Expanding the phenotypic spectrum of ARCN1-related syndrome.

PURPOSE: This study aimed to describe the phenotypic and molecular characteristics of ARCN1-related syndrome. METHODS: Patients with ARCN1 variants were identified, and clinician researchers were connected using GeneMatcher and physician referrals. Clinical histories were collected from each patient. RESULTS: In total, we identified 14 cases of ARCN1-related syndrome, (9 pediatrics, and 5 fetal cases from 3 families). The clinical features these newly identified cases were compared to 6 previously reported cases for a total of 20 cases. Intrauterine growth restriction, micrognathia, and short stature were present in all patients. Other common features included prematurity (11/15, 73.3%), developmental delay (10/14, 71.4%), genitourinary malformations in males (6/8, 75%), and microcephaly (12/15, 80%). Novel features of ARCN1-related syndrome included transient liver dysfunction and specific glycosylation abnormalities during illness, giant cell hepatitis, hepatoblastoma, cataracts, and lethal skeletal manifestations. Developmental delay was seen in 73% of patients, but only 3 patients had intellectual disability, which is less common than previously reported. CONCLUSION: ARCN1-related syndrome presents with a wide clinical spectrum ranging from a severe embryonic lethal syndrome to a mild syndrome with intrauterine growth restriction, micrognathia, and short stature without intellectual disability. Patients with ARCN1-related syndrome should be monitored for liver dysfunction during illness, cataracts, and hepatoblastoma. Additional research to further define the phenotypic spectrum and possible genotype-phenotype correlations are required.

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.

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.

Defining the Phenotype and Assessing Severity in Phosphoglucomutase-1 Deficiency.

OBJECTIVE: To define phenotypic groups and identify predictors of disease severity in patients with phosphoglucomutase-1 deficiency (PGM1-CDG). STUDY DESIGN: We evaluated 27 patients with PGM1-CDG who were divided into 3 phenotypic groups, and group assignment was validated by a scoring system, the Tulane PGM1-CDG Rating Scale (TPCRS). This scale evaluates measurable clinical features of PGM1-CDG. We examined the relationship between genotype, enzyme activity, and TPCRS score by using regression analysis. Associations between the most common clinical features and disease severity were evaluated by principal component analysis. RESULTS: We found a statistically significant stratification of the TPCRS scores among the phenotypic groups (P < .001). Regression analysis showed that there is no significant correlation between genotype, enzyme activity, and TPCRS score. Principal component analysis identified 5 variables that contributed to 54% variance in the cohort and are predictive of disease severity: congenital malformation, cardiac involvement, endocrine deficiency, myopathy, and growth. CONCLUSIONS: We established a scoring algorithm to reliably evaluate disease severity in patients with PGM1-CDG on the basis of their clinical history and presentation. We also identified 5 clinical features that are predictors of disease severity; 2 of these features can be evaluated by physical examination, without the need for specific diagnostic testing and thus allow for rapid assessment and initiation of therapy.