Search

Liver cirrhosis is one of the most prevalent chronic liver disorders with high mortality. We aimed to explore changed gut microbiome and urine metabolome in compensatory liver cirrhosis (CLC) patients, thus providing novel diagnostic biomarkers for CLC. Forty fecal samples from healthy volunteers (control: 19) and CLC patients (patient: 21) were undertaken 16S rDNA sequencing. Chromatography-mass spectrometry was performed on 40 urine samples (20 controls and 20 patients). Microbiome and metabolome data were separately analyzed using corresponding bioinformatics approaches. The diagnostic model was constructed using the least absolute shrinkage and selection operator regression. The optimal diagnostic model was determined by five-fold cross-validation. Pearson correlation analysis was applied to clarify the relations among the diagnostic markers. 16S rDNA sequencing analyses showed changed overall alpha diversity and beta diversity in patient samples compared with those of controls. Similarly, we identified 841 changed metabolites. Pathway analysis revealed that the differential metabolites were mainly associated with pathways, such as tryptophan metabolism, purine metabolism, and steroid hormone biosynthesis. A 9-maker diagnostic model for CLC was determined, including 7 microorganisms and 2 metabolites. In this model, there were multiple correlations between microorganisms and metabolites. Subdoligranulum, Agathobacter, norank_f_Eubacterium_coprostanoligenes_group, Butyricicoccus, Lachnospiraceae_UCG_004, and L-2,3-Dihydrodipicolinate were elevated in CLC patients, whereas Blautia, Monoglobus, and 5-Acetamidovalerate were reduced. A novel diagnostic model for CLC was constructed and verified to be reliable, which provides new strategies for the diagnosis and treatment of CLC. [ABSTRACT FROM AUTHOR]

Abstract Dietary biomarkers in urine remain elusive when evaluating diet-induced oxidative stress and inflammation. In our previous study, we conducted a randomized controlled crossover trial to compare the short-term (4-weeks) effects of the balanced Korean diet (BKD) with Western diets, including the 2010 dietary guidelines for Americans (2010 DGA) and typical American diet (TAD), on various metabolic indices in obese Korean adults. Building on this work, the current research focuses on the impact of these dietary interventions on oxidative stress (d-ROMs and BAP) and inflammation (CRP, TNF-α, IL-6, IL-1β, MCP-1) biomarkers in serum, and the concurrent urine metabolomes. Each dietary regimen was in silico and experimentally examined for their antioxidant levels using ABTS, DPPH, and FRAP assays, as well as total flavonoid (TFC) and total phenolic (TPC) contents. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants (n = 48, average age: 41 years). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD (p 0.7, p

Dietary biomarkers in urine remain elusive when evaluating diet-induced oxidative stress and inflammation. In our previous study, we conducted a randomized controlled crossover trial to compare the short-term (4-weeks) effects of the balanced Korean diet (BKD) with Western diets, including the 2010 dietary guidelines for Americans (2010 DGA) and typical American diet (TAD), on various metabolic indices in obese Korean adults. Building on this work, the current research focuses on the impact of these dietary interventions on oxidative stress (d-ROMs and BAP) and inflammation (CRP, TNF-α, IL-6, IL-1β, MCP-1) biomarkers in serum, and the concurrent urine metabolomes. Each dietary regimen was in silico and experimentally examined for their antioxidant levels using ABTS, DPPH, and FRAP assays, as well as total flavonoid (TFC) and total phenolic (TPC) contents. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants (n = 48, average age: 41 years). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD (p < 0.05). Butanol extracts from recommended diets (BKD and 2010 DGA) showed significantly higher antioxidant activity compared to TAD in ABTS (p < 0.01), DPPH, and FRAP (p < 0.05) assays. Consistent results were observed in total phenolic and flavonoid contents, mirroring their respective antioxidant activities. Following the intervention period, oxidative stress & inflammation markers in serum varied marginally, however, the urine metabolite profiles were clearly demarcated for the BKD and Western dietary groups (PC1 = 5.41%). For BKD group, the pre- and post-intervention urine metabolite profiles were clearly segregated (PLS2 = 2.93%). Compared to TAD, urine extracts from the recommended dietary group showed higher abundance of benzoic acid & phenolic derivatives (VIP > 0.7, p < 0.05). Metabolites associated with oxidative stress were observed higher in the urine samples from Western dietary groups compared to BKD. Urine metabolomics data delineated the post-intervention effects of three dietary interventions which corroborates the respective findings for their effects on metabolic indices. [ABSTRACT FROM AUTHOR]

BackgroundAutism spectrum disorder (ASD) is often linked to gastrointestinal issues and altered serotonin metabolism. Emerging evidence suggests gut microbiota influence both, with fecal microbiota transplantation (FMT) offering a potential therapeutic approach. However, its impact on serotonin metabolism and ASD symptoms is not well understood. In this study, we aimed to evaluate the clinical effects of FMT and examine changes in specific urinary metabolites in children with ASD.MethodsA randomized double-blind controlled trial was performed to evaluate the clinical effects of FMT on GI and ASD-related symptoms. Gastrointestinal symptoms were assessed using the Gastrointestinal Symptom Rating Scale (GSRS), and the ASD-related symptoms were assessed using the Childhood Autism Rating Scale (CARS), Aberrant Behavior Checklist (ABC), and Social Responsiveness Scale (SRS) scores. Urinary metabolites were analyzed by homogeneous enzyme immunoassay using commercially available kits.ResultsSignificant improvements in GI and core ASD symptoms were observed following FMT intervention. The average GSRS scores decreased from 30.17 (before) to 19 (after; p

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets. [ABSTRACT FROM AUTHOR]

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings. [ABSTRACT FROM AUTHOR]

As an important medicinal and dietary flower tea, Chrysanthemi Flos has hypotensive, hypolipidemic and hypoglycaemic benefits. This study investigated the effects of two types of processed Chrysanthemi Flos products—oven-dried Chrysanthemi Flos (DCF) and shade-dried Chrysanthemi Flos (SCF)—on rats with metabolic syndrome (MetS) and their potential mechanisms of action. The pharmacodynamic analysis showed that DCF and SCF improved hypertension, regulated lipid profiles, and reduced liver and kidney damage. Metabolomics analysis revealed eight metabolites, including L-serine, oxaloacetate and succinate as potential biomarkers for mitigating metabolic disorders in MetS rats. Our findings provide scientific evidence for the integration of Chrysanthemi Flos-based products into clinical dietary interventions, offering insights into the mechanisms through which these products can ameliorate MetS. These results have important implications for the development of functional foods that can improve metabolic health.

The study of age‐related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of age‐related changes within and between compartments as these changes are likely highly interconnected. Understanding age‐related differences by compartments may shed light on the mechanism of their reciprocal interactions, which may contribute to the phenotypic manifestations of aging. To study such possible interactions, we carried out a targeted metabolomic analysis of plasma, skeletal muscle, and urine collected from healthy participants, age 22–92 years, and identified 92, 34, and 35 age‐associated metabolites, respectively. The metabolic pathways that were identified across compartments included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function. [ABSTRACT FROM AUTHOR]

