Methodological aspects for metabolome visualization and characterization

Grape Seed Proanthocyanidin Extract Attenuates Cafeteria-Diet-Induced Liver Metabolic Disturbances in Rats: Influence of Photoperiod

This study investigated the influence of photoperiod (day length) on the efficacy of grape seed proanthocyanidin extract (GSPE) in mitigating metabolic disorders in obese rats fed a cafeteria diet. Rats were exposed to standard (L12), long (L18), or short (L6) photoperiods and treated with GSPE or vehicle. In the standard photoperiod, GSPE reduced body weight gain (50.5%), total cholesterol (37%), and triglycerides (34.8%), while increasing the expression of hepatic metabolic genes. In the long photoperiod, GSPE tended to decrease body weight gain, increased testosterone levels (68.3%), decreased liver weight (12.4%), and decreased reverse serum amino acids. In the short photoperiod, GSPE reduced glycemia (~10%) and lowered triglyceride levels (38.5%), with effects modified by diet. The standard photoperiod showed the greatest efficacy against metabolic syndrome-associated diseases. The study showed how day length affects GSPE's benefits and underscores considering biological rhythms in metabolic disease therapies.

Exploring Metabolic and Gut Microbiome Responses to Paraquat Administration in Male Wistar Rats: Implications for Oxidative Stress

In this study, we examined the metabolic and gut microbiome responses to paraquat (PQ) in male Wistar rats, focusing on oxidative stress effects. Rats received a single intraperitoneal injection of PQ at 15 and 30 mg/kg, and various oxidative stress parameters (i.e., MDA, SOD, ROS, 8-isoprostanes) were assessed after three days. To explore the omic profile, GC-qTOF and UHPLC-qTOF were performed to assess the plasma metabolome; 1H-NMR was used to assess the urine metabolome; and shotgun metagenomics sequencing was performed to study the gut microbiome. Our results revealed reductions in body weight and tissue changes, particularly in the liver, were observed, suggesting a systemic effect of PQ. Elevated lipid peroxidation and reactive oxygen species levels in the liver and plasma indicated the induction of oxidative stress. Metabolic profiling revealed changes in the tricarboxylic acid cycle, accumulation of ketone body, and altered levels of key metabolites, such as 3-hydroxybutyric acid and serine, suggesting intricate links between energy metabolism and redox reactions. Plasma metabolomic analysis revealed alterations in mitochondrial metabolism, nicotinamide metabolism, and tryptophan degradation. The gut microbiome showed shifts, with higher PQ doses influencing microbial populations (e.g., Escherichia coli and Akkermansia muciniphila) and metagenomic functions (pyruvate metabolism, fermentation, nucleotide and amino acid biosynthesis). Overall, this study provides comprehensive insights into the complex interplay between PQ exposure, metabolic responses, and gut microbiome dynamics. These findings enhance our understanding of the mechanisms behind oxidative stress-induced metabolic alterations and underscore the connections between xenobiotic exposure, gut microbiota, and host metabolism.

Developing a model to predict the early risk of hypertriglyceridemia based on inhibiting lipoprotein lipase (LPL): a translational study

Hypertriglyceridemia (HTG) is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). One of the multiple origins of HTG alteration is impaired lipoprotein lipase (LPL) activity, which is an emerging target for HTG treatment. We hypothesised that early, even mild, alterations in LPL activity might result in an identifiable metabolomic signature. The aim of the present study was to assess whether a metabolic signature of altered LPL activity in a preclinical model can be identified in humans. A preclinical LPL-dependent model of HTG was developed using a single intraperitoneal injection of poloxamer 407 (P407) in male Wistar rats. A rat metabolomics signature was identified, which led to a predictive model developed using machine learning techniques. The predictive model was applied to 140 humans classified according to clinical guidelines as (1) normal, less than 1.7 mmol/L; (2) risk of HTG, above 1.7 mmol/L. Injection of P407 in rats induced HTG by effectively inhibiting plasma LPL activity. Significantly responsive metabolites (i.e. specific triacylglycerols, diacylglycerols, phosphatidylcholines, cholesterol esters and lysophospholipids) were used to generate a predictive model. Healthy human volunteers with the impaired predictive LPL signature had statistically higher levels of TG, TC, LDL and APOB than those without the impaired LPL signature. The application of predictive metabolomic models based on mechanistic preclinical research may be considered as a strategy to stratify subjects with HTG of different origins. This approach may be of interest for precision medicine and nutritional approaches.

Imbalances in TCA, Short Fatty Acids and One-Carbon Metabolisms as Important Features of Homeostatic Disruption Evidenced by a Multi-Omics Integrative Approach of LPS-Induced Chronic Inflammation in Male Wistar Rats

