Analysis of plasma metabolomes from 11 309 subjects in five population-based cohorts

Plasma metabolomics holds potential for precision medicine, but limited information is available to compare the performance of such methods across multiple cohorts. We compared plasma metabolite profiles after an overnight fast in 11,309 participants of five population-based Swedish cohorts (50-80 years, 52% women). Metabolite profiles were uniformly generated at a core laboratory (Metabolon Inc.) with untargeted liquid chromatography mass spectrometry and a comprehensive reference library. Analysis of a second sample obtained one year later was conducted in a subset. Of 1629 detected metabolites, 1074 (66%) were detected in all cohorts while only 10% were unique to one cohort, most of which were xenobiotics or uncharacterized. The major classes were lipids (28%), xenobiotics (22%), amino acids (14%), and uncharacterized (19%). The most abundant plasma metabolome components were the major dietary fatty acids and amino acids, glucose, lactate and creatinine. Most metabolites displayed a log-normal distribution. Temporal variability was generally similar to clinical chemistry analytes but more pronounced for xenobiotics. Extensive metabolite-metabolite correlations were observed but mainly restricted to within each class. Metabolites were broadly associated with clinical factors, particularly body mass index, sex and renal function. Collectively, our findings inform the conduct and interpretation of metabolite association and precision medicine studies.

Abstract 6607: Dried blood spot (DBS) sample analysis for drug and metabolomic profiling in oncology clinical trials: Cost-effective decentralized sampling modality for precision oncology

The COVID19 pandemic accelerated opportunities for innovation within the decentralization process of clinical trials with opportunities for implementation of patient-centric workflows for efficiency and cost-reduction. Decentralized sample collection, particularly whole blood using dried blood spots (DBS) provides the ideal mechanism for patient driven sample collection with ease of access to sample generation, drug level assessments and metabolomic prMegofiling, providing longitudinal real-time measure of drug specific pharmacodynamic readout for safety and efficacy. In this study, we report the development of a protocol for the capture and comprehensive profiling of metabolomics using dried blood spots from a cohort of 49 healthy volunteer donors. Using liquid chromatography combined with mass spectrometric (UPLC-MS/MS) methods an untargeted metabolomic approach resulted in the identification of >800 biochemicals of which a significant subset was found to be presented in corresponding matched plasma (from whole blood) samples. The biochemicals identified from the DBS samples included metabolites that were part of the lipid, amino acid, nucleotide, peptide, cofactors, carbohydrate and energy super pathways. A significant number of metabolites identified in the DBS samples were xenobiotics including those representing the biotransformation products of drugs. The overall metabolite profiles were analyzed for precision and accuracy of measure, variability in performance and dynamic range to establish benchmarks for evaluation. An additional cohort with a longitudinal sampling as part of the protocol provided the reproducibility of the analytic method for inter-day variability of metabolite performance over time. Although metabolomic profiles varied between individuals from a population perspective, there was minimal variation observed within individuals when samples were profiled longitudinally over several weeks. Thus, the protocols for DBS collection and the corresponding capture of a large set of metabolites with reproducible performance provides an opportunity for its implementation in oncological clinical trials as part of a de-centralized clinical trial solution.

Citation Format: Kelli Goodman, Megan R. Showalter, Anne M. Evans, Matthew W. Mitchell, Rangaprasad Sarangarajan. Dried blood spot (DBS) sample analysis for drug and metabolomic profiling in oncology clinical trials: Cost-effective decentralized sampling modality for precision oncology. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6607.

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.

Matching Drug Metabolites from Non-Targeted Metabolomics to Self-Reported Medication in the Qatar Biobank Study

Modern metabolomics platforms are able to identify many drug-related metabolites in blood samples. Applied to population-based biobank studies, the detection of drug metabolites can then be used as a proxy for medication use or serve as a validation tool for questionnaire-based health assessments. However, it is not clear how well detection of drug metabolites in blood samples matches information on self-reported medication provided by study participants. Here, we curate free-text responses to a drug-usage questionnaire from 6000 participants of the Qatar Biobank (QBB) using standardized WHO Anatomical Therapeutic Chemical (ATC) Classification System codes and compare the occurrence of these ATC terms to the detection of drug-related metabolites in matching blood plasma samples from 2807 QBB participants for which we collected non-targeted metabolomics data. We found that the detection of 22 drug-related metabolites significantly associated with the self-reported use of the corresponding medication. Good agreement of self-reported medication with non-targeted metabolomics was observed, with self-reported drugs and their metabolites being detected in a same blood sample in 79.4% of the cases. On the other hand, only 29.5% of detected drug metabolites matched to self-reported medication. Possible explanations for differences include under-reporting of over-the-counter medications from the study participants, such as paracetamol, misannotation of low abundance metabolites, such as metformin, and inability of the current methods to detect them. Taken together, our study provides a broad real-world view of what to expect from large non-targeted metabolomics measurements in population-based biobank studies and indicates areas where further improvements can be made.

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.

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.

An ambient-temperature storage and stabilization device performs comparably to flash-frozen collection for stool metabolomics in infants

Background

Stool metabolites provide essential insights into the function of the gut microbiome. The current gold standard for storage of stool samples for metabolomics is flash-freezing at − 80 °C which can be inconvenient and expensive. Ambient temperature storage of stool is more practical, however no available methodologies adequately preserve the metabolomic profile of stool. A novel sampling kit (OMNImet.GUT; DNA Genotek, Inc.) was introduced for ambient temperature storage and stabilization of feces for metabolomics; we aimed to test the performance of this kit vs. flash-freezing. To do this stool was collected from an infant’s diaper was divided into two aliquots: 1) flash-frozen and 2) stored in an OMNImet.GUT tube at ambient temperature for 3–4 days. Samples from the same infant were collected at 2 different time points to assess metabolite changes over time. Subsequently, all samples underwent metabolomic analysis by liquid chromatography – tandem mass spectrometry (LC-MS/MS).

Results

Paired fecal samples (flash-frozen and ambient temperature) from 16 infants were collected at 2 time points (32 individual samples, 64 aliquots). Similar numbers of metabolites were detected in both the frozen and ambient temperature samples (1126 in frozen, 1107 in ambient temperature, 1064 shared between sample types). Metabolite abundances were strongly correlated between storage methods (median Spearman correlation Rs = 0.785 across metabolites). Hierarchical clustering analysis and principal component analysis showed that samples from the same individuals at a given time point clustered closely, regardless of the storage method. Repeat samples from the same individual were compared by paired t-test, separately for the frozen and OMNImet.GUT. The number of metabolites in each biochemical class that significantly changed (p < 0.05) at timepoint 2 relative to timepoint 1 was similar in flash-frozen versus ambient temperature storage. Changes in microbiota modified metabolites over time were also consistent across both methodologies.

