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Hereditary spastic paraplegias (HSP) are rare, inherited neurodegenerative or neurodevelopmental disorders that mainly present with lower limb spasticity and muscle weakness due to motor neuron dysfunction. Whole genome sequencing identified bi-allelic truncating variants in AMFR, encoding a RING-H2 finger E3 ubiquitin ligase anchored at the membrane of the endoplasmic reticulum (ER), in two previously genetically unexplained HSP-affected siblings. Subsequently, international collaboration recognized additional HSP-affected individuals with similar bi-allelic truncating AMFR variants, resulting in a cohort of 20 individuals from 8 unrelated, consanguineous families. Variants segregated with a phenotype of mainly pure but also complex HSP consisting of global developmental delay, mild intellectual disability, motor dysfunction, and progressive spasticity. Patient-derived fibroblasts, neural stem cells (NSCs), and in vivo zebrafish modeling were used to investigate pathomechanisms, including initial preclinical therapy assessment. The absence of AMFR disturbs lipid homeostasis, causing lipid droplet accumulation in NSCs and patient-derived fibroblasts which is rescued upon AMFR re-expression. Electron microscopy indicates ER morphology alterations in the absence of AMFR. Similar findings are seen in amfra-/- zebrafish larvae, in addition to altered touch-evoked escape response and defects in motor neuron branching, phenocopying the HSP observed in patients. Interestingly, administration of FDA-approved statins improves touch-evoked escape response and motor neuron branching defects in amfra-/- zebrafish larvae, suggesting potential therapeutic implications. Our genetic and functional studies identify bi-allelic truncating variants in AMFR as a cause of a novel autosomal recessive HSP by altering lipid metabolism, which may potentially be therapeutically modulated using precision medicine with statins.

Context Maternal prepregnancy body mass index (BMI) has a strong influence on gestational metabolism, but detailed metabolic alterations are unknown. Objective First, to examine the associations of maternal prepregnancy BMI with maternal early-pregnancy metabolite alterations. Second, to identify an early-pregnancy metabolite profile associated with birthweight in women with a higher prepregnancy BMI that improved prediction of birthweight compared to glucose and lipid concentrations. Design, Setting, and Participants Prepregnancy BMI was obtained in a subgroup of 682 Dutch pregnant women from the Generation R prospective cohort study. Main Outcome Measures Maternal nonfasting targeted amino acids, nonesterified fatty acid, phospholipid, and carnitine concentrations measured in blood serum at mean gestational age of 12.8 weeks. Birthweight was obtained from medical records. Results A higher prepregnancy BMI was associated with 72 altered amino acids, nonesterified fatty acid, phospholipid and carnitine concentrations, and 6 metabolite ratios reflecting Krebs cycle, inflammatory, oxidative stress, and lipid metabolic processes (P-values Conclusions A higher maternal prepregnancy BMI was associated with altered maternal early-pregnancy amino acids, nonesterified fatty acids, phospholipids, and carnitines. Using these metabolites, we identified a maternal metabolite profile that improved prediction of birthweight in women with a higher prepregnancy BMI compared to glucose and lipid concentrations.

Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.

Oligosaccharidoses, sphingolipidoses and mucolipidoses are lysosomal storage disorders (LSDs) in which defective breakdown of glycan-side chains of glycosylated proteins and glycolipids leads to the accumulation of incompletely degraded oligosaccharides within lysosomes. In metabolic laboratories, these disorders are commonly diagnosed by thin-layer chromatography (TLC) but more recently also mass spectrometry-based approaches have been published. To expand the possibilities to screen for these diseases, we developed an ultra-high-performance liquid chromatography (UHPLC) with a high-resolution accurate mass (HRAM) mass spectrometry (MS) screening platform, together with an open-source iterative bioinformatics pipeline. This pipeline generates comprehensive biomarker profiles and allows for extensive quality control (QC) monitoring. Using this platform, we were able to identify α-mannosidosis, β-mannosidosis, α-N-acetylgalactosaminidase deficiency, sialidosis, galactosialidosis, fucosidosis, aspartylglucosaminuria, GM1 gangliosidosis, GM2 gangliosidosis (M. Sandhoff) and mucolipidosis II/III in patient samples. Aberrant urinary oligosaccharide excretions were also detected for other disorders, including NGLY1 congenital disorder of deglycosylation, sialic acid storage disease, MPS type IV B and GSD II (Pompe disease). For the latter disorder, we identified heptahexose (Hex7), as a potential urinary biomarker, in addition to glucose tetrasaccharide (Glc4), for the diagnosis and monitoring of young onset cases of Pompe disease. Occasionally, so-called “neonate” biomarker profiles were observed in young patients, which were probably due to nutrition. Our UHPLC/HRAM-MS screening platform can easily be adopted in biochemical laboratories and allows for simple and robust screening and straightforward interpretation of the screening results to detect disorders in which aberrant oligosaccharides accumulate.

