Amadori rearrangement products as potential biomarkers for inborn errors of amino-acid metabolism.

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.

Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles.

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 < 0.05). We identified 206 diagnostic metabolites in targeted analysis. In a subset of 20 high-intensity metabolites and 10 biomarkers, 17 (57%) were age-dependent. For each neurometabolic patient, ≥1 specific biomarker(s) could be identified in CSF, thus confirming the diagnosis. In two cases, age-matching was essential for correct interpretation of the metabolomic profile. In conclusion, NGMS in CSF is a powerful tool in defining a diagnosis for neurometabolic disorders. Using our database with many (age-dependent) features in CSF, our untargeted approach will facilitate biomarker discovery and further understanding of mechanisms of neurometabolic disorders.

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.

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.

Autoreactivity against induced or upregulated abundant self-peptides in HLA-A*0201 following measles virus infection.

Infectious agents have been implied as causative environmental factors in the development of autoimmunity. However, the exact nature of their involvement remains unknown. We describe a possible mechanism for the activation of autoreactive T cells induced by measles virus (MV) infection. The display of HLA-A*0201 associated peptides obtained from MV infected cells was compared with that from uninfected cells by mass spectrometry. We identified two abundant self peptides, IFI-6-16(74-82) and Hsp90beta(570-578), that were induced or upregulated, respectively, following infection. Their parental proteins, the type I interferon inducible protein IFI-6-16, and the beta chain of heat shock protein 90, have not been involved in MV pathogenesis. MV infection caused minor and major changes in the intracellular expression patterns of these proteins, possibly leading to altered peptide processing. CD8+ T cells capable of recognizing the self-peptides in the context of HLA-A*0201 were detectable at low basal levels in the neonatal and adult human T cell repertoire, but were functionally silent. In contrast, peptide-specific producing IFN-gamma producing effector cells were present in MV patients during acute infection. Thus, MV infection induces an enhanced display of self-peptides in MHC class I, which may lead to the temporary activation of autoreactive T cells.

Dynamics of measles virus protein expression are reflected in the MHC class I epitope display.

Following measles virus (MV) infection, viral peptides are presented to CTL by MHC class I molecules on infected antigen presenting cells at widely different epitope densities. Whereas three MV epitopes (MV-M(211-219), MV-F(438-446) and MV-H(30-38)) derived from different structural proteins occur at regular densities, one peptide derived from the non-structural C protein (MV-C(84-92)) fully dominates the MV peptide display in HLA class I molecules on end-stage-infected human B cells. Here we demonstrate that this hierarchy in MV epitope density is not a constant, but varies with progression of infection. While MV-M(211-219), MV-F(438-446) and MV-H(30-38) epitopes were already presented by HLA class I molecules early in infection, expression of MV-C(84-92) was restricted to the later phases of infection. These dynamics in epitope densities correlated with features of MV protein expression. Synthesis of C protein mainly focused towards the final stages of infection, while the other MV proteins were more readily synthesised from earlier time points on, in line with the emergence of their respective epitopes. Furthermore, the most abundant MV epitope was derived from the most unstable viral protein and vice versa, suggesting that the stability of viral proteins may be an indicator for the final abundance of their epitopes. Thus, even though many other factors may influence the generation of peptide-MHC class I complexes, we here report that the regulation of viral protein expression seems closely linked to the viral MHC class I epitope display. Finally, the observed dynamics in viral epitope hierarchy may have important implications for the induction of antiviral T cell immunity.

A measles virus glycoprotein-derived human CTL epitope is abundantly presented via the proteasomal-dependent MHC class I processing pathway.

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-F(438-446). 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-F(438-446) 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-F(438-446) precursors, such as precise C-terminal excision by proteasomes, efficient TAP transport and strong HLA binding, dictate the abundant functional expression of the MV-F(438-446) CTL epitope in HLA-B*2705 at the surface of MV-infected cells.