Integrating Genome Sequencing and Untargeted Metabolomics in Monozygotic Twins with a Rare Complex Neurological Disorder.

Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools in the diagnosis of rare diseases. We used untargeted metabolomics and whole-genome sequencing (WGS) to gain a more comprehensive understanding of a rare disease with a complex presentation affecting female twins from a consanguineous family. The sisters presented with polymicrogyria, a Dandy-Walker malformation, respiratory distress, and multiorgan dysfunctions. Through WGS, we identified two rare homozygous variants in both subjects, a pathogenic variant in ADGRG1(p.Arg565Trp) and a novel variant in CNTNAP1(p.Glu910Val). These genes have been previously associated with autosomal recessive polymicrogyria and hypomyelinating neuropathy with/without contractures, respectively. The twins exhibited symptoms that overlapped with both of these conditions. The results of the untargeted metabolomics analysis revealed significant metabolic perturbations relating to neurodevelopmental abnormalities, kidney dysfunction, and microbiome. The significant metabolites belong to essential pathways such as lipids and amino acid metabolism. The identification of variants in two genes, combined with the support of metabolic perturbation, demonstrates the rarity and complexity of this phenotype and provides valuable insights into its underlying mechanisms.

A Case Study of Dysfunctional Nicotinamide Metabolism in a 20-Year-Old Male.

We present a case study of a 20-year-old male with an unknown neurodegenerative disease who was referred to the Undiagnosed Diseases Network Vanderbilt Medical Center site. A previous metabolic panel showed that the patient had a critical deficiency in nicotinamide intermediates that are generated during the biosynthesis of NAD(H). We followed up on these findings by evaluating the patient's ability to metabolize nicotinamide. We performed a global metabolic profiling analysis of plasma samples that were collected: (1) under normal fed conditions (baseline), (2) after the patient had fasted, and (3) after he was challenged with a 500 mg nasogastric tube bolus of nicotinamide following the fast. Our findings showed that the patient's nicotinamide N-methyltransferase (NNMT), a key enzyme in NAD(H) biosynthesis and methionine metabolism, was not functional under normal fed or fasting conditions but was restored in response to the nicotinamide challenge. Altered levels of metabolites situated downstream of NNMT and in neighboring biochemical pathways provided further evidence of a baseline defect in NNMT activity. To date, this is the only report of a critical defect in NNMT activity manifesting in adulthood and leading to neurodegenerative disease. Altogether, this study serves as an important reference in the rare disease literature and also demonstrates the utility of metabolomics as a diagnostic tool for uncharacterized metabolic diseases.

Comparison of Untargeted Metabolomic Profiling vs Traditional Metabolic Screening to Identify Inborn Errors of Metabolism.

Importance: Recent advances in newborn screening (NBS) have improved the diagnosis of inborn errors of metabolism (IEMs); however, many potentially treatable IEMs are not included on NBS panels, nor are they covered in standard, first-line biochemical testing. Objective: To examine the utility of untargeted metabolomics as a primary screening tool for IEMs by comparing the diagnostic rate of clinical metabolomics with the recommended traditional metabolic screening approach. Design, Setting, and Participants: This cross-sectional study compares data from 4464 clinical samples received from 1483 unrelated families referred for trio testing of plasma amino acids, plasma acylcarnitine profiling, and urine organic acids (June 2014 to October 2018) and 2000 consecutive plasma samples from 1807 unrelated families (July 2014 to February 2019) received for clinical metabolomic screening at a College of American Pathologists and Clinical Laboratory Improvement Amendments-certified biochemical genetics laboratory. Data analysis was performed from September 2019 to August 2020. Exposures: Metabolic and molecular tests performed at a genetic testing reference laboratory in the US and available clinical information for each patient were assessed to determine diagnostic rate. Main Outcomes and Measures: The diagnostic rate of traditional metabolic screening compared with clinical metabolomic profiling was assessed in the context of expanded NBS. Results: Of 1483 cases screened by the traditional approach, 912 patients (61.5%) were male and 1465 (98.8%) were pediatric (mean [SD] age, 4.1 [6.0] years; range, 0-65 years). A total of 19 families were identified with IEMs, resulting in a 1.3% diagnostic rate. A total of 14 IEMs were detected, including 3 conditions not included in the Recommended Uniform Screening Panel for NBS. Of the 1807 unrelated families undergoing plasma metabolomic profiling, 1059 patients (58.6%) were male, and 1665 (92.1%) were pediatric (mean [SD] age, 8.1 [10.4] years; range, 0-80 years). Screening identified 128 unique cases with IEMs, giving an overall diagnostic rate of 7.1%. In total, 70 different metabolic conditions were identified, including 49 conditions not presently included on the Recommended Uniform Screening Panel for NBS. Conclusions and Relevance: These findings suggest that untargeted metabolomics provided a 6-fold higher diagnostic yield compared with the conventional screening approach and identified a broader spectrum of IEMs. Notably, with the expansion of NBS programs, traditional metabolic testing approaches identify few disorders beyond those covered on the NBS. These data support the capability of clinical untargeted metabolomics in screening for IEMs and suggest that broader screening approaches should be considered in the initial evaluation for metabolic disorders.

