Interobserver Agreement on Intracranial Hemorrhage on Magnetic Resonance Imaging in Patients With Ischemic Stroke.

BACKGROUND: The Heidelberg Bleeding Classification, developed for computed tomography, is also frequently used to classify intracranial hemorrhage (ICH) on magnetic resonance imaging. Additionally, the presence of any ICH is frequently used as (safety) outcome measure in clinical stroke trials that evaluate acute interventions. We assessed the interobserver agreement on the presence of any ICH and the type of ICH according to the Heidelberg Bleeding Classification on magnetic resonance imaging in patients treated with reperfusion therapy. METHODS: We used 300 magnetic resonance imaging scans including susceptibility-weighted imaging or T2*-weighted gradient echo imaging of ischemic stroke patients within 1 week after reperfusion therapy. Six observers, blinded to clinical characteristics except for suspected location of the infarction, independently rated ICH according to the Heidelberg Bleeding Classification in random pairs. Percent agreement and Cohen's kappa (κ) were estimated for the presence of any ICH (yes/no), and for agreement on the Heidelberg Bleeding Classification class 1 and 2. For the Heidelberg Bleeding Classification class 1 and 2, weighted κ was estimated to take the degree of disagreement into account. RESULTS: In 297 of 300 scans, the quality of scans was sufficient to score ICH. Observers agreed on the presence or absence of any ICH in 264 of 297 scans (88.9%; κ 0.78 [95% CI, 0.71-0.85]). There was agreement on the Heidelberg Bleeding Classification class 1 and 2 and no ICH in class 1 and 2 in 226 of 297 scans (76.1%; κ 0.63 [95% CI, 0.56-0.69]; weighted κ 0.90 [95% CI, 0.87-0.93]). CONCLUSIONS: The presence of any ICH can be reliably scored on magnetic resonance imaging and can, therefore, be used as (safety) outcome measure in clinical stroke trials that evaluate acute interventions. Agreement of ICH types according to the Heidelberg Bleeding Classification is substantial and disagreements are small.

Diagnosing, discarding, or de-VUSsing: A practical guide to (un)targeted metabolomics as variant-transcending functional tests.

PURPOSE: For patients with inherited metabolic disorders (IMDs), any diagnostic delay should be avoided because early initiation of personalized treatment could prevent irreversible health damage. To improve diagnostic interpretation of genetic data, gene function tests can be valuable assets. For IMDs, variant-transcending functional tests are readily available through (un)targeted metabolomics assays. To support the application of metabolomics for this purpose, we developed a gene-based guide to select functional tests to either confirm or exclude an IMD diagnosis. METHODS: Using information from a diagnostic IMD exome panel, Kyoto Encyclopedia of Genes and Genomes, and Inborn Errors of Metabolism Knowledgebase, we compiled a guide for metabolomics-based gene function tests. From our practical experience with this guide, we retrospectively selected illustrative cases for whom combined metabolomic/genomic testing improved diagnostic success and evaluated the effect hereof on clinical management. RESULTS: The guide contains 2047 metabolism-associated genes for which a validated or putative variant-transcending gene function test is available. We present 16 patients for whom metabolomic testing either confirmed or ruled out the presence of a second pathogenic variant, validated or ruled out pathogenicity of variants of uncertain significance, or identified a diagnosis initially missed by genetic analysis. CONCLUSION: Metabolomics-based gene function tests provide additional value in the diagnostic trajectory of patients with suspected IMD by enhancing and accelerating diagnostic success.

Comparison of diffusion weighted imaging b0 with T2*-weighted gradient echo or susceptibility weighted imaging for intracranial hemorrhage detection after reperfusion therapy for ischemic stroke.