Chronic inflammation is an important risk factor in a broad variety of physical and mental disorders leading to highly prevalent non-communicable diseases (NCDs). However, there is a need for a deeper understanding of this condition and its progression to the disease state. For this reason, it is important to define metabolic pathways and complementary biomarkers associated with homeostatic disruption in chronic inflammation. To achieve that, male Wistar rats were subjected to intraperitoneal and intermittent injections with saline solution or increasing lipopolysaccharide (LPS) concentrations (0.5, 5 and 7.5 mg/kg) thrice a week for 31 days. Biochemical and inflammatory parameters were measured at the end of the study. To assess the omics profile, GC-qTOF and UHPLC-qTOF were performed to evaluate plasma metabolome; 1H-NMR was used to evaluate urine metabolome; additionally, shotgun metagenomics sequencing was carried out to characterize the cecum microbiome. The chronicity of inflammation in the study was evaluated by the monitoring of monocyte chemoattractant protein-1 (MCP-1) during the different weeks of the experimental process. At the end of the study, together with the increased levels of MCP-1, levels of interleukin-6 (IL-6), tumour necrosis factor alpha (TNF-α) and prostaglandin E2 (PGE2) along with 8-isoprostanes (an indicative of oxidative stress) were significantly increased (p-value < 0.05). The leading features implicated in the current model were tricarboxylic acid (TCA) cycle intermediates (i.e., alpha-ketoglutarate, aconitic acid, malic acid, fumaric acid and succinic acid); lipids such as specific cholesterol esters (ChoEs), lysophospholipids (LPCs) and phosphatidylcholines (PCs); and glycine, as well as N, N-dimethylglycine, which are related to one-carbon (1C) metabolism. These metabolites point towards mitochondrial metabolism through TCA cycle, β-oxidation of fatty acids and 1C metabolism as interconnected pathways that could reveal the metabolic effects of chronic inflammation induced by LPS administration. These results provide deeper knowledge concerning the impact of chronic inflammation on the disruption of metabolic homeostasis.

Alterations in Metabolome and Microbiome Associated with an Early Stress Stage in Male Wistar Rats: A Multi-Omics Approach

Stress disorders have dramatically increased in recent decades becoming the most prevalent psychiatric disorder in the United States and Europe. However, the diagnosis of stress disorders is currently based on symptom checklist and psychological questionnaires, thus making the identification of candidate biomarkers necessary to gain better insights into this pathology and its related metabolic alterations. Regarding the identification of potential biomarkers, omic profiling and metabolic footprint arise as promising approaches to recognize early biochemical changes in such disease and provide opportunities for the development of integrative candidate biomarkers. Here, we studied plasma and urine metabolites together with metagenomics in a 3 days Chronic Unpredictable Mild Stress (3d CUMS) animal approach that aims to focus on the early stress period of a well-established depression model. The multi-omics integration showed a profile composed by a signature of eight plasma metabolites, six urine metabolites and five microbes. Specifically, threonic acid, malic acid, alpha-ketoglutarate, succinic acid and cholesterol were proposed as key metabolites that could serve as key potential biomarkers in plasma metabolome of early stages of stress. Such findings targeted the threonic acid metabolism and the tricarboxylic acid (TCA) cycle as important pathways in early stress. Additionally, an increase in opportunistic microbes as virus of the Herpesvirales was observed in the microbiota as an effect of the primary stress stages. Our results provide an experimental biochemical characterization of the early stage of CUMS accompanied by a subsequent omic profiling and a metabolic footprinting that provide potential candidate biomarkers.

Urinary biomarkers of dietary intake: a review

Dietary intakes are commonly assessed by established methods including food frequency questionnaires, food records, or recalls. These self-report methods have limitations impacting validity and reliability. Dietary biomarkers provide objective verification of self-reported food intakes, and represent a rapidly evolving area. This review aims to summarize the urinary biomarkers of individual foods, food groups, dietary patterns, or nutritional supplements that have been evaluated to date. Six electronic databases were searched. Included studies involved healthy populations, were published from 2000, and compared measured dietary intake with urinary markers. The initial search identified 9985 studies; of these, 616 full texts were retrieved and 109 full texts were included. Of the included studies, 67 foods and food components were studied, and 347 unique urinary biomarkers were identified. The most reliable biomarkers identified were whole grains (alkylresorcinols), soy (isoflavones), and sugar (sucrose and fructose). While numerous novel urinary biomarkers have been identified, further validation studies are warranted to verify the accuracy of self-reported intakes and utility within practice.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved the treatment of RA, patients often inquire about dietary interventions to improve RA symptoms, as they perceive pain and/or swelling after the consumption or avoidance of certain foods. There is evidence that some foods have pro- or anti-inflammatory effects mediated by diet-related metabolites. In addition, recent literature has shown a link between diet-related metabolites and microbiome changes, since the gut microbiome is involved in the metabolism of some dietary ingredients. But diet and the gut microbiome are not the only factors linked to circulating pro- and anti-inflammatory metabolites. Other factors including smoking, associated comorbidities, and therapeutic drugs might also modify the circulating metabolomic profile and play a role in RA pathogenesis. This article summarizes what is known about circulating pro- and anti-inflammatory metabolites in RA. It also emphasizes factors that might be involved in their circulating concentrations and diet-related metabolites with a beneficial effect in RA.

Habitual Nut Exposure, Assessed by Dietary and Multiple Urinary Metabolomic Markers, and Cognitive Decline in Older Adults: The InCHIANTI Study

SCOPE

The association between self-reported dietary intake and urinary metabolomic markers of habitual nut exposure with cognitive decline over a 3-year follow-up in an older Italian population is prospectively evaluated.