Global biochemical analysis of plasma, serum and whole blood collected using various anticoagulant additives.

INTRODUCTION: Analysis of blood for the evaluation of clinically relevant biomarkers requires precise collection and sample handling by phlebotomists and laboratory staff. An important consideration for the clinical application of metabolomics are the different anticoagulants utilized for sample collection. Most studies that have characterized differences in metabolite levels in various blood collection tubes have focused on single analytes. We define analyte levels on a global metabolomics platform following blood sampling using five different, but commonly used, clinical laboratory blood collection tubes (i.e., plasma anticoagulated with either EDTA, lithium heparin or sodium citrate, along with no additive (serum), and EDTA anticoagulated whole blood). METHODS: Using an untargeted metabolomics platform we analyzed five sample types after all had been collected and stored at -80°C. The biochemical composition was determined and differences between the samples established using matched-pair t-tests. RESULTS: We identified 1,117 biochemicals across all samples and detected a mean of 1,036 in the sample groups. Compared to the levels of metabolites in EDTA plasma, the number of biochemicals present at statistically significant different levels (p<0.05) ranged from 452 (serum) to 917 (whole blood). Several metabolites linked to screening assays for rare diseases including acylcarnitines, bilirubin and heme metabolites, nucleosides, and redox balance metabolites varied significantly across the sample collection types. CONCLUSIONS: Our study highlights the widespread effects and importance of using consistent additives for assessing small molecule levels in clinical metabolomics. The biochemistry that occurs during the blood collection process creates a reproducible signal that can identify specimens collected with different anticoagulants in metabolomic studies. IMPACT STATEMENT: In this manuscript, normal/healthy donors had peripheral blood collected using multiple anticoagulants as well as serum during a fasted blood draw. Global metabolomics is a new technology being utilized to draw clinical conclusions and we interrogated the effects of different anticoagulants on the levels of biochemicals from each of the donors. Characterizing the effects of the anticoagulants on biochemical levels will help researchers leverage the information using global metabolomics in order to make conclusions regarding important disease biomarkers.

Assessment of the effects of repeated freeze thawing and extended bench top processing of plasma samples using untargeted metabolomics.

INTRODUCTION: Clinical metabolomics has utility as a screen for inborn errors of metabolism (IEM) and variant classification in patients with rare disease. It is important to understand and characterize preanalytical factors that influence assay performance during patient sample testing. OBJECTIVES: To evaluate the impact of extended thawing of human EDTA plasma samples on ice prior to extraction as well as repeated freeze-thaw cycling of samples to identify compounds that are unstable prior to metabolomic analysis. METHODS: Twenty-four (24) donor EDTA plasma samples were collected and immediately frozen at - 80 °C. Twelve samples were thawed on ice and extracted for analysis at time 0, 2, 4, and 6 h. Twelve other donor samples were repeatedly thawed and frozen up to four times and analyzed at each cycle. Compound levels at each time point/freeze-thaw cycle were compared to the control samples using matched-paired t tests to identify analytes affected by each condition. RESULTS: We identified 1026 biochemicals across all samples. Incubation of thawed EDTA plasma samples on ice for up to 6 h resulted in < 1% of biochemicals changing significantly. Freeze-thaw cycles affected a greater percentage of the metabolome; ~ 2% of biochemicals changed after 3 freeze-thaw cycles. CONCLUSIONS: Our study highlights that the number and magnitude of these changes are not as widespread as other aspects of improper sample handling. In total, < 3% of the metabolome detected on our clinical metabolomics platform should be disqualified when multiple freeze-thaw cycles or extended thawing at 4 °C are performed on a given sample.