Depression is a chronic, relapsing mental illness, often accompanied by loss of appetite, increased fatigue, insomnia and poor concentration. Here, we performed serum and urine metabolomics and fecal 16S rDNA sequencing studies on 57 unmedicated patients with major depressive disorder (MDD) and 57 healthy controls to characterize the metabolic and flora profile of MDD patients. We observed significant differences in serum and urinary metabolome between MDD patients and healthy individuals. Specifically, glycerophospholipid metabolism, primary bile acid biosynthesis and linoleic acid metabolism were significantly disordered in serum, and aminoacyl-tRNA biosynthesis, arginine biosynthesis, purine metabolism, phenylalanine metabolism, alanine, aspartate and glutamate metabolism, and pyrimidine metabolism were significantly impaired in urine. On this basis, we identified four potential diagnostic biomarkers for carnitine and four fatty acid classes in serum and urine, respectively. In addition, we observed significant disturbances of the gut microbiota in MDD patients. Spearman correlation analysis showed that imbalances in the gut microbiota were associated with metabolic disturbances, suggesting an important role of the gut microbiota in the pathogenesis of MDD. Our study provides a theoretical basis for further understanding of the pathogenesis of depression and for future clinical diagnosis and screening, as well as a basis for targeting the gut flora to optimize its structure for the prevention and treatment of depression. • Metabolic and gut microbiota profiles were analyzed in MDD patients and healthy individuals. • MDD patients have disturbed blood and urine metabolism and imbalanced gut microbiota. • Gut microbiota is involved in the pathophysiological mechanisms of overall metabolism in MDD patients. • Gut microbiota is an important target for the treatment of MDD. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate‐specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)‐based metabolomics has proven to be promising for advancing early‐detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers. This retrospective study of urine‐NMR samples, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate—key metabolites involved in cellular proliferation and microbiome effects, respectively—were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis. [ABSTRACT FROM AUTHOR]

IntroductionAlzheimer’s disease is a prevalent disease with a heavy global burden and is suggested to be a metabolic disease in the brain in recent years. The metabolome is considered to be the most promising phenotype which reflects changes in genetic, transcript, and protein profiles as well as environmental effects. Aiming to obtain a comprehensive understanding and convenient diagnosis of MCI and AD from another perspective, researchers are working on AD metabolomics. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.MethodsWe first enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples and conducted an LC–MS/MS analysis. In parallel, clinical data were collected and clinical examinations were performed. After statistical and bioinformatics analyzes, significant risk factors and differential urinary metabolites were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.ResultsFifty-seven AD patients, 43 MCI patients and 62 CN subjects were enrolled. A total of 2,140 metabolites were identified among which 125 significantly differed between the AD and CN groups, including 46 upregulated ones and 79 downregulated ones. In parallel, there were 93 significant differential metabolites between the MCI and CN groups, including 23 upregulated ones and 70 downregulated ones. AD diagnostic panel (30 metabolites+ age + APOE) achieved an AUC of 0.9575 in the test set while MCI diagnostic panel (45 metabolites+ age + APOE) achieved an AUC of 0.7333 in the test set. Atropine, S-Methyl-L-cysteine-S-oxide, D-Mannose 6-phosphate (M6P), Spiculisporic Acid, N-Acetyl-L-methionine, 13,14-dihydro-15-keto-tetranor Prostaglandin D2, Pyridoxal 5’-Phosphate (PLP) and 17(S)-HpDHA were considered valuable for both AD and MCI diagnosis and defined as hub metabolites. Besides, diagnostic metabolites were weakly correlated with cognitive functions.DiscussionIn conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN. Atropine, M6P and PLP were evidence-based hub metabolites in AD.

Background: Epigenetic age is an estimator of biological age based on DNA methylation; its discrepancy from chronologic age warrants further investigation. We recently reported that greater polyphenol intake benefitted ectopic fats, brain function, and gut microbiota profile, corresponding with elevated urine polyphenols. The effect of polyphenol-rich dietary interventions on biological aging is yet to be determined. Methods: We calculated different biological aging epigenetic clocks of different generations (Horvath2013, Hannum2013, Li2018, Horvath skin and blood2018, PhenoAge2018, PCGrimAge2022), their corresponding age and intrinsic age accelerations, and DunedinPACE, all based on DNA methylation (Illumina EPIC array; pre-specified secondary outcome) for 256 participants with abdominal obesity or dyslipidemia, before and after the 18-month DIRECT PLUS randomized controlled trial. Three interventions were assigned: healthy dietary guidelines, a Mediterranean (MED) diet, and a polyphenol-rich, low-red/processed meat Green-MED diet. Both MED groups consumed 28 g walnuts/day (+ 440 mg/day polyphenols). The Green-MED group consumed green tea (3–4 cups/day) and Mankai (Wolffia globosa strain) 500-ml green shake (+ 800 mg/day polyphenols). Adherence to the Green-MED diet was assessed by questionnaire and urine polyphenols metabolomics (high-performance liquid chromatography quadrupole time of flight). Results: Baseline chronological age (51.3 ± 10.6 years) was significantly correlated with all methylation age (mAge) clocks with correlations ranging from 0.83 to 0.95; p < 2.2e − 16 for all. While all interventions did not differ in terms of changes between mAge clocks, greater Green-Med diet adherence was associated with a lower 18-month relative change (i.e., greater mAge attenuation) in Li and Hannum mAge (beta = − 0.41, p = 0.004 and beta = − 0.38, p = 0.03, respectively; multivariate models). Greater Li mAge attenuation (multivariate models adjusted for age, sex, baseline mAge, and weight loss) was mostly affected by higher intake of Mankai (beta = − 1.8; p = 0.061) and green tea (beta = − 1.57; p = 0.0016) and corresponded with elevated urine polyphenols: hydroxytyrosol, tyrosol, and urolithin C (p < 0.05 for all) and urolithin A (p = 0.08), highly common in green plants. Overall, participants undergoing either MED-style diet had ~ 8.9 months favorable difference between the observed and expected Li mAge at the end of the intervention (p = 0.02). Conclusions: This study showed that MED and green-MED diets with increased polyphenols intake, such as green tea and Mankai, are inversely associated with biological aging. To the best of our knowledge, this is the first clinical trial to indicate a potential link between polyphenol intake, urine polyphenols, and biological aging. Trial registration: ClinicalTrials.gov, NCT03020186. [ABSTRACT FROM AUTHOR]

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings.

This study aimed to assess the growth performance and blood metabolites, as well as metabolic profiles in the urine of lambs fed on dietary rumen-protected choline (RPC). Thirty-six Dorper × Hu lambs weighing approximately 20 kg were equally assigned to three groups, and fed on three diets supplemented with different RPC concentrations (0, 0.25% and 0.75%) for 45 days. Supplementation of RPC significantly increased average daily gain (ADG) and decreased feed-to-gain ratio (F/G) of lambs (p < 0.05). Dietary RPC was significantly associated with elevated plasma high-density lipoprotein (HDL) and suppressed low-density lipoprotein (LDL) levels when compared to the control group (p < 0.05). Moreover, concentrations of very-low-density lipoprotein (VLDL) exhibited an increasing trend (p = 0.065), whereas β-hydroxybutyrate (BHBA) levels decreased (p = 0.086) in plasma. Analysis of urine metabolome revealed that RPC supplementation significantly suppressed urinary concentrations of pyruvate (p < 0.05), while increased urinary concentrations of trimethylamine oxide, p-cresol, phenylacetylglycine and hippurate (p < 0.05). These findings suggest that RPC supplementation can promote weight gain, alter plasma lipid metabolism and modify urinary metabolome which is correlated with energy metabolism, lipid metabolism and intestinal microbial metabolism in lambs. In conclusion, based on our findings, we recommend 0.25% RPC as a supplement for growing lambs. [ABSTRACT FROM AUTHOR]

