Increased Clinical Sensitivity and Specificity of Plasma Protein N-Glycan Profiling for Diagnosing Congenital Disorders of Glycosylation by Use of Flow Injection–Electrospray Ionization–Quadrupole Time-of-Flight Mass Spectrometry
Abstract BACKGROUND Congenital disorders of glycosylation (CDG) represent 1 of the largest groups of metabolic disorders with >130 subtypes identified to date. The majority of CDG subtypes are disorders of N-linked glycosylation, in which carbohydrate residues, namely, N-glycans, are posttranslationally linked to asparagine molecules in peptides. To improve the diagnostic capability for CDG, we developed and validated a plasma N-glycan assay using flow injection–electrospray ionization–quadrupole time-of-flight mass spectrometry. METHODS After PNGase F digestion of plasma glycoproteins, N-glycans were linked to a quinolone using a transient amine group at the reducing end, isolated by a hydrophilic interaction chromatography column, and then identified by accurate mass and quantified using a stable isotope-labeled glycopeptide as the internal standard. RESULTS This assay differed from other N-glycan profiling methods because it was free of any contamination from circulating free glycans and was semiquantitative. The low end of the detection range tested was at 63 nmol/L for disialo-biantennary N-glycan. The majority of N-glycans in normal plasma had <1% abundance. Abnormal N-glycan profiles from 19 patients with known diagnoses of 11 different CDG subtypes were generated, some of which had previously been reported to have normal N-linked protein glycosylation by carbohydrate-deficient transferrin analysis. CONCLUSIONS The clinical specificity and sensitivity of N-glycan analysis was much improved with this method. Additional CDGs can be diagnosed that would be missed by carbohydrate-deficient transferrin analysis. The assay provides novel biomarkers with diagnostic and potentially therapeutic significance.
National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines: Follow-Up Testing for Metabolic Disease Identified by Expanded Newborn Screening Using Tandem Mass Spectrometry; Executive Summary
AbstractBackground: Almost all newborns in the US are screened at birth for multiple inborn errors of metabolism using tandem mass spectrometry. Screening tests are designed to be sufficiently sensitive so that cases are not missed. The NACB recognized a need for standard guidelines for laboratory confirmation of a positive newborn screen such that all babies would benefit from equal and optimal follow-up by confirmatory testing.Methods: A committee was formed to review available data pertaining to confirmatory testing. The committee evaluated previously published guidelines, published methodological and clinical studies, clinical case reports, and expert opinion to support optimal confirmatory testing. Grading was based on guidelines adopted from criteria derived from the US Preventive Services Task Force and on the strength of recommendations and the quality of the evidence. Three primary methods of analyte measurement were evaluated for confirmatory testing including measurement of amino acids, organic acids, and carnitine esters. The committee graded the evidence for diagnostic utility of each test for the screened conditions.Results: Ample data and experience were available to make strong recommendations for the practice of analyzing amino acids, organic acids, and acylcarnitines. Likewise, strong recommendations were made for the follow-up test menu for many disorders, particularly those with highest prevalence. Fewer data exist to determine the impact of newborn screening on patient outcomes in all but a few disorders. The guidelines also provide an assessment of developing technology that will fuel a refinement of current practice and ultimate expansion of the diseases detectable by tandem mass spectrometry.Conclusions: Guidelines are provided for optimal follow-up testing for positive newborn screens using tandem mass spectrometry. The committee regards these tests as reliable and currently optimal for follow-up testing. .