Pattern Of Urinary Metabolites Research Articles

Evaluation of a self-monitoring protocol for assessing soot and polycyclic aromatic hydrocarbon exposure among chimney sweeps.

Traditional methods for measuring chemical exposure have challenges in terms of obtaining sufficient data; therefore, improved methods for better assessing occupational exposure are needed. One possible approach to mitigate these challenges is to use self-monitoring methods such as sensors, diaries, or biomarkers. In the present study, a self-monitored method for measuring soot exposure, which included real-time air monitoring, a work diary, and the collection of urine samples, was evaluated. To validate the method, exposure measurements during the workday and diary entries were compared with velocities calculated from GPS tracking and the expected polycyclic aromatic hydrocarbon (PAH) metabolite patterns in urine. The method was applied with chimney sweeps, an occupational group at a high risk of many severe health outcomes and for whom effective control measures for reducing exposure are needed. In the study, 20 chimney sweeps followed a self-monitoring protocol for 8 consecutive workdays. Personal exposure to soot was measured as black carbon (BC) using micro-aethalometers. A diary was used to record the work tasks performed, and urine samples were collected and analysed for PAH metabolites. From the expected 160 full day measurements, 146 (91%) BC measurements and 149 (93%) diaries were collected. From the expected 320 urine samples, 304 (95%) were collected. The tasks noted in the diaries overlapped with information obtained from the GPS tracking of the chimney sweeps, which covered 96% of the measurement time. The PAH metabolites in urine increased during the work week. Factors believed to have positively influenced the sample collection and task documentation were the highly motivated participants and the continuous presence of trained occupational hygiene professionals during the planning of the study and throughout the measurement stage, during which they were available to inform, instruct, and address questions. In conclusion, the self-monitored protocol used in this study with chimney sweeps is a valuable and valid method that can be used to collect larger numbers of samples. This is especially valuable for occupations in which the employees are working independently and the exposure is difficult to monitor with traditional occupational hygiene methods.

Association of Ultraprocessed Foods Intake with Untargeted Metabolomics Profiles in Adolescents and Young Adults in the DONALD Cohort Study

BackgroundHigh consumption of ultraprocessed foods (UPFs) continues to draw significant public health interest because of the associated negative health outcomes. Metabolomics can contribute to the understanding of the biological mechanisms through which UPFs may influence health. ObjectivesTo investigate urine and plasma metabolomic biomarkers of UPF intake in adolescents and young adults. MethodsWe used data from the Dortmund Nutritional and Anthropometric Longitudinally Designed study to investigate cross-sectional associations of UPF intake with concentrations of urine metabolites in adolescents using 3d weighed dietary records (3d-WDR) and 24-h urine samples (n = 339), and associations of repeatedly assessed UPF intake with concentrations of circulating plasma metabolites in young adults with 3–6 3d-WDRs within 5 y preceding blood measurement (n = 195). Urine and plasma samples were analyzed using mass spectrometry-based metabolomics. Biosample-specific metabolite patterns (MPs) were determined using robust sparse principal components analysis. Multivariable linear regression models were applied to assess the associations of UPF consumption (as a percentage of total food intake in g/d) with concentrations of individual metabolites and MP scores. ResultsThe median proportion of UPF intake was 22.0% [interquartile range (IQR): 12.3, 32.9] in adolescents and 23.2% (IQR: 16.0, 31.6) in young adults. We identified 42 and 6 UPF intake-associated metabolites in urine and plasma samples, respectively. One urinary MP, “xenobiotics and amino acids” [β = 0.042, 95% confidence interval (CI): 0.014, 0.070] and 1 plasma MP, “lipids, xenobiotics, and amino acids” (β = 0.074, 95% CI: 0.031, 0.117) showed positive association with UPF intake. Both patterns shared 29 metabolites, mostly of xenobiotic metabolism. ConclusionsWe identified urine and plasma metabolites associated with UPF intake in adolescents and young adults, which may represent some of the biological mechanisms through which UPFs may influence metabolism and health.