METHODS AND RESULTS

A total of 119 older participants are selected, based on self-referred nut intake: the non-nut consumer (n = 72) and the regular consumer (≥2.9 g d^-1 , n = 47). Nut exposure is measured at baseline either with the use of a validated food frequency questionnaire or with an HPLC-Q-ToF-MS metabolomic approach. Three years after, 28 from the nonconsumers and 10 from the consumers experienced cognitive decline. Dietary nut exposure is characterized by urinary metabolites of polyphenols and fatty acids pathways. Nut consumption estimated either by the dietary marker or by the urinary marker model is in both cases associated with less cognitive decline (OR: 0.78, 95% CI: 0.61,0.99; p = 0.043 and OR: 0.995, 95% CI: 0.991,0.999; p = 0.016, respectively) with AUCs 73.2 (95% CI: 62.9, 83.6) and 73.1 (62.5, 83.7), respectively.

CONCLUSIONS

A high intake of nuts may protect older adults from cognitive decline. Metabolomics provides accurate and complementary information of the nut exposure and reinforces the results obtained using dietary information.

Metabolite variation in three edible Italian Allium cepa L. by NMR-based metabolomics: a comparative study in fresh and stored bulbs

INTRODUCTION

In fruits and vegetables, comparative analysis of metabolic plant profiles has a high potential for quality control of active components. Onion (Allium cepa L.) is used fresh or stored as food, spice, and in traditional medicine. Its metabolic content, often with nutraceutical value, makes its level an important factor in agronomic production.

OBJECTIVE

To describe for the first time the metabolome of "San Pietro" white onion (WP), and compare its chemical profile with the red onion var. Tropea (RT) and the yellow onion var. Montoro (CM). Furthermore, we also aim to obtain a multivariate model based on NMR fingerprints to discriminate the three Italian A. cepa L. cultivars.

METHODS

For the chemical fingerprinting we used NMR-based metabolomics. We investigated the aqueous and chloroform extracts of fresh onion at harvesting time, and after 9-month storage. Principal component analysis (PCA), Partial least squares discriminant analysis (PLS-DA) and Orthogonal partial least squares (OPLS-DA) were used to build reliable models.

RESULTS

We obtained a clear discrimination of A. cepa L. varieties for the fresh and stored batches. The statistical model highlighted higher levels of fructo-oligosaccharides (FOS) in the fresh WP; RT showed a high content of glucose, citrate and amino acids, while CM had many sulfur components. In the stored samples (CMS, RTS), carbohydrates and sulfur components decreased, while in WPS the free monosaccharides concentration increased. Linoleic acid was overexpressed in the apolar extracts of CMF and WPF cultivars.

CONCLUSION

Metabolomics allows a reliable differentiation among onion varieties, and highlights the potential of fingerprinting for food authentication purposes.

Flavanol Bioavailability in Two Cocoa Products with Different Phenolic Content. A Comparative Study in Humans

Cocoa has beneficial health effects partly due to its high flavanol content. This study was aimed at assessing the absorption and metabolism of polyphenols in two soluble cocoa products: a conventional (CC) and a flavanol-rich product (CC-PP). A crossover, randomized, blind study was performed in 13 healthy men and women. On two different days, after an overnight fast, volunteers consumed one serving of CC (15 g) or CC-PP (25 g) in 200 mL of semi-skimmed milk containing 19.80 mg and 68.25 mg of flavanols, respectively. Blood and urine samples were taken, before and after CC and CC-PP consumption, and analyzed by high-performance liquid chromatography coupled to electrospray ionisation and quadrupole time-of-flight mass spectrometry (HPLC-ESI-QToF-MS). Up to 10 and 30 metabolites were identified in plasma and urine, respectively. Phase II derivatives of epicatechin were identified with kinetics compatible with small intestine absorption, although the most abundant groups of metabolites were phase II derivatives of phenyl-γ-valerolactone and phenylvaleric acid, formed at colonic level. 5-(4′-Hydroxyphenyl)-γ-valerolactone-sulfate could be a sensitive biomarker of cocoa flavanol intake. CC and CC-PP flavanols showed a dose-dependent absorption with a recovery of 35%. In conclusion, cocoa flavanols are moderately bioavailable and extensively metabolized, mainly by the colonic microbiota.

Impact of Cocoa Products Intake on Plasma and Urine Metabolites: A Review of Targeted and Non-Targeted Studies in Humans

Cocoa is continuously drawing attention due to growing scientific evidence suggesting its effects on health. Flavanols and methylxanthines are some of the most important bioactive compounds present in cocoa. Other important bioactives, such as phenolic acids and lactones, are derived from microbial metabolism. The identification of the metabolites produced after cocoa intake is a first step to understand the overall effect on human health. In general, after cocoa intake, methylxanthines show high absorption and elimination efficiencies. Catechins are transformed mainly into sulfate and glucuronide conjugates. Metabolism of procyanidins is highly influenced by the polymerization degree, which hinders their absorption. The polymerization degree over three units leads to biotransformation by the colonic microbiota, resulting in valerolactones and phenolic acids, with higher excretion times. Long term intervention studies, as well as untargeted metabolomic approaches, are scarce. Contradictory results have been reported concerning matrix effects and health impact, and there are still scientific gaps that have to be addresed to understand the influence of cocoa intake on health. This review addresses different cocoa clinical studies, summarizes the different methodologies employed as well as the metabolites that have been identified in plasma and urine after cocoa intake.

