Metabolite fingerprinting of urine suggests breed-specific dietary metabolism differences in domestic dogs

A revisiting of "the hallmarks of aging" in domestic dogs: current status of the literature

A progressive decline in biological function and fitness is, generally, how aging is defined. However, in 2013, a description on the "hallmarks of aging" in mammals was published, and within it, it described biological processes that are known to alter the aging phenotype. These include genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication (inflammation), and changes within the microbiome. This mini-review provides a detailed account of the progress on each of these hallmarks of aging in the domestic dog within the last 5 years. Additionally, when there are gaps in the literature between other mammalian species and dogs, I highlight the aging biomarkers that may be missing for dogs as aging models. I also argue for the importance of dog aging studies to include several breeds of dogs at differing ages and for age corrections for breeds with differing mean lifespans throughout.

Metabolomics of aging in primary fibroblasts from small and large breed dogs

Among several animal groups (eutherian mammals, birds, reptiles), lifespan positively correlates with body mass over several orders of magnitude. Contradicting this pattern are domesticated dogs, with small dog breeds exhibiting significantly longer lifespans than large dog breeds. The underlying mechanisms of differing aging rates across body masses are unclear, but it is generally agreed that metabolism is a significant regulator of the aging process. Herein, we performed a targeted metabolomics analysis on primary fibroblasts isolated from small and large breed young and old dogs. Regardless of size, older dogs exhibited lower glutathione and ATP, consistent with a role for oxidative stress and bioenergetic decline in aging. Furthermore, several size-specific metabolic patterns were observed with aging, including the following: (i) An apparent defect in the lower half of glycolysis in large old dogs at the level of pyruvate kinase. (ii) Increased glutamine anaplerosis into the TCA cycle in large old dogs. (iii) A potential defect in coenzyme A biosynthesis in large old dogs. (iv) Low nucleotide levels in small young dogs that corrected with age. (v) An age-dependent increase in carnitine in small dogs that was absent in large dogs. Overall, these data support the hypothesis that alterations in metabolism may underlie the different lifespans of small vs. large breed dogs, and further work in this area may afford potential therapeutic strategies to improve the lifespan of large dogs.

Applying metabolomics to veterinary pharmacology and therapeutics

Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.

Metabolomics shows the Australian dingo has a unique plasma profile

Dingoes occupy a wide range of the Australian mainland and play a crucial role as an apex predator with a generalist omnivorous feeding behaviour. Dingoes are ecologically, phenotypically and behaviourally distinct from modern breed dogs and have not undergone artificial selection since their arrival in Australia. In contrast, humans have selected breed dogs for novel and desirable traits. First, we examine whether the distinct evolutionary histories of dingoes and domestic dogs has lead to differences in plasma metabolomes. We study metabolite composition differences between dingoes (n = 15) and two domestic dog breeds (Basenji n = 9 and German Shepherd Dog (GSD) n = 10). Liquid chromatography mass spectrometry, type II and type III ANOVA with post-hoc tests and adjustments for multiple comparisons were used for data evaluation. After accounting for within group variation, 62 significant metabolite differences were detected between dingoes and domestic dogs, with the majority of differences in protein (n = 14) and lipid metabolites (n = 12), mostly lower in dingoes. Most differences were observed between dingoes and domestic dogs and fewest between the domestic dog breeds. Next, we collect a second set of data to investigate variation between pure dingoes (n = 10) and dingo-dog hybrids (n = 10) as hybridisation is common in regional Australia. We detected no significant metabolite differences between dingoes and dingo-dog hybrids after Bonferroni correction. However, power analysis showed that increasing the sample size to 15 could result in differences in uridine 5′-diphosphogalactose (UDPgal) levels related to galactose metabolism. We suggest this may be linked to an increase in Amylase 2B copy number in hybrids. Our study illustrates that the dingo metabolome is significantly different from domestic dog breeds and hybridisation is likely to influence carbohydrate metabolism.

