Synergistic mechanism of stir-baked curcumae radix with vinegar in dysmenorrhea rats based on UPLC-Q-TOF/MS metabolomics

Curcumae Radix (i.e. Huangsiyujin: HSYJ), a well-known traditional Chinese medicine (TCM), has been widely used in clinical practice for many years to treat depression and primary dysmenorrhea. Modern pharmacological researches have demonstrated its anti-inflammatory, antidepressant, and dysmenorrhea relief effects. According to the processing theory of TCM, it is believed that stir-baked HSYJ with vinegar may enhance the ability to disperse stagnant hepatoqi and alleviate pain. However, whether the vinegar concoction of HSYJ can enhance the therapeutic effect on the Qi stagnation due to liver depression (LDQS) type of dysmenorrhea and what its mechanism has not been well explained. Based on the processing drugs theory of "stir-baked with vinegar into liver", a metabolomic approach was used to investigate the therapeutic effect and mechanism of stir-baked HSYJ with vinegar to enhance the treatment of dysmenorrhea in rats. By establishing a rat model of dysmenorrhea of the "LDQS" type, observation of hemorheology, uterine pathological sections, COX-2 and OTR protein expression and other indicators; analysis of urinary metabolic changes in rats by UPLC-Q-TOF-MS technique, to compare the differential biomarkers and metabolic pathways in the treatment of dysmenorrhea due to "liver stagnation and qi stagnation" before and after stir-baked HSYJ with vinegar. Stir-baked HSYJ with vinegar significantly inhibited the writhing response of rats, improved hemorheology, repaired damaged diseased uterus and inhibited high expression of COX-2 and OTR proteins in uterus; 68 differential metabolites were screened from the urine of rats, compared with the raw HSYJ, the levels of 14 metabolites were significantly changed in stir-baked HSYJ with vinegar, involving the pathways of phenylalanine, tyrosine and tryptophan metabolism, cysteine and methionine metabolism, aspartate and glutamate metabolism. The potentiating effect of stir-baked HSYJ with vinegar may be related to the regulation of multiple amino acid metabolic pathways.

Characteristics of gut microbiota and metabolic phenotype in patients with major depressive disorder based on multi-omics analysis

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.

Identification of Diagnostic Biomarkers for Compensatory Liver Cirrhosis Based on Gut Microbiota and Urine Metabolomics Analyses

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.

The effect of polyphenols on DNA methylation-assessed biological age attenuation: the DIRECT PLUS randomized controlled trial

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.

Combined systematic pharmacology and urine metabonomics to study the therapeutic mechanism of type 2 diabetic treated with the herbal pair of Salvia miltiorrhiza Bunge and Pueraria montana var. lobata (Willd.) Sanjappa & Pradeep

BACKGROUND

The herbal pair of Salvia miltiorrhiza Bunge and Pueraria montana var. lobata (Willd.) Sanjappa & Pradeep (DG) is commonly used in the treatment of type 2 diabetes (T2DM) in traditional Chinese medicine (TCM). The drug pair DG was designed by Dr. Zhu chenyu to improve the treatment of T2DM.

AIM

This study combined with systematic pharmacology and urine metabonomics to explore the mechanism of DG in the treatment of T2DM.

METHODS

The therapeutic effect of DG on T2DM was evaluated by fasting blood glucose (FBG) and biochemical indexes. Systematic pharmacology was used to screen the active components and targets that may be related to DG. Metabonomics was established to find urinary metabolites and pathways that may be induced by DG. Finally, integrate the results of these two parts for mutual verification.

RESULTS

FBG and biochemical indexes showed that DG could reduce FBG and adjust the related biochemical indexes. Metabolomics analysis indicated that 39 metabolites were related to DG for T2DM treatment. In addition, systematic pharmacology showed compounds and potential targets which were associated with DG. Finally, 12 promising targets were selected as targets for T2DM therapy by integrating the results.

CONCLUSION

The combination of metabonomics and systematic pharmacology based on LC-MS is feasible and effective, which provides strong support for exploring the effective components and pharmacological mechanism of TCM.

Development of a predictive algorithm to identify pre-school children at risk for behavior changes associated with sleep-related breathing disorders

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.

Studies on the mechanism of Panax Ginseng in the treatment of deficiency of vital energy dementia rats based on urine metabolomics

Panax Ginseng (PG) has been used to strengthen memory and physique for thousands of years, because its main components ginsenosides (GS) and ginseng polysaccharides (GP) play a major role, but its mechanism is not clear. In this study, a rat model of dementia with vital energy deficiency (DED) was established through intraperitoneal injection with D-galactose and AlCl₃ and combined with exhaustive swimming. Pharmacological studies and the urine metabolomics based on ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) were employed for evaluation the efficacy of PG and exploring this treatment mechanism. Through urine metabolic profiling, it can be seen that DED rats after PG administration are close to normal group (NG) rats, and PG can regulate the in vivo status of DED rats which tend to NG. The results of behavioral, biochemical indicators and immunohistochemistry further verified the above results, and the mechanism of action of each component is refined. Ultimately, we believe that the mechanism of PG in the treatment of DED is that ginsenosides (GS) intervenes in phenylalanine tryptophan and tyrosine metabolism, stimulates dopamine production, inhibits Aβ deposition and neuroinflammation; and that ginseng polysaccharides (GP) provides energy to strengthen the TCA cycle and improve immune capacity.