Bioavailability and metabolism of selected cocoa bioactive compounds: A comprehensive review

Cocoa beans and their co-products are a rich source of beneficial compounds for health promotion, including polyphenols and methylxanthines. Knowledge of bioavailability and in vivo bioactivity of these phytochemicals is crucial to understand their role and function in human health. Therefore, many studies concerning bioavailability and bioactivity of cocoa bioactive compound have been done in both in vivo animal models and in humans. This critical review comprehensively summarizes the existing knowledge about the bioavailability and the major metabolic pathways of selected cocoa bioactive compounds (i.e. monomeric flavan-3-ols, procyanidins, anthocyanins, flavonols, phenolic acids, N-phenylpropenoyl-L-amino acids, stilbenes, and methylxanthines). The compiled results indicated that many of these compounds undergo extensive metabolism prior to absorption. Different factors have been suggested to influence the bioavailability of polyphenols and methylxanthines among them the role of gut microbiota, structure of these compounds, food matrix and occurrence of other substances were the most often considered. Aforementioned factors decided about the site where these bioactive compounds are digested and absorbed from the alimentary tract, as well as the pathway by which they are metabolized. These factors also determine of the type of transport through the intestine barrier (passive, involving specific enzymes or mediated by specific transporters) and their metabolic path and profile.

Recent Advances in the Application of Metabolomics for Nutrition and Health

Metabolomics is the study of small molecules called metabolites in biological samples. Application of metabolomics to nutrition research has expanded in recent years, with emerging literature supporting multiple applications. Key examples include applications of metabolomics in the identification and development of objective biomarkers of dietary intake, in developing personalized nutrition strategies, and in large-scale epidemiology studies to understand the link between diet and health. In this review, we provide an overview of the current applications and identify key challenges that need to be addressed for the further development of the field. Successful development of metabolomics for nutrition research has the potential to improve dietary assessment, help deliver personalized nutrition, and enhance our understanding of the link between diet and health.

High copper levels in follicular fluid affect follicle development in polycystic ovary syndrome patients: Population-based and in vitro studies

Although the adverse effects of copper overexposure on the liver, kidney, spleen and intestinal organs are well known, information about the impact of copper toxicity on human reproduction is limited. A total of 348 infertile patients were enrolled in our present study, including 89 with polycystic ovary syndrome (PCOS), 145 with fallopian tube obstruction and 114 controls. The follicular fluid concentrations of 22 trace elements were measured by inductively coupled plasma mass spectrometry (ICP-MS). Principal component analysis was used to identify trace element profile alterations in different groups. The mRNA levels of steroidogenesis-related genes were measured by real-time PCR. Our results showed that the trace element profile in follicular fluid was obviously altered in PCOS patients. Copper concentrations were significantly (p < .05) higher in the PCOS group than in the other two groups. Increased copper levels in follicular fluid were associated with a higher number of retrievable oocytes in the PCOS group (B = 1.785, p = .001) but a lower rate of high-quality embryos (B = -6.360, p = .050). Moreover, follicular fluid copper levels were positively correlated with follicular fluid progesterone levels (r = 0.275, p = .010) and testosterone levels (r = 0.250, p = .022). Cultured human granulosa cells overexposed to copper showed significantly (p < .05) increased estradiol secretion and decreased testosterone levels. Real-time quantitative PCR revealed a significant (p < .05) increase in CYP19A1 and HSD3b mRNA expression. Our results indicate that increased copper levels in follicular fluid could affect follicle development in PCOS patients, and the mechanism may be related to copper-induced abnormalities in steroidogenesis.

Pharmacokinetic profile and metabolite identification of bornyl caffeate and caffeic acid in rats by high performance liquid chromatography coupled with mass spectrometry

Bornyl caffeate was initially discovered as a bioactive compound in medicinal plants. Despite the promising pharmacological activities including anti-tumor and antibacterial activities, the pharmacokinetics of the compound remain open. This work developed a high performance liquid chromatography-tandem mass spectrometric method for the determination of bornyl caffeate and caffeic acid (major metabolite and a main unit of bornyl caffeate) in vivo. Successful application of the method included identification of its metabolites and investigation on the drug pharmacokinetics. A total of 30 compounds were identified as the metabolites of bornyl caffeate in rats. We attributed these metabolites to phase I metabolic routes of reduction, oxidation, hydrolysis and phase II metabolic reactions of glucuronidation, sulfation, O-methylation and glycine. Glucuronidation, sulfation, O-methylation and reduction were the main metabolic pathways of bornyl caffeate. The method presented a linear range of 1–4000 ng mL⁻¹. The pharmacokinetic profile of bornyl caffeate was found to be a three compartment open model, while caffeic acid fitted to a two compartment open model when it was administered alone or served as the main metabolite of bornyl caffeate. The time to peak concentration (T_max) and the maximum plasma concentration (C_max) of bornyl caffeate were 0.53 h and 409.33 ng mL⁻¹. Compared with original caffeic acid, the compound displayed an increased half-life of elimination (T_1/2β), area under the concentration time curve from 0 to t (AUC_0–t) and area under the concentration time curve from 0 to ∞ (AUC_0–∞), a decreased half-life of absorption (T_1/2α) and an identical C_max. Taking together, we concluded that bornyl caffeate is able to rapidly initiate therapeutic effect and last for a relatively long time in rats; metabolic pathways of O-methylation and reduction is key to interpret the mechanism and toxicity of bornyl caffeate.

