Urinary Metabolomics Profiles Associated to Bovine Meat Ingestion in Humans

Gut microbiota drives colon cancer risk associated with diet: a comparative analysis of meat-based and pesco-vegetarian diets

BACKGROUND

Colorectal cancer (CRC) risk is strongly affected by dietary habits with red and processed meat increasing risk, and foods rich in dietary fibres considered protective. Dietary habits also shape gut microbiota, but the role of the combination between diet, the gut microbiota, and the metabolite profile on CRC risk is still missing an unequivocal characterisation.

METHODS

To investigate how gut microbiota affects diet-associated CRC risk, we fed Apc-mutated PIRC rats and azoxymethane (AOM)-induced rats the following diets: a high-risk red/processed meat-based diet (MBD), a normalised risk diet (MBD with α-tocopherol, MBDT), a low-risk pesco-vegetarian diet (PVD), and control diet. We then conducted faecal microbiota transplantation (FMT) from PIRC rats to germ-free rats treated with AOM and fed a standard diet for 3 months. We analysed multiple tumour markers and assessed the variations in the faecal microbiota using 16S rRNA gene sequencing together with targeted- and untargeted-metabolomics analyses.

RESULTS

In both animal models, the PVD group exhibited significantly lower colon tumorigenesis than the MBD ones, consistent with various CRC biomarkers. Faecal microbiota and its metabolites also revealed significant diet-dependent profiles. Intriguingly, when faeces from PIRC rats fed these diets were transplanted into germ-free rats, those transplanted with MBD faeces developed a higher number of preneoplastic lesions together with distinctive diet-related bacterial and metabolic profiles. PVD determines a selection of nine taxonomic markers mainly belonging to Lachnospiraceae and Prevotellaceae families exclusively associated with at least two different animal models, and within these, four taxonomic markers were shared across all the three animal models. An inverse correlation between nonconjugated bile acids and bacterial genera mainly belonging to the Lachnospiraceae and Prevotellaceae families (representative of the PVD group) was present, suggesting a potential mechanism of action for the protective effect of these genera against CRC.

CONCLUSIONS

These results highlight the protective effects of PVD while reaffirming the carcinogenic properties of MBD diets. In germ-free rats, FMT induced changes reminiscent of dietary effects, including heightened preneoplastic lesions in MBD rats and the transmission of specific diet-related bacterial and metabolic profiles. Importantly, to the best of our knowledge, this is the first study showing that diet-associated cancer risk can be transferred with faeces, establishing gut microbiota as a determinant of diet-associated CRC risk. Therefore, this study marks the pioneering demonstration of faecal transfer as a means of conveying diet-related cancer risk, firmly establishing the gut microbiota as a pivotal factor in diet-associated CRC susceptibility. Video Abstract.

Changes in urinary metabolomic profile show the effectiveness of a nutritional intervention in children 6-12 years old: The ALINFA study

Diet plays an essential role in health and disease. Therefore, its determination is an important component of many investigations. The aim of the study was to evaluate the effect of a nutritional intervention on the urinary metabolome in children aged 6-12 years. Also, it was intended to identify biomarkers of diet quality and dietary intake. A 2-month, randomized, controlled, parallel trial was conducted in Spanish children. The analyses focused on the ALINFA group, which followed a full-fixed meal plan including healthy products, ready-to-eat meals, and healthy recipes. Diet quality was assessed by the KIDMED index and dietary intake by a food frequency questionnaire. Untargeted metabolomic analysis on urine samples was carried out, and multivariate analyses were performed for pattern recognition and characteristic metabolite identification. PLS-DA and Volcano plot analyses were performed to identify the discriminating metabolites of this group. 12 putative metabolites were found to be the most relevant to this intervention. Most of them were products derived from protein and amino acid metabolism (N-Ribosylhistidine, indolacrylic acid, and peptides) and lipid metabolism (3-oxo-2-pentylcyclopentane-1-hexanoic acid methyl, Suberoyl-L-carnitine, and 7-Dehydrodichapetalin E). All these metabolites decreased after the intervention, which was mainly associated with a decrease in the consumption of fatty meat and total fat, especially saturated fat. In turn, N-Ribosylhistidine and Suberoyl-L-carnitine were negatively associated with diet quality, as well as able to predict the change in KIDMED index. In conclusion, the changes observed in urinary metabolome demonstrate the effectiveness of the ALINFA nutritional intervention.