Noninvasive urine metabolomics of prostate cancer and its therapeutic approaches: a current scenario and future perspective

INTRODUCTION

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.

AREA COVERED

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.

EXPERT OPINION

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.

Urinary metabonomics study of anti-depressive mechanisms of Millettia speciosa Champ on rats with chronic unpredictable mild stress-induced depression

As a traditional Chinese medicine (TCM), Millettia speciosa Champ (MSC), exerts a wide range of pharmacological activities. Our research group previously found that MSC has antidepressant effects, but the specific antidepressant mechanisms remain unclear. Therefore, in this study, urine metabolomics based on ultra-performance liquid chromatography/quadrupole time of flight mass spectrometry (UPLC-Q-TOF/MS) combined with pharmacodynamics was used to explore the pathogenesis of depression and the antidepressant effects of MSC. The results showed that MSC treatment could significantly improve chronic unpredictable mild stress (CUMS)-induced depression. Urine metabolic showed that the profiles of the CUMS model group were significantly separated from the control group, while the drug-treated groups were closer to the control group, especially the MSC group treated with a 14 g/kg dose of MSC. Furthermore, 9 metabolites, including glutaric acid, L-isoleucine, L-Dopa, sebacic acid, 3-methylhistidine, allantoin, caprylic acid, tryptophol, and 2-phenylethanol glucuronide, were identified as potential biomarkers of depression. Metabolic pathway analysis showed that these potential biomarkers were mainly involved in valine, leucine, and isoleucine biosynthesis, aminoacyl-tRNA biosynthesis, valine, leucine and isoleucine degradation, tyrosine metabolism, histidine metabolism, fatty acid biosynthesis, and pentose and glucuronate interconversions. Through Receiver operating characteristic (ROC) analysis and Pearson correlation analysis, the combination of L-isoleucine, sebacic acid, and allantoin, were further screened out as potential pharmacodynamic biomarkers associated with the efficacy of MSC. This study suggests that the integration of metabolomics with pharmacodynamics helps to further understand the pathogenesis of depression and provides novel insight into the efficacy of TCM.

Based on urine metabolomics to study the mechanism of Qi-deficiency affecting type 2 diabetes rats using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Qi-deficiency also called energy deficiency, which approximates to the term of sub-health in contemporary medical theory. Diabetes is similar to the symptoms of "xiaoke" in traditional Chinese medicine (TCM) which is linked with Qi-deficiency. However, the mechanism of Qi-deficiency on type 2 diabetes (T2D) has not been completely elucidated. In this study, a model on Qi-deficiency T2D rat was established by using diet with high fat and high sugar and small-dose STZ induction combined with exhaustive swimming, and the model was evaluated by pathological section, hematological index and serum biochemical parameters. Applying urine metabolomics based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to explore the underlying molecular mechanism of Qi-deficiency on T2D and 32 urinary metabolites were identified as prospective biomarkers for Qi-deficiency T2D rats. Metabolic pathway analysis indicated that synthesis and degradation of ketone bodies, starch and sucrose metabolism, phenylalanine metabolism, arachidonic acid metabolism, butanoate metabolism and TCA cycle, etc., were closely related to potential mechanisms of Qi-deficiency on T2D. The metabolomics results can provide reliable data support for complex TCM syndrome diagnosis.

Impact of short-term exposure to fine particulate matter air pollution on urinary metabolome: A randomized, double-blind, crossover trial

BACKGROUND

Metabolomics is a novel tool to explore the biological mechanisms of the health effects of fine particulate matter (PM_2.5) air pollution. Very few studies have examined the urinary metabolomic changes associated with PM_2.5 exposure.

OBJECTIVE

To assess the alternation in urine metabolomics in response to short-term PM_2.5 exposure.

METHODS

We conducted a randomized, double-blind, crossover trial of 9-day real or sham indoor air purification among 45 healthy college students in Shanghai, China. Urine samples were collected immediately at the end of each intervention stage and were analyzed for metabolomics using ultrahigh performance liquid chromatography-mass spectrometry. Orthogonal partial least square-discriminant analysis and linear mixed effect models were used to examine metabolomic changes between interventional scenarios and their associations with continuous PM_2.5 exposure.

RESULTS

The time-weighted average personal PM_2.5 exposure in the real-purified scenario was 50% lower than in the sham-purified air scenario (28.3 μg/m³ VS 56.9 μg/m³). A total of 40 differentiated urinary metabolites at a false discovery rate <0.05 were identified for the effects of both intervention and continuous PM_2.5 exposure, including 16 lipids, 5 purine metabolites, 2 neurotransmitters, and 3 coenzymes.