We revealed the metabolic profile of bornyl caffeate by HPLC-Q-TOF/MS, and then simultaneously examined the pharmacokinetics of bornyl caffeate and CA after administration of a single dose of bornyl caffeate by HPLC ion trap MS.

Biomarker of food intake for assessing the consumption of dairy and egg products

Dairy and egg products constitute an important part of Western diets as they represent an excellent source of high-quality proteins, vitamins, minerals and fats. Dairy and egg products are highly diverse and their associations with a range of nutritional and health outcomes are therefore heterogeneous. Such associations are also often weak or debated due to the difficulty in establishing correct assessments of dietary intake. Therefore, in order to better characterize associations between the consumption of these foods and health outcomes, it is important to identify reliable biomarkers of their intake. Biomarkers of food intake (BFIs) provide an accurate measure of intake, which is independent of the memory and sincerity of the subjects as well as of their knowledge about the consumed foods. We have, therefore, conducted a systematic search of the scientific literature to evaluate the current status of potential BFIs for dairy products and BFIs for egg products commonly consumed in Europe. Strikingly, only a limited number of compounds have been reported as markers for the intake of these products and none of them have been sufficiently validated. A series of challenges hinders the identification and validation of BFI for dairy and egg products, in particular, the heterogeneous composition of these foods and the lack of specificity of the markers identified so far. Further studies are, therefore, necessary to validate these compounds and to discover new candidate BFIs. Untargeted metabolomic strategies may allow the identification of novel biomarkers, which, when taken separately or in combination, could be used to assess the intake of dairy and egg products.

Biomarkers of food intake for cocoa and liquorice (products): a systematic review

Background

To unravel true links between diet and health, it is important that dietary exposure is accurately measured. Currently, mainly self-reporting methods (e.g. food frequency questionnaires and 24-h recalls) are used to assess food intake in epidemiological studies. However, these traditional instruments are subjective measures and contain well-known biases. Especially, estimating the intake of the group of confectionary products, such as products containing cocoa and liquorice, remains a challenge. The use biomarkers of food intake (BFIs) may provide a more objective measurement. However, an overview of current candidate biomarkers and their validity is missing for both cocoa- and liquorice-containing foods.

Objective

The purpose of the current study was to (1) identify currently described candidate BFIs for cocoa (products) and liquorice, (2) to evaluate the validity of these identified candidate BFIs and (3) to address further validation and/or identification work to be done.

Methods

This systematic review was based on a comprehensive literature search of three databases (PubMed, Scopus and ISI web of Science), to identify candidate BFIs. Via a second search step in the Human Metabolome Database (HMDB), the Food Database (FooDB) and Phenol-Explorer, the specificity of the candidate BFIs was evaluated, followed by an evaluation of the validity of the specific candidate BFIs, via pre-defined criteria.

Results

In total, 37 papers were included for cocoa and 8 papers for liquorice. For cocoa, 164 unique candidate BFIs were obtained, and for liquorice, four were identified in total. Despite the high number of identified BFIs for cocoa, none of the metabolites was specific. Therefore, the validity of these compounds was not further examined. For liquorice intake, 18-glycyrrhetinic acid (18-GA) was found to have the highest assumed validity.

Conclusions

For cocoa, specific BFIs were missing, mainly because the individual BFIs were also found in foods having a similar composition, such as tea (polyphenols) or coffee (caffeine). However, a combination of individual BFIs might lead to discriminating profiles between cocoa (products) and foods with a similar composition. Therefore, studies directly comparing the consumption of cocoa to these similar products are needed, enabling efforts to find a unique profile per product. For liquorice, we identified 18-GA as a promising BFI; however, important information on its validity is missing; thus, more research is necessary. Our findings indicate a need for more studies to determine acceptable BFIs for both cocoa and liquorice.

Novel chinmedomics strategy for discovering effective constituents from ShenQiWan acting on ShenYangXu syndrome

Elucidation of the efficacy of traditional Chinese medicine (TCM) is of importance for scientists of modern medicine to understand the value of TCM clinical experience, and it is necessary to have a biological language to scientifically describe the efficacy of TCM. With this background?Chinmedomics has been proposed by our team, which includes integrating serum pharmacochemistry and metabolomics technology, defining theory and research methods for expressing the efficacy of TCMs based on the biomarkers discovery of TCM syndrome and elucidating the efficacy of TCM formulae, discovering effective constituents, and finally elucidating the scientific value of TCM. In the present study, the innovative chinmedomics strategy was conducted to evaluate the therapeutic effects of ShenQiWan (SQW) acting on ShenYangXu (kidney-yang deficiency syndrome, KYDS). We analyzed the urine metabolic trajectory between the model and control groups, and identified the biomarkers by the multivariate analysis. We found that SQW caused significant restoration of abnormal metabolism of KYDs. Using the method of metabolomics, 17 potential urine biomarkers were analyzed through 4 repeated tests in our serial studies on SQW and KYDS. Under the premise of therapeutic efficacy, a total of 56 peaks were tentatively characterized in vivo by the use of serum pharmacochemistry. Correlation analysis between marker metabolites and in vivo constituents of SQW showed that 28 compositions had a close relationship with urine biomarkers of therapeutic effects, whichmight play a key role in the therapeutic effect of SQW. These compounds were imported into an online database to predict their targets. Twenty-three important potential targets were identified, which were related to the metabolism of steroid hormone, tryptophan utilization, and thyroid hormone. In conclusion, chinmedomics is a useful strategy for discovery of potentially effective constituents from complex TCM formulae.

