Differences In Urinary Metabolites Research Articles

Urine metabolomics phenotyping and urinary biomarker exploratory in mild cognitive impairment and Alzheimer's disease.

Alzheimer'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. We 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. Fifty-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. In 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.

Effects of electroacupuncture on urinary metabolome and microbiota in presenilin1/2 conditional double knockout mice.

The treatment of Alzheimer's disease (AD) is still a worldwide problem due to the unclear pathogenesis and lack of effective therapeutic targets. In recent years, metabolomic and gut microbiome changes in patients with AD have received increasing attention, and the microbiome-gut-brain (MGB) axis has been proposed as a new hypothesis for its etiology. Considering that electroacupuncture (EA) efficiently moderates cognitive deficits in AD and its mechanisms remain poorly understood, especially regarding its effects on the gut microbiota, we performed urinary metabolomic and microbial community profiling on EA-treated AD model mice, presenilin 1/2 conditional double knockout (PS cDKO) mice, to observe the effect of EA treatment on the gut microbiota in AD and find the connection between affected gut microbiota and metabolites. After 30 days of EA treatment, the recognition memory ability of PS cDKO mice was evaluated by the Y maze and the novel object recognition task. Urinary metabolomic profiling was conducted with the untargeted GC-MS method, and 16S rRNA sequence analysis was applied to analyze the microbial community. In addition, the association between differential urinary metabolites and gut microbiota was clarified by Spearman's correlation coefficient analysis. In addition to reversed cognitive deficits, the urinary metabolome and gut microbiota of PS cDKO mice were altered as a result of EA treatment. Notably, the increased level of isovalerylglycine and the decreased levels of glycine and threonic acid in the urine of PS cDKO mice were reversed by EA treatment, which is involved in glyoxylate and dicarboxylate metabolism, as well as glycine, serine, and threonine metabolism. In addition to significantly enhancing the diversity and richness of the microbial community, EA treatment significantly increased the abundance of the genus Mucispirillum, while displaying no remarkable effect on the other major altered gut microbiota in PS cDKO mice, norank_f_Muribaculaceae, Lactobacillus, and Lachnospiraceae_NK4A136 group. There was a significant correlation between differential urinary metabolites and differential gut microbiota. Electroacupuncture alleviates cognitive deficits in AD by modulating gut microbiota and metabolites. Mucispirillum might play an important role in the underlying mechanism of EA treatment. Our study provides a reference for future treatment of AD from the MGB axis.

Urinary Metabolomics Study on the Protective Role of Cocoa in Zucker Diabetic Rats via 1H-NMR-Based Approach.

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.

Exploration of urinary metabolite dynamicity for early detection of pregnancy in water buffaloes

Early and precise pregnancy diagnosis can reduce the calving interval by minimizing postpartum period. The present study explored the differential urinary metabolites between pregnant and non-pregnant Murrah buffaloes (Bubalus bubalis) during early gestation to identify potential pregnancy detection biomarkers. Urine samples were collected on day 0, 10, 18, 35 and 42 of gestation from the pregnant (n = 6) and on day 0, 10 and 18 post-insemination from the non-pregnant (n = 6) animals. 1H-NMR-based untargeted metabolomics followed by multivariate analysis initially identified twenty-four differentially expressed metabolites, among them 3-Hydroxykynurenine, Anthranilate, Tyrosine and 5-Hydroxytryptophan depicted consistent trends and matched the selection criteria of potential biomarkers. Predictive ability of these individual biomarkers through ROC curve analyses yielded AUC values of 0.6–0.8. Subsequently, a logistic regression model was constructed using the most suitable metabolite combination to improve diagnostic accuracy. The combination of Anthranilate, 3-Hydroxykynurenine, and Tyrosine yielded the best AUC value of 0.804. Aromatic amino acid biosynthesis, Tryptophan metabolism, Phenylalanine and Tyrosine metabolism were identified as potential pathway modulations during early gestation. The identified biomarkers were either precursors or products of these metabolic pathways, thus justifying their relevance. The study facilitates precise non-invassive urinary metabolite-based pen-side early pregnancy diagnostics in buffaloes, eminently before 21 days post-insemination.

