huijben K
Keng WT
Speck-Martins CE
de Carvalho DR
de Rizzo IMPO
de Mello WD
Heiner-Fokkema R
Gorman K
Grunewald S
Michelakakis H
Moraitou M
Martinelli D
van Scherpenzeel M
Janssen M
de Boer L
van den Heuvel LP
Thiel C
Lefeber DJ
Source :
Journal of inherited metabolic disease [J Inherit Metab Dis] 2022 Jul; Vol. 45 (4), pp. 769-781. Date of Electronic Publication: 2022 Mar 28.
Publication Year :
2022

Abstract

Congenital disorders of glycosylation type 1 (CDG-I) comprise a group of 27 genetic defects with heterogeneous multisystem phenotype, mostly presenting with nonspecific neurological symptoms. The biochemical hallmark of CDG-I is a partial absence of complete N-glycans on transferrin. However, recent findings of a diagnostic N-tetrasaccharide for ALG1-CDG and increased high-mannose N-glycans for a few other CDG suggested the potential of glycan structural analysis for CDG-I gene discovery. We analyzed the relative abundance of total plasma N-glycans by high resolution quadrupole time-of-flight mass spectrometry in a large cohort of 111 CDG-I patients with known (n = 75) or unsolved (n = 36) genetic cause. We designed single-molecule molecular inversion probes (smMIPs) for sequencing of CDG-I candidate genes on the basis of specific N-glycan signatures. Glycomics profiling in patients with known defects revealed novel features such as the N-tetrasaccharide in ALG2-CDG patients and a novel fucosylated N-pentasaccharide as specific glycomarker for ALG1-CDG. Moreover, group-specific high-mannose N-glycan signatures were found in ALG3-, ALG9-, ALG11-, ALG12-, RFT1-, SRD5A3-, DOLK-, DPM1-, DPM3-, MPDU1-, ALG13-CDG, and hereditary fructose intolerance. Further differential analysis revealed high-mannose profiles, characteristic for ALG12- and ALG9-CDG. Prediction of candidate genes by glycomics profiling in 36 patients with thus far unsolved CDG-I and subsequent smMIPs sequencing led to a yield of solved cases of 78% (28/36). Combined plasma glycomics profiling and targeted smMIPs sequencing of candidate genes is a powerful approach to identify causative mutations in CDG-I patient cohorts.<br /> (© 2022 The Authors. Journal of Inherited Metabolic Disease published by John Wiley & Sons Ltd on behalf of SSIEM.)

Details

Language :
English
ISSN :
1573-2665
Volume :
45
Issue :
4
Database :
MEDLINE
Journal :
Journal of inherited metabolic disease
Publication Type :
Academic Journal
Accession number :
35279850
Full Text :
https://doi.org/10.1002/jimd.12496