PURPOSE: Diffusion-weighted imaging (DWI) b0 may be able to substitute T2*-weighted gradient echo (GRE) or susceptibility-weighted imaging (SWI) in case of comparable detection of intracranial hemorrhage (ICH), thereby reducing MRI examination time. We evaluated the diagnostic accuracy of DWI b0 compared to T2*GRE or SWI for detection of ICH after reperfusion therapy for ischemic stroke. METHODS: We pooled 300 follow-up MRI scans acquired within 1 week after reperfusion therapy. Six neuroradiologists each rated DWI images (b0 and b1000; b0 as index test) of 100 patients and, after a minimum of 4 weeks, T2*GRE or SWI images (reference standard) paired with DWI images of the same patients. Readers assessed the presence of ICH (yes/no) and type of ICH according to the Heidelberg Bleeding Classification. We determined the sensitivity and specificity of DWI b0 for detection of any ICH, and the sensitivity for detection of hemorrhagic infarction (HI1 & HI2) and parenchymal hematoma (PH1 & PH2). RESULTS: We analyzed 277 scans of ischemic stroke patients with complete image series and sufficient image quality (median age 65 years [interquartile range, 54-75], 158 [57%] men). For detection of any ICH on DWI b0, the sensitivity was 62% (95% CI: 50-76) and specificity 96% (95% CI: 93-99). The sensitivity of DWI b0 was 52% (95% CI: 28-68) for detection of hemorrhagic infarction and 84% (95% CI: 70-92) for parenchymal hematoma. CONCLUSION: DWI b0 is inferior for detection of ICH compared to T2*GRE/SWI, especially for smaller and more subtle hemorrhages. Follow-up MRI protocols should include T2*GRE/SWI for detection of ICH after reperfusion therapy.

Bi-allelic GOT2 Mutations Cause a Treatable Malate-Aspartate Shuttle-Related Encephalopathy.

Early-infantile encephalopathies with epilepsy are devastating conditions mandating an accurate diagnosis to guide proper management. Whole-exome sequencing was used to investigate the disease etiology in four children from independent families with intellectual disability and epilepsy, revealing bi-allelic GOT2 mutations. In-depth metabolic studies in individual 1 showed low plasma serine, hypercitrullinemia, hyperlactatemia, and hyperammonemia. The epilepsy was serine and pyridoxine responsive. Functional consequences of observed mutations were tested by measuring enzyme activity and by cell and animal models. Zebrafish and mouse models were used to validate brain developmental and functional defects and to test therapeutic strategies. GOT2 encodes the mitochondrial glutamate oxaloacetate transaminase. GOT2 enzyme activity was deficient in fibroblasts with bi-allelic mutations. GOT2, a member of the malate-aspartate shuttle, plays an essential role in the intracellular NAD(H) redox balance. De novo serine biosynthesis was impaired in fibroblasts with GOT2 mutations and GOT2-knockout HEK293 cells. Correcting the highly oxidized cytosolic NAD-redox state by pyruvate supplementation restored serine biosynthesis in GOT2-deficient cells. Knockdown of got2a in zebrafish resulted in a brain developmental defect associated with seizure-like electroencephalography spikes, which could be rescued by supplying pyridoxine in embryo water. Both pyridoxine and serine synergistically rescued embryonic developmental defects in zebrafish got2a morphants. The two treated individuals reacted favorably to their treatment. Our data provide a mechanistic basis for the biochemical abnormalities in GOT2 deficiency that may also hold for other MAS defects.

Metabolite Identification Using Infrared Ion Spectroscopy─Novel Biomarkers for Pyridoxine-Dependent Epilepsy.

Untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics strategies are being increasingly applied in metabolite screening for a wide variety of medical conditions. The long-standing "grand challenge" in the utilization of this approach is metabolite identification─confidently determining the chemical structures of m/z-detected unknowns. Here, we use a novel workflow based on the detection of molecular features of interest by high-throughput untargeted LC-MS analysis of patient body fluids combined with targeted molecular identification of those features using infrared ion spectroscopy (IRIS), effectively providing diagnostic IR fingerprints for mass-isolated targets. A significant advantage of this approach is that in silico-predicted IR spectra of candidate chemical structures can be used to suggest the molecular structure of unknown features, thus mitigating the need for the synthesis of a broad range of physical reference standards. Pyridoxine-dependent epilepsy (PDE-ALDH7A1) is an inborn error of lysine metabolism, resulting from a mutation in the ALDH7A1 gene that leads to an accumulation of toxic levels of α-aminoadipic semialdehyde (α-AASA), piperideine-6-carboxylate (P6C), and pipecolic acid in body fluids. While α-AASA and P6C are known biomarkers for PDE in urine, their instability makes them poor candidates for diagnostic analysis from blood, which would be required for application in newborn screening protocols. Here, we use combined untargeted metabolomics-IRIS to identify several new biomarkers for PDE-ALDH7A1 that can be used for diagnostic analysis in urine, plasma, and cerebrospinal fluids and that are compatible with analysis in dried blood spots for newborn screening. The identification of these novel metabolites has directly provided novel insights into the pathophysiology of PDE-ALDH7A1.

