A single extraction 96-well method for LC-MS/MS quantification of urinary eicosanoids, steroids and drugs.

Urinary eicosanoid concentrations reflect inflammatory processes in multiple diseases and have been used as biomarkers of disease as well as suggested for patient stratification in precision medicine. However, implementation of urinary eicosanoid profiling in large-scale analyses is restricted due to sample preparation limits. Here we demonstrate a single solid-phase extraction of 300 µL urine in 96-well-format for prostaglandins, thromboxanes, isoprostanes, cysteinyl-leukotriene E4 and the linoleic acid-derived dihydroxy-octadecenoic acids (9,10- and 12,13-DiHOME). A simultaneous screening protocol was also developed for cortisol/cortisone and 7 exogenous steroids as well as 3 cyclooxygenase inhibitors. Satisfactory performance for quantification of eicosanoids with an appropriate internal standard was demonstrated for intra-plate analyses (CV = 8.5-15.1%) as well as for inter-plate (n = 35) from multiple studies (CV = 22.1-34.9%). Storage stability was evaluated at - 20 °C, and polar tetranors evidenced a 50% decrease after 5 months, while the remaining eicosanoids evidenced no significant degradation. All eicosanoids were stable over 3.5-years in urine stored at - 80 °C. This method will facilitate the implementation of urinary eicosanoid quantification in large-scale screening.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial.

BACKGROUND: Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health. OBJECTIVES: To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification. METHODS: In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs. RESULTS: After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP. CONCLUSIONS: Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

Kinetic Profile of Urine Metabolites after Acute Intake of a Phenolic Compounds-Rich Juice of Juçara (Euterpe edulis Mart.) and Antioxidant Capacity in Serum and Erythrocytes: A Human Study.

The juçara palm tree produces a small spherical and black-purple fruit similar to açaí. It is rich in phenolic compounds, especially anthocyanins. A clinical trial evaluated the absorption and excretion of the main bioactive compounds in urine and the antioxidant capacity in serum and erythrocytes of 10 healthy subjects after juçara juice intake. Blood samples were collected before (0.0 h) and 0.5 h, 1 h, 2 h, and 4 h after a single dose (400 mL) of juçara juice, while urine was collected at baseline and 0-3 and 3-6 h after juice intake. Seven phenolic acids and conjugated phenolic acids were identified in urine deriving from the degradation of anthocyanins: protocatechuic acid, vanillic acid, vanillic acid glucuronide, hippuric acid, hydroxybenzoic acid, hydroxyphenylacetic acid, and ferulic acid derivative. In addition, kaempferol glucuronide was also found in urine as a metabolite of the parent compound in juçara juice. Juçara juice caused a decrease in the total oxidant status of serum after 0.5 h in comparison to baseline values (p < 0.05) and increased the phenolic acid metabolites excretion. This study shows the relationship between the production of metabolites of juçara juice and the total antioxidant status in human serum, indicating evidence of its antioxidant capacity.

Change in Urinary Myoinositol/Citrate Ratio Associates with Progressive Loss of Renal Function in ADPKD Patients.

