Oral sialic acid supplementation in NANS-CDG: Results of a single center, open-label, observational pilot study.

NANS-CDG is a congenital disorder of glycosylation (CDG) caused by biallelic variants in NANS, encoding an essential enzyme in de novo sialic acid synthesis. It presents with intellectual developmental disorder (IDD), skeletal dysplasia, neurologic impairment, and gastrointestinal dysfunction. Some patients suffer progressive intellectual neurologic deterioration (PIND), emphasizing the need for a therapy. In a previous study, sialic acid supplementation in knockout nansa zebrafish partially rescued skeletal abnormalities. Here, we performed the first in-human pre- and postnatal sialic-acid study in NANS-CDG. In this open-label observational study, 5 patients with NANS-CDG (range 0-28 years) were treated with oral sialic acid for 15 months. The primary outcome was safety. Secondary outcomes were psychomotor/cognitive testing, height and weight, seizure control, bone health, gastrointestinal symptoms, and biochemical and hematological parameters. Sialic acid was well tolerated. In postnatally treated patients, there was no significant improvement. For the prenatally treated patient, psychomotor and neurologic development was better than two other genotypically identical patients (one treated postnatally, one untreated). The effect of sialic acid treatment may depend on the timing, with prenatal treatment potentially benefiting neurodevelopmental outcomes. Evidence is limited, however, and longer-term follow-up in a larger number of prenatally treated patients is required.

Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients.

The implementation of whole-exome sequencing in clinical diagnostics has generated a need for functional evaluation of genetic variants. In the field of inborn errors of metabolism (IEM), a diverse spectrum of targeted biochemical assays is employed to analyze a limited amount of metabolites. We now present a single-platform, high-resolution liquid chromatography quadrupole time of flight (LC-QTOF) method that can be applied for holistic metabolic profiling in plasma of individual IEM-suspected patients. This method, which we termed "next-generation metabolic screening" (NGMS), can detect >10,000 features in each sample. In the NGMS workflow, features identified in patient and control samples are aligned using the "various forms of chromatography mass spectrometry (XCMS)" software package. Subsequently, all features are annotated using the Human Metabolome Database, and statistical testing is performed to identify significantly perturbed metabolite concentrations in a patient sample compared with controls. We propose three main modalities to analyze complex, untargeted metabolomics data. First, a targeted evaluation can be done based on identified genetic variants of uncertain significance in metabolic pathways. Second, we developed a panel of IEM-related metabolites to filter untargeted metabolomics data. Based on this IEM-panel approach, we provided the correct diagnosis for 42 of 46 IEMs. As a last modality, metabolomics data can be analyzed in an untargeted setting, which we term "open the metabolome" analysis. This approach identifies potential novel biomarkers in known IEMs and leads to identification of biomarkers for as yet unknown IEMs. We are convinced that NGMS is the way forward in laboratory diagnostics of IEMs.