Does urinary metabolite signature act as a biomarker of post-stroke depression?

BackgroundIt is difficult to conduct the precise diagnosis of post-stroke depression (PSD) in clinical practice due to the complex psychopathology of depressive disorder. Several studies showed that gas chromatography–mass spectrometry (GC-MS)-identified urinary metabolite biomarkers could significantly discriminate PSD from stroke survivors.MethodsA systematic review was performed for the keywords of “urinary metabolite” and “PSD” using Medline, Cochrane Library, Embase, Web of Science, PsycINFO, Wanfang, CNKI, CBM, and VIP database from inception to 31 March 2022.ResultsFour related studies were included in the review. Differential urinary metabolites including lactic acid, palmitic acid, azelaic acid, and tyrosine were identified in all the included studies. As a significant deviation in the metabolite biomarker panel, glyceric acid, azelaic acid, phenylalanine, palmitic acid, pseudouridine, and tyrosine were found in at least 2 included studies, which indicated good potential for the differentiation of PSD.ConclusionThe systematic review provided evidence that differential urinary metabolites analyzed by the GC-MS-based approach might be used as a biomarker for the diagnosis and prognosis of PSD.

Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats.

In recent years, many reports focus on the hepatotoxicity of Gynura segetum root extract (GSrE), but the interaction between GSrE and the gut microbiota is still unclear. This study investigated the mechanism of GSrE-induced hepatotoxicity of different doses and exposure durations by combining metabolomics and gut microbiota analysis. SD rats were divided into 3 groups: blank, low-dose (7.5 g/kg), and high-dose (15 g/kg) groups. Urine and feces samples were collected on day 0, day 10, and day 21. Metabolomics based on gas chromatography-mass spectrometry (GC-MS) was carried out to identify metabolites and metabolic pathways. 16S rDNA gene sequencing was applied to investigate the composition of gut microbiota before and after GSrE-induced hepatotoxicity. Finally, a correlation analysis of metabolites and gut microbiota was performed. Differential metabolites in urine and feces involved amino acids, carbohydrates, lipids, organic acids, and short chain fatty acids. Among them, L-valine, L-proline, DL-arabinose, pentanoic acid, D-allose, and D-glucose in urine and D-lactic acid and glycerol in fecal metabolites depended on the exposure of time and dose. In addition, 16S rDNA sequencing analysis revealed that GSrE-induced hepatotoxicity significantly altered the composition of gut microbiota, namely, f_Muribaculaceae_Unclassified, Lactobacillus, Bacteroides, Lachnospiraceae_NK4A136_group, f_Ruminococcaceae_Unclassified, Prevotellaceae_Ga6A1_group, and Escherichia-Shigella. The correlation analysis between gut microbiota and differential metabolites showed the crosstalk between the gut microbiota and metabolism in host involving energy, lipid, and amino acid metabolisms. In summary, our findings revealed that peripheral metabolism and gut microbiota disorders were time- and dose-related and the correlation between gut microbiota and metabolites in GSrE-induced hepatotoxicity.

Personal care product use and lifestyle affect phthalate and DINCH metabolite levels in teenagers and young adults

Humans are widely exposed to phthalates and their novel substitutes, and considering the negative health effects associated with some phthalates, it is crucial to understand population levels and exposure determinants. This study is focused on 300 urine samples from teenagers (aged 12–17) and 300 from young adults (aged 18–37) living in Czechia collected in 2019 and 2020 to assess 17 plasticizer metabolites as biomarkers of exposure. We identified widespread phthalate exposure in the study population. The diethyl phthalate metabolite monoethyl phthalate (MEP) and three di (2-ethylhexyl) phthalate metabolites were detected in the urine of >99% of study participants. The highest median concentrations were found for metabolites of low-molecular-weight (LMW) phthalates: mono-n-butyl phthalate (MnBP), monoisobutyl phthalate (MiBP) and MEP (60.7; 52.6 and 17.6 μg/L in young adults). 1,2-cyclohexanedicarboxylic acid diisononyl ester (DINCH) metabolites were present in 68.2% of the samples with a median of 1.24 μg/L for both cohorts. Concentrations of MnBP and MiBP were similar to other European populations, but 5–6 times higher than in populations in North America. We also observed large variability in phthalate exposures within the study population, with 2–3 orders of magnitude differences in urinary metabolites between high and low exposed individuals. The concentrations varied with season, gender, age, and lifestyle factors. A relationship was found between high levels of MEP and high overall use of personal care products (PCPs). Cluster analysis suggested that phthalate exposures depend on season and multiple lifestyle factors, like time spent indoors and use of PCPs, which combine to lead to the observed widespread presence of phthalate metabolites in both study populations. Participants who spent more time indoors, particularly noticeably during colder months, had higher levels of high-molecular weight phthalate metabolites, whereas participants with higher PCP use, particularly women, tended to have higher concentration of LMW phthalate metabolites.

