Clinical and biochemical footprints of congenital disorders of glycosylation: Proposed nosology.

We have identified 200 congenital disorders of glycosylation (CDG) caused by 189 different gene defects and have proposed a classification system for CDG based on the mode of action. This classification includes 8 categories: 1. Disorders of monosaccharide synthesis and interconversion, 2. Disorders of nucleotide sugar synthesis and transport, 3. Disorders of N-linked protein glycosylation, 4. Disorders of O-linked protein glycosylation, 5. Disorders of lipid glycosylation, 6. Disorders of vesicular trafficking, 7. Disorders of multiple glycosylation pathways and 8. Disorders of glycoprotein/glycan degradation. Additionally, using information from IEMbase, we have described the clinical involvement of 19 organs and systems, as well as essential laboratory investigations for each type of CDG. Neurological, dysmorphic, skeletal, and ocular manifestations were the most prevalent, occurring in 81%, 56%, 53%, and 46% of CDG, respectively. This was followed by digestive, cardiovascular, dermatological, endocrine, and hematological symptoms (17-34%). Immunological, genitourinary, respiratory, psychiatric, and renal symptoms were less frequently reported (8-12%), with hair and dental abnormalities present in only 4-7% of CDG. The information provided in this study, including our proposed classification system for CDG, may be beneficial for healthcare providers caring for individuals with metabolic conditions associated with CDG.

Significance of utilizing in silico structural analysis and phenotypic data to characterize phenylalanine hydroxylase variants: A PAH landscape.

Phenylketonuria (PKU) is a genetic disorder caused by variations in the phenylalanine hydroxylase (PAH) gene. Among the 3369 reported PAH variants, 33.7% are missense alterations. Unfortunately, 30% of these missense variants are classified as variants of unknown significance (VUS), posing challenges for genetic risk assessment. In our study, we focused on analyzing 836 missense PAH variants following the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines specified by ClinGen PAH Variant Curation Expert Panel (VCEP) criteria. We utilized and compared variant annotator tools like Franklin and Varsome, conducted 3D structural analysis of PAH, and examined active and regulatory site hotspots. In addition, we assessed potential splicing effect of apparent missense variants. By evaluating phenotype data from 22962 PKU patients, our aim was to reassess the pathogenicity of missense variants. Our comprehensive approach successfully reclassified 309 VUSs out of 836 missense variants as likely pathogenic or pathogenic (37%), upgraded 370 likely pathogenic variants to pathogenic, and reclassified one previously considered likely benign variant as likely pathogenic. Phenotypic information was available for 636 missense variants, with 441 undergoing 3D structural analysis and active site hotspot identification for 180 variants. After our analysis, only 6% of missense variants were classified as VUSs, and three of them (c.23A>C/p.Asn8Thr, c.59_60delinsCC/p.Gln20Pro, and c.278A >T/p.Asn93Ile) may be influenced by abnormal splicing. Moreover, a pathogenic variant (c.168G>T/p.Glu56Asp) was identified to have a risk exceeding 98% for modifications of the consensus splice site, with high scores indicating a donor loss of 0.94. The integration of ACMG/AMP guidelines with in silico structural analysis and phenotypic data significantly reduced the number of missense VUSs, providing a strong basis for genetic counseling and emphasizing the importance of metabolic phenotype information in variant curation. This study also sheds light on the current landscape of PAH variants.

Does hyperphenylalaninemia induce brain glucose hypometabolism? Cerebral spinal fluid findings in treated adult phenylketonuric patients.

Despite numerous studies in human patients and animal models for phenylketonuria (PKU; OMIM#261600), the pathophysiology of PKU and the underlying causes of brain dysfunction and cognitive problems in PKU patients are not well understood. In this study, lumbar cerebral spinal fluid (CSF) was obtained immediately after blood sampling from early-treated adult PKU patients who had fasted overnight. Metabolite and amino acid concentrations in the CSF of PKU patients were compared with those of non-PKU controls. The CSF concentrations and CSF/plasma ratios for glucose and lactate were found to be below normal, similar to what has been reported for glucose transporter1 (GLUT1) deficiency patients who exhibit many of the same clinical symptoms as untreated PKU patients. CSF glucose and lactate levels were negatively correlated with CSF phenylalanine (Phe), while CSF glutamine and glutamate levels were positively correlated with CSF Phe levels. Plasma glucose levels were negatively correlated with plasma Phe concentrations in PKU subjects, which partly explains the reduced CSF glucose concentrations. Although brain glucose concentrations are unlikely to be low enough to impair brain glucose utilization, it is possible that the metabolism of Phe in the brain to produce phenyllactate, which can be transported across the blood-brain barrier to the blood, may consume glucose and/or lactate to generate the carbon backbone for glutamate. This glutamate is then converted to glutamine and carries the Phe-derived ammonia from the brain to the blood. While this mechanism remains to be tested, it may explain the correlations of CSF glutamine, glucose, and lactate concentrations with CSF Phe.

Clinical, Neuroimaging, and Metabolic Footprint of the Neurodevelopmental Disorder Caused by Monoallelic HK1 Variants.

Background and Objectives: Hexokinase 1 (encoded by HK1) catalyzes the first step of glycolysis, the adenosine triphosphate-dependent phosphorylation of glucose to glucose-6-phosphate. Monoallelic HK1 variants causing a neurodevelopmental disorder (NDD) have been reported in 12 individuals. Methods: We investigated clinical phenotypes, brain MRIs, and the CSF of 15 previously unpublished individuals with monoallelic HK1 variants and an NDD phenotype. Results: All individuals had recurrent variants likely causing gain-of-function, representing mutational hot spots. Eight individuals (c.1370C>T) had a developmental and epileptic encephalopathy with infantile onset and virtually no development. Of the other 7 individuals (n = 6: c.1334C>T; n = 1: c.1240G>A), 3 adults showed a biphasic course of disease with a mild static encephalopathy since early childhood and an unanticipated progressive deterioration with, e.g., movement disorder, psychiatric disease, and stroke-like episodes, epilepsy, starting in adulthood. Individuals who clinically presented in the first months of life had (near)-normal initial neuroimaging and severe cerebral atrophy during follow-up. In older children and adults, we noted progressive involvement of basal ganglia including Leigh-like MRI patterns and cerebellar atrophy, with remarkable intraindividual variability. The CSF glucose and the CSF/blood glucose ratio were below the 5th percentile of normal in almost all CSF samples, while blood glucose was unremarkable. This biomarker profile resembles glucose transporter type 1 deficiency syndrome; however, in HK1-related NDD, CSF lactate was significantly increased in all patients resulting in a substantially different biomarker profile. Discussion: Genotype-phenotype correlations appear to exist for HK1 variants and can aid in counseling. A CSF biomarker profile with low glucose, low CSF/blood glucose, and high CSF lactate may point toward monoallelic HK1 variants causing an NDD. This can help in variant interpretation and may aid in understanding the pathomechanism. We hypothesize that progressive intoxication and/or ongoing energy deficiency lead to the clinical phenotypes and progressive neuroimaging findings.