Prognostic value of gut microbe-generated metabolite phenylacetylglutamine in patients with heart failure

AIM

Phenylacetylglutamine (PAGln) is a phenylalanine-derived metabolite produced by gut microbiota with mechanistic links to heart failure (HF)-relevant phenotypes. We sought to investigate the prognostic value of PAGln in patients with stable HF.

METHODS AND RESULTS

Fasting plasma PAGln levels were measured by stable-isotope-dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with stable HF from two large cohorts. All-cause mortality was assessed at 5-year follow-up in the Cleveland cohort, and HF, hospitalization, or mortality were assessed at 3-year follow-up in the Berlin cohort. Within the Cleveland cohort, median PAGln levels were 4.2 (interquartile range [IQR] 2.4-6.9) μM. Highest quartile of PAGln was associated with 3.09-fold increased mortality risk compared to lowest quartile. Following adjustments for traditional risk factors, as well as race, estimated glomerular filtration rate, amino-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, left ventricular ejection fraction, ischaemic aetiology, and HF drug treatment, elevated PAGln levels remained predictive of 5-year mortality in quartile comparisons (adjusted hazard ratio [HR] [95% confidence interval, CI] for Q4 vs Q1: 1.64 [1.07-2.53]). In the Berlin cohort, a similar distribution of PAGln levels was observed (median 3.2 [IQR 2.0-4.8] μM), and PAGln levels were associated with a 1.92-fold increase in 3-year HF hospitalization or all-cause mortality risk (adjusted HR [95% CI] for Q4 vs Q1: 1.92 [1.02-3.61]). Prognostic value of PAGln appears to be independent of trimethylamine N-oxide levels.

CONCLUSION

High levels of PAGln are associated with adverse outcomes independent of traditional cardiac risk factors and cardio-renal risk markers.

Pipecolate and Taurine are Rat Urinary Biomarkers for Lysine and Threonine Deficiencies

BACKGROUND

The consumption of poor-quality protein increases the risk of essential amino acid (EAA) deficiency, particularly for lysine and threonine. Thus, it is necessary to be able to detect easily EAA deficiency.

OBJECTIVES

The purpose of this study was to develop metabolomic approaches to identify specific biomarkers for an EAA deficiency, such as lysine and threonine.

METHODS

Three experiments were performed on growing rats. In experiment 1, rats were fed for 3 weeks with lysine (L30), or threonine (T53)-deficient gluten diets, or nondeficient gluten diet (LT100) in comparison with the control diet (milk protein, PLT). In experiments 2a and 2b, rats were fed at different concentrations of lysine (L) or threonine (T) deficiency: L/T15, L/T25, L/T40, L/T60, L/T75, P20, L/T100 and L/T170. Twenty-four-hour urine and blood samples from portal vein and vena cava were analyzed using LC-MS. Data from experiment 1 were analyzed by untargeted metabolomic and Independent Component - Discriminant Analysis (ICDA) and data from experiments 2a and 2b by targeted metabolomic and a quantitative Partial Least- Squares (PLS) regression model. Each metabolite identified as significant by PLS or ICDA was then tested by 1-way ANOVA to evaluate the diet effect. A two-phase linear regression analysis was used to determine lysine and threonine requirements.

RESULTS

ICDA and PLS found molecules that discriminated between the different diets. A common metabolite, the pipecolate, was identified in experiments 1 and 2a, confirming that it could be specific to lysine deficiency. Another metabolite, taurine, was found in experiments 1 and 2b, so probably specific to threonine deficiency. Pipecolate or taurine breakpoints obtained give a value closed to the values obtained by growth indicators.

CONCLUSIONS

Our results showed that the EAA deficiencies influenced the metabolome. Specific urinary biomarkers identified could be easily applied to detect EAA deficiency and to determine which AA is deficient.

Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry

Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.

Metabolomic markers mediate erythrocyte anisocytosis in older adults: Results from three independent aging cohorts

BACKGROUND

Anisocytosis reflects unequal-sized red blood cells and is quantified using red blood cell distribution width (RDW). RDW increases with age and has been consistently associated with adverse health outcomes, such as cardiovascular disease and mortality. Why RDW increases with age is not understood. We aimed to identify plasma metabolomic markers mediating anisocytosis with aging.

METHODS

We performed mediation analyses of plasma metabolomics on the association between age and RDW using resampling techniques after covariate adjustment. We analyzed data from adults aged 70 or older from the main discovery cohort of the Baltimore Longitudinal Study of Aging (BLSA, n = 477, 46% women) and validation cohorts of the Health, Aging and Body Composition Study (Health ABC, n = 620, 52% women) and Invecchiare in Chianti, Aging in the Chianti Area (InCHIANTI) study (n = 735, 57% women). Plasma metabolomics was assayed using the Biocrates MxP Quant 500 kit in BLSA and Health ABC and liquid chromatography with tandem mass spectrometry in InCHIANTI.

RESULTS

In all three cohorts, symmetric dimethylarginine (SDMA) significantly mediated the association between age and RDW. Asymmetric dimethylarginine (ADMA) and 1-methylhistidine were also significant mediators in the discovery cohort and one validation cohort. In the discovery cohort, we also found choline, homoarginine, and several long-chain triglycerides significantly mediated the association between age and RDW.

CONCLUSIONS AND RELEVANCE

This metabolomics study of three independent aging cohorts identified a specific set of metabolites mediating anisocytosis with aging. Whether SDMA, ADMA, and 1-methylhistidine are released by the damaged erythrocytes with high RDW or they affect the physiology of erythrocytes causing high RDW should be further investigated.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats

SCOPE

High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated.

METHODS AND RESULTS

Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet.

CONCLUSION

Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Chemotherapy-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating side effect of many common anti-cancer agents that can lead to dose reduction or treatment discontinuation, which decrease chemotherapy efficacy. Long-term CIPN can interfere with activities of daily living and diminish the quality of life. The mechanism of CIPN is not yet fully understood, and biomarkers are needed to identify patients at high risk and potential treatment targets. Metabolomics can capture the complex behavioral and pathophysiological processes involved in CIPN. This chapter is to review the CIPN metabolomics studies to find metabolic pathways potentially involved in CIPN. These potential CIPN metabolites are then investigated to determine whether there is evidence from studies of other neuropathy etiologies such as diabetic neuropathy and Leber hereditary optic neuropathy to support the importance of these pathways in peripheral neuropathy. Six potential biomarkers and their putative mechanisms in peripheral neuropathy were reviewed. Among these biomarkers, histidine and phenylalanine have clear roles in neurotransmission or neuroinflammation in peripheral neuropathy. Further research is needed to discover and validate CIPN metabolomics biomarkers in large clinical studies.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis (ASCA) was conducted, revealing that the inter-individual variability accounted for 30 % of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

Development and validation of a metabolite score for red meat intake: an observational cohort study and randomized controlled dietary intervention

BACKGROUND

Self-reported meat consumption is associated with disease risk but objective assessment of different dimensions of this heterogeneous dietary exposure in observational and interventional studies remains challenging.

OBJECTIVES

We aimed to derive and validate scores based on plasma metabolites for types of meat consumption. For the most predictive score, we aimed to test whether the included metabolites varied with change in meat consumption, and whether the score was associated with incidence of type 2 diabetes (T2D) and other noncommunicable diseases.

METHODS

We derived scores based on 781 plasma metabolites for red meat, processed meat, and poultry consumption assessed with 7-d food records among 11,432 participants in the EPIC-Norfolk (European Prospective Investigation into Cancer and Nutrition-Norfolk) cohort. The scores were then tested for internal validity in an independent subset (n = 853) of the same cohort. In focused analysis on the red meat metabolite score, we examined whether the metabolites constituting the score were also associated with meat intake in a randomized crossover dietary intervention trial of meat (n = 12, Lyon, France). In the EPIC-Norfolk study, we assessed the association of the red meat metabolite score with T2D incidence (n = 1478) and other health endpoints.