PD50-03 NO ASSOCIATION BETWEEN STATINS AND INCREASED NEPHROLITHIASIS RISK

You have accessJournal of UrologyCME1 May 2022PD50-03 NO ASSOCIATION BETWEEN STATINS AND INCREASED NEPHROLITHIASIS RISK Wilson Sui, Christina J. Peterson, Naren Nimmagadda, Nicholas L. Kavoussi, Nicole L. Miller, S. Duke Herrell, and Ryan S. Hsi Wilson SuiWilson Sui More articles by this author , Christina J. PetersonChristina J. Peterson More articles by this author , Naren NimmagaddaNaren Nimmagadda More articles by this author , Nicholas L. KavoussiNicholas L. Kavoussi More articles by this author , Nicole L. MillerNicole L. Miller More articles by this author , S. Duke HerrellS. Duke Herrell More articles by this author , and Ryan S. HsiRyan S. Hsi More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002621.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Recently studies have shown inconclusive evidence for the association of statin intake and risk of nephrolithiasis in large cohort studies, while the impact of statin use on urinary chemistry factors related to stone risk are unknown. Therefore, we sought to examine the association between statin use and incident kidney stone risk and evaluate statin use on 24-hour urine analysis. METHODS: We performed a single center, retrospective study of patients with the diagnosis of hyperlipidemia (HLD) and without a history of kidney stones across the electronic health record (EHR). Medication information on statin use was extracted and then the occurrence of an incident kidney stone diagnosis or procedure was identified. Kaplan-Meier analysis was used to estimate risk of incident kidney stone diagnoses. Then, among patients with HLD and kidney stones undergoing 24-hour urine metabolic testing, we compared 24-hour urine parameters with and without concurrent statin use. RESULTS: We identified n=109,866 patients with HLD without prior medical therapy and without kidney stone history, of which 89,599 (81.6%) were exposed to statin over a median 6.5 years of follow-up. The statin exposed were more likely to have history of stroke, coronary artery disease, gout, hypertension, and diabetes. On survival analysis, statin use was not associated with improved stone-free survival (log rank p=0.84). Among patients with 24-hour urine profiles (n=539), those with statin exposure had higher mean BMI, were more often male, and more likely to have a history of hypertension or coronary artery disease. Comparing 24-hour urine parameters, the statin-exposed had higher mean calcium (234 vs 206.1 mg, p=0.02), but there were no other differences in other analytes observed. CONCLUSIONS: Contrary to prior studies, statin use does not appear to be associated with decreased risk of kidney stones. Additionally, there are no identifiable differences in urinary metabolites on 24-hour urine analysis that would suggest a benefit in reducing stone risk. Source of Funding: The project described was supported by CTSA award No. UL1 TR002243 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e836 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Wilson Sui More articles by this author Christina J. Peterson More articles by this author Naren Nimmagadda More articles by this author Nicholas L. Kavoussi More articles by this author Nicole L. Miller More articles by this author S. Duke Herrell More articles by this author Ryan S. Hsi More articles by this author Expand All Advertisement PDF DownloadLoading ...