Introduction: Urine metabolomics has been a promising technique in the liquid biopsy of urothelial cancer (UC). The comparison of upper tract urothelial cancer (UTUC), lower tract urothelial cancer (BCa), and healthy controls (HCs) need to be performed to find related biomarkers. Methods: In our investigation, urine samples from 35 UTUCs, 44 BCas, and 53 gender- and age-matched HCs were analyzed using liquid chromatographyhigh resolution mass spectrometry (LC-HRMS). In different groups, the differential metabolites and the disturbed metabolism pathways were explored. Transcriptomics and urine metabolomics are combined to identify the probably disturbed gene in BCa. Results: With an area under the curve (AUC) of 0.815, the panel consisting of prostaglandin I2, 5-methyldeoxycytidine, 2,6-dimethylheptanoyl carnitine, and deoxyinosine was able to discriminate UC from HCs. With an AUC of 0.845, the validation group also demonstrated strong predictive ability. UTUC and BCa without hematuria could be distinguished using the panel of 5'- methylthioadenosine, L-beta-aspartyl-L-serine, dehydroepiandrosterone sulfate, and N'-formylkynurenine (AUC=0.858). The metabolite panel comprising aspartyl-methionine, 7-methylinosine, and alpha-CEHC glucuronide could discriminate UTUC from BCa with hematuria with an AUC of 0.83. Fatty acid biosynthesis, purine metabolism, tryptophan metabolism, pentose and glucuronate interconversions, and arachidonic acid metabolism were dysregulated when comparing UC with HCs. PTGIS and BCHE, the genes related to the metabolism of prostaglandin I2 and myristic acid respectively, were significantly associated with the survival of BCa. Discussion: Not only could LC-HRMS urine metabolomic investigations distinguish UC from HCs, but they could also identify UTUC from BCa. Additionally, urine metabolomics combined with transcriptomics can find out the potential aberrant genes in the metabolism. [ABSTRACT FROM AUTHOR]

Urine metabolomics is gaining traction as a means of identifying metabolic signatures associated with health and disease states. Thirty-one (31) late preterm (LP) neonates admitted to the neonatal intensive care unit (NICU) and 23 age-matched healthy LPs admitted to the maternity ward of a tertiary hospital were included in the study. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed for urine metabolomic analysis on the 1st and 3rd days of life of the neonates. The data were analyzed using univariate and multivariate statistical analysis. A unique metabolic pattern of enhanced metabolites was identified in the NICU-admitted LPs from the 1st day of life. Metabolic profiles were distinct in LPs presenting with respiratory distress syndrome (RDS). The discrepancies likely reflect differences in the gut microbiota, either due to variations in nutrient intake or as a result of medical interventions, such as the administration of antibiotics and other medications. Altered metabolites could potentially serve as biomarkers for identifying critically ill LP neonates or those at high risk for adverse outcomes later in life, including metabolic risks. The discovery of novel biomarkers may uncover potential targets for drug discovery and optimal periods for effective intervention, offering a personalized approach. [ABSTRACT FROM AUTHOR]

Captive animal urine is rich in metabolites which is an important biological material for determining its estrus, pregnancy, health status, stress level and animal welfare by means of metabolite technique. However, urine samples are difficult to collect directly from the animal due to safety considerations. Urine samples were usually collected from the floor of animal’s enclosure after the animal’s excretion and moved to other place of the enclosure. Those samples are often contaminated by bacteria, which in turn affect the results of metabolite determination. It is necessary to explore a low-polluting and convenient urine collection and pretreatment method. In this paper, we collected 27 urine samples from eight captive giant pandas(Ailuropoda melanoleuca) (3 ♀, 5 ) by traditional methods, then each sample was divided into three groups for the control, filtrating with 0.22 μm filtration membrane and adding sodium azide treatments, respectively. Next, we used microbial cultures and Nuclear Magnetic Resonance (NMR) analysis and metabolite analysis to assay the bacteria removal efficacy of three treatments. The results showed that no bacteria were cultured in urine samples treated by filtration membrane, and there were no significant differences in the metabolites of NMR among three treatments. Further analysis found that seven and eight urinary metabolites significantly differed in genders and differed among age groups(both p < 0.05), respectively. The results suggest that the filter membrane pretreatment is effective for removing bacteria from urine samples, and can be used as a standard method for urine sample pretreatment and further evaluation of physiological indexes of giant pandas in metabolomics. Our findings not only enrich the basic metabolism database of giant pandas, and also provide data support for the health status monitoring, estrus and stress level assay in giant pandas and other captive wild animals. [ABSTRACT FROM AUTHOR]

Nowadays, developing effective intervention substances for hyperuricemia has become a public health issue. Herein, the therapeutic ability of anserine, a bioactive peptide, was validated through a comprehensive multiomics analysis of a rat model of hyperuricemia. Anserine was observed to improve liver and kidney function and modulate urate-related transporter expressions in the kidneys. Urine metabolomics showed that 15 and 9 metabolites were significantly increased and decreased, respectively, in hyperuricemic rats after the anserine intervention. Key metabolites such as fructose, xylose, methionine, erythronic acid, glucaric acid, pipecolic acid and trans-ferulic acid were associated with ameliorating kidney injury. Additionally, anserine regularly changed the gut microbiota, thereby ameliorating purine metabolism abnormalities and alleviating inflammatory responses. The integrated multiomics analysis indicated that Saccharomyces, Parasutterella excrementihominis and Emergencia timonensis were strongly associated with key differential metabolites. Therefore, we propose that anserine improved hyperuricemia via the gut–kidney axis, highlighting its potential in preventing and treating hyperuricemia. [ABSTRACT FROM AUTHOR]

Study Objectives: Children with late-onset (2-5 years) or persistent (3 months-5 years) sleep-related breathing disorder (SRBD) have an increased risk of behavior problems compared to children with no or early-onset SRBD. We sought to determine whether a combination of urine metabolites and sleep questionnaires could identify children at risk for SRBD-associated behavior problems.Methods: Urine and data were analyzed from the Edmonton site of the CHILD birth cohort study. We measured urine metabolites (random, mid-stream) at age three-years among a sub-cohort of participants (n = 165). Random Forest with a Boruta wrapper was used to identify important metabolites (creatinine-corrected, z-scores) for late/persistent SRBD versus no/early SRBD (reference). An algorithm was subsequently generated to predict late/persistent SRBD in children with a history of snoring using a metabolite composite score (z-scores < or ≥ 0) plus the SDBeasy score defined as [age (yrs.) of most recent positive SRBD]2 - [age (yrs.) first reported ever snoring]2.Results: Of the 165 children with SRBD data, 40 participants had late/persistent SRBD. Seven urinary metabolites in addition to the SDBeasy score were confirmed as important for late/persistent SRBD (AUC = 0.87). Among children with an ever-snoring history and a metabolite composite score ≥0, those with SDBeasy score ≥3 were over 13-fold more likely to have late/persistent SRBD (OR 13.7; 95%CI: 3.0, 62.1; p = 0.001). This algorithm has a Sensitivity of 69.6%, Specificity of 85.7% and a positive likelihood ratio (+LR) of 4.9.Conclusions: We developed a predictive algorithm using a combination of questionnaires and urine metabolites at age three-years to identify children with late/persistent SRBD by five-years of age. [ABSTRACT FROM AUTHOR]

Abstract Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by a deficiency of the arylsulfatase A (ARSA). ARSA deficiency leads to an accumulation of sulfatides primarily in the nervous system ultimately causing demyelination. With evolving therapeutic options, there is an increasing need for indicators to evaluate disease progression. Here, we report targeted metabolic urine profiling of 56 MLD patients including longitudinal sampling, using 1H (proton) nuclear magnetic resonance (NMR) spectroscopy. 1H‐NMR urine spectra of 119 MLD samples and 323 healthy controls were analyzed by an in vitro diagnostics research (IVDr) tool, covering up to 50 endogenous and 100 disease‐related metabolites on a 600‐MHz IVDr NMR spectrometer. Quantitative data reports were analyzed regarding age of onset, clinical course, and therapeutic intervention. The NMR data reveal metabolome changes consistent with a multiorgan affection in MLD patients in comparison to controls. In the MLD cohort, N‐acetylaspartate (NAA) excretion in urine is elevated. Early onset MLD forms show a different metabolic profile suggesting a metabolic shift toward ketogenesis in comparison to late onset MLD and controls. In samples of juvenile MLD patients who stabilize clinically after hematopoietic stem cell transplantation (HSCT), the macrophage activation marker neopterin is elevated. We were able to identify different metabolic patterns reflecting variable organ disturbances in MLD, including brain and energy metabolism and inflammatory processes. We suggest NAA in urine as a quantitative biomarker for neurodegeneration. Intriguingly, elevated neopterin after HSCT supports the hypothesis that competent donor macrophages are crucial for favorable outcome.