The role of clinical response to treatment in determining pathogenicity of genomic variants.

PURPOSE: The 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for the interpretation of sequence variants provide a framework to standardize terminology in the classification of variants uncovered through genetic testing. We aimed to assess the validity of utilizing clinical response to therapies specifically targeted to a suspected disease in clarifying variant pathogenicity. METHODS: Five families with disparate clinical presentations and different genetic diseases evaluated and treated in multiple diagnostic settings are summarized. RESULTS: Extended evaluations indicated possible genetic diagnoses and assigned candidate causal variants, but the cumulative clinical, biochemical, and molecular information in each instance was not completely consistent with the identified disease. Initiation of treatment specific to the suspected diagnoses in the affected individuals led to clinical improvement in all five families. CONCLUSION: We propose that the effect of therapies that are specific and targeted to treatable genetic diseases embodies an in vivo physiological response and could be considered as additional criteria within the 2015 ACMG/AMP guidelines in determining genomic variant pathogenicity.

A comparison of high-throughput plasma NMR protocols for comparative untargeted metabolomics.

INTRODUCTION: When analyzing the human plasma metabolome with Nuclear Magnetic Resonance (NMR) spectroscopy, the Carr-Purcell-Meiboom-Gill (CPMG) experiment is commonly employed for large studies. However, this process can lead to compromised statistical analyses due to residual macromolecule signals. In addition, the utilization of Trimethylsilylpropanoic acid (TSP) as an internal standard often leads to quantification issues, and binning, as a spectral summarization step, can result in features not clearly assignable to metabolites. OBJECTIVES: Our aim was to establish a new complete protocol for large plasma cohorts collected with the purpose of describing the comparative metabolic profile of groups of samples. METHODS: We compared the conventional CPMG approach to a novel procedure that involves diffusion NMR, using the Longitudinal Eddy-Current Delay (LED) experiment, maleic acid (MA) as the quantification reference and peak picking for spectral reduction. This comparison was carried out using the ultrafiltration method as a gold standard in a simple sample classification experiment, with Partial Least Squares-Discriminant Analysis (PLS-DA) and the resulting metabolic signatures for multivariate data analysis. In addition, the quantification capabilities of the method were evaluated. RESULTS: We found that the LED method applied was able to detect more metabolites than CPMG and suppress macromolecule signals more efficiently. The complete protocol was able to yield PLS-DA models with enhanced classification accuracy as well as a more reliable set of important features than the conventional CPMG approach. Assessment of the quantitative capabilities of the method resulted in good linearity, recovery and agreement with an established amino acid assay for the majority of the metabolites tested. Regarding repeatability, ~ 85% of all peaks had an adequately low coefficient of variation (< 30%) in replicate samples. CONCLUSION: Overall, our comparison yielded a high-throughput untargeted plasma NMR protocol for optimized data acquisition and processing that is expected to be a valuable contribution in the field of metabolic biomarker discovery.

Correction to: A comparison of high­throughput plasma NMR protocols for comparative untargeted metabolomics.

Following publication of the original article, the authors would like to correct a sentence in the paragraph "1H-NMR spectra were recorded at 298 K…" under the heading "NMR experiments".

Exome Sequencing and the Management of Neurometabolic Disorders.

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.).

The genotypic and phenotypic spectrum of MTO1 deficiency.