Urinary metabolomics reveals the biological characteristics of early pregnancy in pigs

BackgroundEmbryo implantation in sows is an important event during pregnancy. During this process, blastocysts undergo dramatic morphologic changes, and the endometrium becomes receptive. Studies have shown that developmental changes associated with the crosstalk between peri-implantation embryos and embryo-uterine are driven by various biomolecules secreted by the endometrium and embryos. In sows, changes in the uterus are also reflected in circulating body fluids and urine. Metabolomics reveals the metabolic state of cells, tissues, and organisms. In this study, we collected urine samples from large white sows during the peri-implantation period. The levels of urinary metabolites at different periods were analyzed using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC–MS/MS) analysis techniques.ResultsA total of 32 samples were collected from 8 sows during the estrus period and at each phase of early pregnancy (9, 12, and 15 days of gestation). A total of 530 metabolites were identified with high confidence in all samples. Compared with samples collected during the estrus phase, 269 differential metabolites were found in samples obtained during early pregnancy.ConclusionsThe identified metabolites included lipids and lipid-like molecules, organic acids and their derivatives, organic oxygen compounds, organoheterocyclic compounds, benzenoids, among others. Metabolites, such as choline and pregnanediol-3-glucuronide, play important roles in pregnancy in sows and other animals. These results reveal the metabolic changes in urine of sows during early pregnancy phase. The differential urinary metabolites can be used for assessing peri-implantation status in sows. Understanding these metabolic changes may promote the management of pregnant sows through various interventions such as provision of proper nutrition.

Screening and identification of differential metabolites in serum and urine of bamaxiang pigs bitten by <i>trimeresurus stejnegeri</i> based on UPLC-Q-TOF/MS metabolomics technology

Trimeresurus stejnegeri is one of the top ten venomous snakes in China, and its bite causes acute and severe diseases. Elucidating the metabolic changes of the body caused by Trimeresurus stejnegeri bite will be beneficial to the diagnosis and treatment of snakebite. Thus, an animal pig model of Trimeresurus stejnegeri bite was established, and then the metabolites of serum and urine were subsequently screened and identified in both ESI+ and ESI- modes identified by ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS) methods. There are 9 differential metabolites in serum, including Oleic acid, Lithocholic acid, Deoxycholic acid, Hypoxanthine, etc. There are 11 differential metabolites in urine, including Dopamine, Thiocysteine, Arginine, Indoleacetaldehyde, etc. Serum enrichment pathway analysis showed that 5 metabolic pathways, including Tryptophanuria, Liver disease due to cystic fibrosis, Hartnup disease, Hyperbaric oxygen exposure and Biliary cirrhosis, the core metabolites in these pathways, including deoxycholic acid, lithocholic acid, tryptophan and hypoxanthine, changed significantly. Urine enrichment pathway analysis showed that 4 metabolic pathways, including Aromatic L-Amino Acid Decarboxylase, Vitiligo, Blue Diaper Syndrome and Hyperargininemia, the core metabolites in these pathways including dopamine, 5-hydroxyindole acetic acid and arginine. Taken together, the current study has successfully established an animal model of Trimeresurus stejnegeri bite, and identified the metabolic markers and metabolic pathways of Trimeresurus stejnegeri bite. These metabolites and pathways may have potential application value and provide a therapeutic basis for the treatment of Trimeresurus stejnegeri bite.

Metabolomics analysis of Semen Cuscutae protection of kidney deficient model rats using ultra high-performance liquid chromatography-quadrupole time-of-flight Mass Spectrometry