Patterns of urinary organophosphate ester metabolite trajectories in children: the HOME Study.

Organophosphate esters (OPEs) have replaced flame retardant polybrominated diphenyl ethers as flame retardants in consumer products, but few longitudinal studies have characterized childhood OPE exposure. We aimed to examine the exposure pattern of urinary OPE metabolites in children. We quantified three urinary OPE metabolites five times in children (1, 2, 3, 5, 8 years) from 312 mother-child pairs in the Health Outcomes and Measures of the Environment (HOME) Study, a prospective pregnancy and birth cohort in Cincinnati, Ohio, USA. We examined the associations of average maternal OPE metabolite concentrations with OPE metabolite concentrations in childhood, characterized childhood OPE trajectories with latent class growth analysis (LCGA), and examined factors related to trajectory membership. Bis(2-chloroethyl) phosphate (BCEP) had the lowest median concentrations over time (0.66-0.97 mg/L) while the median concentrations of bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) increased with age (1.44-3.80 mg/L). The median concentrations of diphenyl phosphate (DPHP) fluctuated between 1.96 and 2.69 mg/L. Intraclass correlation coefficients for urinary metabolites measured at five time points indicated high variability within individuals (0.13-0.24). Average maternal urinary BCEP and BDCIPP were associated with concentrations in early childhood. Maternal education, the birth year of the child, and having a carpet in the main activity room were associated with BCEP and BDCIPP trajectory while none of the factors were associated with DPHP trajectory. The trajectory analysis showed different patterns of urinary OPE metabolite concentrations, suggesting the need to collect multiple samples to adequately reflect OPE exposure. In this well-established cohort, we evaluated the patterns of urinary OPE metabolites in children ages 1-8 years. The number of repeated measures over childhood has not been achieved in prior studies. Our results suggested the high variability of urinary OPE metabolites within individuals. Maternal metabolite concentrations during pregnancy were related to child concentrations at ages 1-3 years. BCEP, BDCIPP, and DPHP demonstrated different trajectories in children, which suggests that multiple samples may be required to capture OPE exposure patterns in childhood.

Metabolomic evidence of independent biotransformation pathways for terpenes in two specialist mammalian herbivores (genus Neotoma).

Herbivory is common in mammals, yet our understanding of detoxification processes used by mammals to biotransform plant secondary compounds (PSCs) is limited. Specialist herbivores are thought to have evolved detoxification mechanisms that rely more heavily on energetically cheap Phase I biotransformation reactions to process high levels of PSCs in their diets. We explored this hypothesis by comparing the urinary metabolite patterns of two specialist herbivores (genus Neotoma). Neotoma stephensi is an obligate specialist on one-seeded juniper (Juniperus monosperma). Neotoma lepida is a generalist forager across its range, yet populations in the Great Basin specialize on Utah juniper (J. osteosperma). While both juniper species have high levels of terpenes, the terpene profiles and quantities differ between the two. Individuals from both woodrat species were fed diets of each juniper in a cross-over design. Urine, collected over a 24-h period, was extracted and analyzed in an untargeted metabolomics approach using both GC-MS and HPLC-MS/MS. The obligate specialist N. stephensi excreted a unique pattern of Phase I metabolites when fed its native juniper, while N. lepida excreted a unique pattern of Phase II metabolites when fed its native juniper. Both woodrat species utilized the Phase II metabolic pathway of glucuronidation more heavily when consuming the more chemically diverse J. osteosperma, and N. stephensi utilized less glucuronidation than N. lepida when consuming J. monosperma. These results are consistent with the hypothesis that obligate specialists may have evolved unique and efficient biotransformation mechanisms for dealing with PSCs in their diet.