RESULTS

The best-performing score was for red meat, comprising 139 metabolites which accounted for 17% of the explained variance of red meat consumption in the validation set. In the intervention, 11 top-ranked metabolites in the red meat metabolite score increased significantly after red meat consumption. In the EPIC-Norfolk study, the red meat metabolite score was associated with T2D incidence (adjusted HR per SD: 1.17; 95% CI: 1.10, 1.24).

CONCLUSIONS

The red meat metabolite score derived and validated in this study contains metabolites directly derived from meat consumption and is associated with T2D risk. These findings suggest the potential for objective assessment of dietary components and their application for understanding diet-disease associations.The trial in Lyon, France, was registered at clinicaltrials.gov as NCT03354130.

Consumption of Boiled, but Not Grilled, Roasted, or Barbecued Beef Modifies the Urinary Metabolite Profiles in Rats

SCOPE

The consumption of processed meat is associated with increased risk of chronic diseases, but determining how the exposure to specific cooking processes alters the metabolome is an analytical challenge. This study aims to evaluate the impact of four typical cooking methods for beef (boiling, barbecuing, grilling, and roasting) on the urinary metabolite profiles in rats, using a non-targeted approach.

METHODS AND RESULTS

Male Wistar rats (n  =  48) are fed for 3 weeks with experimental diets containing either raw or cooked (boiled, barbecued, grilled, and roasted) beef. A control group is fed with milk proteins. The 24 h-urines are analyzed using LC-MS. The consumption of boiled meat leads to the specific excretion of di- and tri-peptides (aspartyl-leucine, glycyl-aspartate, and aspartyl-prolyl-threonine) and a cyclo-prolyl-proline (p < 0.001). No singular metabolite specifically associated with the groups "grilled," "roasted," and "barbecued" meat is observed.

CONCLUSION

Urinary metabolite profiles of rats fed boiled beef are clearly distinct from those of rats fed with raw, grilled, roasted, or barbecued beef. The specific metabolites include the products of non-digested proteins and may be useful as potential intake biomarkers of this meat cooking method.

Amino Acids and Lipids Associated with Long-Term and Short-Term Red Meat Consumption in the Chinese Population: An Untargeted Metabolomics Study

Red meat (RM) consumption is correlated with multiple health outcomes. This study aims to identify potential biomarkers of RM consumption in the Chinese population and evaluate their predictive ability. We selected 500 adults who participated in the 2015 China Health and Nutrition Survey and examined their overall metabolome differences by RM consumption by using elastic-net regression, then evaluate the predictivity of a combination of filtered metabolites; 1108 metabolites were detected. In the long-term RM consumption analysis 12,13-DiHOME, androstenediol (3α, 17α) monosulfate 2, and gamma-Glutamyl-2-aminobutyrate were positively associated, 2-naphthol sulfate and S-methylcysteine were negatively associated with long-term high RM consumption, the combination of metabolites prediction model evaluated by area under the receiver operating characteristic curve (AUC) was 70.4% (95% CI: 59.9–80.9%). In the short-term RM consumption analysis, asparagine, 4-hydroxyproline, and 3-hydroxyisobutyrate were positively associated, behenoyl sphingomyelin (d18:1/22:0) was negatively associated with short-term high RM consumption. Combination prediction model AUC was 75.6% (95% CI: 65.5–85.6%). We identified 10 and 11 serum metabolites that differed according to LT and ST RM consumption which mainly involved branch-chained amino acids, arginine and proline, urea cycle and polyunsaturated fatty acid metabolism. These metabolites may become a mediator of some chronic diseases among high RM consumers and provide new evidence for RM biomarkers.

