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.

Untargeted metabolomics profiling in pediatric patients and adult populations indicates a connection between lipid imbalance and epilepsy.

Introduction: Epilepsy is a common central nervous system disorder characterized by abnormal brain electrical activity. We aimed to compare the metabolic profiles of plasma from patients with epilepsy across different etiologies, seizure frequency, seizure type, and patient age to try to identify common disrupted pathways. Material and methods: We used data from three separate cohorts. The first cohort (PED-C) consisted of 31 pediatric patients with suspicion of a genetic disorder with unclear etiology; the second cohort (AD-C) consisted of 250 adults from the Estonian Biobank (EstBB), and the third cohort consisted of 583 adults ≥ 69 years of age from the EstBB (ELD-C). We compared untargeted metabolomics and lipidomics data between individuals with and without epilepsy in each cohort. Results: In the PED-C, significant alterations (p-value <0.05) were detected in sixteen different glycerophosphatidylcholines (GPC), dimethylglycine and eicosanedioate (C20-DC). In the AD-C, nine significantly altered metabolites were found, mainly triacylglycerides (TAG), which are also precursors in the GPC synthesis pathway. In the ELD-C, significant changes in twenty metabolites including multiple TAGs were observed in the metabolic profile of participants with previously diagnosed epilepsy. Pathway analysis revealed that among the metabolites that differ significantly between epilepsy-positive and epilepsy-negative patients in the PED-C, the lipid superpathway (p = 3.2*10-4) and phosphatidylcholine (p = 9.3*10-8) and lysophospholipid (p = 5.9*10-3) subpathways are statistically overrepresented. Analogously, in the AD-C, the triacylglyceride subclass turned out to be statistically overrepresented (p = 8.5*10-5) with the lipid superpathway (p = 1.4*10-2). The presented p-values are FDR-corrected. Conclusion: Our results suggest that cell membrane fluidity may have a significant role in the mechanism of epilepsy, and changes in lipid balance may indicate epilepsy. However, further studies are needed to evaluate whether untargeted metabolomics analysis could prove helpful in diagnosing epilepsy earlier.

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.

Correction: Turner et al. Steatitis in Cold-Stunned Kemp's Ridley Sea Turtles (Lepidochelys kempii). Animals 2021, 11, 898.

In the original publication [...].

Clinical metabolomics for inborn errors of metabolism.

Metabolism is a highly regulated process that provides nutrients to cells and essential building blocks for the synthesis of protein, DNA and other macromolecules. In healthy biological systems, metabolism maintains a steady state in which the concentrations of metabolites are relatively constant yet are subject to metabolic demands and environmental stimuli. Rare genetic disorders, such as inborn errors of metabolism (IEM), cause defects in regulatory enzymes or proteins leading to metabolic pathway disruption and metabolite accumulation or deficiency. Traditionally, the laboratory diagnosis of IEMs has been limited to analytical methods that target specific metabolites such as amino acids and acyl carnitines. This approach is effective as a screening method for the most common IEM disorders but lacks the comprehensive coverage of metabolites that is necessary to identify rare disorders that present with nonspecific clinical symptoms. Fortunately, advancements in technology and data analytics has introduced a new field of study called metabolomics which has allowed scientists to perform comprehensive metabolite profiling of biological systems to provide insight into mechanism of action and gene function. Since metabolomics seeks to measure all small molecule metabolites in a biological specimen, it provides an innovative approach to evaluating disease in patients with rare genetic disorders. In this review we provide insight into the appropriate application of metabolomics in clinical settings. We discuss the advantages and limitations of the method and provide details related to the technology, data analytics and statistical modeling required for metabolomic profiling of patients with IEMs.

Evaluation of the Respiratory Microbiome and the Use of Tracheal Lavage as a Diagnostic Tool in Kemp's Ridley Sea Turtles (Lepidochelys kempii).