Exploring the association of physical activity with the plasma and urine metabolome in adolescents and young adults

BackgroundRegular physical activity elicits many health benefits. However, the underlying molecular mechanisms through which physical activity influences overall health are less understood. Untargeted metabolomics enables system-wide mapping of molecular perturbations which may lend insights into physiological responses to regular physical activity. In this study, we investigated the associations of habitual physical activity with plasma and urine metabolome in adolescents and young adults.MethodsThis cross-sectional study included participants from the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study with plasma samples n = 365 (median age: 18.4 (18.1, 25.0) years, 58% females) and 24 h urine samples n = 215 (median age: 18.1 (17.1, 18.2) years, 51% females). Habitual physical activity was assessed using a validated Adolescent Physical Activity Recall Questionnaire. Plasma and urine metabolite concentrations were determined using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) methods. In a sex-stratified analysis, we conducted principal component analysis (PCA) to reduce the dimensionality of metabolite data and to create metabolite patterns. Multivariable linear regression models were then applied to assess the associations between self-reported physical activity (metabolic equivalent of task (MET)-hours per week) with single metabolites and metabolite patterns, adjusted for potential confounders and controlling the false discovery rate (FDR) at 5% for each set of regressions.ResultsHabitual physical activity was positively associated with the “lipid, amino acids and xenometabolite” pattern in the plasma samples of male participants only (β = 1.02; 95% CI: 1.01, 1.04, p = 0.001, adjusted p = 0.042). In both sexes, no association of physical activity with single metabolites in plasma and urine and metabolite patterns in urine was found (all adjusted p > 0.05).ConclusionsOur explorative study suggests that habitual physical activity is associated with alterations of a group of metabolites reflected in the plasma metabolite pattern in males. These perturbations may lend insights into some of underlying mechanisms that modulate effects of physical activity.

Geospatial determinants of urinary insecticide concentrations and internalizing disorders in Ecuadorian adolescents

Background: Depression and anxiety are top 5 contributors of increased disability-adjusted life years. Pesticide exposure has been linked to increased depression and anxiety; evidence in adolescents is limited. This study assesses clustering patterns of mental health symptoms and urinary pesticide metabolites, and their relationships with home proximity to floricultural crops in an Ecuadorean agricultural county. Methods: We assessed 514 adolescents (11-17 years) who lived in the 5 parishes of Pedro Moncayo County, Ecuador. We measured 8 urinary metabolites for neonicotinoid, pyrethroid and organophosphate pesticides, and assessed depression and anxiety symptoms using standardized questionnaires. Getis-Ord Gi* evaluated spatial clustering to identify hot and cold spots of pesticide metabolites, depression symptoms and anxiety symptoms. The association between home distance to floricultural greenhouses and anxiety/depression scores were tested using generalized estimating equations, adjusting for confounders. Results: The floricultural surface areas (% of total land) across parishes were: Tocachi: 0.12 km2 (0.001%), La Esperanza: 0.43 km2 (0.01%), Malchingui: 0.04 km2 (0.05%), Tupigachi: 5.36 km2 (12.5%), and Tabacundo: 9.36 km2 (13.2%). The average scores for anxiety (53.0 [SD=9.31]) and depression (58.8 [SD=9.61]) were in the anticipated range. We observed hotspots for anxiety and depression symptoms in Tupigachi (95-99%C [confidence]) and Tabacundo (90-95%C). There were hotpots for organophosphate and pyrethroid metabolites in Tupigachi, coinciding with anxiety and depression hotspots (malathion dicarboxylic acid [90%-99%C], para-nitrophenol [95%], 2-isopropyl-4-methyl-6-hydroxypyrimidine, trans-3-(2,2-Dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid [90%C], and 3-phenoxybenzoic acid [95%C]). Additionally, greater proximity to greenhouses was associated with greater depression (βper100m=0.94 [95%CI: 0.53, 1.36]) and anxiety (βper100m= 0.32 [95%CI: 0.11, 0.54]) scores. Conclusions: We observed hotspots in Tupigachi for both anxiety, depression, and multiple organophosphate/pyrethroid metabolites. Throughout the county, residential proximity to floricultural crops was associated with higher anxiety and depression symptoms. This suggests that off-target pesticide drift from crops may be a contributor to increased internalizing behaviors. Keywords: Pesticides

Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes.