From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids

The stability of lipids and other metabolites in human body fluids ranges from very stable over several days to very unstable within minutes after sample collection. Since the high-resolution analytics of metabolomics and lipidomics approaches comprise all these compounds, the handling of body fluid samples, and thus the pre-analytical phase, is of utmost importance to obtain valid profiling data. This phase consists of two parts, sample collection in the hospital (“bedside”) and sample processing in the laboratory (“bench”). For sample quality, the apparently simple steps in the hospital are much more critical than the “bench” side handling, where (bio)analytical chemists focus on highly standardized processing for high-resolution analysis under well-controlled conditions. This review discusses the most critical pre-analytical steps for sample quality from patient preparation; collection of body fluids (blood, urine, cerebrospinal fluid) to sample handling, transport, and storage in freezers; and subsequent thawing using current literature, as well as own investigations and practical experiences in the hospital. Furthermore, it provides guidance for (bio)analytical chemists to detect and prevent potential pre-analytical pitfalls at the “bedside,” and how to assess the quality of already collected body fluid samples. A knowledge base is provided allowing one to decide whether or not the sample quality is acceptable for its intended use in distinct profiling approaches and to select the most suitable samples for high-resolution metabolomics and lipidomics investigations.

You Are What You Eat: Application of Metabolomics Approaches to Advance Nutrition Research

A healthy condition is defined by complex human metabolic pathways that only function properly when fully satisfied by nutritional inputs. Poor nutritional intakes are associated with a number of metabolic diseases, such as diabetes, obesity, atherosclerosis, hypertension, and osteoporosis. In recent years, nutrition science has undergone an extraordinary transformation driven by the development of innovative software and analytical platforms. However, the complexity and variety of the chemical components present in different food types, and the diversity of interactions in the biochemical networks and biological systems, makes nutrition research a complicated field. Metabolomics science is an "-omic", joining proteomics, transcriptomics, and genomics in affording a global understanding of biological systems. In this review, we present the main metabolomics approaches, and highlight the applications and the potential for metabolomics approaches in advancing nutritional food research.

Plasma and Urinary Amino Acid-Derived Catabolites as Potential Biomarkers of Protein and Amino Acid Deficiency in Rats

OBJECTIVE

Dietary intakes must cover protein and essential amino acid (EAA) requirements. For this purpose, different methods have been developed such as the nitrogen balance method, factorial method, or AA tracer studies. However, these methods are either invasive or imprecise, and the Food and Agriculture Organization of the United Nations (FAO, 2013) recommends new methods and, in particular, metabolomics. The aim of this study is to determine total protein/EAA requirement in the plasma and urine of growing rats.

METHODS

36 weanling rats were fed with diets containing 3, 5, 8, 12, 15, and 20% protein for 3 weeks. During experimentation, urine was collected using metabolic cages, and blood from the portal vein and vena was taken at the end of the experiment. Metabolomics analyses were performed using LC-MS, and the data were analyzed with a multivariate analysis model, partial least Squares (PLS) regression, and independent component-discriminant analysis (ICDA). Each discriminant metabolite identified by PLS or ICDA was tested by one-way ANOVA to evaluate the effect of diet.

RESULTS

PLS and ICDA allowed us to identify discriminating metabolites between different diet groups. Protein deficiency led to an increase in the AA catabolism enzyme systems inducing the production of breakdown metabolites in the plasma and urine.

CONCLUSION

These results indicate that metabolites are specific for the state of EAA deficiency and sufficiency. Some types of biomarkers such as AA degradation metabolites appear to be specific candidates for protein/EAA requirement.

Urinary Medium-Chained Acyl-Carnitines Sign High Caloric Intake whereas Short-Chained Acyl-Carnitines Sign High -Protein Diet within a High-Fat, Hypercaloric Diet in a Randomized Crossover Design Dietary Trial