Metabolic fingerprint after acute and under sustained consumption of a functional beverage based on grape skin extract in healthy human subjects

Grape-derived polyphenols are considered to be one of the most promising ingredients for functional foods due to their health-promoting activities. We applied a HPLC-MS-based untargeted metabolomic approach in order to evaluate the impact of a functional food based on grape skin polyphenols on the urinary metabolome of healthy subjects. Thirty-one volunteers participated in two dietary crossover randomized intervention studies: with a single-dose intake (187 mL) and with a 15-day sustained consumption (twice per day, 187 mL per day in total) of a functional beverage (FB). Postprandial (4-hour) and 24-hour urine samples collected after acute consumption and on the last day of sustained FB consumption, respectively, were analysed using an untargeted HPLC-qTOF-MS approach. Multivariate modelling with subsequent application of an S-plot revealed differential mass features related to acute and prolonged consumption of FB. More than half of the mass features were shared between the two types of samples, among which several phase II metabolites of grape-derived polyphenols were identified at confidence level II. Prolonged consumption of FB was specifically reflected in urine metabolome by the presence of first-stage microbial metabolites of flavanols: hydroxyvaleric acid and hydroxyvalerolactone derivatives. Overall, several epicatechin and phenolic acid metabolites both of tissular and microbiota origin were the most representative markers of FB consumption. To our knowledge, this is one of the first studies where an untargeted LC-MS metabolomic approach has been applied in nutrition research on a grape-derived FB.

A matrix-induced ion suppression method to normalize concentration in urinary metabolomics studies using flow injection analysis electrospray ionization mass spectrometry

Normalizing the total urine concentration is important for minimizing bias in urinary metabolomics analysis comparisons. In this study, we report a matrix-induced ion suppression (MIIS)-based method to normalize concentration using flow injection analysis coupled with electrospray ionization mass spectrometry (FIA-ESI-MS). An ion suppression indicator (ISI) was spiked into urine samples, and the intensity of the extracted ion chromatogram (EIC) for ISI in a urine matrix was subtracted by the EIC for a blank solution and used to calculate the extent to which the signal was reduced by the urine matrix. A series dilution of pooled urine samples was used to correlate the urine concentration and level of ion suppression for ISI. A regression equation was used to estimate the relative concentration of unknown urine samples. The MIIS method was validated for linearity, precision and accuracy. We obtained a good correlation using a quadratic regression model for 1- to 32-fold urine dilutions (R(2)=0.998). The reproducibility (n=4) and intermediate precision (n=3) were below 5% RSD, and the accuracy ranged from 97.15% to 102.10%. The established method was used to estimate the relative concentrations of 16 urine samples, and the results were compared with commonly used normalization methods. Pearson's correlation test was used to demonstrate that the MIIS method correlated highly with the creatinine and osmolarity methods; the correlation coefficients were 0.93 and 0.99, respectively. We successfully applied this method to a urinary metabolomics study on breast cancer. This study demonstrated the MIIS method is simple, accurate and can contribute to data integrity in urinary metabolomics studies.

Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review

The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

Changes in urinary metabolic profile after oral administration of curcuma extract in rats

The diffusion of phytochemicals in health promoting products is growing, but studies related to their effects on healthy subjects are still lacking despite the large consumption of natural products as nutraceuticals or food supplements. In many cases, research supports the in vitro antioxidant activity of phytochemicals, but the health claims attributed to the final marketed nutraceutical products have dubious scientific foundation. Also, studies focussed on the definition of their biological targets and mechanisms of action can be useful to assess their efficacy and safety. In this study, the effect of oral administration of 80mg/kg of Curcuma longa Linn. extract to 12 healthy rats over 25 days was evaluated by monitoring the changes of urinary composition. 24-h urine was collected during the animal experiment and the composition was analyzed by (1)H NMR and HPLC-MS. The two datasets were studied individually through a metabolomic approach and the multivariate analysis revealed significant differences between the control and the treated group. Curcumin levels were also measured in 24-h urine samples by HPLC-MS. Both the (1)H NMR and the HPLC-MS dataset showed that the administration of 80mg/kg of Curcuma longa extract to healthy animals induces changes in urinary composition. Decreased allantoin urinary levels can be considered a partial demonstration of the in vivo effect of curcumin on oxidative stress in a healthy animal model.

Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study

The beneficial impact of walnuts on human health has been attributed to their unique chemical composition. In order to characterize the dietary walnut fingerprinting, spot urine samples from two sets of 195 (training) and 186 (validation) individuals were analyzed by an HPLC-q-ToF-MS untargeted metabolomics approach, selecting the most discriminating metabolites by multivariate data analysis (VIP ≥ 1.5). Stepwise logistic regression analysis was used to design a multimetabolite prediction biomarker model. The global performance of the model and each included metabolite in it was evaluated by receiver operating characteristic curves, using the area under the curve (AUC) values. Dietary exposure to walnuts was characterized by 18 metabolites, including markers of fatty acid metabolism, ellagitannin-derived microbial compounds, and intermediate metabolites of the tryptophan/serotonin pathway. The predictive model of walnut exposure included at least one compound of each class. The AUC (95% CI) for the combined biomarker model was 93.4% (90.1-96.8%) in the training set and 90.2% (85.9-94.6%) in the validation set. The AUCs for individual metabolites were ≤85%. As far as we know, this is the first study proposing a combination of biomarkers of walnut exposure in a population under free-living conditions, as considered in epidemiological studies examining associations between diet and health outcomes.

Cocoa polyphenols and inflammatory markers of cardiovascular disease

Epidemiological studies have demonstrated the beneficial effect of plant-derived food intake in reducing the risk of cardiovascular disease (CVD). The potential bioactivity of cocoa and its polyphenolic components in modulating cardiovascular health is now being studied worldwide and continues to grow at a rapid pace. In fact, the high polyphenol content of cocoa is of particular interest from the nutritional and pharmacological viewpoints. Cocoa polyphenols are shown to possess a range of cardiovascular-protective properties, and can play a meaningful role through modulating different inflammatory markers involved in atherosclerosis. Accumulated evidence on related anti-inflammatory effects of cocoa polyphenols is summarized in the present review.

Mealtime, temporal, and daily variability of the human urinary and plasma metabolomes in a tightly controlled environment

While metabolomics has tremendous potential for diagnostic biomarker and therapeutic target discovery, its utility may be diminished by the variability that occurs due to environmental exposures including diet and the influences of the human circadian rhythm. For successful translation of metabolomics findings into the clinical setting, it is necessary to exhaustively define the sources of metabolome variation. To address these issues and to measure the variability of urinary and plasma metabolomes throughout the day, we have undertaken a comprehensive inpatient study in which we have performed non-targeted metabolomics analysis of blood and urine in 26 volunteers (13 healthy subjects with no known disease and 13 healthy subjects with autosomal dominant polycystic kidney disease not taking medication). These individuals were evaluated in a clinical research facility on two separate occasions, over three days, while on a standardized, weight-based diet. Subjects provided pre- and post-prandial blood and urine samples at the same time of day, and all samples were analyzed by "fast lane" LC-MS-based global metabolomics. The largest source of variability in blood and urine metabolomes was attributable to technical issues such as sample preparation and analysis, and less variability was due to biological variables, meals, and time of day. Higher metabolome variability was observed after the morning as compared to the evening meal, yet day-to-day variability was minimal and urine metabolome variability was greater than that of blood. Thus we suggest that blood and urine are suitable biofluids for metabolomics studies, though nontargeted mass spectrometry alone may not offer sufficient precision to reveal subtle changes in the metabolome. Additional targeted analyses may be needed to support the data from nontargeted mass spectrometric analyses. In light of these findings, future metabolomics studies should consider these sources of variability to allow for appropriate metabolomics testing and reliable clinical translation of metabolomics data.

Metabolomic changes in follicular fluid induced by soy isoflavones administered to rats from weaning until sexual maturity

Female Wistar rats at 21 days of age were treated with one of three concentrations of soy isoflavones (SIF) (50, 100 or 200mg/kg body weight, orally, once per day) from weaning until sexual maturity (3 months) in order to evaluate the influence of SIF on ovarian follicle development. After treatment, the serum sex hormone levels and enumeration of ovarian follicles of the ovary were measured. The metabolic profile of follicular fluid was determined using HPLC-MS. Principal component analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA) was used to identify differences in metabolites and reveal useful toxic biomarkers. The results indicated that modest doses of SIF affect ovarian follicle development, as demonstrated by decreased serum estradiol levels and increases in both ovarian follicle atresia and corpora lutea number in the ovary. SIF treatment-related metabolic alterations in follicular fluid were also found in the PCA and PLS-DA models. The 24 most significantly altered metabolites were identified, including primary sex hormones, amino acids, fatty acids and metabolites involved in energy metabolism. These findings may indicate that soy isoflavones affect ovarian follicle development by inducing metabolomic variations in the follicular fluid.

Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

Although robust associations between dietary intake and population health are evident from conventional observational epidemiology, the outcomes of large-scale intervention studies testing the causality of those links have often proved inconclusive or have failed to demonstrate causality. This apparent conflict may be due to the well-recognised difficulty in measuring habitual food intake which may lead to confounding in observational epidemiology. Urine biomarkers indicative of exposure to specific foods offer information supplementary to the reliance on dietary intake self-assessment tools, such as FFQ, which are subject to individual bias. Biomarker discovery strategies using non-targeted metabolomics have been used recently to analyse urine from either short-term food intervention studies or from cohort studies in which participants consumed a freely-chosen diet. In the latter, the analysis of diet diary or FFQ information allowed classification of individuals in terms of the frequency of consumption of specific diet constituents. We review these approaches for biomarker discovery and illustrate both with particular reference to two studies carried out by the authors using approaches combining metabolite fingerprinting by MS with supervised multivariate data analysis. In both approaches, urine signals responsible for distinguishing between specific foods were identified and could be related to the chemical composition of the original foods. When using dietary data, both food distinctiveness and consumption frequency influenced whether differential dietary exposure could be discriminated adequately. We conclude that metabolomics methods for fingerprinting or profiling of overnight void urine, in particular, provide a robust strategy for dietary exposure biomarker-lead discovery.