External quality assurance (EQA) is crucial to monitor and improve the quality of biochemical genetic testing. ERNDIM (www.erndim.org), established in 1994, aims at reliable and standardized procedures for diagnosis, treatment and monitoring of inherited metabolic disease (IMD) by providing EQA schemes and educational activities. Currently, ERNDIM provides 16 different EQA schemes including quantitative schemes for various metabolite groups, and interpretive schemes such as diagnostic proficiency testing (DPT). DPT schemes focus on the ability of laboratories to correctly identify and interpret abnormalities in authentic urine samples across a wide range of IMDs. In the DPT schemes, six samples each year are distributed together with clinical information. Laboratories choose and perform the tests needed to reach a diagnosis. Data were collected on 345 samples, distributed to up to 105 laboratories worldwide. Diagnostic proficiency (the % of total points possible for all participating laboratories within a scheme for analysis and interpretation) ranged widely: amino acid disorders (n = 20), range 33%–100%, mean 84%; organic acid disorders (n = 35), range 14%–100%, mean 84%; lysosomal storage disorders (n = 13), range 20%–97%, mean 73%; purine/pyrimidine disorders (n = 9), range 37%–100%, mean 70%; miscellaneous disorders (n = 8), range 17%–100%, mean 65%; no IMD, range 65%–95%, mean 85%. When a sample with the same disorder was distributed in a subsequent survey, performance improved in 75 cases with no improvement seen in 32, suggesting overall improvement of performance. ERNDIM diagnostic proficiency testing is a valuable activity which can help to assess laboratory performance, identify methodological/technical challenges, be informative during quality audits and contribute to a better clinical appreciation of diagnostic uncertainty.

Background: Adaptations in maternal and foetal metabolic pathways may predispose to altered foetal growth and adverse birth outcomes. Objective: To assess the associations of maternal early-pregnancy metabolite profiles and infant metabolite profiles at birth with foetal growth from first trimester onwards and the odds of adverse birth outcomes. Methods: In a prospective population-based cohort among 976 Dutch pregnant women and their children, serum concentrations of amino acids, non-esterified fatty acids (NEFA), phospholipids (PL) and carnitines in maternal early-pregnancy blood and in cord blood were obtained by liquid-chromatography tandem mass spectrometry. Information on foetal growth was available from first trimester onwards. Results: After false discovery rate correction for multiple testing, higher infant total and individual NEFA concentrations were associated with a lower weight, length, and head circumference at birth. Higher infant total and individual acyl-lysophosphatidylcholine (lyso.PC.a) and alkyl-lysophosphatidylcholine concentrations were associated with higher weight and head circumference (lyso.PC.a only) at birth, higher odds of LGA and lower odds of SGA. Few individual maternal metabolites were associated with foetal growth measures in third trimester and at birth, but not with the odds of adverse birth outcomes. Conclusions: Our results suggest that infant metabolite profiles, particularly total and individual lyso.PC.a and NEFA concentrations, were strongly related to growth measures at birth and the odds of adverse birth outcomes. Few individual maternal early-pregnancy metabolites, but not total metabolite concentrations, are associated with foetal growth measures in third trimester and at birth.