The western dietary pattern is known for its frequent meals rich in saturated fat and protein, resulting in a postprandial state for a large part of the day. Therefore, our aim was to investigate the postprandial glucose and lipid metabolism in response to high (HP) or normal (NP) protein, high-fat hypercaloric diet and to identify early biomarkers of protein intake and hepatic lipid accumulation. In a crossover design, 17 healthy subjects were randomly assigned to consume a HP or NP hypercaloric diet for two weeks. In parallel, a control group (CD; n = 10) consumed a weight-maintaining control diet. Biomarkers of postprandial lipid and glucose metabolism were measured in 24 h urine and in plasma before and following a meal challenge. The metabolic profile of urine but not plasma, showed increased excretion of ¹³C, carnitine and short chain acyl-carnitines after adaptation to the HP diet. Urinary excretion of decatrienoylcarnitine and octenoylcarnitine increased after adaptation to the NP diet. Our results suggest that the higher excretion of short-chain urinary acyl-carnitines could facilitate the elimination of excess fat of the HP diet and thereby reduce hepatic fat accumulation previously reported, whereas the higher excretion medium-chains acyl-carnitine could be early biomarkers of hepatic lipid accumulation.

A metabolomic study of red and processed meat intake and acylcarnitine concentrations in human urine and blood

BACKGROUND

Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited.

OBJECTIVES

To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort.

METHODS

In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires.

RESULTS

In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression).

CONCLUSIONS

AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Untargeted Metabolomics to Reveal Red versus White Meat-Associated Gut Metabolites in a Prudent and Western Dietary Context

SCOPE

To improve understanding of the epidemiological link between red and processed meat consumption and chronic diseases, more insight into the formation of metabolites during meat digestion is warranted.

METHODS AND RESULTS

Untargeted mass-spectrometry-based metabolomics is applied to explore the impact of red and processed meat consumption (compared to chicken), combined with a prudent or Western dietary pattern. A pig feeding study (n = 32), as a sentinel for humans, is conducted in a 2 × 2 factorial design for 4 weeks. The luminal content of the small intestine and colon are collected to determine their metabolic fingerprints. Seventy-six metabolites (38 in the small intestine, 32 in the colon, and 6 in both intestinal compartments) contributing to the distinct gut metabolic profiles of pigs fed either chicken or red and processed meat are (tentatively) identified. Consumption of red and processed meat results in higher levels of short- and medium-chain acylcarnitines and 3-dehydroxycarnitine, irrespective of dietary context, whereas long-chain acylcarnitines and monoacylglycerols are associated with the red and processed Western diet.

CONCLUSION

The identification of red and processed meat-associated gut metabolites in this study contributes to the understanding of meat digestion in a complex but controlled dietary context and its potential health effects.

Targeted ultra-performance liquid chromatography/tandem mass spectrometric quantification of methylated amines and selected amino acids in biofluids

RATIONALE

Methylated amino compounds and basic amino acids are important analyte classes with high relevance in nutrition, physical activity and physiology. Reliable and easy quantification methods covering a variety of metabolites in body fluids are a prerequisite for efficient investigations in the field of food and nutrition.

METHODS

Targeted ultra-performance liquid chromatography/tandem mass spectrometric (UHPLC/MS) analysis was performed using HILIC separation and timed ESI-MRM detection, combined with a short sample preparation. Calibration in urine and blood plasma was achieved by matrix-matched standards, isotope-labelled internal standards and standard addition. The method was fully validated and the performance was evaluated using a subset from the Karlsruhe Metabolomics and Nutrition (KarMeN) study.

RESULTS

Within this method, a total of 30 compounds could be quantified simultaneously in a short run of 9 min in both body fluids. This covers a variety of free amino compounds which are present in very different concentrations. The method is easy, precise and robust, and has a broad working range. As a proof of principle, literature-based associations of certain metabolites with dietary intake of respective foods were clearly confirmed in the KarMeN subset.

CONCLUSIONS

Overall, the method turned out to be well suited for application in nutrition studies, as shown for the example of food intake biomarkers in KarMeN. Application to a variety of questions such as food-related effects or physical activity will support future studies in the context of nutrition and health.

Novel Findings From a Metabolomics Study of Left Ventricular Diastolic Function: The Bogalusa Heart Study

Background

Diastolic dysfunction is one important causal factor for heart failure with preserved ejection fraction, yet the metabolic signature associated with this subclinical phenotype remains unknown.