Aims/HypothesisLarge-scale prediabetes screening is still a challenge since fasting blood glucose and HbA1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites.MethodsNon-targeted, modification group-assisted metabolomics by liquid chromatography–mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA1c, and fasting insulin.ResultsFemale- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA1c, insulin, or a combination of FPG and HbA1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA1c. In comparison, the AUCs of FPG, HbA1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide).Conclusions/InterpretationOur results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.

Addition of grapes to both a standard and a high-fat Western pattern diet modifies hepatic and urinary metabolite profiles in the mouse.

The benefits of fruit and vegetable dietary consumption are largely defined in epidemiological terms. Relatively little is known about the discrete effects on metabolic pathways elicited by individual dietary fruits and vegetables. To address this, grape powder was added to both a standard and a high-fat Western pattern diet given to 10-week-old female C57BL/6J mice for a period of 91 days, whereupon 24 h urines were collected and the mice euthanized after a 12 h fast for the collection of liver tissue. Alterations in hepatic and urinary metabolite patterns were determined by gas chromatography-mass spectrometry-based metabolomics. Urinary excretion of the gut microbiota metabolites 4-hydroxyphenylacetic acid, 5-hydroxyindole, glyceric acid, gluconic acid and myo-inositol was attenuated when grape was added to the standard diet but the gut microbiota metabolites gluconic acid, scyllo-inositol, mannitol, xylitol, 5-hydroxyindole and 2-deoxyribonic acid were increased in urine when grape was added to the high-fat diet. Increased hepatic ascorbic acid and 5-oxoproline levels indicated the anti-oxidant effect of grape powder on the liver. Pathway enrichment analysis demonstrated that for both standard and high-fat diets, grape addition significantly upregulated the malate-aspartate shuttle indicating enhanced hepatic utilization of glucose via cytosolic glycolysis for mitochondrial ATP production. It is concluded that a grape diet reprogrammes gut microbiota metabolism, attenuates the hepatic oxidative stress of a high-fat diet and increases the efficiency of glucose utilization by the liver for energy production.

Early Infant Formula Feeding Impacts Urinary Metabolite Profile at 3 Months of Age.

There is a growing consensus that nutritional programming may persist and influence risk for several chronic diseases in adulthood. In the present study, we used urinary metabolic analysis in assessing diet effects on early-life metabolism. Urine samples from healthy three-month-old infants fed human milk (HM; n = 93), cow’s milk-based infant formula [MF; n = 80], or soy protein-based infant formula (SF; n = 76) were analyzed with an untargeted metabolomics approach using GC-TOF MS. PLS-DA and ANOVA analyses were performed using MetaboAnalyst (v4.0). A total of 150 metabolites differed significantly among the feeding groups, including dietary-specific patterns of urinary metabolites of sugars, sugar alcohols, amino acids, and polyphenols. Urinary metabolites may mirror the infant’s overall metabolism and serve as a noninvasive tool to examine the neonatal effects of diet on early-infant metabolism.

Urinary Concentrations of Phthalate Metabolite Mixtures in Relation to Serum Biomarkers of Thyroid Function and Autoimmunity among Women from a Fertility Center.