INTRODUCTION: In autosomal dominant polycystic kidney disease (ADPKD) patients, predicting renal disease progression is important to make a prognosis and to support the clinical decision whether to initiate renoprotective therapy. Conventional markers all have their limitations. Metabolic profiling is a promising strategy for risk stratification. We determined the prognostic performance to identify patients with a fast progressive disease course and evaluated time-dependent changes in urinary metabolites. METHODS: Targeted, quantitative metabolomics analysis (1H NMR-spectroscopy) was performed on spot urinary samples at two time points, baseline (n = 324, 61% female; mean age 45 years, SD 11; median eGFR 61 mL/min/1.73 m2, IQR 42-88; mean years of creatinine follow-up 3.7, SD 1.3) and a sample obtained after 3 years of follow-up (n = 112). Patients were stratified by their eGFR slope into fast and slow progressors based on an annualized change of > -3.0 or ≤ -3.0 mL/min/1.73 m2/year, respectively. Fifty-five urinary metabolites and ratios were quantified, and the significant ones were selected. Logistic regression was used to determine prognostic performance in identifying those with a fast progressive course using baseline urine samples. Repeated-measures ANOVA was used to analyze whether changes in urinary metabolites over a 3-year follow-up period differed between fast and slow progressors. RESULTS: In a single urinary sample, the prognostic performance of urinary metabolites was comparable to that of a model including height-adjusted total kidney volume (htTKV, AUC = 0.67). Combined with htTKV, the predictive value of the metabolite model increased (AUC = 0.75). Longitudinal analyses showed an increase in the myoinositol/citrate ratio (p < 0.001) in fast progressors, while no significant change was found in those with slow progression, which is in-line with an overall increase in the myoinositol/citrate ratio as GFR declines. CONCLUSION: A metabolic profile, measured at a single time point, showed at least equivalent prognostic performance to an imaging-based risk marker in ADPKD. Changes in urinary metabolites over a 3-year follow-up period were associated with a fast progressive disease course.

An observation study of urinary biomarker exploratory in Alzheimer's disease using high-resolution mass spectrometry.

Alzheimer's disease (AD) is regarded as a progressive neurodegenerative dementia, characterized by degeneration of distinct neuronal populations. A case-control study was carried out using high-resolution mass spectrometry to explore AD-associated urinary metabolic biomarkers from 30 AD patients and 30 cognitively normal (CN) individuals. In total, 49 metabolites were determined and validated as known compounds using LC/MS analysis. Using the two-sample t-test statistical analysis (P < 0.05), 19 metabolites were shown to be significantly different from AD to CN. A diagnostic model of the receiver operating characteristic curve was constructed with a combination of nine molecules out of 19 metabolites, it yielded a separation with an area under the curve value of 0.976 between the two groups. This study indicated that urinary metabolites showed a significant expression between AD and CN. AD-related metabolites enable to satisfy the diagnostic power of disease discrimination. In addition, as a noninvasive approach, urine collection is done easily in clinical diagnosis of AD.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study.

BACKGROUND: Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD. METHODS: To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. RESULTS: Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%). CONCLUSIONS: This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Urine Metabolite Levels, Adverse Kidney Outcomes, and Mortality in CKD Patients: A Metabolome-wide Association Study.

RATIONALE & OBJECTIVE: Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms. STUDY DESIGN: Metabolome-wide association study. SETTING & PARTICIPANTS: 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study. EXPOSURES: Measurements of 1,487 metabolites in urine. OUTCOMES: End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality. ANALYTICAL APPROACH: Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models. RESULTS: After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation. LIMITATIONS: Findings among patients of European ancestry with CKD may not be generalizable to the general population. CONCLUSIONS: Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.

Urine tricarboxylic acid cycle signatures of early-stage diabetic kidney disease.

INTRODUCTION: Urine tricarboxylic acid (TCA) cycle organic anions (OAs) are elevated in diabetes and may be biomarkers for diabetic kidney disease (DKD) progression. OBJECTIVES: We assessed associations of 10 urine TCA cycle OAs with estimated glomerular filtration rate (eGFR) and eGFR slope. METHODS: This study is ancillary to the Simultaneous Risk Factor Control Using Telehealth to SlOw Progression of Diabetic Kidney Disease (STOP-DKD) Trial-a randomized trial of pharmacist-led medication and behavior management in 281 patients with early to moderate DKD at Duke from 2014 to 2015. We used linear mixed models to assess associations of urine TCA cycle OAs with outcomes and modelled TCA cycle OAs as: (1) the average of z-scores for each OA; and (2) principal component (PC) scores derived by principal component analysis (PCA). Untargeted urine metabolomics were added for additional discovery. RESULTS: Among 132 participants with 24 h urine samples (50% men; 58% Black; mean age 64 years [SD 9]; mean eGFR 74 ml/min/1.73m2 [SD 21] and median urine albumin-to-creatinine [UACR] 20 mg/g [IQR 8-95]), PCA identified 3 OA metabolite PCs. Malate, fumarate, pyruvate, α-ketoglutarate, lactate, succinate and citrate/isocitrate loaded positively on PC1; methylsuccinate, ethylmalonate and succinate loaded positively on PC2; and methylmalonate, ethylmalonate and citrate/isocitrate loaded negatively on PC3. Over a median follow-up of 1.8 years (IQR, 1.2 to 2.2), higher average OA z-score was strongly associated with higher eGFR after covariate adjustment (p = 0.01), but not with eGFR slope (p = 0.9). Higher PC3, but not other PCs, was associated with lower eGFR (p < 0.001). Conditional random forests and smooth clipped absolute deviation models confirmed methylmalonate, citrate/isocitrate, and ethylmalonate, and added lactate as top ranked metabolites in models of baseline eGFR (R-squared 0.32 and 0.33, respectively). Untargeted urine metabolites confirmed association of urine TCA cycle OAs with kidney function. CONCLUSION: Thus, lower urine TCA cycle OAs, most notably lower methylmalonate, ethylmalonate and citrate/isocitrate, are potential indicators of kidney impairment in early stage DKD.