BACKGROUND: Mitochondrial diseases, a group of multi-systemic disorders often characterized by tissue-specific phenotypes, are usually progressive and fatal disorders resulting from defects in oxidative phosphorylation. MTO1 (Mitochondrial tRNA Translation Optimization 1), an evolutionarily conserved protein expressed in high-energy demand tissues has been linked to human early-onset combined oxidative phosphorylation deficiency associated with hypertrophic cardiomyopathy, often referred to as combined oxidative phosphorylation deficiency-10 (COXPD10). MATERIAL AND METHODS: Thirty five cases of MTO1 deficiency were identified and reviewed through international collaboration. The cases of two female siblings, who presented at 1 and 2years of life with seizures, global developmental delay, hypotonia, elevated lactate and complex I and IV deficiency on muscle biopsy but without cardiomyopathy, are presented in detail. RESULTS: For the description of phenotypic features, the denominator varies as the literature was insufficient to allow for complete ascertainment of all data for the 35 cases. An extensive review of all known MTO1 deficiency cases revealed the most common features at presentation to be lactic acidosis (LA) (21/34; 62% cases) and hypertrophic cardiomyopathy (15/34; 44% cases). Eventually lactic acidosis and hypertrophic cardiomyopathy are described in 35/35 (100%) and 27/34 (79%) of patients with MTO1 deficiency, respectively; with global developmental delay/intellectual disability present in 28/29 (97%), feeding difficulties in 17/35 (49%), failure to thrive in 12/35 (34%), seizures in 12/35 (34%), optic atrophy in 11/21 (52%) and ataxia in 7/34 (21%). There are 19 different pathogenic MTO1 variants identified in these 35 cases: one splice-site, 3 frameshift and 15 missense variants. None have bi-allelic variants that completely inactivate MTO1; however, patients where one variant is truncating (i.e. frameshift) while the second one is a missense appear to have a more severe, even fatal, phenotype. These data suggest that complete loss of MTO1 is not viable. A ketogenic diet may have exerted a favourable effect on seizures in 2/5 patients. CONCLUSION: MTO1 deficiency is lethal in some but not all cases, and a genotype-phenotype relation is suggested. Aside from lactic acidosis and cardiomyopathy, developmental delay and other phenotypic features affecting multiple organ systems are often present in these patients, suggesting a broader spectrum than hitherto reported. The diagnosis should be suspected on clinical features and the presence of markers of mitochondrial dysfunction in body fluids, especially low residual complex I, III and IV activity in muscle. Molecular confirmation is required and targeted genomic testing may be the most efficient approach. Although subjective clinical improvement was observed in a small number of patients on therapies such as ketogenic diet and dichloroacetate, no evidence-based effective therapy exists.

Unraveling the unknown areas of the human metabolome: the role of infrared ion spectroscopy.

The identification of molecular biomarkers is critical for diagnosing and treating patients and for establishing a fundamental understanding of the pathophysiology and underlying biochemistry of inborn errors of metabolism. Currently, liquid chromatography/high-resolution mass spectrometry and nuclear magnetic resonance spectroscopy are the principle methods used for biomarker research and for structural elucidation of small molecules in patient body fluids. While both are powerful techniques, several limitations exist that often make the identification of unknown compounds challenging. Here, we describe how infrared ion spectroscopy has the potential to be a valuable orthogonal technique that provides highly-specific molecular structure information while maintaining ultra-high sensitivity. Here, we characterize and distinguish two well-known biomarkers of inborn errors of metabolism, glutaric acid for glutaric aciduria and ethylmalonic acid for short-chain acyl-CoA dehydrogenase deficiency, using infrared ion spectroscopy. In contrast to tandem mass spectra, in which ion fragments can hardly be predicted, we show that the prediction of an IR spectrum allows reference-free identification in the case that standard compounds are either commercially or synthetically unavailable. Finally, we illustrate how functional group information can be obtained from an IR spectrum for an unknown and how this is valuable information to, for example, narrow down a list of candidate structures resulting from a database query. Early diagnosis in inborn errors of metabolism is crucial for enabling treatment and depends on the identification of biomarkers specific for the disorder. Infrared ion spectroscopy has the potential to play a pivotal role in the identification of challenging biomarkers.

Autism spectrum disorder: an early and frequent feature in cerebrotendinous xanthomatosis.