Untargeted metabolomics as an unbiased approach to the diagnosis of inborn errors of metabolism of the non-oxidative branch of the pentose phosphate pathway.

Inborn errors of metabolism (IEM) involving the non-oxidative pentose phosphate pathway (PPP) include the two relatively rare conditions, transketolase deficiency and transaldolase deficiency, both of which can be difficult to diagnosis given their non-specific clinical presentations. Current biochemical testing approaches require an index of suspicion to consider targeted urine polyol testing. To determine whether a broad-spectrum biochemical test could accurately identify a specific metabolic pattern defining IEMs of the non-oxidative PPP, we employed the use of clinical metabolomic profiling as an unbiased novel approach to diagnosis. Subjects with molecularly confirmed IEMs of the PPP were included in this study. Targeted quantitative analysis of polyols in urine and plasma samples was accomplished with chromatography and mass spectrometry. Semi-quantitative unbiased metabolomic analysis of urine and plasma samples was achieved by assessing small molecules via liquid chromatography and high-resolution mass spectrometry. Results from untargeted and targeted analyses were then compared and analyzed for diagnostic acuity. Two siblings with transketolase (TKT) deficiency and three unrelated individuals with transaldolase (TALDO) deficiency were identified for inclusion in the study. For both IEMs, targeted polyol testing and untargeted metabolomic testing on urine and/or plasma samples identified typical perturbations of the respective disorder. Additionally, untargeted metabolomic testing revealed elevations in other PPP metabolites not typically measured with targeted polyol testing, including ribonate, ribose, and erythronate for TKT deficiency and ribonate, erythronate, and sedoheptulose 7-phosphate in TALDO deficiency. Non-PPP alternations were also noted involving tryptophan, purine, and pyrimidine metabolism for both TKT and TALDO deficient patients. Targeted polyol testing and untargeted metabolomic testing methods were both able to identify specific biochemical patterns indicative of TKT and TALDO deficiency in both plasma and urine samples. In addition, untargeted metabolomics was able to identify novel biomarkers, thereby expanding the current knowledge of both conditions and providing further insight into potential underlying pathophysiological mechanisms. Furthermore, untargeted metabolomic testing offers the advantage of having a single effective biochemical screening test for identification of rare IEMs, like TKT and TALDO deficiencies, that may otherwise go undiagnosed due to their generally non-specific clinical presentations.

Precision of a Clinical Metabolomics Profiling Platform for Use in the Identification of Inborn Errors of Metabolism.

BACKGROUND: The application of whole-exome sequencing for the diagnosis of genetic disease has paved the way for systems-based approaches in the clinical laboratory. Here, we describe a clinical metabolomics method for the screening of metabolic diseases through the analysis of a multi-pronged mass spectrometry platform. By simultaneously measuring hundreds of metabolites in a single sample, clinical metabolomics offers a comprehensive approach to identify metabolic perturbations across multiple biochemical pathways. METHODS: We conducted a single- and multi-day precision study on hundreds of metabolites in human plasma on 4, multi-arm, high-throughput metabolomics platforms. RESULTS: The average laboratory coefficient of variation (CV) on the 4 platforms was between 9.3 and 11.5% (median, 6.5-8.4%), average inter-assay CV on the 4 platforms ranged from 9.9 to 12.6% (median, 7.0-8.3%) and average intra-assay CV on the 4 platforms ranged from 5.7 to 6.9% (median, 3.5-4.4%). In relation to patient sample testing, the precision of multiple biomarkers associated with IEM disorders showed CVs that ranged from 0.2 to 11.0% across 4 analytical batches. CONCLUSIONS: This evaluation describes single and multi-day precision across 4 identical metabolomics platforms, comprised each of 4 independent method arms, and reproducibility of the method for the measurement of key IEM metabolites in patient samples across multiple analytical batches, providing evidence that the method is robust and reproducible for the screening of patients with inborn errors of metabolism.