Temporal variability of organophosphate flame retardant metabolites in spot, first morning, and 24-h urine samples among healthy adults.

A single measurement of organophosphate flame retardant (OPFR) metabolites in a spot sample is often used in epidemiological studies to estimate individual exposures. Over seven consecutive days, we collected 661 spot samples, including 127 first morning voids (FMVs) and 123 simulated 24-h collections, from 20 healthy adults and analyzed for eight OPFR metabolites. Intraclass correlation coefficients (ICCs) were calculated to evaluate the variability of the analyzed metabolites. In spot samples group, serial measurements of OPFR metabolites showed poor reproducibility (0.0422 ≤ ICC ≤ 0.349), and the within-day variability was the main contributor of the total variability. The estimated ICCs based on different correction methods for urine dilution (i.e., specific gravity-adjusted, creatinine-adjusted, and creatinine as a covariate) were similar, but varied according to gender and body mass index. Uniformly low sensitivities (0.417-0.633) were observed when using a single FMV or spot sample to predict the 1-week highly (top 33.0%) exposed volunteers. Therefore, using a single urinary measurement to predict chronic exposure to OPFRs can lead to a high degree of classification errors. When multiple urine samples are collected, considering the sampling type, the time of collection, and demographic characteristics may provide a more complete approach to assess exposure to diverse OPFRs.

Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats.

Acetaminophen (APAP) is the most commonly used analgesic and antipyretic drug in the world. Yet, it poses a major risk of liver injury when taken in excess of the therapeutic dose. Current clinical markers do not detect the early onset of liver injury associated with excess APAP-information that is vital to reverse injury progression through available therapeutic interventions. Hence, several studies have used transcriptomics, proteomics, and metabolomics technologies, both independently and in combination, in an attempt to discover potential early markers of liver injury. However, the casual relationship between these observations and their relation to the APAP mechanism of liver toxicity are not clearly understood. Here, we used Sprague-Dawley rats orally gavaged with a single dose of 2 g/kg of APAP to collect tissue samples from the liver and kidney for transcriptomic analysis and plasma and urine samples for metabolomic analysis. We developed and used a multi-tissue, metabolism-based modeling approach to integrate these data, characterize the effect of excess APAP levels on liver metabolism, and identify a panel of plasma and urine metabolites that are associated with APAP-induced liver toxicity. Our analyses, which indicated that pathways involved in nucleotide-, lipid-, and amino acid-related metabolism in the liver were most strongly affected within 10 h following APAP treatment, identified a list of potential metabolites in these pathways that could serve as plausible markers of APAP-induced liver injury. Our approach identifies toxicant-induced changes in endogenous metabolism, is applicable to other toxicants based on transcriptomic data, and provides a mechanistic framework for interpreting metabolite alterations.

GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection.