Background:Although previous epidemiological studies have explored associations of phthalate metabolites with thyroid function, no studies to date have assessed associations of mixtures with thyroid function and autoimmunity among potentially susceptible subgroups such as subfertile women.Objective:We aimed to explore associations of mixtures of urinary phthalate metabolites with serum markers of thyroid function and autoimmunity.Methods:This cross-sectional study included 558 women attending a fertility center who provided one spot urine and one blood sample at enrollment (2005–2015). We quantified urinary concentrations of eight phthalate metabolites using mass spectrometry, and biomarkers of thyroid function [thyroid-stimulating hormone (TSH), free and total thyroxine (, ) and triiodothyronine (, ), and autoimmunity [thyroid peroxidase and thyroglobulin antibodies (TPOAb and TgAb, respectively)] in serum using electrochemiluminescence assays. We applied principal component analysis (PCA) and Bayesian kernel machine regression (BKMR) to identify the main patterns of urinary phthalate metabolites. We used linear mixed models to assess the association between PCA-derived factor scores in quintiles and serum thyroid function and autoimmunity, adjusting for age, body mass index (BMI), specific gravity (SG), and, for the PCA, other factor scores.Results:We observed two factors using PCA, one representing the di(2-ethylhexyl) (DEHP) and another non-DEHP metabolites. Compared to women in the lowest quintile of the DEHP factor scores, women in the highest quintile had significantly lower serum concentrations of , , , and [absolute difference: ; 95% confidence interval (CI): , ; ; absolute difference: ; 95% CI: , ; ; absolute difference: ; 95% CI: 0.54, ; ; and absolute difference: ; 95% CI: , ; , respectively]. Using BKMR, we observed that mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) was the primary contributor to these negative associations. DEHP and non-DEHP factor scores were not associated with serum TSH, TgAb, or TPOAb.Conclusions:Mixtures of urinary DEHP metabolites were inversely associated with serum biomarkers of thyroid function but not with autoimmunity, which were within normal ranges for healthy adult women. https://doi.org/10.1289/EHP6740

An NMR-Based Approach to Identify Urinary Metabolites Associated with Acute Physical Exercise and Cardiorespiratory Fitness in Healthy Humans-Results of the KarMeN Study.

Knowledge on metabolites distinguishing the metabolic response to acute physical exercise between fit and less fit individuals could clarify mechanisms and metabolic pathways contributing to the beneficial adaptations to exercise. By analyzing data from the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study, we characterized the acute effects of a standardized exercise tolerance test on urinary metabolites of 255 healthy women and men. In a second step, we aimed to detect a urinary metabolite pattern associated with the cardiorespiratory fitness (CRF), which was determined by measuring the peak oxygen uptake (VO2peak) during incremental exercise. Spot urine samples were collected pre- and post-exercise and 47 urinary metabolites were identified by nuclear magnetic resonance (NMR) spectroscopy. While the univariate analysis of pre-to-post-exercise differences revealed significant alterations in 37 urinary metabolites, principal component analysis (PCA) did not show a clear separation of the pre- and post-exercise urine samples. Moreover, both bivariate correlation and multiple linear regression analyses revealed only weak relationships between the VO2peak and single urinary metabolites or urinary metabolic pattern, when adjusting for covariates like age, sex, menopausal status, and lean body mass (LBM). Taken as a whole, our results show that several urinary metabolites (e.g., lactate, pyruvate, alanine, and acetate) reflect acute exercise-induced alterations in the human metabolism. However, as neither pre- and post-exercise levels nor the fold changes of urinary metabolites substantially accounted for the variation of the covariate-adjusted VO2peak, our results furthermore indicate that the urinary metabolites identified in this study do not allow to draw conclusions on the individual’s physical fitness status. Studies investigating the relationship between the human metabolome and functional variables like the CRF should adjust for confounders like age, sex, menopausal status, and LBM.

Urinary NMR Profiling in Pediatric Acute Kidney Injury-A Pilot Study.

Acute kidney injury (AKI) in critically ill children and adults is associated with significant short- and long-term morbidity and mortality. As serum creatinine- and urine output-based definitions of AKI have relevant limitations, there is a persistent need for better diagnostics of AKI. Nuclear magnetic resonance (NMR) spectroscopy allows for analysis of metabolic profiles without extensive sample manipulations. In the study reported here, we examined the diagnostic accuracy of NMR urine metabolite patterns for the diagnosis of neonatal and pediatric AKI according to the Kidney Disease: Improving Global Outcomes (KDIGO) definition. A cohort of 65 neonatal and pediatric patients (0–18 years) with established AKI of heterogeneous etiology was compared to both a group of apparently healthy children (n = 53) and a group of critically ill children without AKI (n = 31). Multivariate analysis identified a panel of four metabolites that allowed diagnosis of AKI with an area under the receiver operating characteristics curve (AUC-ROC) of 0.95 (95% confidence interval 0.86–1.00). Especially urinary citrate levels were significantly reduced whereas leucine and valine levels were elevated. Metabolomic differentiation of AKI causes appeared promising but these results need to be validated in larger studies. In conclusion, this study shows that NMR spectroscopy yields high diagnostic accuracy for AKI in pediatric patients.

