9 research outputs found

    A Distinct Metabolite Signature in Military Personnel Exposed to Repetitive Low-Level Blasts

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    Military Breachers and Range Staff (MBRS) are subjected to repeated sub-concussive blasts, and they often report symptoms that are consistent with a mild traumatic brain injury (mTBI). Biomarkers of blast injury would potentially aid blast injury diagnosis, surveillance and avoidance. Our objective was to identify plasma metabolite biomarkers in military personnel that were exposed to repeated low-level or sub-concussive blast overpressure. A total of 37 military members were enrolled (18 MBRS and 19 controls), with MBRS having participated in 8–20 breaching courses per year, with a maximum exposure of 6 blasts per day. The two cohorts were similar except that the number of blast exposures were significantly higher in the MBRS, and the MBRS cohort suffered significantly more post-concussive symptoms and poorer health on assessment. Metabolomics profiling demonstrated significant differences between groups with 74% MBRS classification accuracy (CA). Feature reduction identified 6 metabolites that resulted in a MBRS CA of 98%, and included acetic acid (23.7%), formate (22.6%), creatine (14.8%), acetone (14.2%), methanol (12,7%), and glutamic acid (12.0%). All 6 metabolites were examined with individual receiver operating characteristic (ROC) curve analyses and demonstrated areas-under-the-curve (AUCs) of 0.82–0.91 (P ≤ 0.001) for MBRS status. Several parsimonious combinations of three metabolites increased accuracy of ROC curve analyses to AUCs of 1.00 (P \u3c 0.001), while a combination of volatile organic compounds (VOCs; acetic acid, acetone and methanol) yielded an AUC of 0.98 (P \u3c 0.001). Candidate biomarkers for chronic blast exposure were identified, and if validated in a larger cohort, may aid surveillance and care of military personnel. Future point-of-care screening could be developed that measures VOCs from breath, with definitive diagnoses confirmed with plasma metabolomics profiling

    Quantitative characterization of the urine and serum metabolomes of children is essential for ‘omics’ studies

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    Abstract Understanding the long-term health impacts of the early-life exposome requires the characterization and assimilation of multi ‘omics’ data to ultimately link molecular changes to exposures. In this way, markers associated with negative health outcomes, such as increased disease risk, can be ascertained. However, determining the extent and direction of metabolic perturbations relies on comparisons to existing metabolomic reference profiles. While such resources are increasingly available for adult populations, analogous tools for children are decidedly lacking. Lau et al. have compiled robust, translatable quantitative metabolomics data on urine and serum samples for European children across six study locations. Metabolites were associated with body mass index, diet and demographics, and correlated within and between biofluids. As a result, a novel association between urinary 4-deoxyerythronic acid and body mass index was uncovered. This work serves as a crucial reference for future studies in exposomics, and – more broadly – represents a significant step forward for metabolomics by creating the foundation for a comprehensive reference metabolome for children. Please see related article: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1190-

    Carnitine in alcohol use disorders: a scoping review.

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    Recent studies in alcohol use disorders (AUDs) have demonstrated some connections between carnitine metabolism and the pathophysiology of the disease. In this scoping review, we aimed to collate and examine existing research available on carnitine metabolism and AUDs and develop hypotheses surrounding the role carnitine may play in AUD. A scoping review method was used to search electronic databases in September 2019. The database search terms used included "alcohol, alcoholism, alcohol abuse, alcohol consumption, alcohol drinking patterns, alcohol-induced disorders, alcoholic intoxication, alcohol-related disorders, binge drinking, Wernicke encephalopathy, acylcarnitine, acetyl-l-carnitine, acetylcarnitine, carnitine and palmitoylcarnitine." The inclusion criteria included English language, human-based, AUD diagnosis and measured blood or tissue carnitine or used carnitine as a treatment. Of 586 studies that were identified and screened, 65 underwent abstract review, and 41 were fully reviewed. Eighteen studies were ultimately included for analysis. Data were summarized in an electronic data extraction form. We found that there is limited literature available. Alcohol use appears to impact carnitine metabolism, most clearly in the setting of alcoholic cirrhosis. Six studies found carnitine to be increased in AUD, of which 5 were conducted in patients with alcoholic cirrhosis. Only 3 placebo-controlled trials were identified and provide some support for the use of carnitine in AUD to decrease cravings, anhedonia, and withdrawal and improve cognition. The increase in plasma carnitine in alcoholic cirrhosis may be related to disordered fatty acid metabolism and oxidative stress that occurs in AUD. The multiple possible therapeutic effects carnitine could have on ethanol metabolism and the early evidence available for carnitine supplementation as a treatment for AUD provide a foundation for future randomized control trials of carnitine for treating AUD