CONCLUSIONS

This real-world randomized crossover trial demonstrated that short-term PM_2.5 exposure could result in significant changes in urinary metabolomic profile, which may further lead to perturbation in energy metabolism, oxidative stress and inflammation.

Timing for the second fecal microbiota transplantation to maintain the long-term benefit from the first treatment for Crohn's disease. Appl Microbiol Biotechnol. 2019;103:349-360. [PMID: 30357440 PMCID: PMC6311185 DOI: 10.1007/s00253-018-9447-x]

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.

Using urine metabolomics to understand the pathogenesis of infant respiratory syncytial virus (RSV) infection and its role in childhood wheezing

BACKGROUND

Respiratory syncytial virus (RSV) infection in infants causes significant morbidity and is the strongest risk factor associated with asthma. Metabolites, which reflect the interactions between host cell and virus, provide an opportunity to identify the pathways that underlie severe infections and asthma development.

OBJECTIVE

To study metabolic profile differences between infants with RSV infection, and human rhinovirus (HRV) infection, and healthy infants. To compare infant metabolic differences between children who do and do not wheeze.

METHODS

In a term birth cohort, urine was collected while healthy and during acute viral respiratory infection with RSV and HRV. We used ¹H-NMR to identify urinary metabolites. Multivariate and univariate statistics were used to discriminate metabolic profiles of infants with either RSV ARI, or HRV ARI, and healthy infants. Multivariable logistic regression was used to assess the association of urine metabolites with 1st-, 2nd-, and 3rd-year recurrent wheezing.

RESULTS

Several metabolites in nicotinate and nicotinamide metabolism pathways were down-regulated in infants with RSV infection compared to healthy controls. There were no significant differences in metabolite profiles between infants with RSV infection and infants with HRV Infection. Alanine was strongly associated with reduced risk of 1st-year wheezing (OR 0.18[0.0, 0.46]) and 2nd-year wheezing (OR 0.31[0.13, 0.73]), while 2-hydroxyisobutyric acid was associated with increased 3rd-year wheezing (OR 5.02[1.49, 16.93]) only among the RSV infected subset.

CONCLUSION

The metabolites associated with infant RSV infection and recurrent-wheezing are indicative of viral takeover of the cellular machinery and resources to enhance virulence, replication, and subversion of the host immune-response, highlighting metabolic pathways important in the pathogenesis of RSV infection and wheeze development.

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

BACKGROUND

Previous studies have examined and documented fluctuations in urine metabolites in response to disease processes and drug toxicity affecting glomerular filtration, tubule cell metabolism, reabsorption, oxidative stress, purine degradation, active secretion and kidney amino acylase activity representative of diminished renal function. However, a high-throughput assay that incorporates metabolites that are surrogate markers for such changes into a kidney dysfunction panel has yet to be described.

METHODS

A high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) assay for the quantification of ten metabolites associated with the Krebs cycle, purine degradation, and oxidative stress in human urine was developed and validated. Normal values were assessed in healthy adult (n=120) and pediatric (n=36) individuals. In addition, 9 pediatric renal transplant recipients patients were evaluated before and after initial dosing of the immunosuppressant tacrolimus in a proof-of-concept study.

RESULTS

The assay met all predefined acceptance criteria. The lower limit of quantification ranged from 0.1 to 1000 μmol/l. Inter-day trueness and imprecisions ranged from 91.4-112.9% and 1.5-12.4%, respectively. The total assay run time was 5.5 minutes. Concentrations of glucose, sorbitol, and trimethylamine oxide (TMAO) were elevated in pediatric renal transplant patients (n=9) prior to transplantation as well as before and immediately after initial dosing of tacrolimus. One month post-transplant urine metabolite patterns matched those of healthy children (n=36).

CONCLUSIONS

The LC-MS/MS assay will provide the basis for further large-scale clinical studies to explore these analytes as molecular markers for the patients with renal insufficiency.

CE-MS based on moving reaction boundary method for urinary metabolomic analysis of gastric cancer patients

There is still a lack of satisfactory tumor markers for gastric cancer (GasC). This study is aimed at optimizing parameters in CE-MS based on moving reaction boundary (MRB) so as to improve its sensitivity and stability, and at searching for potential tumor markers of GasC in patients' urine samples via MRB-CE-MS. In this study, several parameters of MRB-CE-MS were investigated and optimized in order to gain optimal stability, sensitivity, and specificity, and was afterwards evaluated as valid. Subsequently, urine samples from GasC patients and control subjects were subjected to MRB-CE-MS analysis under optimized conditions, which successfully distinguished GasC patients from controls, as well as early-stage patients from advanced stage patients. Differentiation performance was evaluated by area under the curve, which showed fine differential value between GasC patients and controls, as well as between early and advanced stage patients (area under the curve value 1.0 and 0.847, respectively). In conclusion, this study established a set of feasible and useful methodology in searching potential tumor markers in urine samples from GasC patients. Moreover, several amino acids have been recognized as potential tumor markers that deserve further investigation.