BACKGROUND: Acute renal allograft rejection is a common complication after renal transplantation that often leads to chronic rejection and ultimate graft loss. While renal allograft biopsy remains the gold standard for diagnosis of acute rejection, the possibility of biopsy-associated complications cannot be overlooked. The development of noninvasive methods for accurate detection of acute renal allograft rejection is thus of significant clinical importance. METHODS: Gas chromatography-mass spectrometry (GC/MS) was employed for analysis of urine metabolites in 15 renal allograft recipients with acute rejection and 15 stable renal transplant recipients. Partial least squares (PLS) regression and leave-one-out analyses were performed to ascertain whether the metabolites identified could be exploited to distinguish acute rejection from stable groups as well as their sensitivity and specificity. RESULTS: Overall, 14 metabolites were significantly altered in the acute rejection group (11 and 3 metabolites displayed higher and lower levels, respectively) relative to the stable transplant group. Data from PLS and leave-one-out analyses revealed that the differential metabolites identified not only distinguished acute rejection from stable transplant recipients but also showed high sensitivity and specificity for diagnosis of renal allograft recipients with acute rejection. CONCLUSION: Urine metabolites identified with GC/MS can effectively distinguish acute rejection from stable transplant recipients, supporting the potential utility of metabolome analysis in non-invasive diagnosis of acute rejection.

Effects of low dietary cation-anion difference induced by ruminal ammonium chloride infusion on performance, serum, and urine metabolites of lactating dairy cows.

OBJECTIVE: The objective of the present study was to determine ammonium chloride tolerance of lactating dairy cows, by examining effects of negative dietary cation anion difference (DCAD) induced by ruminal ammonium chloride infusion on performance, serum and urine minerals, serum metabolites and enzymes of lactating dairy cows. METHODS: Four primiparous lactating Chinese Holstein cows fitted with ruminal cannulas were infused with increasing amounts (0, 150, 300, or 450 g/d) of ammonium chloride in a crossover design. The DCAD of the base diet was 279 mEq/kg dry matter (DM) using the DCAD formula (Na + K - Cl - S)/kg of DM. Ammonium chloride infusion added the equivalent of 0, 128, 330, and 536 mEq/kg DM of Cl in treatments. According to the different dry matter intakes (DMI), the resulting actual DCAD of the four treatments was 279, 151, -51, and -257 mEq/kg DM, respectively. RESULTS: DMI decreased linearly as DCAD decreased. Yields of milk, 4% fat-corrected milk, energy-corrected milk, milk fat, and milk protein decreased linearly as DCAD decreased. Concentrations of milk protein and milk urea nitrogen increased linearly with decreasing DCAD. Concentration of Cl- in serum increased linearly and concentration of PO43- in serum increased quadratically as DCAD decreased. Urine pH decreased linearly and calculated urine volume increased linearly with decreasing DCAD. Linear increases in daily urinary excretion of Cl-, Ca2+, PO43-, urea N, and ammonium were observed as DCAD decreased. Activities of alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transferase in serum and urea N concentration in serum increased linearly as DCAD decreased. CONCLUSION: In conclusion, negative DCAD induced by ruminal ammonium chloride infusion resulted in a metabolic acidosis, had a negative influence on performance, and increased serum enzymes indicating potential liver and kidney damage in lactating dairy cows. Daily ammonium chloride intake by lactating dairy cows should not exceed 300 g, and 150 g/d per cow may be better.

Variability and predictors of urinary concentrations of organophosphate flame retardant metabolites among pregnant women in Rhode Island.