The aim of this study was to compare the urine metabolic fingerprint of healthy neonates exclusively breastfed with that of neonates fed with a synbiotic-enriched formula (Rontamil® Complete 1) at four time points (the 3rd and 15th days of life and the 2nd and 3rd months). The determination of urine metabolic fingerprint was performed using NMR metabolomics. Multivariate data analyses were performed with SIMCA-P 15.0 software and R language. Non-distinct profiles for both groups (breastfeeding and synbiotic formula) for the two first time points (3rd and 15th days of life) were detected, whereas after the 2nd month of life, a discrimination trend was observed between the two groups, which was further confirmed at the 3rd month of life. A clear discrimination of the synbiotic formula samples was evident when comparing the metabolites taken in the first days of life (3rd day) with those taken in the 2nd and 3rd months of life. In both cases, OPLS-DA models explained more than 75% of the metabolic variance. Non-distinct metabolomic profiles were obtained between breastfed and synbiotic-formula-fed neonates up to the 15th day of life. Discrimination trends were observed only after the 2nd month of the study, which could be attributed to breastfeeding variations and the consequent dynamic profile of urine metabolites compared to the stable ingredients of the synbiotic formula. [ABSTRACT FROM AUTHOR]

Poncirin (PC) and its aglycone, isosakuranetin (IR), occur naturally in citrus fruits. This study aimed to explore the pathways behind the different health benefits of PC and IR by evaluating the effect of these two bioactive flavonoids on the gut microbial diversity and metabolomics of mice. The 16S rRNA gene sequencing was used to analyze the alteration of gut microbiota in mice after PC and IR intervention. The metabolic impact of PC and IR in mice were studied using a metabolomics approach based on LC-MS analysis. Results showed that, after 7 days intervention, PC and IR multiplied the abundance of Parabacteroides in mice's intestinal tracts by 1.2 and 1.0 times, respectively. PC increased the abundance of Bacteroides by 2.4 times. IR reduced the Allobaculum abundance by 1.0 time and increased Alloprevotella abundance by 1.5 times. When mice were given PC, their fecal acetic acid level increased by 1.8 times, while their isobutyric and isovaleric acid content increased by 1.2 and 1.3 times, respectively. Supplementation with IR had no significant effect on the content of short-chain fatty acids (SCFAs) in the feces of mice. The potential urine biomarkers of mice in the PC group were involved in the digestion and absorption of protein and carbohydrate, as well as the metabolism of amino acids, such as glycine, serine, threonine, tryptophan, D-arginine, D-ornithine, etc. IR mainly affected the amino acid metabolic pathways in mice, including taurine and hypotaurine metabolism, glutathione metabolism, histidine metabolism, D-glutamate metabolism, etc. This study provided valuable clues for future research on the health promoting mechanisms of PC and IR. [ABSTRACT FROM AUTHOR]

Urine metabolomics is gaining traction as a means of identifying metabolic signatures associated with health and disease states. Thirty-one (31) late preterm (LP) neonates admitted to the neonatal intensive care unit (NICU) and 23 age-matched healthy LPs admitted to the maternity ward of a tertiary hospital were included in the study. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed for urine metabolomic analysis on the 1st and 3rd days of life of the neonates. The data were analyzed using univariate and multivariate statistical analysis. A unique metabolic pattern of enhanced metabolites was identified in the NICU-admitted LPs from the 1st day of life. Metabolic profiles were distinct in LPs presenting with respiratory distress syndrome (RDS). The discrepancies likely reflect differences in the gut microbiota, either due to variations in nutrient intake or as a result of medical interventions, such as the administration of antibiotics and other medications. Altered metabolites could potentially serve as biomarkers for identifying critically ill LP neonates or those at high risk for adverse outcomes later in life, including metabolic risks. The discovery of novel biomarkers may uncover potential targets for drug discovery and optimal periods for effective intervention, offering a personalized approach.

[Display omitted] • A total of 50 chemical compounds were identified from the aqueous decoction of oven-dried (DCF) and shade-dried Chrysanthemi Flos (SCF). • Chrysanthemi Flos showed hypotensive, lipid-regulating, and liver and kidney damage-reducing effects in MetS disease. • The eight metabolites considered as potential biomarkers for the treatment of MetS. • No significant difference between DCF and SCF for the treatment of MetS. As an important medicinal and dietary flower tea, Chrysanthemi Flos has hypotensive, hypolipidemic and hypoglycaemic benefits. This study investigated the effects of two types of processed Chrysanthemi Flos products—oven-dried Chrysanthemi Flos (DCF) and shade-dried Chrysanthemi Flos (SCF)—on rats with metabolic syndrome (MetS) and their potential mechanisms of action. The pharmacodynamic analysis showed that DCF and SCF improved hypertension, regulated lipid profiles, and reduced liver and kidney damage. Metabolomics analysis revealed eight metabolites, including L-serine, oxaloacetate and succinate as potential biomarkers for mitigating metabolic disorders in MetS rats. Our findings provide scientific evidence for the integration of Chrysanthemi Flos -based products into clinical dietary interventions, offering insights into the mechanisms through which these products can ameliorate MetS. These results have important implications for the development of functional foods that can improve metabolic health. [ABSTRACT FROM AUTHOR]

• >150 organic metabolites are oxidised over chloride and urea in unconcentrated, non-hydrolysed urine acidified to pH 3.0. • Heat-activated peroxydisulphate removed >50% TOC and degraded >40% ΣOMs with <10% nitrogen loss. • Heating real, unconcentrated urine acidified to pH 3.0 at 90 °C for 1 h activated >90% of 60 mM peroxydisulphate. • Concentrated urine had lower persulfate activation but higher chloride & urea degradation compared to unconcentrated urine. The human urine metabolome is complex, containing a wide range of organic metabolites that affect treatment of urine collected in resource-oriented sanitation systems. In this study, an advanced oxidation process involving heat-activated peroxydisulphate was used to selectively oxidise organic metabolites in urine over urea and chloride. Initial experiments evaluated optimal conditions (peroxydisulphate dose, temperature, time, pH) for activation of peroxydisulphate in unconcentrated, non-hydrolysed synthetic urine and real urine acidified to pH 3.0. Subsequent experiments determined the fate of 268 endogenous organic metabolites (OMs) and removal of COD from unconcentrated and concentrated real urine (80–90% mass reduced by evaporation). The results revealed >90% activation of 60 mM peroxydisulphate in real unconcentrated urine heated to 90 °C for 1 h, resulting in 43% ΣOMs degradation, 22% COD removal and 56% total organic carbon removal, while >94% of total nitrogen and >97% of urea in real unconcentrated urine were recovered. The mechanism of urea degradation was identified to be chemical hydrolysis to ammonia, with the rate constant for this reaction determined to be 1.9 × 10−6 s−1 at pH 3.0 and 90 °C. Treating concentrated real urine resulted in similar removal of COD, ΣOMs degradation and total nitrogen loss as observed for unconcentrated urine, but with significantly higher chloride oxidation and chemical hydrolysis of urea. Targeted metabolomic analysis revealed that peroxydisulphate treatment degraded 157 organic metabolites in urine, of which 67 metabolites were degraded by >80%. The rate constant for the reaction of sulphate radicals with oxidisable endogenous organic metabolites in urine was estimated to exceed 108 M−1 s−1. These metabolites were preferentially oxidised over chloride and urea in acidified, non-hydrolysed urine treated with peroxydisulphate. Overall, the findings support the development of emerging urine recycling technologies, including alkaline/acid dehydration and reverse osmosis, where the presence of endogenous organic urine metabolites significantly influences treatment parameters such as energy demand and product purity. [ABSTRACT FROM AUTHOR]