Digital Microfluidic Platform to Maximize Diagnostic Tests with Low Sample Volumes from Newborns and Pediatric Patients.

"Children are not tiny adults" is an adage commonly used in pediatrics to emphasize the fact that children often have different physiological responses to sickness and trauma compared to adults. However, despite widespread acceptance of this concept, diagnostic blood testing is an excellent example of clinical care that is not yet customized to the needs of children, especially newborns. Cumulative blood loss resulting from clinical testing does not typically impact critically ill adult patients, but can quickly escalate in children, leading to iatrogenic anemia and related comorbidities. Moreover, the tests prioritized for rapid, near-patient testing in adults are not always the most clinically relevant tests for children or newborns. This report describes the development of a digital microfluidic testing platform and associated clinical assays purposely curated to address current shortcomings in pediatric laboratory testing by using microliter volumes (<50 µL) of samples. The automated platform consists of a small instrument and single-use cartridges, which contain all reagents necessary to prepare the sample and perform the assay. Electrowetting technology is used to precisely manipulate nanoliter-sized droplets of samples and reagents inside the cartridge. To date, we have automated three disparate types of assays (biochemical assays, immunoassays, and molecular assays) on the platform and have developed over two dozen unique tests, each with important clinical application to newborns and pediatric patients. Cell lysis, plasma preparation, magnetic bead washing, thermocycling, incubation, and many other essential functions were all performed on the cartridge without any user intervention. The resulting assays demonstrate performance comparable to standard clinical laboratory assays and are economical due to the reduced hands-on effort required for each assay and lower overall reagent consumption. These capabilities allow a wide range of assays to be run simultaneously on the same cartridge using significantly reduced sample volumes with results in minutes.

2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis.

Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in ABAT and resulting in accumulation of GABA in the cerebrospinal fluid (CSF). For that reason, measurement of GABA in CSF is currently the primary approach to diagnosis. GABA-transaminase deficiency results in severe developmental delay with intellectual disability, seizures, and movement disorder, and is often associated with death in childhood. Using an untargeted metabolomics platform, we analyzed EDTA plasma, urine, and CSF specimens from four individuals with GABA-transaminase deficiency to identify biomarkers by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. Metabolomic analyses of over 1,000 clinical plasma samples revealed a rich source of biochemical information. Three out of four patients showed significantly elevated levels of the molecule 2-pyrrolidinone (Z-score ≥2) in plasma, and whole exome sequencing revealed variants of uncertain significance in ABAT. Additionally, these same patients also had elevated levels of succinimide in plasma, urine, and CSF and/or homocarnosine in urine and CSF. In the analysis of clinical EDTA plasma samples, the levels of succinimide and 2-pyrrolidinone showed a high level of correlation (R = 0.73), indicating impairment in GABA metabolism and further supporting the association with GABA-transaminase deficiency and the pathogenicity of the ABAT variants. Further analysis of metabolomic data across our patient population revealed the association of elevated levels of 2-pyrrolidinone with administration of vigabatrin, a commonly used anti-seizure medication and a known inhibitor of GABA-transaminase. These data indicate that anti-seizure medications may alter the biochemical and metabolomic data, potentially impacting the interpretation and diagnosis for the patient. Further, these data demonstrate the power of combining broad scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and support the use of metabolic phenotyping of plasma to screen for GABA-transaminase deficiency.

Untargeted metabolomics identifies unique though benign biochemical changes in patients with pathogenic variants in UROC1.

Urocanic aciduria is caused by a deficiency in the enzyme urocanase (E.C. 4.2.1.49) encoded by the gene UROC1. In the past, deficiency of urocanase has been associated with intellectual disability in a few case studies with some suggestion that the enzyme deficiency was the causative etiology. Here, we describe two phenotypically normal siblings with compound heterozygous pathogenic variants in UROC1 and characteristic biochemical evidence of urocanase deficiency collected utilizing untargeted metabolomic analysis. These findings suggest that urocanic aciduria may represent an otherwise benign biochemical phenotype and that those individuals with concurrent developmental delay should continue to be evaluated for other underlying causes for their symptoms.