The traditional Chinese medicine syndrome "Kidney yang deficiency" is a kind of chronic kidney disease. With the development of society, the incidence of chronic kidney disease is increasing year by year, which also brings great economic pressure to people. Semen Cuscutae is an important traditional Chinese medicine to tonify liver and kidney, mainly used to tonify deficiency of liver and kidney, spleen and kidney deficiency and diarrhea. Although there are a lot of research at the molecular and cellular level to study the Semen Cuscutae on the treatment of Kidney yang deficiency syndrome, but there's no comprehensive research complete with metabolomics method from plasma, feces and urine metabolites aspects. The purpose of this study is to find the potential differential biomarkers of the Kidney yang deficiency model and blank group rats in plasma, urine and feces, and to investigate the mechanism of Semen Cuscutae in the treatment of Kidney yang deficiency syndrome. In this study, ultra high-performance liquid chromatography-quadrupole time-of-flight Mass Spectrometry (UPLC-QTOF/MS) was used to identify potential biomarkers. Through the analysis of metabolic profiles of plasma, urine, and feces, as well as multivariate statistical analysis and pathway analysis, the therapeutic mechanism of Semen Cuscutae for Kidney yang deficiency syndrome was described. The results showed that there were 69 differential metabolites in plasma, 93 differential metabolites in feces and 62 differential metabolites in urine, and the changes of the levels of these biomarkers showed that Semen Cuscutae had a good therapeutic effect on Kidney yang deficiency syndrome. Through the analysis of the channel, the metabolite changes mainly affected the steroid hormone biosynthesis, arachidonic acid metabolism, primary bile acid biosynthesis, sheath lipid metabolism and biosynthesis of tyrosine, phenylalanine metabolism, retinol metabolism,taurine and hypotaurine metabolism, lysine degradation and vitamin B6 metabolism, tryptophan metabolism, terpenoid backbone biosynthesis and starch and sucrose metabolism. Therefore, the results suggested that Semen Cuscutae could exert a good therapeutic effect by reversing the levels of some biomarkers.

Urinary Metabolites as Predictors of Acute Mountain Sickness Severity.

Individuals sojourning at high altitude (≥2,500m) often develop acute mountain sickness (AMS). However, substantial unexplained inter-individual variability in AMS severity exists. Untargeted metabolomics assays are increasingly used to identify novel biomarkers of susceptibility to illness, and to elucidate biological pathways linking environmental exposures to health outcomes. This study used untargeted nuclear magnetic resonance (NMR)-based metabolomics to identify urine metabolites associated with AMS severity during high altitude sojourn. Following a 21-day stay at sea level (SL; 55m), 17 healthy males were transported to high altitude (HA; 4,300m) for a 22-day sojourn. AMS symptoms measured twice daily during the first 5days at HA were used to dichotomize participants according to AMS severity: moderate/severe AMS (AMS; n=11) or no/mild AMS (NoAMS; n=6). Urine samples collected on SL day 12 and HA days 1 and 18 were analyzed using proton NMR tools and the data were subjected to multivariate analyses. The SL urinary metabolite profiles were significantly different (p≤0.05) between AMS vs. NoAMS individuals prior to high altitude exposure. Differentially expressed metabolites included elevated levels of creatine and acetylcarnitine, and decreased levels of hypoxanthine and taurine in the AMS vs. NoAMS group. In addition, the levels of two amino acid derivatives (4-hydroxyphenylpyruvate and N-methylhistidine) and two unidentified metabolites (doublet peaks at 3.33ppm and a singlet at 8.20ppm) were significantly different between groups at SL. By HA day 18, the differences in urinary metabolites between AMS and NoAMS participants had largely resolved. Pathway analysis of these differentially expressed metabolites indicated that they directly or indirectly play a role in energy metabolism. These observations suggest that alterations in energy metabolism before high altitude exposure may contribute to AMS susceptibility at altitude. If validated in larger cohorts, these markers could inform development of a non-invasive assay to screen individuals for AMS susceptibility prior to high altitude sojourn.

Urinary metabolomic changes and microbiotic alterations in presenilin1/2 conditional double knockout mice