Dementia is a chronic and multifactor‐induced neurodegenerative disorder that occurs frequently in the elderly with weak constitution and insufficient vital energy. However, the relationship between vital energy deficiency and the occurrence and development of dementia is still unclear. In this study, a rat model of dementia with vital energy deficiency was established through intraperitoneal injection with d‐galactose and AlCl3 and combined with exhaustive swimming. Changes in the dementia with vital energy deficiency rat model were assessed by examining behaviors, hippocampal histopathological and biochemical parameters, and serum biochemical parameters. Urine metabolomics based on ultra‐high‐performance liquid chromatography coupled with an orbitrap mass spectrometer was also used to discover endogenous metabolic profile and disease‐related biomarkers and investigate the potential mechanism of dementia with vital energy deficiency. Among the 31 potential biomarkers that were identified, nine involved metabolic pathways. The four main types were phenylalanine, tyrosine and tryptophan metabolism, taurine and hypotaurine metabolism, and citrate cycle and pyrimidine metabolism. The pathogenesis of dementia with vital energy deficiency is mainly neurotoxin accumulation and body aging that leads to oxidative stress injury and loss of neuronal protective substances. Vital energy deficiency inhibits the body's energy metabolism and eventually leads to aggravate the dementia. [ABSTRACT FROM AUTHOR]

Introduction: Psidium friedrichsthalianum fruits have in vitro antioxidant activity and their intake has been suggested to have potential health benefits; however, there is still no evidence on the potential in vivo effect of their consumption. Objective: We aim to study the effect of the oral administration of a P. friedrichsthalianum juice on the urinary metabolome of adult male Wistar rats. Methods: Acute and short-term interventions were carried out and urine sample metabolites were analyzed in a 600 MHz NMR instrument with a NOESY-presat sequence.and post-treatment effects were identified by comparison against control conditions. Results: Acute administration caused a decrease in the excretion of citrate and allantoin in the 0 to 6 h period and citrate and α-ketoglutarate in the 6 to 12 h period. Lactate and Krebs cycle intermediates showed reduced excretion in the 12 to 24 h period. Short-term administration (for 7 days) decreased the excretion of Krebs cycle intermediates together with lactate and allantoin. The effect was stronger after short-term administration suggesting a dose-dependent effect. Conclusion: P. friedrichsthalianum juice caused a change in rat excretion of energy metabolites, probably associated with an increase in aerobic metabolism, suggesting in vivo modulation of the redox balance.

The sensitive, specific, fast, robust and noninvasive biomarkers for the evaluation of prostate cancer (PC) remain elusive in medical research. However, efforts are in full sway to investigate and resolve these puzzles for clinical practice. Advances in modern analytical techniques, sample processing, and the emergence of multiple omics approaches have created a great hope for the development of better detection modalities for PC. The objective of the present review is to provide a concise overview of the PC metabolomics-based potential discriminating molecules in urine samples using nuclear magnetic resonance spectroscopy and mass spectrometry. A literature search was executed to find the studies reporting the noninvasive urine-based biomarkers for the diagnosis and prognosis of underlying disease. Most studies have extensivelyreported PC discriminating molecules with their respective controls. Additionally, pathophysiology and the treatment paradigm of PC are summarized and related to the insights underpinning the therapeutic intervention of PC. With multi-centric, global, comprehensive omics approaches via either a non- or least-invasive bio-matrix may open new avenues of research for PC biomarker discovery, backed by a molecular mechanistic outline. [ABSTRACT FROM AUTHOR]

Comprehensive analyses of multi-omics data may provide insights into interactions between different biological layers concerning distinct clinical features. We integrated data on the gut microbiota, blood parameters and urine metabolites of treatment-naive individuals presenting a wide range of metabolic disease phenotypes to delineate clinically meaningful associations. Trans-omics correlation networks revealed that candidate gut microbial biomarkers and urine metabolite feature were covaried with distinct clinical phenotypes. Integration of the gut microbiome, the urine metabolome and the phenome revealed that variations in one of these three systems correlated with changes in the other two. In a specific note about clinical parameters of liver function, we identified Eubacteriumeligens, Faecalibacteriumprausnitzii and Ruminococcuslactaris to be associated with a healthy liver function, whereas Clostridium bolteae, Tyzzerellanexills, Ruminococcusgnavus, Blautiahansenii, and Atopobiumparvulum were associated with blood biomarkers for liver diseases. Variations in these microbiota features paralleled changes in specific urine metabolites. Network modeling yielded two core clusters including one large gut microbe-urine metabolite close-knit cluster and one triangular cluster composed of a gut microbe-blood-urine network, demonstrating close inter-system crosstalk especially between the gut microbiome and the urine metabolome. Distinct clinical phenotypes are manifested in both the gut microbiome and the urine metabolome, and inter-domain connectivity takes the form of high-dimensional networks. Such networks may further our understanding of complex biological systems, and may provide a basis for identifying biomarkers for diseases. Deciphering the complexity of human physiology and disease requires a holistic and trans-omics approach integrating multi-layer data sets, including the gut microbiome and profiles of biological fluids. By studying the gut microbiome on carotid atherosclerosis, we identified microbial features associated with clinical parameters, and we observed that groups of urine metabolites correlated with groups of clinical parameters. Combining the three data sets, we revealed correlations of entities across the three systems, suggesting that physiological changes are reflected in each of the omics. Our findings provided insights into the interactive network between the gut microbiome, blood clinical parameters and the urine metabolome concerning physiological variations, and showed the promise of trans-omics study for biomarker discovery. [ABSTRACT FROM AUTHOR]

Canine babesiosis is a tick-borne disease with a worldwide distribution, caused by the haemoprotozoan parasites of the genus Babesia. One of the most prevalent complication is acute kidney injury, and an early diagnosis of altered kidney function remains a challenge for veterinary practice. The aim of this study was to assess the urine metabolic profile from dogs with babesiosis and different degree of kidney function using untargeted and targeted MS-based metabolomics approaches. In this study, 22 dogs naturally infected with Babesia canis and 12 healthy dogs were included. Untargeted metabolomics approach identified 601 features with a differential abundance between the healthy group and groups of dogs with babesiosis and different level of kidney function, with 27 of them identified as a match to known standards; while targeted approach identified 17 metabolites with significantly different concentrations between the groups. A pattern of significantly altered metabolites referring to the inflammatory host response, oxidative stress, and energy metabolism modulation in babesiosis was presented. Our findings have demonstrated that kidney dysfunction accompanying canine babesiosis was associated with changes in amino acid metabolism, energy metabolism, fatty acid metabolism, and biochemical pathways such as urea cycle and ammonia detoxication. These findings will enable the inclusion of urinary markers for the detection and monitoring of renal damage in babesiosis, as well as in other similar diseases. [ABSTRACT FROM AUTHOR]

The current diagnostic work‐up of inborn errors of metabolism (IEM) is rapidly moving toward integrative analytical approaches. We aimed to develop an innovative, targeted urine metabolomics (TUM) screening procedure to accelerate the diagnosis of patients with IEM. Urinary samples, spiked with three stable isotope‐labeled internal standards, were analyzed for 258 diagnostic metabolites with an ultra‐high performance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry (UHPLC‐QTOF‐MS) configuration run in positive and negative ESI modes. The software automatically annotated peaks, corrected for peak overloading, and reported peak quality and shifting. Robustness and reproducibility were satisfactory for most metabolites. Z‐scores were calculated against four age‐group‐matched control cohorts. Disease phenotypes were scored based on database metabolite matching. Graphical reports comprised a needle plot, annotating abnormal metabolites, and a heatmap showing the prioritized disease phenotypes. In the clinical validation, we analyzed samples of 289 patients covering 78 OMIM phenotypes from 12 of the 15 society for the study of inborn errors of metabolism (SSIEM) disease groups. The disease groups include disorders in the metabolism of amino acids, fatty acids, ketones, purines and pyrimidines, carbohydrates, porphyrias, neurotransmitters, vitamins, cofactors, and creatine. The reporting tool easily and correctly diagnosed most samples. Even subtle aberrant metabolite patterns as seen in mild multiple acyl‐CoA dehydrogenase deficiency (GAII) and maple syrup urine disease (MSUD) were correctly called without difficulty. Others, like creatine transporter deficiency, are illustrative of IEM that remain difficult to diagnose. We present TUM as a powerful diagnostic screening tool that merges most urinary diagnostic assays expediting the diagnostics for patients suspected of an IEM. [ABSTRACT FROM AUTHOR]