Conclusion

Ambient temperature storage and stabilization of stool in the OMNImet.GUT device yielded comparable metabolomic results to flash freezing in terms of 1) the identity and abundance of detected biochemicals 2) the distinct metabolomic profiles of subjects and 3) changes in metabolites over time that are plausibly microbiota-induced. This method potentially provides a more convenient, less expensive home collection and storage option for stool metabolomic analysis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02104-6.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics.

OBJECTIVES

In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics.

METHODS

All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach.

RESULTS

For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%).

CONCLUSIONS

Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Incident depression in patients diagnosed with multiple sclerosis: a multi-database study

BACKGROUND AND PURPOSE

Data on rates of newly diagnosed depression after multiple sclerosis (MS) diagnosis are sparse. Here, incident, treated depression in MS patients after diagnosis compared with matched non-MS patients is described.

METHODS

A matched cohort study was conducted in two separate electronic medical databases: the US Department of Defense (US-DOD) military healthcare system and the UK's Clinical Practice Research Datalink GOLD (UK-CPRD). The study population included all patients with a first recorded diagnosis of MS and matched non-MS patients. Patients with a history of treated depression were excluded. Incidence rates and incidence rate ratios with 95% confidence intervals for treated depression after MS diagnosis/matched date were estimated.

RESULTS

Incidence rate ratios of treated depression amongst MS patients compared with non-MS patients were 3.20 (95% confidence interval 3.05-3.35) in the US-DOD and 1.90 (95% confidence interval 1.74-2.06) in the UK-CPRD. Incidence rate ratios were elevated across age and sex. Rates were higher in females than males but, compared to non-MS patients, males with MS had a higher relative risk than females with MS.

CONCLUSIONS

Multiple sclerosis patients in the UK and the USA have a two- to three-fold increased risk of new, treated depression compared to matched non-MS patients.

Infections in patients diagnosed with multiple sclerosis: A multi-database study

BACKGROUND

Recent data on the rates of infections among patients with multiple sclerosis (MS) are sparse. The objective of this study was to quantify incidence of infections in patients with MS compared with a matched sample of patients without MS (non-MS).

METHODS

This study was conducted in two separate electronic medical databases: the United States Department of Defense (US-DOD) military health care system and the United Kingdom's Clinical Practice Research Datalink GOLD (UK-CPRD). We identified patients with a first recorded diagnosis of MS between 2001 and 2016 (UK-CPRD) or 2004 and 2017 (US-DOD) and matched non-MS patients. We identified infections recorded after the MS diagnosis date (or the matched date in non-MS patients) and calculated incidence rates (IRs) and incidence rate ratios (IRRs) with 95% confidence intervals (CIs) by infection site and type.

RESULTS

Relative to non-MS patients, MS patients had higher rates of any infection (US-DOD IRR 1.76; 95% CI 1.72-1.80 and UK-CPRD IRR 1.25; 95% CI 1.21-1.29) and a two-fold higher rate of hospitalized infections (US-DOD IRR 2.43; 95% CI 2.23-2.63 and UK-CPRD IRR 2.00; 95% CI 1.84-2.17). IRs of any infection were higher in females compared with males in both MS and non-MS patients, while IRs of hospitalized infections were similar between sexes in both MS and non-MS patients. The IR of first urinary tract or kidney infection was nearly two-fold higher in MS compared with non-MS patients (US-DOD IRR 1.88; 95% CI 1.81-1.95 and UK-CPRD IRR 1.97; 95% CI 1.86-2.09) with higher rates in females compared with males. IRs for any opportunistic infection, candidiasis and any herpes virus were increased between 20 and 52% among MS patients compared with non-MS patients. IRs of meningitis, tuberculosis, hepatitis B and C were all low.

CONCLUSION

MS patients have an increased risk of infection, notably infections of the renal tract, and a two-fold increased risk of hospitalized infections compared with non-MS patients.

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.

Serum Metabolomic Alterations Associated with Proteinuria in CKD

BACKGROUND AND OBJECTIVES

Data are scarce on blood metabolite associations with proteinuria, a strong risk factor for adverse kidney outcomes. We sought to investigate associations of proteinuria with serum metabolites identified using untargeted profiling in populations with CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using stored serum samples from the African American Study of Kidney Disease and Hypertension (AASK; n=962) and the Modification of Diet in Renal Disease (MDRD) study (n=620), two rigorously conducted clinical trials with per-protocol measures of 24-hour proteinuria and GFR, we evaluated cross-sectional associations between urine protein-to-creatinine ratio and 637 known, nondrug metabolites, adjusting for key clinical covariables. Metabolites significantly associated with proteinuria were tested for associations with CKD progression.

RESULTS

In the AASK and the MDRD study, respectively, the median urine protein-to-creatinine ratio was 80 (interquartile range [IQR], 28-359) and 188 (IQR, 54-894) mg/g, mean age was 56 and 52 years, 39% and 38% were women, 100% and 7% were black, and median measured GFR was 48 (IQR, 35-57) and 28 (IQR, 18-39) ml/min per 1.73 m2. Linear regression identified 66 serum metabolites associated with proteinuria in one or both studies after Bonferroni correction (P<7.8×10-5), 58 of which were statistically significant in a meta-analysis (P<7.8×10-4). The metabolites with the lowest P values (P<10-27) were 4-hydroxychlorthalonil and 1,5-anhydroglucitol; all six quantified metabolites in the phosphatidylethanolamine pathway were also significant. Of the 58 metabolites associated with proteinuria, four were associated with ESKD in both the AASK and the MDRD study.

CONCLUSIONS

We identified 58 serum metabolites with cross-sectional associations with proteinuria, some of which were also associated with CKD progression.

PODCAST

This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2019_02_07_CJASNPodcast_19_03_.mp3.

Variability of Two Metabolomic Platforms in CKD

BACKGROUND AND OBJECTIVES

Nontargeted metabolomics can measure thousands of low-molecular-weight biochemicals, but important gaps limit its utility for biomarker discovery in CKD. These include the need to characterize technical and intraperson analyte variation, to pool data across platforms, and to outline analyte relationships with eGFR.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Plasma samples from 49 individuals with CKD (eGFR<60 ml/min per 1.73 m² and/or ≥1 g proteinuria) were examined from two study visits; 20 samples were repeated as blind replicates. To enable comparison across two nontargeted platforms, samples were profiled at Metabolon and the Broad Institute.

RESULTS

The Metabolon platform reported 837 known metabolites and 483 unnamed compounds (selected from 44,953 unknown ion features). The Broad Institute platform reported 594 known metabolites and 26,106 unknown ion features. Median coefficients of variation (CVs) across blind replicates were 14.6% (Metabolon) and 6.3% (Broad Institute) for known metabolites, and 18.9% for (Metabolon) unnamed compounds and 24.5% for (Broad Institute) unknown ion features. Median CVs for day-to-day variability were 29.0% (Metabolon) and 24.9% (Broad Institute) for known metabolites, and 41.8% for (Metabolon) unnamed compounds and 40.9% for (Broad Institute) unknown ion features. A total of 381 known metabolites were shared across platforms (median correlation 0.89). Many metabolites were negatively correlated with eGFR at P<0.05, including 35.7% (Metabolon) and 18.9% (Broad Institute) of known metabolites.

