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The identification of disease biomarkers plays a crucial role in developing diagnostic strategies for inborn errors of metabolism and understanding their pathophysiology. A primary metabolite that accumulates in the inborn error phenylketonuria is phenylalanine, however its levels do not always directly correlate with clinical outcomes. Here we combine infrared ion spectroscopy and NMR spectroscopy to identify the Phe-glucose Amadori rearrangement product as a biomarker for phenylketonuria. Additionally, we find analogous amino acid-glucose metabolites formed in the body fluids of patients accumulating methionine, lysine, proline and citrulline. Amadori rearrangement products are well-known intermediates in the formation of advanced glycation end-products and have been associated with the pathophysiology of diabetes mellitus and ageing, but are now shown to also form under conditions of aminoacidemia. They represent a general class of metabolites for inborn errors of amino acid metabolism that show potential as biomarkers and may provide further insight in disease pathophysiology., Rianne van Outersterp et al. combine mass spectrometry, NMR, and infrared ion spectroscopy to identify amino acid-hexose conjugates in the blood plasma from patients with metabolic disorders such as phenylketonuria (PKU). These conjugates, or Amadori rearrangement products, are generally not detectable in blood samples from unaffected individuals, and may therefore represent disease biomarkers.

Timely diagnosis is essential for patients with neurometabolic disorders to enable targeted treatment. Next‐Generation Metabolic Screening (NGMS) allows for simultaneous screening of multiple diseases and yields a holistic view of disturbed metabolic pathways. We applied this technique to define a cerebrospinal fluid (CSF) reference metabolome and validated our approach with patients with known neurometabolic disorders. Samples were measured using ultra‐high‐performance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry followed by (un)targeted analysis. For the reference metabolome, CSF samples from patients with normal general chemistry results and no neurometabolic diagnosis were selected and grouped based on sex and age (0‐2/2‐5/5‐10/10‐15 years). We checked the levels of known biomarkers in CSF from seven patients with five different neurometabolic disorders to confirm the suitability of our method for diagnosis. Untargeted analysis of 87 control CSF samples yielded 8036 features for semiquantitative analysis. No sex differences were found, but 1782 features (22%) were different between age groups (q

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. Electronic supplementary material The online version of this article (10.1007/s10545-017-0131-6) contains supplementary material, which is available to authorized users.

Corrigendum: NANS-mediated synthesis of sialic acid is required for brain and skeletal development

We identified biallelic mutations in NANS, the gene encoding the synthase for N-acetylneuraminic acid (NeuNAc; sialic acid), in nine individuals with infantile-onset severe developmental delay and skeletal dysplasia. Patient body fluids showed an elevation in N-acetyl-D-mannosamine levels, and patient-derived fibroblasts had reduced NANS activity and were unable to incorporate sialic acid precursors into sialylated glycoproteins. Knockdown of nansa in zebrafish embryos resulted in abnormal skeletal development, and exogenously added sialic acid partially rescued the skeletal phenotype. Thus, NANS-mediated synthesis of sialic acid is required for early brain development and skeletal growth. Normal sialylation of plasma proteins was observed in spite of NANS deficiency. Exploration of endogenous synthesis, nutritional absorption, and rescue pathways for sialic acid in different tissues and developmental phases is warranted to design therapeutic strategies to counteract NANS deficiency and to shed light on sialic acid metabolism and its implications for human nutrition.

Peptides derived from measles virus (MV) are presented by MHC class I molecules at widely divergent levels, but it is currently unknown how functional these levels are. Here, for the first time, we studied the natural occurrence and the underlying processing events of a known MV CTL epitope derived from the fusion glycoprotein (MV-F) and restricted via HLA-B*2705. Using MHC–peptide elution of MV-infected cells followed by sensitive mass spectrometry we determined the naturally occurring sequence to be RRYPDAVYL, corresponding to MV-F438–446. Its level of expression was enumerated at approximately 1500 copies per cell, which is considered to be abundant, but lies within the range described for other viral CTL epitopes in human MHC class I molecules. We found that processing of the MV-F438–446 epitope occurs primarily via the classic MHC class I loading pathway, since presentation to CTL depends on both the transporter associated with antigen presentation (TAP) and the proteasome. Even though it is cotranslationally inserted into the ER, a major part of MV-F is located in the cytosol, where it accumulates rapidly in the presence of proteasome inhibitors. We therefore conclude that a substantial cytosolic turnover of MV-F, together with some excellent processing features of MV-F438–446 precursors, such as precise C-terminal excision by proteasomes, efficient TAP transport and strong HLA binding, dictate the abundant functional expression of the MV-F438–446 CTL epitope in HLA-B*2705 at the surface of MV-infected cells.