Comprehensive analyses of multi-omics data may provide insights into interactions between different biological layers concerning distinct clinical features. We integrated data on the gut microbiota, blood parameters and urine metabolites of treatment-naive individuals presenting a wide range of metabolic disease phenotypes to delineate clinically meaningful associations. Trans-omics correlation networks revealed that candidate gut microbial biomarkers and urine metabolite feature were covaried with distinct clinical phenotypes. Integration of the gut microbiome, the urine metabolome and the phenome revealed that variations in one of these three systems correlated with changes in the other two. In a specific note about clinical parameters of liver function, we identified Eubacteriumeligens, Faecalibacteriumprausnitzii and Ruminococcuslactaris to be associated with a healthy liver function, whereas Clostridium bolteae, Tyzzerellanexills, Ruminococcusgnavus, Blautiahansenii, and Atopobiumparvulum were associated with blood biomarkers for liver diseases. Variations in these microbiota features paralleled changes in specific urine metabolites. Network modeling yielded two core clusters including one large gut microbe-urine metabolite close-knit cluster and one triangular cluster composed of a gut microbe-blood-urine network, demonstrating close inter-system crosstalk especially between the gut microbiome and the urine metabolome. Distinct clinical phenotypes are manifested in both the gut microbiome and the urine metabolome, and inter-domain connectivity takes the form of high-dimensional networks. Such networks may further our understanding of complex biological systems, and may provide a basis for identifying biomarkers for diseases. Deciphering the complexity of human physiology and disease requires a holistic and trans-omics approach integrating multi-layer data sets, including the gut microbiome and profiles of biological fluids. By studying the gut microbiome on carotid atherosclerosis, we identified microbial features associated with clinical parameters, and we observed that groups of urine metabolites correlated with groups of clinical parameters. Combining the three data sets, we revealed correlations of entities across the three systems, suggesting that physiological changes are reflected in each of the omics. Our findings provided insights into the interactive network between the gut microbiome, blood clinical parameters and the urine metabolome concerning physiological variations, and showed the promise of trans-omics study for biomarker discovery.

Canine babesiosis is a tick-borne disease with a worldwide distribution, caused by the haemoprotozoan parasites of the genus Babesia. One of the most prevalent complication is acute kidney injury, and an early diagnosis of altered kidney function remains a challenge for veterinary practice. The aim of this study was to assess the urine metabolic profile from dogs with babesiosis and different degree of kidney function using untargeted and targeted MS-based metabolomics approaches. In this study, 22 dogs naturally infected with Babesia canis and 12 healthy dogs were included. Untargeted metabolomics approach identified 601 features with a differential abundance between the healthy group and groups of dogs with babesiosis and different level of kidney function, with 27 of them identified as a match to known standards; while targeted approach identified 17 metabolites with significantly different concentrations between the groups. A pattern of significantly altered metabolites referring to the inflammatory host response, oxidative stress, and energy metabolism modulation in babesiosis was presented. Our findings have demonstrated that kidney dysfunction accompanying canine babesiosis was associated with changes in amino acid metabolism, energy metabolism, fatty acid metabolism, and biochemical pathways such as urea cycle and ammonia detoxication. These findings will enable the inclusion of urinary markers for the detection and monitoring of renal damage in babesiosis, as well as in other similar diseases.

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury.Setting: Outpatient sports medicine clinic.Participants: Twenty-six male youth sport participants.Methods: Urine was analyzed pre-injury and after SRC by 1H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome.Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036).Conclusion: We found that 1H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Few studies have addressed the impact of diagnostic urine metabolites and the clinical outcomes associated with genitourinary urothelial (GU) cancer to date. Furthermore, longitudinal analysis of the dynamics of urine metabolites contributing to the detection of GU cancer has not yet been fully investigated; therefore, the discovery of novel diagnostic urine biomarkers is of enormous interest. We explored the correlation of the urine metabolomic profiles to GU cancers. The aqueous metabolites of the GU cancer and the control were also identified and analyzed through high-resolution1H nuclear magnetic resonance (NMR) spectroscopy. Compared with the control, the urine metabolites of the tumor were studied in relation to changes over time in a linear mixed model for repeated measures. The urine metabolites of sixty-three (44 male and 19 female) patients with GU cancers were systemically analyzed. The urine metabolite profile in GU cancer was significantly higher than those in the control group (p

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury. Setting: Outpatient sports medicine clinic. Participants: Twenty-six male youth sport participants. Methods: Urine was analyzed pre-injury and after SRC by 1H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t -test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome. Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t -test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036). Conclusion: We found that 1H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion. [ABSTRACT FROM AUTHOR]

Few studies have addressed the impact of diagnostic urine metabolites and the clinical outcomes associated with genitourinary urothelial (GU) cancer to date. Furthermore, longitudinal analysis of the dynamics of urine metabolites contributing to the detection of GU cancer has not yet been fully investigated; therefore, the discovery of novel diagnostic urine biomarkers is of enormous interest. We explored the correlation of the urine metabolomic profiles to GU cancers. The aqueous metabolites of the GU cancer and the control were also identified and analyzed through high-resolution1H nuclear magnetic resonance (NMR) spectroscopy. Compared with the control, the urine metabolites of the tumor were studied in relation to changes over time in a linear mixed model for repeated measures. The urine metabolites of sixty-three (44 male and 19 female) patients with GU cancers were systemically analyzed. The urine metabolite profile in GU cancer was significantly higher than those in the control group (p<0.05). Sevenurine metabolites including histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, and isoleucine as well as other pathways were identified statistically and were significantly associated with GU cancer detection with longitudinal analysis. We discovered that histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, isoleucine, succinic acid, lysine2-aminobutyric acid, and acetic acid are involved significantly in all types of male patients in whom the type (upper tract) of urine metabolites were found to be statistically significant compared with the control. We did not find any statistical significance in urine biomarkers between female and male patients. However, a statistically insignificant correlation was found among the grade and stage with the metabolites. [ABSTRACT FROM AUTHOR]

Poncirin (PC) and its aglycone, isosakuranetin (IR), occur naturally in citrus fruits. This study aimed to explore the pathways behind the different health benefits of PC and IR by evaluating the effect of these two bioactive flavonoids on the gut microbial diversity and metabolomics of mice. The 16S rRNA gene sequencing was used to analyze the alteration of gut microbiota in mice after PC and IR intervention. The metabolic impact of PC and IR in mice were studied using a metabolomics approach based on LC-MS analysis. Results showed that, after 7 days intervention, PC and IR multiplied the abundance of Parabacteroides in mice’s intestinal tracts by 1.2 and 1.0 times, respectively. PC increased the abundance of Bacteroides by 2.4 times. IR reduced the Allobaculum abundance by 1.0 time and increased Alloprevotella abundance by 1.5 times. When mice were given PC, their fecal acetic acid level increased by 1.8 times, while their isobutyric and isovaleric acid content increased by 1.2 and 1.3 times, respectively. Supplementation with IR had no significant effect on the content of short-chain fatty acids (SCFAs) in the feces of mice. The potential urine biomarkers of mice in the PC group were involved in the digestion and absorption of protein and carbohydrate, as well as the metabolism of amino acids, such as glycine, serine, threonine, tryptophan, D-arginine, D-ornithine, etc. IR mainly affected the amino acid metabolic pathways in mice, including taurine and hypotaurine metabolism, glutathione metabolism, histidine metabolism, D-glutamate metabolism, etc. This study provided valuable clues for future research on the health promoting mechanisms of PC and IR.

