Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.

Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics.

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.

Comparison of dried blood spot and plasma sampling for untargeted metabolomics.

INTRODUCTION: Untargeted metabolomics holds significant promise for biomarker detection and development. In resource-limited settings, a dried blood spot (DBS)-based platform would offer significant advantages over plasma-based approaches that require a cold supply chain. OBJECTIVES: The primary goal of this study was to compare the ability of DBS- and plasma-based assays to characterize maternal metabolites. Utility of the two assays was also assessed in the context of a case-control predictive model in pregnant women living with HIV. METHODS: Untargeted metabolomics was performed on archived paired maternal plasma and DBS from n = 79 women enrolled in a large clinical trial. RESULTS: A total of 984 named biochemicals were detected across both plasma and DBS samples, of which 627 (63.7%), 260 (26.4%), and 97 (9.9%) were detected in both plasma and DBS, plasma alone, and DBS alone, respectively. Variation attributable to study individual (R2 = 0.54, p < 0.001) exceeded that of the sample type (R2 = 0.21, p < 0.001), suggesting that both plasma and DBS were capable of differentiating individual metabolomic profiles. Log-transformed metabolite abundances were strongly correlated (mean Spearman rho = 0.51) but showed low agreement (mean intraclass correlation of 0.15). However, following standardization, DBS and plasma metabolite profiles were strongly concordant (mean intraclass correlation of 0.52). Random forests classification models for cases versus controls identified distinct feature sets with comparable performance in plasma and DBS (86.5% versus 91.2% mean accuracy, respectively). CONCLUSION: Maternal plasma and DBS samples yield distinct metabolite profiles highly predictive of the individual subject. In our case study, classification models showed similar performance albeit with distinct feature sets. Appropriate normalization and standardization methods are critical to leverage data from both sample types. Ultimately, the choice of sample type will likely depend on the compounds of interest as well as logistical demands.

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.

Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study.

BACKGROUND: Estimation of glomerular filtration rate (GFR) using estimated glomerular filtration rate creatinine (eGFRcr) is central to clinical practice but has limitations. We tested the hypothesis that serum metabolomic profiling can identify novel markers that in combination can provide more accurate GFR estimates. METHODS: We performed a cross-sectional study of 200 African American Study of Kidney Disease and Hypertension (AASK) and 265 Multi-Ethnic Study of Atherosclerosis (MESA) participants with measured GFR (mGFR). Untargeted gas chromatography/dual mass spectrometry- and liquid chromatography/dual mass spectrometry-based quantification was followed by the development of targeted assays for 15 metabolites. On the log scale, GFR was estimated from single- and multiple-metabolite panels and compared with eGFR using the Chronic Kidney Disease Epidemiology equations with creatinine and/or cystatin C using established metrics, including the proportion of errors >30% of mGFR (1-P30), before and after bias correction. RESULTS: Of untargeted metabolites in the AASK and MESA, 283 of 780 (36%) and 387 of 1447 (27%), respectively, were significantly correlated (P ≤ 0.001) with mGFR. A targeted metabolite panel eGFR developed in the AASK and validated in the MESA was more accurate (1-P30 3.7 and 1.9%, respectively) than eGFRcr [11.2 and 18.5%, respectively (P < 0.001 for both)] and estimating GFR using cystatin C (eGFRcys) [10.6% (P = 0.02) and 9.1% (P < 0.05), respectively] but was not consistently better than eGFR using both creatinine and cystatin C [3.7% (P > 0.05) and 9.1% (P < 0.05), respectively]. A panel excluding creatinine and demographics still performed well [1-P30 6.4% (P = 0.11) and 3.4% (P < 0.001) in the AASK and MESA] versus eGFRcr. CONCLUSIONS: Multimetabolite panels can enable accurate GFR estimation. Metabolomic equations, preferably excluding creatinine and demographic characteristics, should be tested for robustness and generalizability as a potential confirmatory test when eGFRcr is unreliable.

Values for timed limb coordination tests in a sample of healthy older adults.