CONCLUSIONS

Nontargeted metabolomics quantifies >1000 analytes with low technical CVs, and agreement for overlapping metabolites across two leading platforms is excellent. Many metabolites demonstrate substantial intraperson variation and correlation with eGFR.

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.

Serum 6-Bromotryptophan Levels Identified as a Risk Factor for CKD Progression

Background Metabolite levels reflect physiologic homeostasis and may serve as biomarkers of disease progression. Identifying metabolites associated with APOL1 risk alleles-genetic variants associated with CKD risk commonly present in persons of African descent-may reveal novel markers of CKD progression relevant to other populations.Methods We evaluated associations between the number of APOL1 risk alleles and 760 serum metabolites identified via untargeted profiling in participants of the African American Study of Kidney Disease and Hypertension (AASK) (n=588; Bonferroni significance threshold P<6.5×10^-5) and replicated findings in 678 black participants with CKD in BioMe, an electronic medical record-linked biobank. We tested the metabolite association with CKD progression in AASK, BioMe, and the Modification of Diet in Renal Disease (MDRD) Study.Results One metabolite, 6-bromotryptophan, was significant in AASK (P=4.7×10^-5) and replicated in BioMe (P=5.7×10^-3) participants, with lower levels associated with more APOL1 risk alleles. Lower levels of 6-bromotryptophan were associated with CKD progression in AASK and BioMe participants and in white participants in the MDRD Study, independent of demographics and clinical characteristics, including baseline GFR (adjusted hazard ratio per two-fold higher 6-bromotryptophan level, AASK, 0.76; 95% confidence interval [95% CI], 0.64 to 0.91; BioMe, 0.61; 95% CI, 0.43 to 0.85; MDRD, 0.52; 95% CI, 0.34 to 0.79). The interaction between the APOL1 risk alleles and 6-bromotryptophan was not significant. The identity of 6-bromotryptophan was confirmed in experiments comparing its molecular signature with that of authentic standards of other bromotryptophan isomers.Conclusions Serum 6-bromotryptophan is a consistent and novel risk factor for CKD progression.

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.

Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

We sought to determine the molecular composition of human cerebrospinal fluid (CSF) and identify the biochemical pathways represented in CSF to understand the potential for untargeted screening of inborn errors of metabolism (IEMs). Biochemical profiles for each sample were obtained using an integrated metabolomics workflow comprised of four chromatographic techniques followed by mass spectrometry. Secondarily, we wanted to compare the biochemical profile of CSF with those of plasma and urine within the integrated mass spectrometric-based metabolomic workflow. Three sample types, CSF (N=30), urine (N=40) and EDTA plasma (N=31), were analyzed from retrospectively collected pediatric cohorts of equivalent age and gender characteristics. We identified 435 biochemicals in CSF representing numerous biological and chemical/structural families. Sixty-three percent (273 of 435) of the biochemicals detected in CSF also were detected in urine and plasma, another 32% (140 of 435) were detected in either plasma or urine, and 5% (22 of 435) were detected only in CSF. Analyses of several metabolites showed agreement between clinically useful assays and the metabolomics approach. An additional set of CSF and plasma samples collected from the same patient revealed correlation between several biochemicals detected in paired samples. Finally, analysis of CSF from a pediatric case with dihydropteridine reductase (DHPR) deficiency demonstrated the utility of untargeted global metabolic phenotyping as a broad assessment to screen samples from patients with undifferentiated phenotypes. The results indicate a single CSF sample processed with an integrated metabolomics workflow can be used to identify a large breadth of biochemicals that could be useful for identifying disrupted metabolic patterns associated with IEMs.

Registered Replication Report: Rand, Greene, and Nowak (2012)

In an anonymous 4-person economic game, participants contributed more money to a common project (i.e., cooperated) when required to decide quickly than when forced to delay their decision (Rand, Greene & Nowak, 2012), a pattern consistent with the social heuristics hypothesis proposed by Rand and colleagues. The results of studies using time pressure have been mixed, with some replication attempts observing similar patterns (e.g., Rand et al., 2014) and others observing null effects (e.g., Tinghög et al., 2013; Verkoeijen & Bouwmeester, 2014). This Registered Replication Report (RRR) assessed the size and variability of the effect of time pressure on cooperative decisions by combining 21 separate, preregistered replications of the critical conditions from Study 7 of the original article (Rand et al., 2012). The primary planned analysis used data from all participants who were randomly assigned to conditions and who met the protocol inclusion criteria (an intent-to-treat approach that included the 65.9% of participants in the time-pressure condition and 7.5% in the forced-delay condition who did not adhere to the time constraints), and we observed a difference in contributions of -0.37 percentage points compared with an 8.6 percentage point difference calculated from the original data. Analyzing the data as the original article did, including data only for participants who complied with the time constraints, the RRR observed a 10.37 percentage point difference in contributions compared with a 15.31 percentage point difference in the original study. In combination, the results of the intent-to-treat analysis and the compliant-only analysis are consistent with the presence of selection biases and the absence of a causal effect of time pressure on cooperation.

Nanojunctions of the Sarcoplasmic Reticulum Deliver Site- and Function-Specific Calcium Signaling in Vascular Smooth Muscles

Vasoactive agents may induce myocyte contraction, dilation, and the switch from a contractile to a migratory-proliferative phenotype(s), which requires changes in gene expression. These processes are directed, in part, by Ca²⁺ signals, but how different Ca²⁺ signals are generated to select each function is enigmatic. We have previously proposed that the strategic positioning of Ca²⁺ pumps and release channels at membrane-membrane junctions of the sarcoplasmic reticulum (SR) demarcates cytoplasmic nanodomains, within which site- and function-specific Ca²⁺ signals arise. This chapter will describe how nanojunctions of the SR may: (1) define cytoplasmic nanospaces about the plasma membrane, mitochondria, contractile myofilaments, lysosomes, and the nucleus; (2) provide for functional segregation by restricting passive diffusion and by coordinating active ion transfer within a given nanospace via resident Ca²⁺ pumps and release channels; (3) select for contraction, relaxation, and/or changes in gene expression; and (4) facilitate the switch in myocyte phenotype through junctional reorganization. This should serve to highlight the need for further exploration of cellular nanojunctions and the mechanisms by which they operate, that will undoubtedly open up new therapeutic horizons.

Metabolomic Profiling of Human Urine as a Screen for Multiple Inborn Errors of Metabolism

AIMS

We wished to determine the efficacy of using urine as an analyte to screen for a broad range of metabolic products associated with multiple different types of inborn errors of metabolism (IEMs), using an automated mass spectrometry-based assay. Urine was compared with plasma samples from a similar cohort analyzed using the same assay. Specimens were analyzed using two different commonly utilized urine normalization methods based on creatinine and osmolality, respectively.