Metabolic Changes in Serum Metabolome of Beagle Dogs Fed Black Ginseng

The effects of black ginseng, which has many kinds of biological activities, on dogs was investigated. Serum samples of beagle dogs, which were fed with black ginseng for 8 weeks, were measured using high-resolution magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectrometry. Acquired NMR data from the serum of dogs fed for 0, 4, and 8 weeks were analyzed by metabolic profiling and multivariate statistical analysis. In statistical analysis and biomarker analysis results of metabolite profiles, formate, glutamine, histidine, isoleucine, leucine, proline, and valine had variable importance in projection (VIP) scores above 1.0 and excellent area under the curve (AUC) values of receiver operating characteristic (ROC) curves above 0.9. In the result of multivariate statistical analysis, the score plot showed the discrimination between before and after feeding of black ginseng. These differences in metabolic profiles are considered to be due to the involvement of metabolic processes following black ginseng administration, such as enhancing immunity and energy metabolism. Through metabolomics analysis, we confirmed the biological efficacy of black ginseng in dogs and also confirmed that metabolomics can be applied to the pet health industry.

Canine metabolomics advances

INTRODUCTION

Canis lupus familiaris is a domestic dog and many owners consider their pets as a family member. Medical bills with dogs are overcame only by the health care received by humans. Medical care is constantly progressing, and so is veterinary care. Metabolomics is the ''omic" technique aimed to the study of metabolome, low-molecular weight molecules, through biofluids or tissue samples. And it also allows to evaluate disease diagnosis and prognosis, therapeutic evaluation and toxicological studies.

OBJECTIVES

The goal of this paper is to review the current and potential applications of metabolomics in domestic dogs.

METHOD

ScienceDirect, Scopus, Reaxys and PubMed were searched for papers that performed canine metabolomics in any research area.

RESULTS

We analysed 38 papers, published until April 2019 in canine metabolomics approach. Metabolomic research in dogs so far can be divided into three areas: (a) Metabolomics studies in veterinary science, such as improving pet dogs health and welfare. (b) Diet, breeds and species discrimination. (c) Use of dogs as animal model in different diseases and drug development (evaluation toxicity and effect).

CONCLUSIONS

The results of this review showed that interest in metabolomics is growing in veterinary research. Several canine diseases have been evaluated with some promise for potential biomarker and/or disease mechanism discovery. Because canine metabolomics is a relatively new area, the researches spread across different research areas and with few studies in each area.

Serum lipidome analysis of healthy beagle dogs receiving different diets

INTRODUCTION

Food and dietary ingredients have significant effects on metabolism and health.

OBJECTIVE

To evaluate whether and how different diets affected the serum lipidomic profile of dogs.

METHODS

Sixteen healthy beagles were fed a commercial dry diet for 3 months (control diet). After an overnight fasting period, a blood sample was taken for serum lipidomic profile analysis, and each dog was then randomly assigned to one of two groups. Group 1 was fed a commercial diet (Diet 1) and group 2 was fed a self-made, balanced diet supplemented with linseed oil and salmon oil (Diet 2) for 3 months. After an overnight fasting period, a blood sample was taken from each dog. Serum cholesterol and triacylglycerol analyses were performed and the serum lipidomic profiles were analyzed using targeted liquid chromatography-mass spectrometry.

RESULTS

Dogs fed the supplemented self-made diet (Diet 2) had significantly higher omega-3 fatty acid-containing lipids species and significantly lower saturated and mono- and di-unsaturated lipid species. Concentrations of sphingosine 1-phosphate species S1P d16:1 and S1P d17:1 were significantly increased after feeding Diet 2.

CONCLUSION

This study found that different diets had significant effects on the dog's serum lipidomic profile. Therefore, in studies that include lipidomic analyses, diet should be included as a confounding factor.