BackgroundGiven the clinical low efficient treatment based on mono-brain-target design in Alzheimer’s disease (AD) and an increasing emphasis on microbiome-gut-brain axis which was considered as a crucial pathway to affect the progress of AD along with metabolic changes, integrative metabolomic signatures and microbiotic community profilings were applied on the early age (2-month) and mature age (6-month) of presenilin1/2 conditional double knockout (PS cDKO) mice which exhibit a series of AD-like phenotypes, comparing with gender and age-matched C57BL/6 wild-type (WT) mice to clarify the relationship between microbiota and metabolomic changes during the disease progression of AD.Materials and methodsUrinary and fecal samples from PS cDKO mice and gender-matched C57BL/6 wild-type (WT) mice both at age of 2 and 6 months were collected. Urinary metabolomic signatures were measured by the gas chromatography-time-of-flight mass spectrometer, as well as 16S rRNA sequence analysis was performed to analyse the microbiota composition at both ages. Furthermore, combining microbiotic functional prediction and Spearman’s correlation coefficient analysis to explore the relationship between differential urinary metabolites and gut microbiota.ResultsIn addition to memory impairment, PS cDKO mice displayed metabolic and microbiotic changes at both of early and mature ages. By longitudinal study, xylitol and glycine were reduced at both ages. The disturbed metabolic pathways were involved in glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, starch and sucrose metabolism, and citrate cycle, which were consistent with functional metabolic pathway predicted by the gut microbiome, including energy metabolism, lipid metabolism, glycan biosynthesis and metabolism. Besides reduced richness and evenness in gut microbiome, PS cDKO mice displayed increases in Lactobacillus, while decreases in norank_f_Muribaculaceae, Lachnospiraceae_NK4A136_group, Mucispirillum, and Odoribacter. Those altered microbiota were exceedingly associated with the levels of differential metabolites.ConclusionsThe urinary metabolomics of AD may be partially mediated by the gut microbiota. The integrated analysis between gut microbes and host metabolism may provide a reference for the pathogenesis of AD.

Urine metabolic phenotyping in children with nocturnal enuresis and comorbid neurobehavioral disorders

Nocturnal enuresis (NE) is a common problem among 10% school-aged children. The etiologies underlying childhood NE is complex and not fully understood nowadays. Nevertheless, increasing evidence suggests a potential link between neurobehavioral disorders and enuresis in children. In this study, we aimed to explore novel metabolomic insights into the pathophysiology of NE and also, its association with pediatric psychiatric problems. Urine collected from 41 bedwetting children and 27 healthy control children was analyzed by using 1H-nuclear magnetic resonance spectroscopy from August 2017 to December 2018. At regular follow-up, there were 14 children with refractory NE having a diagnosis of attention deficient hyperactivity disorder (ADHD) or anxiety. Eventually, we identified eight significantly differential urinary metabolites and particularly increased urinary excretion of betaine, creatine and guanidinoacetate linked to glycine, serine and threonine metabolism were associated with a comorbidity of neurobehavioral disorders in refractory bedwetting children. Notably, based on physiological functions of betaine acting as a renal osmolyte and methyl group donor, we speculated its potential role in modulation of renal and/or central circadian clock systems, becoming a useful urinary metabolic marker in diagnosis of treatment-resistant NE in children affected by these two disorders.

Study on urine biomarkers of radiation-induced injury guided by Caenorhabditis elegans as a model organism

ObjectiveUnder the guidance of model organism Caenorhabditis elegans with fine olfactory system, small molecular metabolites sensitive to high dose radiation were screened as biomarkers of acute radiation-induced injury, and their metabolic pathways were elucidated by enrichment. MethodsRats were irradiated with 12 ​Gy γ-rays to establish an acute radiation injury model, and their urine was fingerprinted using UPLC-Q/TOF-MS. Further, under the guidance of Caenorhabditis elegans as olfactory-sensitive model organism, the key differential metabolites in urine were found as biomarkers of radiation-induced injury. ResultsAfter rats were irradiated, the radiation injury urine showed a difference from control (sham-irradiated) urine, which could be distinguished by Caenorhabditis elegans. Based on metabolomics analysis, a total of 21 key differential metabolites with P value ​< ​0.05 and fold change either >2 or <0.5 were identified, which can be used as sensitive and reliable biomarkers of radiation-induced injury. The pathways were further enriched, and it was found that disorders of five metabolic pathways, including citric acid cycle and amino acid metabolism, play an important role in radiation-induced injury. ConclusionsDue to radiation injury, the metabolites in urine will change significantly. The study on biomarkers guided by model organism Caenorhabditis elegans provides a new perspective to explain the details of metabolic disorders, and also provides experimental basis for the development of new biological dosimeters.

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression.