METHODS

Biochemical profiles for each sample (from both affected and unaffected subjects) were obtained using a mass spectrometry-based platform and population-based statistical analyses.

RESULTS

We identified over 1200 biochemicals from among 100 clinical urine samples and identified clear biochemical signatures for 16 of 18 IEM diseases tested. The two diseases that did not result in clear signatures, X-linked creatine transporter deficiency and ornithine transcarbamylase deficiency, were from individuals under treatment, which masked biomarker signatures. Overall the process variability and coefficient of variation for isolating and identifying biochemicals by running technical replicates of each urine sample was 10%.

CONCLUSIONS

A single urine sample analyzed with our integrated metabolomic platform can identify signatures of IEMs that are traditionally identified using many different assays and multiple sample types. Creatinine and osmolality-normalized data were robust to the detection of the disorders and samples tested here.

Hypoxia, AMPK activation and uterine artery vasoreactivity

Genes near adenosine monophosphate-activated protein kinase-α1 (PRKAA1) have been implicated in the greater uterine artery (UtA) blood flow and relative protection from fetal growth restriction seen in altitude-adapted Andean populations. Adenosine monophosphate-activated protein kinase (AMPK) activation vasodilates multiple vessels but whether AMPK is present in UtA or placental tissue and influences UtA vasoreactivity during normal or hypoxic pregnancy remains unknown. We studied isolated UtA and placenta from near-term C57BL/6J mice housed in normoxia (n = 8) or hypoxia (10% oxygen, n = 7-9) from day 14 to day 19, and placentas from non-labouring sea level (n = 3) or 3100 m (n = 3) women. Hypoxia increased AMPK immunostaining in near-term murine UtA and placental tissue. RT-PCR products for AMPK-α1 and -α2 isoforms and liver kinase B1 (LKB1; the upstream kinase activating AMPK) were present in murine and human placenta, and hypoxia increased LKB1 and AMPK-α1 and -α2 expression in the high- compared with low-altitude human placentas. Pharmacological AMPK activation by A769662 caused phenylephrine pre-constricted UtA from normoxic or hypoxic pregnant mice to dilate and this dilatation was partially reversed by the NOS inhibitor l-NAME. Hypoxic pregnancy sufficient to restrict fetal growth markedly augmented the UtA vasodilator effect of AMPK activation in opposition to PE constriction as the result of both NO-dependent and NO-independent mechanisms. We conclude that AMPK is activated during hypoxic pregnancy and that AMPK activation vasodilates the UtA, especially in hypoxic pregnancy. AMPK activation may be playing an adaptive role by limiting cellular energy depletion and helping to maintain utero-placental blood flow in hypoxic pregnancy.

Metabolite profiling reveals new insights into the regulation of serum urate in humans

Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.

Metabolomic profile of response to supplementation with β-carotene in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study

BACKGROUND

Two chemoprevention trials found that supplementation with β-carotene increased the risk of lung cancer and overall mortality. The biologic basis of these findings remains poorly understood.

OBJECTIVE

The objective was to compare the on-study change in metabolomic profiles of men randomly assigned to receive or not receive β-carotene supplements in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study.

DESIGN

The ATBC Study was a randomized, double-blind, placebo-controlled, primary cancer prevention trial; participants were Finnish male smokers assigned to 1 of 4 intervention groups: 1) α-tocopherol, 2) β-carotene, 3) both, or 4) placebo. Fifty participants with both baseline and follow-up fasting serum samples were randomly selected from each of these groups. Metabolomic profiling was conducted by mass spectrometry. The association between change in each metabolite over time and trial assignment (β-carotene or no β-carotene) was estimated by linear regression.

RESULTS

We measured 489 metabolites, and 17 changed significantly (P < 0.05) in response to β-carotene supplementation. More of these 17 metabolites were of xenobiotic origin than would be expected by chance (9 of 60, or 15%; P = 0.00004). We also found a suggestive association with 1,5-anhydroglucitol-a marker of glycemic control (β = -0.379, P = 0.0071).

CONCLUSIONS

Male smokers supplemented with β-carotene developed metabolomic profiles consistent with the induction of cytochrome P450 enzymes, the primary metabolizers of xenobiotics in humans. These findings may shed light on the increased mortality associated with β-carotene supplementation in the ATBC Study and suggest the need to explore potential interactions between medication use and dietary supplements, particularly among smokers. This trial was registered at clinicaltrials.gov as NCT00342992.

Metabolomic profiles in individuals with negative affectivity and social inhibition: a population-based study of Type D personality

BACKGROUND

Individuals with negative affectivity who are inhibited in social situations are characterized as distressed, or Type D, and have an increased risk of cardiovascular disease (CVD). The underlying biomechanisms that link this psychological affect to a pathological state are not well understood. This study applied a metabolomic approach to explore biochemical pathways that may contribute to the Type D personality.

METHODS

Type D personality was determined by the Type D Scale-14. Small molecule biochemicals were measured using two complementary mass-spectrometry based metabolomics platforms. Metabolic profiles of Type D and non-Type D participants within a population-based study in Southern Germany were compared in cross-sectional regression analyses. The PHQ-9 and GAD-7 instruments were also used to assess symptoms of depression and anxiety, respectively, within this metabolomic study.

RESULTS

668 metabolites were identified in the serum of 1502 participants (age 32-77); 386 of these individuals were classified as Type D. While demographic and biomedical characteristics were equally distributed between the groups, a higher level of depression and anxiety was observed in Type D individuals. Significantly lower levels of the tryptophan metabolite kynurenine were associated with Type D (p-value corrected for multiple testing=0.042), while no significant associations could be found for depression and anxiety. A Gaussian graphical model analysis enabled the identification of four potentially interesting metabolite networks that are enriched in metabolites (androsterone sulfate, tyrosine, indoxyl sulfate or caffeine) that associate nominally with Type D personality.

CONCLUSIONS

This study identified novel biochemical pathways associated with Type D personality and demonstrates that the application of metabolomic approaches in population studies can reveal mechanisms that may contribute to psychological health and disease.

Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information

Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these “unknown metabolites” is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical modeling with metabolomics to predict the identity of the unknown metabolites. We apply our method to original data of 517 metabolic traits, of which 225 are unknowns, and genotyping information on 655,658 genetic variants, measured in 1,768 human blood samples. We report previously undescribed genotype–metabotype associations for six distinct gene loci (SLC22A2, COMT, CYP3A5, CYP2C18, GBA3, UGT3A1) and one locus not related to any known gene (rs12413935). Overlaying the inferred genetic associations, metabolic networks, and knowledge-based pathway information, we derive testable hypotheses on the biochemical identities of 106 unknown metabolites. As a proof of principle, we experimentally confirm nine concrete predictions. We demonstrate the benefit of our method for the functional interpretation of previous metabolomics biomarker studies on liver detoxification, hypertension, and insulin resistance. Our approach is generic in nature and can be directly transferred to metabolomics data from different experimental platforms.