BACKGROUND: Cerebrotendinous xanthomatosis (CTX) is an autosomal recessively inherited inborn error of metabolism (IEM) due to mutations in the CYP27A1 gene. The clinical picture ranges from being nearly asymptomatic in early childhood, up to severe disability at adult age. Infantile-onset diarrhea and juvenile-onset cataract are the earliest symptoms in childhood. In the current study, we evaluated the presence of autism spectrum disorder (ASD) in a large cohort of CTX patients. METHODS: We performed a retrospective patient file study in 77 genetically confirmed Dutch CTX patients to determine the frequency of ASD. In addition, we compared plasma cholestanol levels in CTX patients with and without a diagnosis of ASD and tried to establish a relation between CYP27A1 genotype and ASD. RESULTS: In our CTX cohort, 10 patients (13%; nine pediatric and one adult) with ASD were identified. At the time of diagnosis of ASD, most patients only exhibited symptoms of diarrhea and/or intellectual disability without signs of cataract or neurological symptoms. No correlation was found between the presence of ASD and the level of cholestanol or CYP27A1 genotype. The behavioral problems stabilized or improved after treatment initiation with chenodeoxycholic acid (CDCA) in all pediatric patients. CONCLUSIONS: We conclude that ASD is an early and probably underestimated frequent feature in CTX. Metabolic screening for CTX should be performed in patients with ASD when accompanied by diarrhea, intellectual disability, juvenile cataract, and/or neurological involvement. Early recognition allows for earlier initiation of specific treatment and will improve clinical outcome. Our results add CTX to the list of treatable IEMs associated with ASD.

Fast and accurate quantitative organic acid analysis with LC-QTOF/MS facilitates screening of patients for inborn errors of metabolism.

Since organic acid analysis in urine with gaschromatography-mass spectrometry (GC-MS) is a time-consuming technique, we developed a new liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) method to replace the classical analysis for diagnosis of inborn errors of metabolism (IEM). Sample preparation is simple and experimental time short. Targeted mass extraction and automatic calculation of z-scores generated profiles characteristic for the IEMs in our panel consisting of 71 biomarkers for defects in amino acids, neurotransmitters, fatty acids, purine, and pyrimidine metabolism as well as other disorders. In addition, four medication-related metabolites were included in the panel. The method was validated to meet Dutch NEN-EN-ISO 15189 standards. Cross validation of 24 organic acids from 28 urine samples of the ERNDIM scheme showed superiority of the UPLC-QTOF/MS method over the GC-MS method. We applied our method to 99 patient urine samples with 32 different IEMs, and 88 control samples. All IEMs were unambiguously established/diagnosed using this new QTOF method by evaluation of the panel of 71 biomarkers. In conclusion, we present a LC-QTOF/MS method for fast and accurate quantitative organic acid analysis which facilitates screening of patients for IEMs. Extension of the panel of metabolites is easy which makes this application a promising technique in metabolic diagnostics/laboratories.

Structural elucidation of novel biomarkers of known metabolic disorders based on multistage fragmentation mass spectra.

Specific diagnostic markers are the key to effective diagnosis and treatment of inborn errors of metabolism (IEM). Untargeted metabolomics allows for the identification of potential novel diagnostic biomarkers. Current separation techniques coupled to high-resolution mass spectrometry provide a powerful tool for structural elucidation of unknown compounds in complex biological matrices. This is a proof-of-concept study testing this methodology to determine the molecular structure of as yet uncharacterized m/z signals that were significantly increased in plasma samples from patients with phenylketonuria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. A hybrid linear ion trap-orbitrap high resolution mass spectrometer, capable of multistage fragmentation, was used to acquire accurate masses and product ion spectra of the uncharacterized m/z signals. In order to determine the molecular structures, spectral databases were searched and fragmentation prediction software was used. This approach enabled structural elucidation of novel compounds potentially useful as biomarkers in diagnostics and follow-up of IEM patients. Two new conjugates, glutamyl-glutamyl-phenylalanine and phenylalanine-hexose, were identified in plasma of phenylketonuria patients. These novel markers showed high inter-patient variation and did not correlate to phenylalanine levels, illustrating their potential added value for follow-up. As novel biomarkers for 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, three positional isomers of 3-methylglutaconyl carnitine could be detected in patient plasma. Our results highlight the applicability of current accurate mass multistage fragmentation techniques for structural elucidation of unknown metabolites in human biofluids, offering an unprecedented opportunity to gain further biochemical insights in known inborn errors of metabolism by enabling high confidence identification of novel biomarkers.