BACKGROUND: Organophospate flame retardants (PFRs) are chemicals of emerging concern due to restrictions on polybrominated diphenyl ether flame retardant formulations. We describe the occurrence, variability, and predictors of urinary metabolites of PFRs among pregnant women. METHODS: In 2014-2015, 59 women from Providence, RI provided up to 3 spot urine samples during pregnancy (~12, 28, and 35 weeks' gestation). We created a pooled urine sample per woman and measured nine relevant metabolites in individual and pooled samples. We used linear mixed models to calculate intraclass correlation coefficients (ICCs) across the 3 measurements and to assess sociodemographic and dietary predictors of PFRs. RESULTS: The median (IQR) of bis-2-chloroethyl phosphate (BCEP), bis(1,3-dichloro-2-propyl) phosphate (BDCPP), and diphenyl phosphate (DPhP), the metabolites most frequently detected, from pooled samples were: 0.31 µg/L (0.17-0.54), 1.18 µg/L (0.64-2.19), 0.93 µg/L (0.72-1.97), respectively. We observed fair to good reproducibility for BCEP (ICC = 0.50), BDCPP (ICC = 0.60), and DPhP (ICC = 0.43), and excellent agreement between the urinary flame retardant metabolite concentrations averaged across pregnancy versus pooled urine sample concentrations for BCEP (ICC = 0.95), BDCPP (ICC = 0.89), and DPhP (ICC = 0.93). Adjusting for pertinent sociodemographic factors and gestational week of urine collection, each 1 kg increase in pre-pregnancy weight was associated with greater BCEP (1.1%; 95% CI: 0.1, 2.1), BDCPP (1.5%; 95% CI: 0.3, 2.7), and DPhP (0.5%; 95% CI: 0.0, 1.1). Dietary factors were generally not associated with urinary flame retardant metabolites. CONCLUSIONS: Urinary concentrations of BCEP, BDCPP, and DPhP were frequently detected among women in this pilot study and had fair reproducibility across pregnancy. Body size may be an important predictor of urinary flame retardant metabolite concentrations.

Fluid balance and hydration assessment during the weight-stable preparation phase in elite youth boxers.

This study investigated (i) the prevalence of hypohydration and (ii) association between urinary indices of hydration status and confounding factors (e.g., urine protein content, water intake) in elite youth boxers during their weight-stable phase before competition. Sixteen national champion boxers (all male, 17 ± 1 y) were measured on 3 occasions (baseline, day 3, day 10), 30-day prior to competition. Body mass, total body water, urine specific gravity (USG), osmolality (UOSM) and total protein content (TPC) were evaluated to determine hydration status and fluid balance. Overall macronutrient and water intake were assessed using dietary records. Both UOSM and USG increased from day 3 to day 10 by 16% and 0.4% (P < 0.001), despite athletes being in their weight-stability period, and regardless of ad libitum fluid intake. Hypohydration was universally prevalent among all athletes on both test days with USG: 1.027 ± 0.003 g · mL-1 and UOSM: 1035 ± 108 mOsmol · kg-1. An inverse association between mean UOSM values and mean water intake was observed (R = -0.52, P = 0.04), while TPC was not associated with any urinary dehydration markers (USG, P = 0.51; UOSM, P = 0.61). The present outcomes find that the most prevalent urinary dehydration markers used to classify hydration status in competition exhibit large variability, even during weight-stable periods.

Urine phyto-oestrogen metabolites are not significantly associated with risk of type 2 diabetes: the Singapore Chinese health study.

We evaluated the relationship between urine concentrations of phyto-oestrogens (isoflavones and lignans) and risk of incident type 2 diabetes in middle-aged and elderly Chinese residing in Singapore. Urine metabolites of isoflavones and lignans were assayed by HPLC among 564 diabetes cases and 564 matched controls in a case-control study nested within the Singapore Chinese Health Study cohort. Participants were free of diagnosed diabetes, CVD and cancer at morning urine collections during 1999-2004. Cases were participants who reported to have physician-diagnosed diabetes at follow-up visits during 2006-2010, whereas controls were randomly selected among those who remained free of diabetes and were matched to the index cases by age, sex, dialect group and date of urine collection. Conditional logistic regression models were used to calculate OR and 95 % CI with adjustment for potential confounders. The mean age of the participants at the time of urine collection was 59·8 years, and the average interval between urine collection and diabetes diagnosis was 4·0 years. The multivariate-adjusted OR for diabetes were 1·00 (reference), 0·76 (95 % CI 0·52, 1·11), 0·78 (95 % CI 0·53, 1·14) and 0·79 (95 % CI 0·54, 1·15) across quartiles of urine isoflavones (P for trend=0·54), and were 1·00 (reference), 0·87 (95 % CI 0·60, 1·27), 1·10 (95 % CI 0·77, 1·56) and 0·93 (95 % CI 0·63, 1·37) for lignans (P for trend=0·93). The results were similar in men and women, as well as for individual metabolites of isoflavones (genistein, daidzein, glycitin and equol) or lignans (enterodiol and enterolactone). The present study did not find a significant association between urine phyto-oestrogen metabolites and risk of type 2 diabetes in Chinese adults.