    High Throughput Screening Method for Systematic Surveillance of Drugs of Abuse by Multisegment Injection–Capillary Electrophoresis–Mass Spectrometry

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    New technologies are urgently required for reliable drug screening given a worldwide epidemic of prescription drug abuse and its devastating socioeconomic impacts on public health. Primary screening of drugs of abuse (DoA) currently relies on immunoassays that are prone to bias and are not applicable to detect an alarming array of psychoactive stimulants, tranquilizers, and synthetic opioids. These limitations impact patient safety when monitoring for medication compliance, drug substitution, or misuse/abuse and require follow-up confirmatory testing by more specific yet lower throughput instrumental methods. Herein, we introduce a high throughput platform for nontargeted screening of a broad spectrum of DoA and their metabolites based on multisegment injection–capillary electrophoresis–mass spectrometry (MSI–CE–MS). We demonstrate that MSI–CE–MS enables serial injections of 10 samples within a single run (<3 min/sample) where multiplexed electrophoretic separations are coupled to high resolution MS with full-scan data acquisition. Unambiguous drug identification was achieved by four or more independent parameters, including comigration with a deuterated internal standard or in silico prediction of electromigration behavior together with accurate mass, most likely molecular formula, as well as MS/MS as required for confirmation testing. Acceptable precision was demonstrated for over 50 DoA at 3 concentration levels over 4 days (median coefficient of variance = 13%, <i>n</i> = 117) with minimal ion suppression, isobaric interferences, and sample carry-over (<1%). This approach offers a rapid yet accurate method for simultaneous detection and identification of DoA at their recommended screening cutoff levels in human urine while allowing for systematic surveillance, specimen verification, and retrospective testing of designer drugs that elude conventional drug tests

    Temporal Signal Pattern Recognition in Mass Spectrometry: A Method for Rapid Identification and Accurate Quantification of Biomarkers for Inborn Errors of Metabolism with Quality Assurance

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    Mass spectrometry (MS)-based metabolomic initiatives that use conventional separation techniques are limited by low sample throughput and complicated data processing that contribute to false discoveries. Herein, we introduce a new strategy for unambiguous identification and accurate quantification of biomarkers for inborn errors of metabolism (IEM) from dried blood spots (DBS) with quality assurance. A multiplexed separation platform based on multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) was developed to provide comparable sample throughput to flow injection analysis-tandem MS (FIA-MS/MS) but with greater selectivity as required for confirmatory testing and discovery-based metabolite profiling of volume-restricted biospecimens. Mass spectral information is encoded temporally within a separation by serial injection of three or more sample pairs, each having a unique dilution pattern, alongside a quality control (QC) that serves as a reference in every run to facilitate between-sample comparisons and/or batch correction due to system drift. Optimization of whole blood extraction conditions on DBS filter paper cut-outs was first achieved to maximize recovery of a wide range of polar metabolites from DBS extracts. An interlaboratory comparison study was also conducted using a proficiency test and retrospective neonatal DBS that demonstrated good agreement between MSI-CE-MS and validated FIA-MS/MS methods within an accredited facility. Our work demonstrated accurate identification of various IEM based on reliable measurement of a panel of primary or secondary biomarkers above an upper cutoff concentration limit for presumptive screen-positive cases without stable isotope-labeled reagents. Additionally, nontargeted metabolite profiling by MSI-CE-MS with temporal signal pattern recognition revealed new biomarkers for early detection of galactosemia, such as <i>N</i>-galactated amino acids, that are a novel class of pathognomonic marker due to galactose stress in affected neonates

    Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics

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    Sport concussions can be difficult to diagnose and if missed, they can expose athletes to greater injury risk and long-lasting neurological disabilities. Discovery of objective biomarkers to aid concussion diagnosis is critical to protecting athlete brain health. To this end, we performed targeted proteomics on plasma obtained from adolescent athletes suffering a sports concussion. A total of 11 concussed male athletes were enrolled at our academic Sport Medicine Concussion Clinic, as well as 24 sex-, age- and activity-matched healthy control subjects. Clinical evaluation was performed and blood was drawn within 72 h of injury. Proximity extension assays were performed for 1,472 plasma proteins; a total of six proteins were considered significantly different between cohorts (P \u3c 0.01; five proteins decreased and one protein increased). Receiver operating characteristic curves on the six individual protein biomarkers identified had areas-under-the-curves (AUCs) for concussion diagnosis ≥0.78; antioxidant 1 copper chaperone (ATOX1; AUC 0.81, P = 0.003), secreted protein acidic and rich in cysteine (SPARC; AUC 0.81, P = 0.004), cluster of differentiation 34 (CD34; AUC 0.79, P = 0.006), polyglutamine binding protein 1 (PQBP1; AUC 0.78, P = 0.008), insulin-like growth factor-binding protein-like 1 (IGFBPL1; AUC 0.78, P = 0.008) and cytosolic 5\u27-nucleotidase 3A (NT5C3A; AUC 0.78, P = 0.009). Combining three of the protein biomarkers (ATOX1, SPARC and NT5C3A), produced an AUC of 0.98 for concussion diagnoses (P \u3c 0.001; 95% CI: 0.95, 1.00). Despite a paucity of studies on these three identified proteins, the available evidence points to their roles in modulating tissue inflammation and regulating integrity of the cerebral microvasculature. Taken together, our exploratory data suggest that three or less novel proteins, which are amenable to a point-of-care immunoassay, may be future candidate biomarkers for screening adolescent sport concussion. Validation with protein assays is required in larger cohorts

    Serum and Adipose Tissue Amino Acid Homeostasis in the Metabolically Healthy Obese

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    A subgroup of obese individuals, referred to as metabolically healthy obese (MHO), have preserved insulin sensitivity and a normal lipid profile despite being obese. The molecular basis for this improved cardiometabolic profile remains unclear. Our objective was to integrate metabolite and gene expression profiling to elucidate the molecular distinctions between MHO and metabolically unhealthy obese (MUO) phenotypes. A subset of individuals were selected from the Diabetes Risk Assessment study and classified into three groups using anthropometric and clinical measurements: lean healthy (LH), MHO, and MUO. Serum metabolites were profiled using gas chromatography coupled to mass spectrometry. Multivariate data analysis uncovered metabolites that differed between groups, and these were subsequently validated by capillary electrophoresis coupled to mass spectrometry. Subcutaneous adipose tissue (SAT) gene expression profiling using microarrays was performed in parallel. Amino acids were the most relevant class of metabolites distinguishing MHO from MUO individuals. Serum levels of glutamic acid, valine, and isoleucine were positively associated (i.e., LH < MHO < MUO) with homeostasis model assessment-insulin resistance (HOMA-IR) and glycated hemoglobin (HbA1c) values, while leucine was only correlated with HOMA-IR. The glutamine-to-glutamic acid ratio and glycine were inversely correlated (i.e., LH > MHO > MUO) with HbA1c values. Concomitantly, SAT gene expression profiling revealed that genes related to branched-chain amino acid catabolism and the tricarboxylic acid cycle were less down-regulated in MHO individuals compared to MUO individuals. Together, this integrated analysis revealed that MHO individuals have an intermediate amino acid homeostasis compared to LH and MUO individuals
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