Genome-wide association studies on metabolomics data have demonstrated that genetic variation in metabolic enzymes and transporters leads to concentration changes in the respective metabolite levels. The conventional goal of these studies is the detection of novel interactions between the genome and the metabolic system, providing valuable insights for both basic research as well as clinical applications. In this study, we borrow the metabolomics GWAS concept for a novel, entirely different purpose. Metabolite measurements frequently produce signals where a certain substance can be reliably detected in the sample, but it has not yet been elucidated which specific metabolite this signal actually represents. The concept is comparable to a fingerprint: each one is uniquely identifiable, but as long as it is not registered in a database one cannot tell to whom this fingerprint belongs. Obviously, this issue tremendously reduces the usability of a metabolomics analyses. The genetic associations of such an “unknown,” however, give us concrete evidence of the metabolic pathway this substance is most probably involved in. Moreover, we complement the approach with a specific measure of correlation between metabolites, providing further evidence of the metabolic processes of the unknown. For a number of cases, this even allows for a concrete identity prediction, which we then experimentally validate in the lab.

Long-chain acylcarnitine deficiency in patients with chronic fatigue syndrome. Potential involvement of altered carnitine palmitoyltransferase-I activity

OBJECTIVE

The underlying aetiology of chronic fatigue syndrome is currently unknown; however, in the light of carnitine's critical role in mitochondrial energy production, it has been suggested that chronic fatigue syndrome may be associated with altered carnitine homeostasis. This study was conducted to comparatively examine full endogenous carnitine profiles in patients with chronic fatigue syndrome and healthy controls.

DESIGN

A cross-sectional, observational study.

SETTING AND SUBJECTS

Forty-four patients with chronic fatigue syndrome and 49 age- and gender-matched healthy controls were recruited from the community and studied at the School of Pharmacy & Medical Sciences, University of South Australia.

MAIN OUTCOME MEASURES

All participants completed a fatigue severity scale questionnaire and had a single fasting blood sample collected which was analysed for l-carnitine and 35 individual acylcarnitine concentrations in plasma by LC-MS/MS.

RESULTS

Patients with chronic fatigue syndrome exhibited significantly altered concentrations of C8:1, C12DC, C14, C16:1, C18, C18:1, C18:2 and C18:1-OH acylcarnitines; of particular note, oleyl-L-carnitine (C18:1) and linoleyl-L-carnitine (C18:2) were, on average, 30-40% lower in patients than controls (P < 0.0001). Significant correlations between acylcarnitine concentrations and clinical symptomology were also demonstrated.

CONCLUSIONS

It is proposed that this disturbance in carnitine homeostasis is reflective of a reduction in carnitine palmitoyltransferase-I (CPT-I) activity, possibly a result of the accumulation of omega-6 fatty acids previously observed in this patient population. It is hypothesized that the administration of omega-3 fatty acids in combination with l-carnitine would increase CPT-I activity and improve chronic fatigue syndrome symptomology.

A Cochrane review of the evidence for non-surgical interventions for flexible pediatric flat feet

The pediatric flat foot is a frequent presentation in clinical practice, a common concern to parents and continues to be debated within professional ranks. As an entity, it is confused by varied classifications, the notion of well-intended prevention and unsubstantiated, if common, treatment. The available prevalence estimates are all limited by variable sampling, assessment measures and age groups and hence result in disparate findings (0.6-77.9%). Consistently, flat foot has been found to normally reduce with age. The normal findings of flat foot versus children's age estimates that approximately 45% of preschool children, and 15% of older children (average age 10 years) have flat feet. Few flexible flat feet have been found to be symptomatic. Joint hypermobility and increased weight or obesity may increase flat foot prevalence, independently of age. Most attempts at classification of flat foot morphology include the arch, heel position and foot flexibility. Usual assessment methods are footprint measures, X-rays and visual (scaled) observations. There is no standardized framework from which to evaluate the pediatric flat foot. The pediatric flat foot is often unnecessarily treated, being ill-defined and of uncertain prognosis. Contemporary management of the pediatric flat foot is directed algorithmically within this review, according to pain, age, flexibility; considering gender, weight, and joint hypermobility. When foot orthoses are indicated, inexpensive generic appliances will usually suffice. Customised foot orthoses should be reserved for children with foot pain and arthritis, for unusual morphology, or unresponsive cases. Surgery is rarely indicated for pediatric flat foot (unless rigid) and only at the failure of thorough conservative management. The assessment of the pediatric flatfoot needs to be considered with reference to the epidemiological findings, where there is consensus that pediatric flexible flat foot reduces with age and that most children are asymptomatic. Globally, there is need for a standard by which the pediatric flat foot is assessed classified and managed. Until then, assessment should utilize the available evidence-based management model, the p-FFP Future research needs to evaluate the pediatric flat foot from representative samples, of healthy and known disease-group children prospectively, and using validated assessment instruments. The preliminary findings of the benefits of foot exercises, and discrete investigation into the effects of shoes and footwear use are also warranted.

Organization of GC/MS and LC/MS metabolomics data into chemical libraries

Background

Metabolomics experiments involve generating and comparing small molecule (metabolite) profiles from complex mixture samples to identify those metabolites that are modulated in altered states (e.g., disease, drug treatment, toxin exposure). One non-targeted metabolomics approach attempts to identify and interrogate all small molecules in a sample using GC or LC separation followed by MS or MSⁿ detection. Analysis of the resulting large, multifaceted data sets to rapidly and accurately identify the metabolites is a challenging task that relies on the availability of chemical libraries of metabolite spectral signatures. A method for analyzing spectrometry data to identify and Quantify Individual Components in a Sample, (QUICS), enables generation of chemical library entries from known standards and, importantly, from unknown metabolites present in experimental samples but without a corresponding library entry. This method accounts for all ions in a sample spectrum, performs library matches, and allows review of the data to quality check library entries. The QUICS method identifies ions related to any given metabolite by correlating ion data across the complete set of experimental samples, thus revealing subtle spectral trends that may not be evident when viewing individual samples and are likely to be indicative of the presence of one or more otherwise obscured metabolites.

Results

LC-MS/MS or GC-MS data from 33 liver samples were analyzed simultaneously which exploited the inherent biological diversity of the samples and the largely non-covariant chemical nature of the metabolites when viewed over multiple samples. Ions were partitioned by both retention time (RT) and covariance which grouped ions from a single common underlying metabolite. This approach benefitted from using mass, time and intensity data in aggregate over the entire sample set to reject outliers and noise thereby producing higher quality chemical identities. The aggregated data was matched to reference chemical libraries to aid in identifying the ion set as a known metabolite or as a new unknown biochemical to be added to the library.

