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.

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.

Validation of a Metabolite Panel for a More Accurate Estimation of Glomerular Filtration Rate Using Quantitative LC-MS/MS.

BACKGROUND: Clinical practice guidelines recommend estimation of glomerular filtration rate (eGFR) using validated equations based on serum creatinine (eGFRcr), cystatin C (eGFRcys), or both (eGFRcr-cys). However, when compared with the measured GFR (mGFR), only eGFRcr-cys meets recommended performance standards. Our goal was to develop a more accurate eGFR method using a panel of metabolites without creatinine, cystatin C, or demographic variables. METHODS: An ultra-performance liquid chromatography-tandem mass spectrometry assay for acetylthreonine, phenylacetylglutamine, pseudouridine, and tryptophan was developed, and a 20-day, multiinstrument analytical validation was conducted. The assay was tested in 2424 participants with mGFR data from 4 independent research studies. A new GFR equation (eGFRmet) was developed in a random subset (n = 1615) and evaluated in the remaining participants (n = 809). Performance was assessed as the frequency of large errors [estimates that differed from mGFR by at least 30% (1 - P30); goal <10%]. RESULTS: The assay had a mean imprecision (≤10% intraassay, ≤6.9% interassay), linearity over the quantitative range (r 2 > 0.98), and analyte recovery (98.5%-113%). There was no carryover, no interferences observed, and analyte stability was established. In addition, 1 - P30 in the validation set for eGFRmet (10.0%) was more accurate than eGFRcr (13.1%) and eGFRcys (12.0%) but not eGFRcr-cys (8.7%). Combining metabolites, creatinine, cystatin C, and demographics led to the most accurate equation (7.0%). Neither equation had substantial variation among population subgroups. CONCLUSIONS: The new eGFRmet equation could serve as a confirmatory test for GFR estimation.

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.

Identification of an Endogenous Organosulfur Metabolite by Interpretation of Mass Spectrometric Data.

The chemical structure of x11564, a new endogenous organosulfur metabolite, was elucidated by de novo interpretation of mass spectrometric data. The structure was confirmed by comparison to a synthetic standard. Metabolite x11564 is structurally related to intermediates in the methionine salvage pathway.

Structure elucidation of metabolite x17299 by interpretation of mass spectrometric data.

INTRODUCTION: A major bottleneck in metabolomic studies is metabolite identification from accurate mass spectrometric data. Metabolite x17299 was identified in plasma as an unknown in a metabolomic study using a compound-centric approach where the associated ion features of the compound were used to determine the true molecular mass. OBJECTIVES: The aim of this work is to elucidate the chemical structure of x17299, a new compound by de novo interpretation of mass spectrometric data. METHODS: An Orbitrap Elite mass spectrometer was used for acquisition of mass spectra up to MS4 at high resolution. Synthetic standards of N,N,N-trimethyl-l-alanyl-l-proline betaine (l,l-TMAP), a diastereomer, and an enantiomer were chemically prepared. RESULTS: The planar structure of x17299 was successfully proposed by de novo mechanistic interpretation of mass spectrometric data without any laborious purification and nuclear magnetic resonance spectroscopic analysis. The proposed structure was verified by deuterium exchanged mass spectrometric analysis and confirmed by comparison to a synthetic standard. Relative configuration of x17299 was determined by direct chromatographic comparison to a pair of synthetic diastereomers. Absolute configuration was assigned after derivatization of x17299 with a chiral auxiliary group followed by its chromatographic comparison to a pair of synthetic standards. CONCLUSION: The chemical structure of metabolite x17299 was determined to be l,l-TMAP.

LC-MS/MS method for quantitation of seven biomarkers in human plasma for the assessment of insulin resistance and impaired glucose tolerance.

Early detection of insulin resistance (IR) and/or impaired glucose tolerance (IGT) is crucial for delaying and preventing the progression toward type 2 diabetes. We recently developed and validated a straightforward metabolite-based test for the assessment of IR and IGT in a single LC-MS/MS method. Plasma samples were diluted with isotopically-labeled internal standards and extracted by simple protein precipitation. The extracts were analyzed by LC-MS/MS for the quantitation of 2-hydroxybutyric acid (0.500-40.0µg/mL), 3-hydroxybutyric acid (1.00-80.0µg/mL), 4-methyl-2-oxopentanoic acid (0.500-20.0µg/mL), 1-linoleoyl-2-hydroxy-sn-glycero-3-phosphocholine (2.50-100µg/mL), oleic acid (10.0-400µg/mL), pantothenic acid (0.0100-0.800µg/mL), and serine (2.50-100µg/mL). Liquid chromatography was carried out on a reversed phase column with a run time of 3.1min and the mass spectrometer operated in negative MRM mode. Method validation was performed on three identical LC-MS/MS systems with five runs each. Sufficient linearity (R2>0.99) was observed for all the analytes over the ranges. The imprecision (CVs) was found to be less than 5.5% for intra-run and less than 5.8% for inter-run for the seven analytes. The analytical recovery was determined to be between 96.3 and 103% for the seven analytes. This fast and robust method has subsequently been used for patient sample analysis for the assessment of IR and IGT.

Analytical Performance of Multiplexed Screening Test for 10 Antibiotic Resistance Genes from Perianal Swab Samples.

BACKGROUND: Multiantibiotic-resistant bacteria pose a threat to patients and place an economic burden on health care systems. Carbapenem-resistant bacilli and extended-spectrum ß-lactamase (ESBL) producers drive the need to screen infected and colonized patients for patient management and infection control. METHODS: We describe a multiplex microfluidic PCR test for perianal swab samples (Acuitas(®) MDRO Gene Test, OpGen) that detects the vancomycin-resistance gene vanA plus hundreds of gene subtypes from the carbapenemase and ESBL families Klebsiella pneumoniae carbapenemase (KPC), New Delhi metallo-ß-lactamase (NDM), Verona integron-mediated metallo-ß-lactamase (VIM), imipenemase metallo-ß-lactamase (IMP), OXA-23, OXA-48, OXA-51, CTX-M-1, and CTX-M-2, regardless of the bacterial species harboring the antibiotic resistance. RESULTS: Analytical test sensitivity per perianal swab is 11-250 CFU of bacteria harboring the antibiotic resistance genes. Test throughput is 182 samples per test run (1820 antibiotic resistance gene family results). We demonstrate reproducible test performance and 100% gene specificity for 265 clinical bacterial organisms harboring a variety of antibiotic resistance genes. CONCLUSIONS: The Acuitas MDRO Gene Test is a sensitive, specific, and high-throughput test to screen colonized patients and diagnose infections for several antibiotic resistance genes directly from perianal swab samples, regardless of the bacterial species harboring the resistance genes.