Towards polypharmacokinetics: pharmacokinetics of multicomponent drugs and herbal medicines using a metabolomics approach

Determination of pharmacokinetics (PKs) of multicomponent pharmaceuticals and/or nutraceuticals (polypharmacokinetics, poly-PKs) is difficult due to the vast number of compounds present in natural products, their various concentrations across a wide range, complexity of their interactions, as well as their complex degradation dynamics in vivo. Metabolomics coupled with multivariate statistical tools that focus on the comprehensive analysis of small molecules in biofluids is a viable approach to address the challenges of poly-PK. This paper discusses recent advances in the characterization of poly-PK and the metabolism of multicomponent xenobiotic agents, such as compound drugs, dietary supplements, and herbal medicines, using metabolomics strategy. We propose a research framework that integrates the dynamic concentration profile of bioavailable xenobiotic molecules that result from in vivo absorption and hepatic and gut bacterial metabolism, as well as the human metabolic response profile. This framework will address the bottleneck problem in the pharmacological evaluation of multicomponent pharmaceuticals and nutraceuticals, leading to the direct elucidation of the pharmacological and molecular mechanisms of these compounds.

Foodomics: MS-based strategies in modern food science and nutrition

Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples

Conventional tools for measuring dietary exposure have well recognized limitations. Measurement of food-derived metabolites in biofluids provides an alternative approach and our aim was to develop an experimental protocol which ensures that extraneous variability does not obscure metabolic signals from ingested foods. Healthy adults consumed a standardized meal in the evening before each test day and collected pooled overnight urine. On each test day of three different studies, urine was collected in the fasted state and at different time points after consumption of a standardized breakfast. Metabolite fingerprinting of samples using Flow Infusion Electrospray-Ionization Mass Spectrometry followed by multivariate data analysis showed strong discrimination between overnight, fasting and postprandial samples, in each study separately and when data from the three studies were pooled. Such differences were robust and highly reproducible within individuals on separate occasions. Urine volume was an efficient data normalization factor for metabolite fingerprinting data. Postprandial urines had a stable chemical composition over a period of 2-4 h after eating a standardized breakfast, suggesting that there is a flexible time window for urine collection. Fasting urine samples provided a stable baseline for universal comparisons with postprandial samples. A dietary exposure biomarker discovery protocol was validated by demonstrating that top-ranked signals discriminating between fasting and 2-4 h postprandial urine samples could be linked to metabolites abundant in some components of the standardized breakfast. We conclude that the protocol developed will have value in the search for biomarker leads of dietary exposure. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0289-0) contains supplementary material, which is available to authorized users.

Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption

Through an HPLC-Q-TOF-MS-driven nontargeted metabolomics approach, we aimed to discriminate changes in the urinary metabolome of subjects with metabolic syndrome (MetS), following 12 weeks of mixed nuts consumption (30 g/day), compared to sex- and age-matched individuals given a control diet. The urinary metabolome corresponding to the nut-enriched diet clearly clustered in a distinct group, and the multivariate data analysis discriminated relevant mass features in this separation. Metabolites corresponding to the discriminating ions (MS features) were then subjected to multiple tandem mass spectrometry experiments using LC-ITD-FT-MS, to confirm their putative identification. The metabolomics approach revealed 20 potential markers of nut intake, including fatty acid conjugated metabolites, phase II and microbial-derived phenolic metabolites, and serotonin metabolites. An increased excretion of serotonin metabolites was associated for the first time with nut consumption. Additionally, the detection of urinary markers of gut microbial and phase II metabolism of nut polyphenols confirmed the understanding of their bioavailability and bioactivity as a priority area of research in the determination of the health effects derived from nut consumption. The results confirmed how a nontargeted metabolomics strategy may help to access unexplored metabolic pathways impacted by diet, thereby raising prospects for new intervention targets.

Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice

Alcohol abuse is one of the major causes of liver injury and a promoter for hepatocellular carcinoma (HCC). To understand the disease-associated metabolic changes, we investigated and compared the profiles of metabolites in nude mice with alcohol-induced liver injury or bearing a HCC xenograft (HCCX). Alcohol-induced liver injury was achieved by daily administration of grain liquor, and HCC xenografts were generated by subcutaneous inoculation of HepG2 cells in nude mice. Metabolites in serum samples were profiled by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS). The acquired data was analyzed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify potential disease-specific biomarkers. Results showed that the phosphatidylcholine (PC) levels were significantly higher in both liver injury and HCCX mice compared with the control. Interestingly, lysophosphatidylcholines (LPCs) that contain saturated or monounsaturated fatty acids were reduced in both liver injury and HCCX mice, but polyunsaturated fatty acids LPCs were elevated in liver injury mice only. These data delineated the disease-related metabolic alterations of LPCs in liver injury and HCC, suggesting that the LPC profile in serum may be biomarkers for these two common liver diseases.