Conclusion

The QUICS methodology enabled rapid, in-depth evaluation of all possible metabolites (known and unknown) within a set of samples to identify the metabolites and, for those that did not have an entry in the reference library, to create a library entry to identify that metabolite in future studies.

Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems

To address the challenges associated with metabolomics analyses, such as identification of chemical structures and elimination of experimental artifacts, we developed a platform that integrated the chemical analysis, including identification and relative quantification, data reduction, and quality assurance components of the process. The analytical platform incorporated two separate ultrahigh performance liquid chromatography/tandem mass spectrometry (UHPLC/MS/MS(2)) injections; one injection was optimized for basic species, and the other was optimized for acidic species. This approach permitted the detection of 339 small molecules, a total instrument analysis time of 24 min (two injections at 12 min each), while maintaining a median process variability of 9%. The resulting MS/MS(2) data were searched against an in-house generated authentic standard library that included retention time, molecular weight (m/z), preferred adducts, and in-source fragments as well as their associated MS/MS spectra for all molecules in the library. The library allowed the rapid and high-confidence identification of the experimentally detected molecules based on a multiparameter match without need for additional analyses. This integrated platform enabled the high-throughput collection and relative quantitative analysis of analytical data and identified a large number and broad spectrum of molecules with a high degree of confidence.

Effect of ketoprofen and its enantiomers on the renal disposition of methotrexate in the isolated perfused rat kidney

Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to inhibit the renal tubular secretion of methotrexate. However, the relative contribution of the active S- and inactive R-enantiomers is unknown. This study examined the effect of racemic ketoprofen and its enantiomers on the renal disposition of methotrexate in the isolated perfused rat kidney (IPK). Nineteen kidneys were divided between a control and three treatment groups. Controls were perfused with methotrexate alone (25 μg mL−1, n = 5) over three 30-min periods. Treatment groups were perfused with methotrexate (25 μg mL−1) for the first period, followed by a second period of methotrexate (25 μg mL−1) plus R- (n = 5), S- (n = 5) or RS-ketoprofen (n = 4) at 25 μg mL−1, and a third period of methotrexate (25 μg mL−1) plus R-, S- or RS-ketoprofen (50 μg mL−1). Perfusate and urine were collected over 10-min intervals. Methotrexate was measured by HPLC and its binding in perfusate by ultrafiltration. The clearance ratio (CR) for methotrexate was obtained by dividing the renal clearance by the product of its fraction unbound and the glomerular filtration rate. During control experiments, there was no significant change in the CR over 90 min. R-, S- and RS-ketoprofen at 50 μg mL−1 reduced the CR of methotrexate significantly, but there was no difference between the three groups. While the enantiomers of ketoprofen reduced the renal excretion of methotrexate, the interaction was not enantioselective.

Modulation of O(2) sensitive K (+) channels by AMP-activated protein kinase

Hypoxic inhibition of K(+) channels in type I cells is believed to be of central importance in carotid body chemotransduction. We have recently suggested that hypoxic channel inhibition is mediated by AMP-activated protein kinase (AMPK). Here, we have further explored the modulation by AMPK of recombinant K(+) channels (expressed in HEK293 cells) whose native counterparts are considered O(2)-sensitive in the rat carotid body. Inhibition of maxiK channels by AMPK activation with AICAR was found to be independent of [Ca(2+)](i) and occurred regardless of whether the alpha subunit was co-expressed with an auxiliary beta subunit. All effects of AICAR were fully reversed by the AMPK inhibitor compound C. MaxiK channels were also inhibited by the novel AMPK activator A-769662 and by intracellular dialysis with the constitutively active, truncated AMPK mutant, T172D. The molecular identity of the O(2)-sensitive leak K(+) conductance in rat type I cells remains unclear, but shares similarities with TASK-1 and TASK-3. Recombinant TASK-1 was insensitive to AICAR. However, TASK-3 was inhibited by either AICAR or A-769662 in a manner which was reversed by compound C. These data highlight a role for AMPK in the modulation of two proposed O(2) sensitive K(+) channels found in the carotid body.

Analysis of the adult human plasma metabolome

OBJECTIVE

It is well established that disease states are associated with biochemical changes (e.g., diabetes/glucose, cardiovascular disease/cholesterol), as are responses to chemical agents (e.g., medications, toxins, xenobiotics). Recently, nontargeted methods have been used to identify the small molecules (metabolites) in a biological sample to uncover many of the biochemical changes associated with a disease state or chemical response. Given that these experimental results may be influenced by the composition of the cohort, in the present study we assessed the effects of age, sex and race on the relative concentrations of small molecules (metabolites) in the blood of healthy adults.

METHODS

Using gas- and liquid-chromatography in combination with mass spectrometry, a nontargeted metabolomic analysis was performed on plasma collected from an age- and sex-balanced cohort of 269 individuals.

RESULTS

Of the more than 300 unique compounds that were detected, significant changes in the relative concentration of more than 100 metabolites were associated with age. Many fewer differences were associated with sex and fewer still with race. Changes in protein, energy and lipid metabolism, as well as oxidative stress, were observed with increasing age. Tricarboxylic acid intermediates, creatine, essential and nonessential amino acids, urea, ornithine, polyamines and oxidative stress markers (e.g., oxoproline, hippurate) increased with age. Compounds related to lipid metabolism, including fatty acids, carnitine, beta-hydroxybutyrate and cholesterol, were lower in the blood of younger individuals. By contrast, relative concentrations of dehydroepiandrosterone-sulfate (a proposed antiaging androgen) were lowest in the oldest age group. Certain xenobiotics (e.g., caffeine) were higher in older subjects, possibly reflecting decreases in hepatic cytochrome P450 activity.

CONCLUSIONS

Our nontargeted analytical approach detected a large number of metabolites, including those that were found to be statistically altered with age, sex or race. Age-associated changes were more pronounced than those related to differences in sex or race in the population group we studied. Age, sex and race can be confounding factors when comparing different groups in clinical studies. Future studies to determine the influence of diet, lifestyle and medication are also warranted.

Isosteviol reduces plasma glucose levels in the intravenous glucose tolerance test in Zucker diabetic fatty rats

AIM

The aim of this study was to test the effect of isosteviol on blood glucose and insulin levels during the intravenous glucose tolerance test (IVGTT) in Wistar and Zucker diabetic fatty (ZDF) rats.

METHODS

ZDF rats were divided into a control and three isosteviol treatment (1, 5 and 10 mg/kg) groups. Wistar rats were divided into a control group and an isosteviol treatment group (10 mg/kg). The rats were fasted for 12 h prior to infusion of isosteviol and glucose (1.0 g/kg). Blood samples were taken at 0, 5, 15, 30, 60, 90 and 120 min after the injection of glucose. Glucose concentrations were determined by the glucose oxidase method, and plasma insulin was analysed by radioimmunoassay. The area under the curve (AUC) of the net change in plasma glucose concentration was used to compare the isosteviol treatment and control groups.