BackgroundPost-stroke depression (PSD) is a major complication in stroke survivors, especially in elderly stroke survivors. But there are still no objective methods to diagnose depression in elderly stroke survivors. Thus, this study was conducted to identify potential biomarkers for diagnosing elderly PSD subjects.MethodsElderly (60 years or older) stroke survivors with depression were assigned into the PSD group, and elderly stroke survivors without depression and elderly healthy controls (HCs) were assigned into the non-depressed group. Urinary metabolite signatures obtained from gas chromatography-mass spectrometry (GC-MS)-based metabolomic platform were collected. Both univariate and multivariate statistical analysis were used to find the differential urinary metabolites between the two groups.ResultsThe 78 elderly HCs, 122 elderly stroke survivors without depression and 124 elderly PSD subjects were included. A set of 13 differential urinary metabolites responsible for distinguishing PSD subjects from non-depressed subjects were found. The Phenylalanine, tyrosine and tryptophan biosynthesis, Phenylalanine metabolism and Galactose metabolism were found to be significantly changed in elderly PSD subjects. The phenylalanine was significantly negatively correlated with age and depressive symptoms. Meanwhile, a biomarker panel consisting of 3-hydroxyphenylacetic acid, tyrosine, phenylalanine, sucrose, palmitic acid, glyceric acid, azelaic acid and α-aminobutyric acid was identified.ConclusionThese results provided candidate molecules for developing objective methods to diagnose depression in elderly stroke survivors, suggested that taking supplements of phenylalanine might be an effective method to prevent depression in elderly stroke survivors, and would be helpful for future revealing the pathophysiological mechanism of PSD.

Investigation of urinary components in rat model of ketamine-induced bladder fibrosis based on metabolomics

BackgroundKetamine abuse has been linked to the system's damage, presenting with lower urinary tract symptoms (LUTS). While the pathogenesis of ketamine-induced urinary damage is not fully understood, fibrosis is believed to be a potential mechanism. A metabolomic investigation of the urinary metabolites in ketamine abuse was conducted to gain insights into its pathogenesis.MethodsA rat model of ketamine induced bladder fibrosis was established through tail vein injection of ketamine hydrochloride and control group was established through tail vein injection of the equivalent normal saline. Hematoxylin and eosin (H&E) staining and Masson trichrome staining were performed to evaluated bladder pathology. Urinary components were detected based on a metabolomic approach using ultra-high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOFMS platform). Orthogonal projections analyzed the data to latent structures discriminant analysis (OPLS-DA) and bioinformatics analysis.ResultsThe rat model of ketamine induced bladder fibrosis was confirmed through H&E and Masson trichrome staining. There were marked differences in the urinary metabolites between the experimental group and the control group. Compared to the control group, 16 kinds of differential metabolites were up-regulated and 102 differential metabolites were down-regulated in the urine samples of the ketamine group. Bioinformatics analysis revealed the related metabolic pathways.ConclusionsUsing a ketamine-induced bladder fibrosis rat model, this study identified the differential urinary metabolites expressed following ketamine treatment. These results provide vital clues for exploring the pathogenesis of ketamine-induced LUTS and may further contribute to the disease's diagnosis and treatment.

Identification of Potential Metabolite Markers for Middle-Aged Patients with Post-Stroke Depression Using Urine Metabolomics.

BackgroundPost-stroke depression (PSD) is one of the most common complications in stroke survivors. But, there are still no objective methods to diagnose PSD. This study aims to identify potential biomarkers for diagnosing PSD in middle-aged stroke survivors.MethodsMiddle-aged subjects aged 30 to 59 years (92 PSD patients and 89 stroke survivors without depression) were included in this study. Urinary metabolites were detected by gas chromatography-mass spectrometry (GC-MS). Differential urinary metabolites and potential biomarkers were screened by applying statistical analysis.ResultsThe different urinary metabolic phenotypes between PSD patients and stroke survivors without depression were identified. A total of 12 differential urinary metabolites were accurately identified by using orthogonal partial least-squares-discriminant analysis. After analyzing those 12 differential urinary metabolites by step-wise logistic regression analysis, only seven metabolites (palmitic acid, hydroxylamine, myristic acid, glyceric acid, lactic acid, tyrosine and azelaic acid) were finally selected as potential biomarkers for diagnosing PSD in middle-aged stroke survivors. A panel consisting of these potential biomarkers could effectively diagnose middle-aged PSD patients.ConclusionUrinary metabolic profiles were different between middle-aged PSD patients and stroke survivors without depression. Our results would be helpful in future for developing an objective method to diagnose PSD in middle-aged stroke survivors.