Dahuang–Mudan decoction (DMD) is a formula that has been widely used as a complementary treatment for inflammatory bowel disease (IBD). However, the mechanism of action of DMD in IBD has not been clearly elucidated. Therefore, we developed a metabolomics‐based method to evaluate the effects and potential mechanisms of DMD in a 2,4,6‐trinitobenzene sulfonic acid (TNBS)‐induced colitis model. The ultra‐high‐performance liquid chromatography/quadrupole time‐of‐flight mass spectrometry (UPLC/QTOF–MS) method combined with multiple analysis approaches including principal component analysis, partial least square discriminant analysis and orthogonal partial least square discriminant analysis were used to investigate the different urinary metabolites. We identified 29 potential biomarkers of TNBS‐induced colitis that returned to normal conditions after DMD administration. Pathway analysis indicated that changes in these metabolites were associated with cysteine and methionine metabolism, citric acid cycle, glycolysis and glycolic regeneration, pyruvate metabolism, biosynthesis of valine, leucine and isoleucine, biosynthesis of primary bile acids, glycine, serine and threonine metabolism, caffeine metabolism, arginine and proline metabolism and phenylalanine metabolism. It is worth noting that DMD has potential therapeutic effects on TNBS‐induced colitis, which functions by restoring the balance of multiple disturbed pathways to a normal condition. This study suggests the reliability of metabolomics‐based approaches to identifying biomarkers and pathways, which facilitate further investigation of the potential mechanisms of DMD. [ABSTRACT FROM AUTHOR]

Patients are turning into herbs for the management of diabetes, which cause increasing in the demand of plant-based alternative medicines. Ficus deltoidea or locally known as "Mas Cotek" in Malaysia is a famous herbal plant. However, many varieties of F. deltoidea existed with varied antidiabetic activities inspire us to evaluate in vivo antidiabetic activity of the most available varieties of F. deltoidea. Therefore, antihyperglycemic effect of different varieties of F. deltoidea at dose 250 mg/kg was evaluated on streptozotocin-nicotinamide–induced diabetic rats and further assessed their urinary metabolites using proton nuclear magnetic resonance (1H-NMR). The hyperglycemic blood level improved towards normoglycemic state after 30 days of treatment with standardized extracts of F. deltoidea var. trengganuensis, var. kunstleri, and var. intermedia. The extracts also significantly managed the biochemical parameters in diabetic rats. Metabolomics results showed these varieties were able to manage the altered metabolites of diabetic rats by shifting some of the metabolites back to their normal state. This knowledge might be very important in suggesting the use of these herbs in long-term treatment for diabetes. The most potential variety can be recommended, which may be useful for further pharmacological studies and herbal authentication processes. [ABSTRACT FROM AUTHOR]

Background: The pathophysiology of reversible cerebral vasoconstriction syndrome is unclear. An unbiased systems-based approach might help to illustrate the metabolite profiling and underlying pathophysiology.Methods: Urine samples were collected from reversible cerebral vasoconstriction syndrome patients and matched controls recruited in Taipei Veterans General Hospital. 1H-Nuclear magnetic resonance was used to initially explore the metabolic profile, and liquid chromatography tandem mass spectrometry was then used to identify metabolic alterations in reversible cerebral vasoconstriction syndrome. Untargeted metabolite screening was randomly performed on 10 reversible cerebral vasoconstriction syndrome patients and 10 control subjects in the discovery phase. The selected untargeted metabolites were further validated on 47 reversible cerebral vasoconstriction syndrome patients during their ictal stage (with 40 of them having remission samples) and 47 controls in the replication phase.Results and Conclusion: Six metabolites-hippurate, citrate, 1,3,7-trimethyluric acid, ascorbic acid, D-glucurono-6,3-lactone, and D-threo-isocitric acid-with t-test derived p-value < 0.05 and VIP score >1, were identified as potential urine signatures that can well distinguish reversible cerebral vasoconstriction syndrome subjects at ictal stage from controls. Among them, citrate, hippurate, ascorbic acid, and D-glucurono-6,3-lactone were significantly lower, and 1,3,7-trimethyluric acid and D-threo-isocitric acid were higher in reversible cerebral vasoconstriction syndrome patients. Of these, four selected metabolites, citrate, D-glucurono-6,3-lactone, ascorbic acid, and 1,3,7-trimethyluric acid, returned to normal levels in remission. These metabolites are related to pathways associated with free radical scavenging, with the hub molecules being associated with endothelial dysfunction or sympathetic overactivity. Whether these metabolites and their implicated networks play a role in the pathogenesis of reversible cerebral vasoconstriction syndrome remains to be confirmed. [ABSTRACT FROM AUTHOR]

As a well‐known traditional Chinese medicine formula, Ding‐Zhi‐Xiao‐Wan has long been used for the routine treatment of Alzheimer's disease. However, the mechanism of Ding‐Zhi‐Xiao‐Wan in treating Alzheimer's disease is unclear. Therefore, a nontargeted metabolomics method based on ultrahigh performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry has been established to explore the metabolic variations in the urine of Alzheimer's disease rats and investigate the therapeutic mechanism of Ding‐Zhi‐Xiao‐Wan on Alzheimer's disease. To develop a better rat model of Alzheimer's disease, amyloid β25‐35 was injected into the bilateral hippocampus of Sprague–Dawley rats. Multivariate analysis approaches were applied to differentiate the urine components between the four groups. Thereafter, a targeted metabolomics method was used to verify the identified endogenous metabolites and determine the mechanism of action of Ding‐Zhi‐Xiao‐Wan. Altogether, 26 potential biomarkers were found, of which 15 biomarkers (10 of which are potential biomarkers found in nontargeted metabolomics) were identified. The results show that Ding‐Zhi‐Xiao‐Wan mainly affects the pathways of taurine and hypotaurine metabolism, tryptophan metabolism, and phenylalanine metabolism. Ding‐Zhi‐Xiao‐Wan might play a role in the treatment of Alzheimer's disease by mediating antioxidative stress, regulation of energy metabolism, improvement of intestinal microbes, and protection of nerve cells. [ABSTRACT FROM AUTHOR]

Background: Renal cell carcinoma (RCC) is the most common and lethal malignancy of the kidney. Distinguishing RCC from benign renal tumors and healthy controls is still a clinical challenge. Urine metabolomics has been used to identify biomarkers of clinical diseases. Methods: In the present study, we explored the urine metabolomes of a cohort of 61 patients with renal tumors (39 RCC and 22 benign renal tumors) and 68 healthy controls using liquid chromatography coupled with high-resolution mass spectrometry (LC–MS). Results: Metabolic profiling of urine could significantly differentiate RCC from healthy controls and benign renal tumors. Metabolic pathways, including lysine metabolism and phenylalanine metabolism, were found to be disturbed in the RCC group. Steroid hormone biosynthesis was significantly different between the benign tumor group and the RCC group. RCC biomarkers were further explored. A metabolite panel consisting of cortolone, testosterone and L-2-aminoadipate adenylate was discovered to have good ability of distinguishing RCC from benign tumors, with an AUC of 0.868 for tenfold cross-validation and 0.873 for the validation group. In addition, the panel of aminoadipic acid, 2-(formamido)-N1-(5-phospho-d-ribosyl) acetamidine and alpha-N-phenylacetyl-l-glutamine could distinguish the RCC group from the healthy control group, with an AUC of 0.841 for tenfold cross-validation and 0.894 for the validation group. Conclusions: This pilot study suggests that urine metabolomics may be useful in differentiating RCC from healthy controls and benign renal tumors. [ABSTRACT FROM AUTHOR]