Comprehensive Metabolomics Analysis of Xueshuan Xinmaining Tablet in Blood Stasis Model Rats Using UPLC-Q/TOF-MS.

Blood stasis syndrome (BSS) is one of the most common Chinese medicine patterns in coronary heart disease. Our previous work proved that Xueshuan Xinmaining Tablet (XXT) could treat blood stasis through regulating the expression of F13a1, Car1 and Tbxa2r. In the current study, the effect and mechanism of XXT on BSS was comprehensively and holistically investigated based on a metabolomics approach. Urine and plasma samples of 10 BBS rats treated with XXT (XT), 9 BSS model rats (BM) and 11 normal control (NC) rats were collected and then determined by UPLC-Q/TOP-MS. Multivariate analyses were applied to distinguish differentiate urinary and plasma metabolite patterns between three groups. Results showed that a clear separation of three groups was achieved. XT group was located between BM group and NC group, and showing a tendency of recovering to NC group, which was consistent with the results of hemorheological studies. Some significantly changed metabolites like cortexolone, 3α,21-dihydroxy-5β-pregnane-11,20-dione and 19S-hete and leukotriene A4, chiefly involved in steroid hormone biosynthesis, arachidonic acid metabolism and lipid metabolism, were found and identified to explain the mechanism. These potential markers and their corresponding pathways will help explain the mechanism of BSS and XXT treatment. This work also proves that metabolomics is effective in traditional Chinese medicinal research.

Metabolite profiles evaluated, according to sex, do not predict resting energy expenditure and lean body mass in healthy non-obese subjects

PurposeDifferences in resting energy expenditure (REE) between men and women mainly result from sex-related differences in lean body mass (LBM). So far, a little is known about whether REE and LBM are reflected by a distinct human metabolite profile. Therefore, we aimed to identify plasma and urine metabolite patterns that are associated with REE and LBM of healthy subjects.MethodsWe investigated 301 healthy male and female subjects (18–80 years) under standardized conditions in the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study. REE was determined by indirect calorimetry and LBM by dual X-ray absorptiometry. Fasting blood and 24 h urine samples were analyzed by targeted and non-targeted metabolomics methods using GC × GC–MS, GC–MS, LC–MS, and NMR. Data were evaluated by predictive modeling of combined data using different machine learning algorithms, namely SVM, glmnet, and PLS.ResultsWhen evaluating data of men and women combined, we were able to predict REE and LBM with high accuracy (> 90%). This, however, was a clear effect of sex, which is supported by the high degree of overlap in identified important metabolites for LBM, REE, and sex, respectively. The applied machine learning algorithms did not reveal a metabolite pattern predictive of REE or LBM, when analyzing data for men and women, separately.ConclusionsWe could not identify a sex independent predictive metabolite pattern for REE or LBM. REE and LBM have no impact on plasma and urine metabolite profiles in the KarMeN Study participants. Studies applying metabolomics in healthy humans need to consider sex specific data evaluation.

Testing for Short- and Long-Term Thermal Plasticity in Corticosterone Responses of an Ectothermic Vertebrate.