Integration of genomics and metabolomics for prioritization of rare disease variants: a 2018 literature review.

Many inborn errors of metabolism (IEMs) are amenable to treatment; therefore, early diagnosis and treatment is imperative. Despite recent advances, the genetic basis of many metabolic phenotypes remains unknown. For discovery purposes, whole exome sequencing (WES) variant prioritization coupled with clinical and bioinformatics expertise is the primary method used to identify novel disease-causing variants; however, causation is often difficult to establish due to the number of plausible variants. Integrated analysis of untargeted metabolomics (UM) and WES or whole genome sequencing (WGS) data is a promising systematic approach for identifying disease-causing variants. In this review, we provide a literature-based overview of UM methods utilizing liquid chromatography mass spectrometry (LC-MS), and assess approaches to integrating WES/WGS and LC-MS UM data for the discovery and prioritization of variants causing IEMs. To embed this integrated -omics approach in the clinic, expansion of gene-metabolite annotations and metabolomic feature-to-metabolite mapping methods are needed.

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.

Mild orotic aciduria in UMPS heterozygotes: a metabolic finding without clinical consequences.

BACKGROUND: Elevated urinary excretion of orotic acid is associated with treatable disorders of the urea cycle and pyrimidine metabolism. Establishing the correct and timely diagnosis in a patient with orotic aciduria is key to effective treatment. Uridine monophosphate synthase is involved in de novo pyrimidine synthesis. Uridine monophosphate synthase deficiency (or hereditary orotic aciduria), due to biallelic mutations in UMPS, is a rare condition presenting with megaloblastic anemia in the first months of life. If not treated with the pyrimidine precursor uridine, neutropenia, failure to thrive, growth retardation, developmental delay, and intellectual disability may ensue. METHODS AND RESULTS: We identified mild and isolated orotic aciduria in 11 unrelated individuals with diverse clinical signs and symptoms, the most common denominator being intellectual disability/developmental delay. Of note, none had blood count abnormalities, relevant hyperammonemia or altered plasma amino acid profile. All individuals were found to have heterozygous alterations in UMPS. Four of these variants were predicted to be null alleles with complete loss of function. The remaining variants were missense changes and predicted to be damaging to the normal encoded protein. Interestingly, family screening revealed heterozygous UMPS variants in combination with mild orotic aciduria in 19 clinically asymptomatic family members. CONCLUSIONS: We therefore conclude that heterozygous UMPS-mutations can lead to mild and isolated orotic aciduria without clinical consequence. Partial UMPS-deficiency should be included in the differential diagnosis of mild orotic aciduria. The discovery of heterozygotes manifesting clinical symptoms such as hypotonia and developmental delay are likely due to ascertainment bias.

Expanding the phenotype in aminoacylase 1 (ACY1) deficiency: characterization of the molecular defect in a 63-year-old woman with generalized dystonia.

Aminoacylase 1 (ACY1) deficiency is an organic aciduria due to mutations in the ACY1 gene. It is considered much underdiagnosed. Most individuals known to be affected by ACY1 deficiency have presented with neurologic symptoms. We report here a cognitively normal 63-year-old woman who around the age of 12 years had developed dystonic symptoms that gradually evolved into generalized dystonia. Extensive investigations, including metabolic diagnostics and diagnostic exome sequencing, were performed to elucidate the cause of dystonia. Findings were only compatible with a diagnosis of ACY1 deficiency: the urinary metabolite pattern with N-acetylated amino acids was characteristic, there was decreased ACY1 activity in immortalized lymphocytes, and two compound heterozygous ACY1 mutations were detected, one well-characterized c.1057C>T (p.Arg353Cys) and the other novel c.325A>G (p.Arg109Gly). Expression analysis in HEK293 cells revealed high residual activity of the enzyme with the latter mutation. However, following co-transfection of cells with stable expression of the c.1057C>T variant with either wild-type ACY1 or the c.325A>G mutant, only the wild-type enhanced ACY1 activity and ACY1 presence in the Western blot, suggesting an inhibiting interference between the two variants. Our report extends the clinical spectrum of ACY1 deficiency to include dystonia and indicates that screening for organic acidurias deserves consideration in patients with unexplained generalized dystonia.