Genome-wide association studies of 74 plasma metabolites of German shepherd dogs reveal two metabolites associated with genes encoding their enzymes

INTRODUCTION

German shepherd dogs (GSDs) are a popular breed affected by numerous disorders. Few studies have explored genetic variations that influence canine blood metabolite levels.

OBJECTIVES

To investigate genetic variants affecting the natural metabolite variation in GSDs.

METHODS

A total of 82 healthy GSDs were genotyped on the Illumina CanineHD Beadchip, assaying 173,650 markers. For each dog, 74 metabolites were measured through liquid and gas chromatography mass spectrometry (LC-MS and GC-MS) and were used as phenotypes for genome-wide association analyses (GWAS). Sliding window and homozygosity analyses were conducted to fine-map regions of interest, and to identify haplotypes and gene dosage effects.

RESULTS

Summary statistics for 74 metabolites in this population of GSDs are reported. Forty-one metabolites had significant associations at a false discovery rate of 0.05. Two associations were located around genes which encode for enzymes for the relevant metabolites: 4-hydroxyproline was significantly associated to D-amino acid oxidase (DAO), and threonine to L-threonine 3-dehydrogenase (LOC477365). Three of the top ten haplotypes associated to 4-hydroxyproline included at least one SNP on DAO. These haplotypes occurred only in dogs with the highest 15 measurements of 4-hydroxyproline, ranging in frequency from 16.67 to 20%. None of the dogs were homozygous for these haplotypes. The top two haplotypes associated to threonine included SNPs on LOC477365 and were also overrepresented in dogs with the highest 15 measurements of threonine. These haplotypes occurred at a frequency of 90%, with 80% of these dogs homozygous for the haplotypes. In dogs with the lowest 15 measurements of threonine, the haplotypes occurred at a frequency of 26.67% and 0% homozygosity.

CONCLUSION

DAO and LOC477365 were identified as candidate genes affecting the natural plasma concentration of 4-hydroxyproline and threonine, respectively. Further investigations are needed to validate the effects of the variants on these genes.

Metabolomic profiling to identify effects of dietary calcium reveal the influence of the individual and postprandial dynamics on the canine plasma metabolome

Short-term feeding studies have highlighted a phenomenon in Ca regulation that raises concerns around Ca absorption in dogs that may make an impact on commercial diets near to the maximum recommended level. A recent study to determine responses in dogs fed one of two diets differing in dietary Ca over 40 weeks found no evidence to suggest a concern across a range of biological parameters hypothesised to be affected by Ca. Unforeseen consequences of dietary Ca could have occurred and metabolic profiling was deemed a suitable data-driven approach to identify effects of dietary Ca. The objectives were to compare the fasted plasma metabolome (sampled at 8-week intervals over 40 weeks) of dogs fed one of two diets, near to the minimum and maximum recommended levels of dietary Ca. Comparisons with the control diet were also investigated across the postprandial time course (1-4 h) following acute (1 d) and long-term (24 weeks) feeding of the test diet. Comparing fasted plasma samples at each time point, no significant effect (adjusted P < 0·05) of diet on metabolites was observed. In the postprandial state, only phosphate was consistently different between diets and was explained by additional dietary P to maintain Ca:P. Metabolic profiling analysis supports the view that the dietary Ca upper limit is safe. Additionally, the canine plasma metabolome was characterised, providing insights into the stability of individual profiles across 40 weeks, the response to consumption of a nutritionally complete meal over a 4 h postprandial time course and different kinetic categories of postprandial absorption.