Untargeted metabolomic profiling reveals multiple pathway perturbations and new clinical biomarkers in urea cycle disorders.

PURPOSE: Untargeted metabolomic analysis is increasingly being used in the screening and management of individuals with inborn errors of metabolism (IEM). We aimed to test whether untargeted metabolomic analysis in plasma might be useful for monitoring the disease course and management of urea cycle disorders (UCDs). METHODS: Untargeted mass spectrometry-based metabolomic analysis was used to generate z-scores for more than 900 metabolites in plasma from 48 individuals with various UCDs. Pathway analysis was used to identify common pathways that were perturbed in each UCD. RESULTS: Our metabolomic analysis in plasma identified multiple potentially neurotoxic metabolites of arginine in arginase deficiency and, thus, may have utility in monitoring the efficacy of treatment in arginase deficiency. In addition, we were also able to detect multiple biochemical perturbations in all UCDs that likely reflect clinical management, including metabolite alterations secondary to dietary and medication management. CONCLUSION: In addition to utility in screening for IEM, our results suggest that untargeted metabolomic analysis in plasma may be beneficial for monitoring efficacy of clinical management and off-target effects of medications in UCDs and potentially other IEM.

Corrigendum: 2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis.

[This corrects the article DOI: 10.3389/fnins.2019.00394.].

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing.

Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.

A metabolomic map of Zellweger spectrum disorders reveals novel disease biomarkers.

PURPOSE: Peroxisome biogenesis disorders-Zellweger spectrum disorders (PBD-ZSD) are metabolic diseases with multisystem manifestations. Individuals with PBD-ZSD exhibit impaired peroxisomal biochemical functions and have abnormal levels of peroxisomal metabolites, but the broader metabolic impact of peroxisomal dysfunction and the utility of metabolomic methods is unknown. METHODS: We studied 19 individuals with clinically and molecularly characterized PBD-ZSD. We performed both quantitative peroxisomal biochemical diagnostic studies in parallel with untargeted small molecule metabolomic profiling in plasma samples with detection of >650 named compounds. RESULTS: The cohort represented intermediate to mild PBD-ZSD subjects with peroxisomal biochemical alterations on targeted analysis. Untargeted metabolomic profiling of these samples revealed elevations in pipecolic acid and long-chain lysophosphatidylcholines, as well as an unanticipated reduction in multiple sphingomyelin species. These sphingomyelin reductions observed were consistent across the PBD-ZSD samples and were rare in a population of >1,000 clinical samples. Interestingly, the pattern or "PBD-ZSD metabolome" was more pronounced in younger subjects suggesting studies earlier in life reveal larger biochemical changes. CONCLUSION: Untargeted metabolomics is effective in detecting mild to intermediate cases of PBD-ZSD. Surprisingly, dramatic reductions in plasma sphingomyelin are a consistent feature of the PBD-ZSD metabolome. The use of metabolomics in PBD-ZSD can provide insight into novel biomarkers of disease.

Cognitive enhancement in old dogs from dietary supplementation with a nutrient blend containing arginine, antioxidants, B vitamins and fish oil.

This study focused on the hypothesis that cognitive decline in aged dogs could be attenuated by dietary supplementation with a nutrient blend consisting of antioxidants, B vitamins, fish oil and l-arginine, referred to hereafter as the Brain Protection Blend (BPB). Baseline cognitive assessment before the start of treatment was used to establish cognitively equivalent control (10·464+2·33 kg) and treatment (12·118+3·386 kg) groups of aged dogs between 9·1 and 11·5 years of age and with body condition score of 5. After an initial wash-in period, all dogs were tested over a 6-month period on cognitive test protocols that assessed four phases of a landmark discrimination learning protocol, which assessed a spatial learning skill based on utilisation of external cues, and egocentric discrimination task, which assessed spatial learning based on internal body-centred cues. The BPB-supplemented group showed significantly better performance than the controls on the landmark 1 (P=0·0446) discrimination learning tasks, and on two egocentric discrimination reversal learning tasks (P=0·005 and P=0·01, respectively). The groups did not differ significantly (P>0·10) on the landmark zero discrimination task and the egocentric discrimination learning task. These results suggest beneficial effects are positively linked to task complexity. Many of the nutrients supplemented in the BPB diet were significantly higher in plasma, including arginine, α-tocopherol, DHA and EPA. These results indicate that long-term supplementation with the BPB can have cognition-improving effects and support the use of nutritional strategies in targeting brain ageing-associated risk factors as an intervention to delay cognitive ageing.