Phenotypic plasticity, broadly defined as the capacity of one genotype to produce more than one phenotype, is a key mechanism for how animals adapt to environmental (including thermal) variation. Vertebrate glucocorticoid hormones exert broad-scale regulation of physiological, behavioral, and morphological traits that influence fitness under many life-history or environmental contexts. Yet the capacity for vertebrates to demonstrate different types of thermal plasticity, including rapid compensation or longer acclimation in glucocorticoid hormone function, when subject to different environmental temperature regimes remains poorly addressed. Here, we explore whether patterns of urinary corticosterone metabolites respond (i.e., evidence of acclimation) to repeated short-term and sustained long-term temperature exposures in an amphibian, the cane toad (Rhinella marina). In response to three repeated short (30-min) high-temperature (37°C) exposures (at 10-d intervals), toads produced urinary corticosterone metabolite responses of sequentially greater magnitude, relative to controls. However, toads subjected to 4 wk of acclimation to either cool (18°C)- or warm (30°C)-temperature environments did not differ significantly in their urinary corticosterone metabolite responses during exposure to a thermal ramp (18°-36°C). Together, these results indicate that adult toads had different, including limited, capacities for their glucocorticoid responses to demonstrate plasticity to different regimes of environmental temperature variation. We advocate further research as necessary to identify plasticity, or lack thereof, in glucocorticoid physiology, to better understand how vertebrates can regulate organismal responses to environmental variation.

Metabolic markers for differentiation between renal allograft rejection and immunosuppressant toxicity in rat urine

Although current immunosuppressive protocols have dramatically improved 1-year survival of kidney transplants, there has been less progress in terms of long-term graft survival over the last two decades. The key to avoiding late graft loss is early diagnosis and differentiation between anti-allograft immune processes and immunosuppressant toxicity (IS-Tox). Modern bioanalytical technologies have opened new opportunities for the development of sensitive and specific diagnostic tools. There is an immediate need for biomarkers that are able to differentiate between renal allograft rejection and immunosuppressant toxicity. To test our hypothesis that changes of metabolite patterns in urine have the potential to serve as a non-invasive combinatorial biomarker that can differentiate between allograft immune reactions and IS-Tox. We used 1H-NMR spectroscopy and Luminex multiplexing for metabolic profiling of rat urine and the analysis of protein biomarkers in urine and plasma, respectively, to compare the effects of chronic allograft rejection in a Fisher-to-Lewis rat transplant model with IS-Tox induced by cyclosporine, tacrolimus and/or sirolimus in Lewis rats. Our results showed that, while IS-Tox caused changes in metabolite patterns that are typically associated with proximal tubule damage, rejection caused more profuse changes not specifically focused on a particular kidney region. Moreover, metabolite pattern changes were more sensitive than changes in protein markers that were evident only during the later stages of rejection. The present study provides first proof-of-concept that longitudinal monitoring of urine metabolite markers has the potential to differentiate between early renal allograft rejection and immunosuppressant nephrotoxicity.

Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries.

We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography–electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine (r = 0.65; AUC = 89.1%), coffee (r = 0.51; AUC = 89.1%), and olives (r = 0.35; AUC = 82.2%). These metabolite patterns performed better or equally well compared to single polyphenol biomarkers. Neither metabolite patterns nor single biomarkers performed well in explaining habitual intake (as reported in the DQ) of polyphenol-rich foods. This proposed strategy of biomarker pattern identification has the potential of expanding the currently still limited list of available dietary intake biomarkers.

Dietary Fat and Fiber Intakes Are Not Associated with Patterns of Urinary Estrogen Metabolites in Premenopausal Women1–

Interindividual differences in the bioavailability of potentially carcinogenic estrogen and estrogen metabolites (EMs) may play a role in the risk of breast cancer. We examined whether dietary intakes of fiber and fat influence premenopausal EM profiles through effects on estrogen synthesis, metabolism, or excretion. We conducted a cross-sectional analysis of 598 premenopausal women who participated in a reproducibility study (n = 109) or served as controls in a nested case-control study of breast cancer (n = 489) within the Nurses' Health Study II. Dietary intakes of fiber and fat were assessed via semiquantitative food frequency questionnaires in 1995 and 1999. Midluteal urine samples were collected between 1996 and 1999 and EMs were quantified with the use of HPLC-tandem mass spectrometry. Linear mixed models were used to estimate creatinine-adjusted geometric means for individual EMs and their pathway groups across categories of dietary intake while controlling for total energy intake and potential confounders. Higher total dietary fiber intake (>25 g/d vs. ≤15 g/d) was associated with significantly higher concentrations of 4-methoxyestradiol (50% difference, P-difference = 0.01, P-trend = 0.004) and lower concentrations of 17-epiestriol (-27% difference, P-difference = 0.03, P-trend = 0.03), but was not associated with any other EMs. The associations did not vary by fiber intake from different sources. Total fat intake (>35% energy vs. ≤25% energy) was suggestively positively associated with 17-epiestriol (22.6% difference, P-difference = 0.14, P-trend = 0.06); the association was significant for polyunsaturated fatty acid (37% difference, P-difference = 0.01, P-trend = 0.01) and trans fat (36.1% difference, P-difference = 0.01, P-trend = 0.01) intakes. Fiber and fat intakes were not strongly associated with patterns of estrogen metabolism in premenopausal women. Our data suggest estrogen metabolism is not a major mechanism through which dietary fiber and fat may affect breast or other hormone-related cancer risks.