Respiratory disease is a common cause of morbidity and mortality in sea turtles, including the Kemp's ridley sea turtle (Lepidochelys kempii). Although culture-dependent methods are typically used to characterize microbes associated with pneumonia and to determine treatment, culture-independent methods can provide a deeper understanding of the respiratory microbial communities and lead to a more accurate diagnosis. In this study, we characterized the tracheal lavage microbiome from cold-stunned Kemp's ridley sea turtles at three time points during rehabilitation (intake, rehabilitation, and convalescence) by analyzing the 16S rRNA gene collected from tracheal lavage samples. We retrospectively developed a radiographic scoring system to grade the severity of lung abnormalities in these turtles and found no differences in diversity or composition of microbial communities based on radiographic score. We also found that the culture isolates from tracheal lavage samples, as well as other previously reported sea turtle pathogens, were present in variable abundance across sequenced samples. In addition to the tracheal microbial community of live turtles, we characterized microbial communities from other segments of the respiratory tract (glottis, trachea, anterior lung, posterior lung) from deceased turtles. We found a high degree of variability within turtles and a high degree of dissimilarity between different segments of the respiratory tract and the tracheal lavage collected from the same turtle. In summary, we found that the pulmonary microbial community associated with pneumonia in sea turtles is complex and does not correlate well with the microbial community as identified by tracheal lavage. These results underscore the limitations of using tracheal lavage for identification of the causative agents of pneumonia in sea turtles.

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.

Characterization of oral and cloacal microbial communities in cold-stunned Kemp's ridley sea turtles (Lepidochelys kempii) during the time course of rehabilitation.

Microbial communities of animals play a role in health and disease, including immunocompromised conditions. In the northeastern United States, cold-stunning events often cause endangered Kemp's ridley turtles (Lepidochelys kempii) to become stranded on beaches in autumn. These sea turtles are admitted to rehabilitation facilities when rescued alive and are presumed immunocompromised secondary to hypothermia. To better understand the role that microbes play in the health of cold-stunned sea turtles, we characterized the oral and cloacal microbiome from Kemp's ridley turtles at multiple timepoints during rehabilitation, from admission to pre-release, by using Illumina sequencing to analyze the 16S rRNA gene. Microbial communities were distinct between body sites and among turtles that survived and those that died. We found that clinical parameters such as presence of pneumonia or values for various blood analytes did not correlate with oral or cloacal microbial community composition. We also investigated the effect of antibiotics on the microbiome during rehabilitation and prior to release and found that the type of antibiotic altered the microbial community composition, yet overall taxonomic diversity remained the same. The microbiome of cold-stunned Kemp's ridley turtles gradually changed through the course of rehabilitation with environment, antibiotics, and disease status all playing a role in those changes and ultimately the release status of the turtles.

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.

Steatitis in Cold-Stunned Kemp's Ridley Sea Turtles (Lepidochelys kempii).

The pathogenesis of steatitis that infrequently occurs in cold-stunned Kemp's ridley sea turtles (KRT; Lepidochelys kempii) has been undetermined. The objectives of this study were to investigate the clinical (n = 23) and histologic findings (n = 11) in cold-stunned KRT, and to compare plasma concentrations of α-tocopherol (vitamin E), thiobarbituric acid reactive substances (TBARS), and the TBARS to vitamin E (T/E) ratio (an assessment of oxidative stress) between cold-stunned KRT with clinically and/or histologically confirmed steatitis (n = 10) and free-ranging KRT (n = 9). None of the cold-stunned turtles had clinically detectable steatitis at admission, and the median number of days to diagnosis of steatitis was 71 (range 33­469). Histologic findings of affected adipose tissue included heterophilic (n = 9) and/or histiocytic (n = 5) steatitis, fat necrosis (n = 7), myonecrosis (n = 2), and intralesional bacteria (n = 6). Cold-stunned KRT had significantly lower plasma vitamin E concentrations (median = 3.5 nmol/g), lower plasma TBARS concentrations (median = 1.6 nmol/g), and higher T/E ratios (median = 0.50), than controls (62.3 nmol/g; 2.1 nmol/g; 0.03, respectively). These results suggest a multifactorial etiology for the development of steatitis in KRT during rehabilitation, including tissue injury, septicemia, and various factors resulting in imbalances of anti-/oxidative status. By highlighting the need to provide more effective vitamin E supplementation, and the need to re-assess specific components of the diet, this study may lead to reduced incidence and improved medical management of steatitis in cold-stunned sea turtles.

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.

α-Conotoxin Peptidomimetics: Probing the Minimal Binding Motif for Effective Analgesia.

Several analgesic α-conotoxins have been isolated from marine cone snails. Structural modification of native peptides has provided potent and selective analogues for two of its known biological targets-nicotinic acetylcholine and γ-aminobutyric acid (GABA) G protein-coupled (GABAB) receptors. Both of these molecular targets are implicated in pain pathways. Despite their small size, an incomplete understanding of the structure-activity relationship of α-conotoxins at each of these targets has hampered the development of therapeutic leads. This review scrutinises the N-terminal domain of the α-conotoxin family of peptides, a region defined by an invariant disulfide bridge, a turn-inducing proline residue and multiple polar sidechain residues, and focusses on structural features that provide analgesia through inhibition of high-voltage-activated Ca2+ channels. Elucidating the bioactive conformation of this region of these peptides may hold the key to discovering potent drugs for the unmet management of debilitating chronic pain associated with a wide range of medical conditions.