Background: Despite a reduction of child mortality in low-income countries, acutely ill undernourished children still have an elevated risk of death. Those at highest risk are children with severe acute malnutrition (SAM) who often show metabolic dysregulation that remains poorly understood.Objective: We performed a pilot study to examine changes in urinary organic acids during nutritional rehabilitation of children with SAM, and to identify metabolites associated with the presence of edema or with mortality.Methods: This study included 76 children aged between 6 and 60 months, hospitalized for SAM at the Moyo Nutritional Rehabilitation and Research Unit in Blantyre, Malawi. Urine was collected at admission and 3 days after clinical stabilization and metabolomics were performed using gas chromatography-mass spectrometry. Metabolite concentrations were evaluated with both uni- and multivariate approaches.Results: Most metabolites increased 3 days after clinical stabilization, and total urinary concentration changed from 1.2 mM (interquartile range [IQR], 0.78-1.7) at admission to 3.8 mM (IQR, 2.1-6.6) after stabilization (P < .0001). In particular, 6 metabolites showed increases: 3-hydroxybutyric, 4-hydroxyhippuric, p-hydroxyphenylacetic, oxoglutaric, succinic, and lactic acids. Urinary creatinine was low at both time points, but levels did increase from 0.63 mM (IQR, 0.2-1.2) to 2.6 mM (IQR,1.6-4.4; P < .0001). No differences in urinary profiles were found between children who died versus those who survived, nor between children with severe wasting or edematous SAM.Conclusions: Total urinary metabolites and creatinine increase after stabilization and may reflect partial recovery of overall metabolism linked to refeeding. The use of urinary metabolites for risk assessment should be furthered explored.Trial Registration: TranSAM study (ISRCTN13916953). [ABSTRACT FROM AUTHOR]

The identification of insulin resistance and hyperinsulinemia in polycystic ovary syndrome (PCOS) is not a minor issue. The homeostasis model assessment of insulin resistance index (HOMA) is the most used index of IR (Insulin Resistance), validated in overweight and obese patients but not in normal-weight PCOS subjects, who can still present with increased insulin secretion by an oral glucose tolerance test (OGTT). The evaluation of insulin secretion and resistance represents a still unresolved problem. The aim of this study is to identify a possible yet noninvasive method to properly evaluate the insulin metabolism in young non-diabetic subjects. Girls aged 14–22 years, afferent to the center of Gynecological Diseases in Childhood and Adolescence of Cagliari (Italy), were screened for PCOS. A total of 42 subjects comprised the study group. Hormonal assays, OGTT, transabdominal (TA) or transvaginal (TV) US, and urine collection for 1H-NMR analysis were assayed in the early follicular phase. A 1H-NMR coupled multivariate statistical analysis was performed. The OPLS model indicated that the NMR profile of urine had a good fit and prediction ability for the AUC OGTT with R2 = 0.813. Metabolomics can be a promising tool to the potential identification of biomarkers of an exaggerated insulin response to OGTT and can encourage substantial progress for a more accurate and early diagnosis in PCOS.

BACKGROUND: Scraping has been extensively applied in the treatment of lumbar disc herniation, and the underlying mechanism was explored by metabolomics. OBJECTIVE: To investigate the changes of endogenous metabolites in urine of rats with lumbar disc herniation and its mechanism of action by gas chromatography-mass spectrometry metabolomics method, and to analyze the difference in efficacy of different scraping schemes, in order to standardize the scraping therapy, and provide reference and basis for clinical application. METHODS: Forty-eight male Sprague-Dawley rats were randomly divided into blank, model and scraping groups (passing the sputum, acupuncture, sputum, and acupoint groups) (n=8 per group). The rat model of lumbar disc herniation was replicated by autologous nucleus pulposus transplantation. From the 5th day of modeling, the scraping group was intervened with different scraping schemes, once every other day, totally nine times. The study was approved by the Experimental Animal Ethics Committee of Nanjing University of Traditional Chinese Medicine in January 2017. RESULTS AND CONCLUSION: (1) Compared with before modeling, the mechanical pain threshold in the scraping and the model groups after modeling was decreased (P < 0.01). (2) A total of 15 potential biomarkers and 6 metabolic pathways were obtained after screening. After scraping, the content of 3-(3-hydroxyphenyl)propionic acid, aspartic acid and glutamic acid decreased, and the content of glycine, citric acid and cyclic adenosine increased, by adjusting alanine, aspartic acid and glutamine. The acid metabolism pathway was anti-inflammatory with analgesic, glycine, serine and threonine metabolism, glyoxylic acid and dicarboxylic acid metabolism, and a tricarboxylic acid cycle. (3) To conclude, the effect of regulating metabolites in the sputum group is better than that in the other three groups, which is presumed to be the best cure plan. [ABSTRACT FROM AUTHOR]

Increasing evidence has shown that fecal microbiota transplantation (FMT) could be a promising treatment option for Crohn's disease (CD). However, the frequency of FMT for CD treatment remains unclear. This study aimed to evaluate the optimal timing for administering the second course of FMT to maintain the long-term clinical effects from the first FMT for patients with CD. Sixty-nine patients with active CD who underwent FMT twice and benefited from the first FMT were enrolled in this study. Clinical response, stool microbiota, and urine metabolome of patients were assessed during the follow-up. The median time of maintaining clinical response to the first FMT in total 69 patients was 125 days (IQR, 82.5-225.5). The time of maintaining clinical response to the second FMT in 56 of 69 patients was 176.5 days (IQR, 98.5-280). The fecal microbiota composition of each patient post the first FMT was closer to that of his/her donor. Compared to that of the baseline, patients prior to the second course of FMT showed significant differences in urinary metabolic profiles characterized by increased indoxyl sulfate, 4-hydroxyphenylacetate, creatinine, dimethylamine, glycylproline, hippurate, and trimethylamine oxide (TMAO). This study demonstrated that patients with CD could be administered the second course of FMT less than 4 months after the first FMT for maintaining the clinical benefits from the first FMT. This was supported by the host-microbial metabolism changes in patients with active CD. Trial registration: ClinicalTrials.gov, NCT01793831. Registered 18 February 2013. https://clinicaltrials.gov/ct2/show/NCT01793831?term=NCT01793831&rank=1 [ABSTRACT FROM AUTHOR]

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG “Glycine, Serine, and Threonine metabolism” in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

The attention of sports community toward probiotic supplementation as a way to promote exercise and training performance, together with good health, has increased in recent years. This has applied also to horses, with promising results. Here, for the first time, we tested a probiotic mix of several strains of live bacteria typically employed for humans to improve the training performance of Standardbred horses in athletic activity. To evaluate its effects on the horse performance, we measured lactate concentration in blood, a translational outcome largely employed for the purpose, combined with the study of hematological and biochemical parameters, together with urine from a metabolomics perspective. The results showed that the probiotic supplementation significantly reduced postexercise blood lactate concentration. The hematological and biochemical parameters, together with urine molecular profile, suggested that a likely mechanism underlying this positive effect was connected to a switch of energy source in muscle from carbohydrates to short-chain fatty acids. Three sulfur-containing molecules differently concentrated in urines in connection to probiotics administration suggested that such switch was linked to sulfur metabolism. NEW & NOTEWORTHY Probiotic supplementation could reduce postexercise blood lactate concentration in Standardbred horses in athletic activity. Blood parameters, together with urine molecular profile, suggest the mechanism underlying this positive effect is connected to a switch of energy source in muscle from carbohydrates to short-chain fatty acids. Sulfur-containing molecules found in urines in connection to probiotics administration suggested that such switch was linked to sulfur metabolism [ABSTRACT FROM AUTHOR]