RESULTS

In ZDF rats, isosteviol at 5 and 10 mg/kg caused a significant (p < 0.05) reduction in the AUC of glucose during the IVGTT. However, isosteviol did not increase plasma insulin concentrations in ZDF rats. In Wistar rats, isosteviol did not significantly affect plasma glucose or insulin levels during the IVGTT.

CONCLUSION

Isosteviol exerts an antihyperglycaemic effect during IVGTT in ZDF rats but not in Wistar rats. Isosteviol has no significant effect on plasma insulin concentrations. The glucose-lowering effect of isosteviol may be due to changes in the sensitivity of peripheral tissues to insulin.

Transference in the nurse-patient relationship

The therapeutic relationship has been considered foundational to psychiatric nursing practice since at least the mid-20th century. However, this does not, in itself, guarantee either its continuity or relevance to current practice. Concepts such as the therapeutic relationship require sustained attention, both in theory and in practice, to illustrate ongoing relevance to the discipline. This paper addresses the therapeutic relationship in psychiatric nursing via aspects of psychoanalytic theory, particularly the notion of transference, as theorized by both Freud and Lacan. Two case fragments provide practice material, through which transference in the nurse-patient relationship is explored. The nurse, in the context of his/her relationship with the patient, a sick stranger, offers both a listening and the potential development of transference. This transference can be experienced, in part, as a form of attachment to the nurse, one that is not regarded pejoratively as dependency. There is the potential, within the nurse-patient relationship, for a psychical holding to develop, one from within which both the patient can speak and transference might arise. It is argued that listening to the patient has the potential to assist the patient and, with the development of transference, can provide the context for important work.

Identification of class I MHC-associated phosphopeptides as targets for cancer immunotherapy

Alterations in phosphorylation of cellular proteins are a hallmark of malignant transformation. Degradation of these phosphoproteins could generate cancer-specific class I MHC-associated phosphopeptides recognizable by CD8+ T lymphocytes. In a comparative analysis of phosphopeptides presented on the surface of melanoma, ovarian carcinoma, and B lymphoblastoid cells, we find 5 of 36 that are restricted to the solid tumors and common to both cancers. Differential presentation of these peptides can result from differential phosphorylation of the source proteins. Recognition of the peptides on cancer cells by phosphopeptide-specific CD8+ T lymphocytes validates the potential of these phosphopeptides as immunotherapeutic targets.

Prediction of drug absorption based on immobilized artificial membrane (IAM) chromatography separation and calculated molecular descriptors

The aim of this study was to evaluate the usefulness of IAM chromatography in building a model that would allow prediction of drug absorption in humans. The human intestinal absorption values (%HIA) for 52 drugs with low to high intestinal absorption were collected from the literature. The retention (capacity factor, k') of each drug was measured by reverse-phase HPLC using an IAM.PC.DD2 column (prepared with phosphatidylcholine analogs, 12 microM, 300A, 15 cm x 4.6 mm) with an eluent of acetonitrile-0.1M phosphate buffer at pH 5.4. In addition, 76 molecular descriptors and solubility parameters for each drug were calculated using ChemSW from the 3D-molecular structures. Stepwise regression was employed to develop a regression equation that would correlate %HIA with molecular descriptors and k'. Human intestinal absorption was reciprocally correlated to the negative value of the capacity factor (-1/k') (R=0.64). The correlation was further improved with the addition of molecular descriptors representing molecular size and shape (molecular width, length and depth) solubility (solubility parameter, HLB, hydrophilic surface area) and polarity (dipole, polar surface area) (R=0.83). Experimentally measured IAM chromatography retention values and calculated molecular descriptors and solubility parameters can be used to predict intestinal absorption of drugs in humans. Developed QSAR can be used as a screening method in the designing of drugs with appropriate IA and for the selection of drug candidates in the early stage of drug discovery process.

The PANE1 gene encodes a novel human minor histocompatibility antigen that is selectively expressed in B-lymphoid cells and B-CLL

Minor histocompatibility antigens (mHAg's) are peptides encoded by polymorphic genes that are presented by major histocompatibility complex (MHC) molecules and recognized by T cells in recipients of allogeneic hematopoietic cell transplants. Here we report that an alternative transcript of the proliferation-associated nuclear element 1 (PANE1) gene encodes a novel human leukocyte antigen (HLA)-A(*)0301-restricted mHAg that is selectively expressed in B-lymphoid cells. The antigenic peptide is entirely encoded within a unique exon not present in other PANE1 transcripts. Sequencing of PANE1 alleles in mHAg-positive and mHAg-negative cells demonstrates that differential T-cell recognition is due to a single nucleotide polymorphism within the variant exon that replaces an arginine codon with a translation termination codon. The PANE1 transcript that encodes the mHAg is expressed at high levels in resting CD19(+) B cells and B-lineage chronic lymphocytic leukemia (B-CLL) cells, and at significantly lower levels in activated B cells. Activation of B-CLL cells through CD40 ligand (CD40L) stimulation decreases expression of the mHAg-encoding PANE1 transcript and reciprocally increases expression of PANE1 transcripts lacking the mHAg-encoding exon. These studies suggest distinct roles for different PANE1 isoforms in resting compared with activated CD19(+) cells, and identify PANE1 as a potential therapeutic target in B-CLL.

Proteomic Characterization of Messenger Ribonucleoprotein Complexes Bound to Nontranslated or Translated Poly(A) mRNAs in the Rat Cerebral Cortex

Receptor-triggered control of local postsynaptic protein synthesis plays a crucial role for enabling long lasting changes in synaptic functions, but signaling pathways that link receptor stimulation with translational control remain poorly known. Among the putative regulatory factors are mRNA-binding proteins (messenger ribonucleoprotein, mRNP), which control the fate of cytosolic localized mRNAs. Based on the assumption that a subset of mRNA is maintained in an inactive state, mRNP-mRNA complexes were separated into polysome-bound (translated) and polysome-free (nontranslated) fractions by sucrose density centrifugation. Poly(A) mRNA-mRNP complexes were purified from a postmitochondrial extract of rat cerebral cortex by oligo(dT)-cellulose affinity chromatography. The mRNA processing proteins were characterized, from solution, by a nanoflow reverse phase-high pressure liquid chromatography-mu-electrospray ionization mass spectrometry. The majority of detected mRNA-binding proteins was found in both fractions. However, a small number of proteins appeared to be fraction-specific. This subset of proteins is by far the most interesting because the proteins are potentially involved in controlling an activity-dependent onset of translation. They include transducer proteins, kinases, and anchor proteins. This study of the mRNP proteome is the first step in allowing future experimentation to characterize individual proteins responsible for mRNA processing and translation in dendrites.