BACKGROUND: timed limb coordination tests are reliable measures of motor performance but many lack published reference values. OBJECTIVE: to determine mean values for timed tests in an older cohort, examining associations with anthropometric characteristics, handedness, gender and age. DESIGN: cross-sectional. SETTING: community. SUBJECTS: sixty-nine healthy adults divided into three groups: 60-69, 70-79 and 80+ years. METHODS: height, weight and time to complete five repetitions of finger-to-nose, pronation-supination, mass grasp, opposition and heel-on-shin were recorded. Performances were statistically compared with anthropometric characteristics, handedness and across age groups and gender. RESULTS: for all tests, height negatively correlated with speed (r = -0.26 to -0.41). Weight negatively correlated with performance of two tests (r = -0.25 to -0.35). When covariates were controlled, men performed heel-on-shin faster than women. The youngest group completed upper extremity tests faster than the oldest. Adults in their 70 s completed finger-to-nose and pronation-supination faster than persons aged 80+ years. CONCLUSIONS: we report mean values for five clinical tests of timed limb coordination that may aid in identifying mild deficits in otherwise healthy older adults.

Non-Targeted Dried Blood Spot-Based Metabolomics Analysis Showed Rice Bran Supplementation Effects Multiple Metabolic Pathways during Infant Weaning and Growth in Mali.

Rice bran contains essential nutrients, antioxidants, and bioactives with anti-inflammatory and diarrheal protective properties important for infants. This 6-month randomized controlled trial investigated the effects of heat-stabilized rice bran supplementation during Malian infant weaning. Fifty healthy 6-month-old infants were randomized to a rice bran intervention (N = 25) or non-intervention control group (N = 25). Intervention infants received dose-escalating rice bran supplementation for 6 months (1-5 g/day). Monthly infant dried blood spot and anthropometric measurements were collected. Dried blood spot metabolite abundances were compared monthly according to diet for six months. Supplementation resulted in favorable weight-for-age and weight-for-length z-score changes. Non-targeted dried blood spot-based metabolomics identified 796 metabolites, of which 33% had significant fold differences between groups (7-12 months). Lipids and amino acids represented 70.6% of the metabolites identified. Rice bran supplementation during infant weaning significantly modulated the metabolites involved in antioxidant defenses and with neuroactive properties including reduced glutathione, glycine, glutamate, cysteinylglycine, tryptophan betaine, and choline. These findings support rice bran as a weaning ingredient to meet infant nutritional requirements and with the potential to reduce oxidative stress and improve cognitive outcomes. This study provides evidence for dried blood spots as a cost-effective tool to detect infant biomarkers of nutritional and metabolic status.

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.

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.

Gait impairment and optimizing mobility in multiple sclerosis.

Multiple sclerosis (MS) is an immune-mediated disease that causes demyelination and degeneration within the brain and spinal cord. This may result in many impairments, including impaired ambulation, muscle weakness, abnormal tone, visual disturbances, decreased sensation, and fatigue. Rehabilitation helps patients with MS maximize independence by helping to manage and minimize impairments. Deficits seen in ambulation should be addressed to improve energy efficiency and reduce falls. Compensation through appropriate prescription of assistive devices, bracing, and wheelchairs will help improve safety. Rehabilitation can make a significant impact on achieving and maintaining quality of life and independence.

Timed limb coordination performance is associated with walking speed in healthy older adults: a cross-sectional exploratory study.

Walking speed reflects quality of life, health status and physical function in older adults but interpreting measures of walking speed is affected by several confounders such as gender, age and height. Additionally, walking speed is influenced by neurologic conditions that impair limb coordination. In absence of defined pathology, it is less clear how varying levels of limb coordination influence walking speed. The purpose of this study was to examine the relationship between limb coordination and walking speed in older adults, controlling for effects of gender, age and height. Sixty-nine healthy, community-dwelling individuals over the age of 60 participated in the study. Participants completed a battery of timed upper and lower limb coordination tests. Normal and fast walking speed were measured over the inner six meters of a 10 m walkway. Correlation and regression analyses were used to examine the relationship between limb coordination performance and walking speed. Controlling for gender, age and height, variance in normal walking speed was accounted for by variance in pronation-supination performance (partial r = -0.396, partial r(2) = 0.16) and variance in fast walking speed was accounted for by variance in finger-to-nose performance (partial r = -0.356, partial r(2) = 0.13). The findings support our hypothesis that limb coordination performance would correlate with walking speed in healthy older adults. Moreover, limb coordination performance attenuated the effects of gender, age and height on walking speed. Limb coordination may be a modifiable determinant of walking speed in older adults.