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.

Fast skeletal muscle troponin activator CK-2066260 increases fatigue resistance by reducing the energetic cost of muscle contraction.

KEY POINTS: Skeletal muscle fatigue limits performance in various physical activities, with exercise intolerance being a key symptom in a broad spectrum of diseases. We investigated whether a small molecule fast skeletal troponin activator (FSTA), CK-2066260, can mitigate muscle fatigue by reducing the cytosolic free [Ca2+ ] required to produce a given submaximal force and hence decreasing the energy requirement. Isolated intact single mouse muscle fibres and rat muscles in-situ treated with CK-2066260 showed improved muscle endurance., which was accompanied by decreased ATP demand and reduced glycogen usage. CK-2066260 treatment improved in-vivo exercise capacity in healthy rats and in a rat model of peripheral artery insufficiency. In conclusion, we show that the FSTA CK-2066260 effectively counteracts muscle fatigue in rodent skeletal muscle in vitro, in situ, and in vivo. This may translate to humans and provide a promising pharmacological treatment to patients suffering from severe muscle weakness and exercise intolerance. ABSTRACT: Skeletal muscle fatigue limits performance during physical exercise and exacerbated muscle fatigue is a prominent symptom among a broad spectrum of diseases. The present study investigated whether skeletal muscle fatigue is affected by the fast skeletal muscle troponin activator (FSTA) CK-2066260, which increases myofibrillar Ca2+ sensitivity and amplifies the submaximal force response. Because more force is produced for a given Ca2+ , we hypothesized that CK-2066260 could mitigate muscle fatigue by reducing the energetic cost of muscle activation. Isolated single mouse muscle fibres were fatigued by 100 repeated 350 ms contractions while measuring force and the cytosolic free [Ca2+ ] or [Mg2+ ] ([Mg2+ ]i ). When starting fatiguing stimulation at matching forces (i.e. lower stimulation frequency with CK-2066260): force was decreased by ∼50% with and by ∼75% without CK-2066260; [Mg2+ ]i was increased by ∼10% with and ∼32% without CK-2066260, reflecting a larger decrease in [ATP] in the latter. The glycogen content in in situ stimulated rat muscles fatigued by repeated contractions at matching forces was about two times higher with than without CK-2066260. Voluntary exercise capacity, assessed by rats performing rotarod exercise and treadmill running, was improved in the presence of CK-2066260. CK-2066260 treatment also increased skeletal muscle fatigue resistance and exercise performance in a rat model of peripheral artery insufficiency. In conclusion, we demonstrate that the FSTA CK-2066260 mitigates skeletal muscle fatigue by reducing the metabolic cost of force generation.

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 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.

Ameliorating transport-related stress in endangered Kemp's ridley sea turtles (Lepidochelys kempii) with a recovery period in saltwater pools.

Sea turtle rehabilitation clinics and aquaria frequently transport stranded sea turtles long distances out of water, e.g. for release at sites with appropriate water temperatures. Endangered Kemp's ridley turtles (Lepidochelys kempii) are known to exhibit an adrenal stress response during such transports. In an opportunistic study of turtles transported by road from Massachusetts to Georgia for release, we tested whether placing turtles in saltwater pools for short periods after transport would help turtles recover from transport-related stress. Eighteen juvenile Kemp's ridley turtles were examined and blood samples collected (1) immediately pre-transport, (2) immediately post-transport and (3) after a 6 h (n = 9) or 24 h (n = 9) post-transport period in unfamiliar pools, after which all turtles were released to the sea. Blood samples were analyzed for corticosterone, glucose, total white blood cell (WBC) count, heterophil/lymphocyte (H/L) ratio, pH, pO2, pCO2, HCO3 (bicarbonate), sodium, potassium, ionized calcium, lactate and hematocrit. Though the majority of turtles remained in good clinical condition, corticosterone, glucose, WBC and H/L elevated significantly during transport, while potassium declined slightly but significantly. After at least 6 h in a saltwater pool, potassium and glucose returned to pre-transport baselines and corticosterone partially recovered toward baseline. Extending the pool time to 24 h did not markedly enhance the physiological recovery of turtles, and two immune measures (WBC, H/L) remained elevated from the effect of transport. Six hours in a saltwater pool appears to facilitate the recovery of Kemp's ridley sea turtles from transport-related stress and may therefore improve their readiness for release.

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.