Disturbed phospholipid metabolism in serine biosynthesis defects revealed by metabolomic profiling.

Serine biosynthesis defects are autosomal recessive metabolic disorders resulting from the deficiency of any of the three enzymes involved in de novo serine biosynthesis, specifically phosphoglycerate dehydrogenase (PGDH), phosphoserine aminotransferase (PSAT), and phosphoserine phosphatase (PSP). In this study, we performed metabolomic profiling on 4 children with serine biosynthesis defects; 3 with PGDH deficiency and 1 with PSAT deficiency. The evaluations were performed at baseline and with serine and glycine supplementation. Metabolomic profiling performed at baseline showed low phospholipid species, including glycerophosphocholine, glycerophosphoethanolamine, and sphingomyelin. All children had low serine and glycine as expected. Low glycerophosphocholine compounds were found in 4 children, low glycerophosphoethanolamine compounds in 3 children, and low sphingomyelin species in 2 children. Metabolic profiling with serine and glycine supplementation showed normalization of most of the low phospholipid compounds in the 4 children. Phospholipids are the major component of plasma and intracellular membranes, and phosphatidylcholine is the most abundant phospholipid of all mammalian cell types and subcellular organelles. Phosphatidylcholine is of particular importance for the nervous system, where it is essential for neuronal differentiation. The observed low phosphatidylcholine species in children with serine biosynthesis defects that improved after serine supplementation, supports the role of serine as a significant precursor for phosphatidylcholine. The vital role that phosphatidylcholine has during neuronal differentiation and the pronounced neurological manifestations in serine biosynthesis defects suggest that phosphatidylcholine deficiency occurring secondary to serine deficiency may have a significant contribution to the development of the neurological manifestations in individuals with serine biosynthesis defects.

Metabolic Differences between Dogs of Different Body Sizes.

INTRODUCTION: The domesticated dog, Canis lupus familiaris, has been selectively bred to produce extreme diversity in phenotype and genotype. Dogs have an immense diversity in weight and height. Specific differences in metabolism have not been characterized in small dogs as compared to larger dogs. OBJECTIVES: This study aims to identify metabolic, clinical, and microbiota differences between small and larger dogs. METHODS: Gas chromatography/mass spectrometry, liquid chromatography/tandem mass spectrometry, clinical chemistry analysis, dual-energy X-ray absorptiometry, and 16S pyrosequencing were used to characterize blood metabolic, clinical, and fecal microbiome systems, respectively. Eighty-three canines from seven different breeds, fed the same kibble diet for 5 weeks, were used in the study. RESULTS: 449 metabolites, 16 clinical parameters, and 6 bacteria (at the genus level) were significantly different between small and larger dogs. Hierarchical clustering of the metabolites yielded 8 modules associated with small dog size. CONCLUSION: Small dogs had a lower antioxidant status and differences in circulating amino acids. Some of the amino acid differences could be attributed to differences in microflora. Additionally, analysis of small dog metabolites and clinical parameters reflected a network which strongly associates with kidney function.

Biochemical phenotyping unravels novel metabolic abnormalities and potential biomarkers associated with treatment of GLUT1 deficiency with ketogenic diet.