The quantification of paracetamol, paracetamol glucuronide and paracetamol sulphate in plasma and urine using a single high-performance liquid chromatography assay

A range of analytical methods exist for the determination of paracetamol in biological fluids. However, to understand the fate of paracetamol and the effect of other drugs on its disposition in vivo, the major metabolites require quantification in urine and plasma. A method to simultaneously quantify paracetamol, paracetamol glucuronide (PG) and paracetamol sulphate (PS) in plasma and urine with superior sensitivity is therefore desired, especially if the volume of plasma available is low. A simple isocratic reverse phase high-performance liquid chromatography (HPLC) assay with spectrophotometric detection has been developed. The method, requiring only 100 microl of plasma and 50 microl of urine, utilizes a reversed-phase C18 column, a wavelength of 254 nm for detection and a mobile phase composed of potassium dihydrogen orthophosphate (0.1 M)-isopropanol-tetrahydrofuran (THF) (100:1.5:0.1, v/v/v) adjusted to pH 3.7 with phosphoric acid. The method is sensitive and linear in plasma within a concentration range from 0.4 to 200 microM for paracetamol, PG and PS. For PG and PS in urine, the method is sensitive and linear within a concentration range from 100 to 20,000 microM. Over these ranges, accuracy and precision were less than 12%. The assay has been used to measure concentrations of paracetamol and the two metabolites in plasma collected by finger-prick sampling and of the metabolites in urine from healthy volunteers administered a single oral dose of 1000 mg of paracetamol.

Tapasin Is a Facilitator, Not an Editor, of Class I MHC Peptide Binding

Tapasin has been proposed to function as a peptide editor to displace lower affinity peptides and/or to favor the binding of high affinity peptides. Consistent with this, cell surface HLA-B8 molecules in tapasin-deficient cells were less stable and the peptide repertoire was substantially altered. However, the binding affinities of peptides expressed in the absence of tapasin were unexpectedly higher, not lower. The peptide repertoire from cells expressing soluble tapasin was similar in both appearance and affinity to that presented in the presence of full-length tapasin, but the HLA-B8 molecules showed altered cell surface stability characteristics. Similarly, the binding affinities of HLA-A*0201-associated peptides from tapasin(+) and tapasin(-) cells were equivalent, although steady state HLA-A*0201 cell surface expression was decreased and the molecules demonstrated reduced cell surface stability on tapasin(-) cells. These data are inconsistent with a role for tapasin as a peptide editor. Instead, we propose that tapasin acts as a peptide facilitator. In this role, it stabilizes the peptide-free conformation of class I MHC molecules in the endoplasmic reticulum and thus increases the number and variety of peptides bound to class I MHC. Full-length tapasin then confers additional stability on class I MHC molecules that are already associated with peptides.

Identification of the beta cell antigen targeted by a prevalent population of pathogenic CD8+ T cells in autoimmune diabetes

Type 1 diabetes is an autoimmune disease in which autoreactive T cells attack and destroy the insulin-producing pancreatic beta cells. CD8+ T cells are essential for this beta cell destruction, yet their specific antigenic targets are largely unknown. Here, we reveal that the autoantigen targeted by a prevalent population of pathogenic CD8+ T cells in nonobese diabetic mice is islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP). Through tetramer technology, IGRP-reactive T cells are readily detected in islets and peripheral blood directly ex vivo. The human IGRP gene maps to a diabetes susceptibility locus, suggesting that IGRP also may be an antigen for pathogenic T cells in human type 1 diabetes and, thus, a new, potential target for diagnostic and therapeutic approaches.

A receptor for activated C kinase is part of messenger ribonucleoprotein complexes associated with polyA-mRNAs in neurons

Long-lasting changes in synaptic functions after an appropriate stimulus require altered protein expression at the synapse. To restrict changes in protein composition to activated synapses, proteins may be synthesized locally as a result of transmitter receptor-triggered signaling pathways. Second messenger-controlled mechanisms that affect mRNA translation are essentially unknown. Here we report that a receptor for activated C kinase, RACK1, is a component of messenger ribonucleoprotein (mRNP) complexes. RACK1 is predominantly associated with polysome-bound, polyA-mRNAs that are being actively translated. We find it to be present in a complex with beta-tubulin and at least two mRNA-binding proteins, polyA-binding protein 1 and a 130 kDa polyA-mRNA binding protein (KIAA0217). Activation of PKCbeta2 in vitro by phosphatidylserine/diacylglycerol or in hippocampal slices by metabotropic glutamate receptor stimulation increased the amount of RACK1/PKCbeta2 associated with polysome-bound polyA-mRNAs. In vitro, PKCbeta2 can phosphorylate a subset of polyA-mRNA-associated proteins that are also phosphorylated under in vivo conditions. On the basis of these findings plus the somatodendritic localization of RACK1, we hypothesize that metabotropic glutamate receptor-triggered binding of activated PKCbeta2 to mRNP complexes bound to polyA-mRNAs is involved in activity-triggered control of protein synthesis.

Comparative pharmacology of S(+)-ibuprofen and (RS)-ibuprofen

Racemic ibuprofen, which contains equal quantities of R(-)-ibuprofen and S(+)-ibuprofen, has been used as an anti-inflammatory and analgesic agent for over 30 years. Although the S(+)-enantiomer is capable of inhibiting cyclooxygenase (COX) at clinically relevant concentrations, R(-)-ibuprofen is not a COX inhibitor. The two enantiomers of ibuprofen are therefore different in terms of their pharmacological properties and may be regarded as two different 'drugs'. They also differ in terms of their metabolic profiles. For example, R(-)-ibuprofen becomes involved in pathways of lipid metabolism and is incorporated into triglycerides along with endogenous fatty acids. S(+)-Ibuprofen does not appear to become involved in these unusual metabolic reactions, which is why S(+)-ibuprofen is regarded as being metabolically 'cleaner' than racemic ibuprofen. When racemic ibuprofen is given to humans, a substantial fraction of the dose of R(-)-ibuprofen (50%-60%) undergoes 'metabolic inversion' to yield S(+)-ibuprofen. On this basis, it has been argued that to obtain clinical effects that are comparable to those of a given dose of racemic ibuprofen, the dose of S(+)-ibuprofen would need to be about 75% of the dose of the racemate. However, this 'pharmacokinetic' rationale does not take into account the fact that inversion is not instantaneous, that there is variability in the extent of inversion between individuals, and that the kinetics of inversion may differ depending on the dosing situations. For example, the extent of inversion appears to be reduced when the racemate is given to patients experiencing acute pain. Recent studies have demonstrated that the clinical benefits of racemic ibuprofen can be derived from the administration of the single S(+)-enantiomer at a dose that is half that of the racemate. For example, 200 mg of S(+)-ibuprofen has been found to be superior or at least equivalent to 400 mg of the racemate in the relief of dental pain. Possible explanations for this higher than expected efficacy of S(+)-ibuprofen are considered.