Urine metabolite changes after cardiac surgery predict acute kidney injury.

Background: Acute kidney injury (AKI) is a serious complication in patients undergoing cardiac surgery, with the underlying mechanism remaining elusive and a lack of specific biomarkers for cardiac surgery-associated AKI (CS-AKI). Methods: We performed an untargeted metabolomics analysis of urine samples procured from a cohort of patients with or without AKI at 6 and 24 h following cardiac surgery. Based on the differential urinary metabolites discovered, we further examined the expressions of the key metabolic enzymes that regulate these metabolites in kidney during AKI using a mouse model of ischemia-reperfusion injury (IRI) and in hypoxia-treated tubular epithelial cells (TECs). Results: The urine metabolomic profiles in AKI patients were significantly different from those in non-AKI patients, including upregulation of tryptophan metabolism- and aerobic glycolysis-related metabolites, such as l-tryptophan and d-glucose-1-phosphate, and downregulation of fatty acid oxidation (FAO) and tricarboxylic acid (TCA) cycle-related metabolites. Spearman correlation analysis showed that serum creatinine was positively correlated with urinary l-tryptophan and indole, which had high accuracy for predicting AKI. In animal experiments, we demonstrated that the expression of rate-limiting enzymes in glycolysis, such as hexokinase II (HK2), was significantly upregulated during renal IRI. However, the TCA cycle-related key enzyme citrate synthase was significantly downregulated after IRI. In vitro, hypoxia induced downregulation of citrate synthase in TECs. In addition, FAO-related gene peroxisome proliferator-activated receptor alpha (PPARα) was remarkably downregulated in kidney during renal IRI. Conclusion: This study presents urinary metabolites related to CS-AKI, indicating the rewiring of the metabolism in kidney during AKI, identifying potential AKI biomarkers.

Method development with high-throughput enhanced matrix removal followed by UHPLC-QqQ-MS/MS for analysis of grape polyphenol metabolites in human urine.

Grape and grape derived products contain many bioactive phenolics which have a variety of impacts on health. Following oral ingestion, the phenolic compounds and their metabolites may be detectable in human urine. However, developing a reliable method for the analysis of phenolic compounds in urine is challenging. In this work, we developed and validated a new high-throughput, sensitive and reproducible analytical method for the simultaneous analysis of 31 grape phenolic compounds and metabolites using Oasis PRiME HLB cleanup for sample preparation combined with ultra-performance liquid chromatography with triple quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). Using this new method, the accuracy achieved was 69.3 % ∼ 134.9 % (except for six compounds), and the recovery achieved was 52.4 % ∼ 134.7 % (except for two very polar compounds). For each of the 31 target analytes, the value of intra-day precision was less than 14.3 %. The value of inter-day precision was slightly higher than intra-day precision, with a range of 0.7 % ∼ 19.1 %. We report for the first time on the effect of gender and BMI on the accuracy and recovery of human urine samples, and results from analysis of variance (ANOVA), and principal component analysis (PCA) indicated there was no difference in the value of accuracy and recovery between different gender or BMI (>30) using our purposed cleanup and UHPLC-QqQ-MS/MS method. Overall, this newly developed method could serve as a powerful tool for analyzing grape phenolic compounds and metabolites in human urine samples.

Urine Metabolic Profiling for Rapid Lung Cancer Screening: A Strategy Combining Rh-Doped SrTiO3-Assisted Laser Desorption/Ionization Mass Spectrometry and Machine Learning.