Non-targeted urinary metabolomics in pregnancy and associations with fetal growth restriction

Our objective was to identify metabolites associated with fetal growth restriction (FGR) by examining early and late pregnancy differences in non-targeted urinary metabolites among FGR cases and non-FGR controls. An exploratory case-control study within LIFECODES birth cohort was performed. FGR cases (N = 30), defined as birthweight below the 10th percentile, were matched with controls (N = 30) based on maternal age, race, pre-pregnancy body mass index, and gestational age at delivery. Gas chromatography/electron-ionization mass spectrometry was performed on urine samples collected at 10 and 26 weeks of gestation. Differences in urinary metabolite levels in cases and controls at each time point and between the two time points were calculated and then changes compared across pregnancy. 137 unique urinary metabolites were annotated, and several identified that were higher in cases compared to controls. For example, urinary concentrations of benzoic acid were higher in cases compared to controls at both study visits (3.01-fold higher in cases at visit 1, p < 0.01; 3.10-fold higher in cases at visit 3, p = 0.05). However, these findings from our exploratory analysis were not robust to false-discovery-rate adjustment. In conclusion, using a high-resolution, non-targeted approach, we found specific urinary organic acids differed over pregnancy by FGR case status.

Metabolomic signatures and microbial community profiling of depressive rat model induced by adrenocorticotrophic hormone

BackgroundAdrenocorticotrophic hormone (ACTH)-treatment rat model has been utilized as a widely accepted model of treatment-resistant depression. Metabolomic signatures represent the pathophysiological phenotype of diseases. Recent studies in gut microbiota and metabolomics analysis revealed the dramatic role of microbiome in psychoneurological system diseases, but still, the mechanisms underlying gut microbiome–host interaction remain unclear.MethodsMale Wistar rats were s.c. injection of ACTH fragment 1–24 for 14 days to induce treatment-resistant depression. Depression-related behavioral tests, analysis of serum monoamine neurotransmitters and hypothalamic–pituitary–adrenal (HPA) axis-related hormones were determined for assessment of ACTH-induced depression rat model. A gas chromatography-time-of-flight mass spectrometer based urinary metabolomic signatures integrated 16S rRNA sequence analysis based gut microbial profiling was performed, as well as Spearman’s correlation coefficient analysis was used to manifest the covariation between the differential urinary metabolites and gut microbiota of genus level.ResultsChronic injection of ACTH-induced depression-like phenotype (increased immobility time in forced swimming test and tail suspension test) was accompanied by peripheral serotonin down-regulation and HPA axis overactivation (ACTH and corticosterone up-regulation). Urinary metabolomics analysis indicated that pyruvic acid, l-threonine, mannitol, d-gluconic acid, 4-hydroxybenzoic acid, d-arabitol, myo-inositol and ascorbic acid levels were reduced in ACTH-treated rats’ urine, while hippurate level was elevated. In addition, microbial community profiling revealed bacterial enrichment (e.g. Ruminococcus, Klebsiella) and reduction (e.g. Akkermansia, Lactobacillus) in the ACTH-induced depression rat model. Correlation analysis showed that Akkermansia and Lactobacillus were closely relevant to metabolites myo-inositol and hippurate, which were included in host inositol phosphate metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis.ConclusionsDepression rat model induced by ACTH is associated with disturbance of pyruvate metabolism, ascorbate and aldarate metabolism, inositol phosphate metabolism, glycine, serine and threonine metabolism, and glycolysis or gluconeogenesis, as well as changes in microbial community structure. Gut microbiota may participate in the mediation of systemic metabolomic changes in ACTH-induced depression model. Therefore, integrated metabolomic signatures and gut microbial community profiling would provide a basis for further studies on the pathogenesis of depression.