The impact of stress on the prevalence of prednisolone in bovine urine: A metabolic fingerprinting approach

Recent studies support the hypothesis that the glucocorticoid prednisolone can be formed from cortisol under influence of stress. To evaluate this hypothesis, urine samples of supposedly non-stressed bovines (at the farm) and bovines subjected to two different forms of stress, i.e. upon slaughter (natural stress) or following administration of a synthetic analog of the adrenocorticotropic hormone (pharmacologically-induced stress) were analysed, and their urinary cortisol and prednisolone levels evaluated. At the farm, none of the examined samples exhibited urinary prednisolone levels higher than the CCα (0.09μgL−1). Upon slaughter or following synthetically induced stress, significantly positive correlations between cortisol and prednisolone could be demonstrated, 0.52 and 0.69, respectively. Of all prednisolone-positive urine samples (n=84), only one showed a prednisolone levels (i.e. 6.45μgL−1) above the threshold level of 5μgL−1 suggested by the European Reference Laboratories. Subsequently, an untargeted analysis was performed (metabolic fingerprinting) to characterize the urinary metabolite patterns related to the three different cattle groups. In this context, multivariate statistics assigned a total of 169 differentiating metabolites as playing a key role in the urinary pattern in response to stress. Three of these ions were defined as steroids using an in-house created database. As a result, the metabolic fingerprinting approach proved to be a powerful tool to classify unknown bovine urine samples that tested positive for prednisolone, while providing information about the stress status of the animal.

A high-performance liquid chromatography – tandem mass spectrometry – based targeted metabolomics kidney dysfunction marker panel in human urine

BackgroundPrevious studies have examined and documented fluctuations in urine metabolites in response to disease processes and drug toxicity affecting glomerular filtration, tubule cell metabolism, reabsorption, oxidative stress, purine degradation, active secretion and kidney amino acylase activity representative of diminished renal function. However, a high-throughput assay that incorporates metabolites that are surrogate markers for such changes into a kidney dysfunction panel has yet to be described. MethodsA high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) assay for the quantification of ten metabolites associated with the Krebs cycle, purine degradation, and oxidative stress in human urine was developed and validated. Normal values were assessed in healthy adult (n=120) and pediatric (n=36) individuals. In addition, 9 pediatric renal transplant recipients patients were evaluated before and after initial dosing of the immunosuppressant tacrolimus in a proof-of-concept study. ResultsThe assay met all predefined acceptance criteria. The lower limit of quantification ranged from 0.1 to 1000 μmol/l. Inter-day trueness and imprecisions ranged from 91.4–112.9% and 1.5–12.4%, respectively. The total assay run time was 5.5 minutes.Concentrations of glucose, sorbitol, and trimethylamine oxide (TMAO) were elevated in pediatric renal transplant patients (n=9) prior to transplantation as well as before and immediately after initial dosing of tacrolimus. One month post-transplant urine metabolite patterns matched those of healthy children (n=36). ConclusionsThe LC-MS/MS assay will provide the basis for further large-scale clinical studies to explore these analytes as molecular markers for the patients with renal insufficiency.