Lung cancer ranks among the cancers with the highest global incidence rates and mortality. Swift and extensive screening is crucial for the early-stage diagnosis of lung cancer. Laser desorption/ionization mass spectrometry (LDI-MS) possesses clear advantages over traditional analytical methods for large-scale analysis due to its unique features, such as simple sample processing, rapid speed, and high-throughput performance. As n-type semiconductors, titanate-based perovskite materials can generate charge carriers under ultraviolet light irradiation, providing the capability for use as an LDI-MS substrate. In this study, we employ Rh-doped SrTiO3 (STO/Rh)-assisted LDI-MS combined with machine learning to establish a method for urine-based lung cancer screening. We directly analyzed urine metabolites from lung cancer patients (LCs), pneumonia patients (PNs), and healthy controls (HCs) without employing any pretreatment. Through the integration of machine learning, LCs are successfully distinguished from HCs and PNs, achieving impressive area under the curve (AUC) values of 0.940 for LCs vs HCs and 0.864 for LCs vs PNs. Furthermore, we identified 10 metabolites with significantly altered levels in LCs, leading to the discovery of related pathways through metabolic enrichment analysis. These results suggest the potential of this method for rapidly distinguishing LCs in clinical applications and promoting precision medicine.

A calibrated human PBPK model for benzene inhalation with urinary bladder and bone marrow compartments.

A physiologically-based pharmacokinetic (PBPK) model of benzene inhalation based on a recent mouse model was adapted to include bone marrow (target organ) and urinary bladder compartments. Empirical data on human liver microsomal protein levels and linked CYP2E1 activities were incorporated into the model, and metabolite-specific conversion rate parameters were estimated by fitting to human biomonitoring data and adjusting for background levels of urinary metabolites. Human studies of benzene levels in blood and breath, and phenol levels in urine were used to validate the rate of human conversion of benzene to benzene oxide, and urinary benzene metabolites from Chinese benzene worker populations provided model validation for rates of human conversion of benzene to muconic acid (MA) and phenylmercapturic acid (PMA), phenol (PH), catechol (CA), hydroquinone (HQ), and benzenetriol (BT). The calibrated human model reveals that while liver microsomal protein and CYP2E1 activities are lower on average in humans compared to mice, the mouse also shows far lower rates of benzene conversion to MA and PMA, and far higher conversion of benzene to BO/PH, and of BO/PH to CA, HQ, and BT. The model also differed substantially from existing human PBPK models with respect to several metabolic rate parameters of importance to interpreting benzene metabolism and health risks in human populations associated with bone marrow doses. The model provides a new methodological paradigm focused on integrating linked human liver metabolism data and calibration using biomonitoring data, thus allowing for model uncertainty analysis and more rigorous validation.

Metabolic Fate of Lignin in Birch Glucuronoxylan Extracts as Dietary Fiber Studied in a Rat Model.

SCOPE: While previously considered inert, recent studies suggest lignin metabolism with unknown metabolic fates is occurring in the gastrointestinal tract of several animal models. This study focuses on analyzing the potential metabolites of lignin. METHODS AND RESULTS: The diets of rats include relatively pure birch glucuronoxylan (pureGX) with residual lignin or lignin-rich GX (GXpoly) in their diet. Nuclear magnetic spectroscopy of the lignin isolated from the GXpoly-fed rats fecal sample shows high alteration in chemical structure, whereas lignin-carbohydrate complexes (LCCs) are enriched in fecal samples from the pureGX group. Moreover, the increased syringyl-to-guaiacyl (S/G) ratio suggests that lignin G-units are predominantly metabolized based on pyrolysis gas chromatography-mass spectrometry (pyr-GC/MS). The presence of small phenolic metabolites identified in urine samples of the GXpoly group, for example, ferulic and sinapic acids, their sulfate and glucuronide derivatives, and 4-sulfobenzylalcohol, suggests that the small fragmented lignin metabolites in the large intestine enter the plasma, and are further processed in the liver. Finally, the relative abundances of polyphenol-degrading Enterorhabdus and Akkermansia in the gut microbiota are associated with lignin metabolism. CONCLUSION: These findings give further evidence to lignin metabolism in the gut of nonruminants and provide insight to the potential microbes and metabolic routes.