Congenital disorders of glycosylation (CDG) are inherited metabolic diseases that affect the synthesis of glycoconjugates. Defects in mucin-type O-glycosylation occur independently or in combination with N-glycosylation disorders, and the profiling of the O-glycans of apolipoprotein CIII (apoCIII) by mass spectrometry (MS) can be used to support a diagnosis. The biomarkers are site occupancy and sialylation levels, which are indicated by the content of non-glycosylated apoCIII0a isoform and by the ratio of monosialylated apoCIII1 to disialylated apoCIII2 isoforms, respectively. In this report, electrospray ionization (ESI) quadrupole MS of apoCIII was used to identify these biomarkers. Among the instrumental parameters, the declustering potential (DP) induced the fragmentation of the O-glycan moiety including the Thr-GalNAc linkage, resulting in an increase in apoCIII0a ions. This incurs the risk of creating a false positive for reduced site occupancy. The apoCIII1/apoCIII2 ratio was substantially unchanged despite some dissociation of sialic acids. Therefore, appropriate DP settings are especially important when transferrin, which requires a higher DP, for N-glycosylation disorders is analyzed simultaneously with apoCIII in a single ESI MS measurement. Finally, a reference range of diagnostic biomarkers and mass spectra of apoCIII obtained from patients with SLC35A1-, TRAPPC11-, and ATP6V0A2-CDG are presented.
Electrospray ionization (ESI) mass spectrometry of transferrin can be used to diagnose congenital disorders of glycosylation (CDG) by detecting abnormal N-glycosylation due to reduced site occupancy or processing failure. Time-of-flight mass spectrometers are widely used to separate 25-45 charged ions in the m/z 1,700-3,000 range, and a summed zero-charge mass distribution is generated despite the risk of improper deconvolution. In this study, the low m/z region of the multiply-charged ion mass spectrum enabled a robust analysis of CDG. A triple quadrupole mass spectrometer, the standard instrument for newborn screening for inborn errors of metabolism, permitted the identification of the key ions characteristic of different types of CDG affecting PMM2, ALG14, SLC35A1, SLC35A2, MAN1B1 and PGM1 in the m/z 1,970-2,000 region. Charge deconvolution was used as a complementary tool for validating the findings. It was necessary to set a cutoff level for the evaluation, since small peaks indicating glycosylation failure or reduced sialylation were observed, even in control subjects. This method and workflow facilitates the implementation of MS-based analyses and the screening of CDG in clinical laboratories.
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