Methods and Results

Ultra‐high‐performance liquid chromatography–tandem mass spectroscopy was used to conduct untargeted metabolomic analysis of fasting serum samples in 1050 white and black participants of the BHS (Bogalusa Heart Study). After quality control, 1202 metabolites were individually tested for association with 5 echocardiographic measures of left ventricular diastolic function using multivariable‐adjusted linear regression. Measures of left ventricular diastolic function included the ratio of peak early filling velocity to peak late filling velocity, ratio of peak early filling velocity to mitral annular velocity, deceleration time, isovolumic relaxation time, and left atrial maximum volume index (LAVI). Analyses adjusted for multiple cardiovascular disease risk factors and used Bonferroni‐corrected alpha thresholds. Eight metabolites robustly associated with left ventricular diastolic function in the overall population and demonstrated consistent associations in white and black study participants. N‐formylmethionine (B=0.05; P=1.50×10⁻⁷); 1‐methylhistidine (B=0.05; P=1.60×10⁻⁷); formiminoglutamate (B=0.07; P=5.60×10⁻⁷); N2, N5‐diacetylornithine (B=0.05; P=1.30×10⁻⁷); N‐trimethyl 5‐aminovalerate (B=0.04; P=5.10×10⁻⁶); 5‐methylthioadenosine (B=0.04; P=1.40×10⁻⁵); and methionine sulfoxide (B=0.04; P=3.80×10⁻⁶) were significantly associated with the natural log of the ratio of peak early filling velocity to mitral annular velocity. Butyrylcarnitine (B=3.18; P=2.10×10⁻⁶) was significantly associated with isovolumic relaxation time.

Conclusions

The current study identified novel findings of metabolite associations with left ventricular diastolic function, suggesting that the serum metabolome, and its underlying biological pathways, may be implicated in heart failure with preserved ejection fraction pathogenesis.

Biomarkers of meat and seafood intake: an extensive literature review

Meat, including fish and shellfish, represents a valuable constituent of most balanced diets. Consumption of different types of meat and fish has been associated with both beneficial and adverse health effects. While white meats and fish are generally associated with positive health outcomes, red and especially processed meats have been associated with colorectal cancer and other diseases. The contribution of these foods to the development or prevention of chronic diseases is still not fully elucidated. One of the main problems is the difficulty in properly evaluating meat intake, as the existing self-reporting tools for dietary assessment may be imprecise and therefore affected by systematic and random errors. Dietary biomarkers measured in biological fluids have been proposed as possible objective measurements of the actual intake of specific foods and as a support for classical assessment methods. Good biomarkers for meat intake should reflect total dietary intake of meat, independent of source or processing and should be able to differentiate meat consumption from that of other protein-rich foods; alternatively, meat intake biomarkers should be specific to each of the different meat sources (e.g., red vs. white; fish, bird, or mammal) and/or cooking methods. In this paper, we present a systematic investigation of the scientific literature while providing a comprehensive overview of the possible biomarker(s) for the intake of different types of meat, including fish and shellfish, and processed and heated meats according to published guidelines for biomarker reviews (BFIrev). The most promising biomarkers are further validated for their usefulness for dietary assessment by published validation criteria.

Combined Markers to Assess Meat Intake-Human Metabolomic Studies of Discovery and Validation

SCOPE

Biomarkers of red meat may clarify the relationship between meat intake and health. This paper explores the discovery of biomarkers of intake for three types of meat with varying heme iron content. Candidate biomarkers for red and general meat are further evaluated based on defined validation criteria.

METHODS AND RESULTS

In a randomized cross-over meal study, healthy volunteers consume a randomized sequence of four test meals: chicken, pork, beef, and a control made of egg white and pea. Fasting and postprandial urine samples are collected to cover 48 h and profiled by untargeted LC-ESI-qTOF-MS metabolomics. The profiles following the meal challenges are explored by univariate and multivariate analyses. Nine red, four white, and eight general meat biomarkers are selected as putative biomarkers, originating from collagen degradation, flavour compounds, and amino acid metabolism. Heme-related metabolites are masked by the chlorophyll content of the control meal. The candidate biomarkers are confirmed in an independent meal study and validated for plausibility, robustness, time-response, and prediction performance. Combinations of biomarkers are more efficient than single markers in predicting meat intake.

CONCLUSION

New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.