Global metabolomic profiling offers novel opportunities for the discovery of biomarkers and for the elucidation of pathogenic mechanisms that might lead to the development of novel therapies. GLUT1 deficiency syndrome (GLUT1-DS) is an inborn error of metabolism due to reduced function of glucose transporter type 1. Clinical presentation of GLUT1-DS is heterogeneous and the disorder mirrors patients with epilepsy, movement disorders, or any paroxysmal events or unexplained neurological manifestation triggered by exercise or fasting. The diagnostic biochemical hallmark of the disease is a reduced cerebrospinal fluid (CSF)/blood glucose ratio and the only available treatment is ketogenic diet. This study aimed at advancing our understanding of the biochemical perturbations in GLUT1-DS pathogenesis through biochemical phenotyping and the treatment of GLUT1-DS with a ketogenic diet. Metabolomic analysis of three CSF samples from GLUT1-DS patients not on ketogenic diet was feasible inasmuch as CSF sampling was used for diagnosis before to start with ketogenic diet. The analysis of plasma and urine samples obtained from GLUT1-DS patients treated with a ketogenic diet showed alterations in lipid and amino acid profiles. While subtle, these were consistent findings across the patients with GLUT1-DS on ketogenic diet, suggesting impacts on mitochondrial physiology. Moreover, low levels of free carnitine were present suggesting its consumption in GLUT1-DS on ketogenic diet. 3-hydroxybutyrate, 3-hydroxybutyrylcarnitine, 3-methyladipate, and N-acetylglycine were identified as potential biomarkers of GLUT1-DS on ketogenic diet. This is the first study to identify CSF, plasma, and urine metabolites associated with GLUT1-DS, as well as biochemical changes impacted by a ketogenic diet. Potential biomarkers and metabolic insights deserve further investigation.

Clinical Metabolomics to Segregate Aromatic Amino Acid Decarboxylase Deficiency From Drug-Induced Metabolite Elevations.

BACKGROUND: Phenotyping technologies featured in the diagnosis of inborn errors of metabolism, such as organic acid, amino acid, and acylcarnitine analyses, recently have been supplemented by broad-scale untargeted metabolomic phenotyping. We investigated the analyte changes associated with aromatic amino acid decarboxylase (AADC) deficiency and dopamine medication treatment. METHODS: Using an untargeted metabolomics platform, we analyzed ethylenediaminetetraacetic acid plasma specimens, and biomarkers were identified by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. RESULTS: Elevated 3-methoxytyrosine (average z score 5.88) accompanied by significant decreases of dopamine 3-O-sulfate (-2.77), vanillylmandelate (-2.87), and 3-methoxytyramine sulfate (-1.44) were associated with AADC deficiency in three samples from two patients. In five non-AADC patients treated with carbidopa-levodopa, levels of 3-methoxytyrosine were elevated (7.65); however, the samples from non-AADC patients treated with DOPA-elevating drugs had normal or elevated levels of metabolites downstream of aromatic l-amino acid decarboxylase, including dopamine 3-O-sulfate (2.92), vanillylmandelate (0.33), and 3-methoxytyramine sulfate (5.07). In one example, a plasma metabolomic phenotype pointed to a probable AADC deficiency and prompted the evaluation of whole exome sequencing data, identifying homozygosity for a known pathogenic variant, whereas whole exome analysis in a second patient revealed compound heterozygosity for two variants of unknown significance. CONCLUSIONS: These data demonstrate the power of combining broad-scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and suggest that metabolic phenotyping of plasma can be used to identify AADC deficiency and to distinguish it from non-AADC patients with elevated 3-methoxytyrosine caused by DOPA-raising medications.

Analyses of SLC13A5-epilepsy patients reveal perturbations of TCA cycle.

OBJECTIVE: To interrogate the metabolic profile of five subjects from three families with rare, nonsense and missense mutations in SLC13A5 and Early Infantile Epileptic Encephalopathies (EIEE) characterized by severe, neonatal onset seizures, psychomotor retardation and global developmental delay. METHODS: Mass spectrometry of plasma, CSF and urine was used to identify consistently dysregulated analytes in our subjects. RESULTS: Distinctive elevations of citrate and dysregulation of citric acid cycle intermediates, supporting the hypothesis that loss of SLC13A5 function alters tricarboxylic acid cycle (TCA) metabolism and may disrupt metabolic compartmentation in the brain. SIGNIFICANCE: Our results indicate that analysis of plasma citrate and other TCA analytes in SLC13A5 deficient patients define a diagnostic metabolic signature that can aid in diagnosing children with this disease.