The urine metabolome differs between lean and overweight Labrador Retriever dogs during a feed-challenge

Obesity in dogs is an increasing problem and better knowledge of the metabolism of overweight dogs is needed. Identification of molecular changes related to overweight may lead to new methods to improve obesity prevention and treatment. The aim of the study was firstly to investigate whether Nuclear Magnetic Resonance (NMR) based metabolomics could be used to differentiate postprandial from fasting urine in dogs, and secondly to investigate whether metabolite profiles differ between lean and overweight dogs in fasting and postprandial urine, respectively. Twenty-eight healthy intact male Labrador Retrievers were included, 12 of which were classified as lean (body condition score (BCS) 4-5 on a 9-point scale) and 16 as overweight (BCS 6-8). After overnight fasting, a voided morning urine sample was collected. Dogs were then fed a high-fat mixed meal and postprandial urine was collected after 3 hours. Metabolic profiles were generated using NMR and 45 metabolites identified from the spectral data were evaluated using multivariate data analysis. The results revealed that fasting and postprandial urine differed in relative metabolite concentration (partial least-squares discriminant analysis (PLS-DA) 1 comp: R2Y = 0.4, Q2Y = 0.32; cross-validated ANOVA: P = 0.00006). Univariate analyses of discriminant metabolites showed that taurine and citrate concentrations were elevated in postprandial urine, while allantoin concentration had decreased. Interestingly, lean and overweight dogs differed in terms of relative metabolite concentrations in postprandial urine (PLS-DA 1 comp: R2Y = 0.5, Q2Y = 0.36, cross-validated ANOVA: P = 0.005) but not in fasting urine. Overweight dogs had lower postprandial taurine and a trend of higher allantoin concentrations compared with lean dogs. These findings demonstrate that metabolomics can differentiate 3-hour postprandial urine from fasting urine in dogs, and that postprandial urine metabolites may be more useful than fasting metabolites for identification of metabolic alterations linked to overweight. The lowered urinary taurine concentration in overweight dogs could indicate alterations in lipid metabolism and merits further investigation.

Ultra high performance liquid chromatography-high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets

INTRODUCTION AND OBJECTIVES

The purpose of this study was to use high accurate mass metabolomic profiling to investigate differences within a phenotypically diverse canine population, with breed-related morphological, physiological and behavioural differences. Previously, using a broad metabolite fingerprinting approach, lipids appear to dominate inter- and intra- breed discrimination. The purpose here was to use Ultra High Performance Liquid Chromatography-High Resolution Mass Spectrometry (UHPLC-HRMS) to identify in more detail, inter-breed signatures in plasma lipidomic profiles of home-based, client-owned dogs maintained on different diets and fed according to their owners' feeding regimens.

METHODS

Nine dog breeds were recruited in this study (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese: 7-12 dogs per breed). Metabolite profiling on a MTBE lipid extract of fasted plasma was performed using UHPLC-HRMS.

RESULTS

Multivariate modelling and classification indicated that the main source of lipidome variance was between the three breeds Chihuahua, Dachshund and Greyhound and the other six breeds, however some intra-breed variance was evident in Labrador Retrievers. Metabolites associated with dietary intake impacted on breed-associated variance and following filtering of these signals out of the data-set unique inter-breed lipidome differences for Chihuahua, Golden Retriever and Greyhound were identified.

CONCLUSION

By using a phenotypically diverse home-based canine population, we were able to show that high accurate mass lipidomics can enable identification of metabolites in the first pass plasma profile, capturing distinct metabolomic variability associated with genetic differences, despite environmental and dietary variability.

Metabolic Profiling Reveals Effects of Age, Sexual Development and Neutering in Plasma of Young Male Cats

Neutering is a significant risk factor for obesity in cats. The mechanisms that promote neuter-associated weight gain are not well understood but following neutering, acute changes in energy expenditure and energy consumption have been observed. Metabolic profiling (GC-MS and UHPLC-MS-MS) was used in a longitudinal study to identify changes associated with age, sexual development and neutering in male cats fed a nutritionally-complete dry diet to maintain an ideal body condition score. At eight time points, between 19 and 52 weeks of age, fasted blood samples were taken from kittens neutered at either 19 weeks of age (Early Neuter (EN), n = 8) or at 31 weeks of age (Conventional Neuter (CN), n = 7). Univariate and multivariate analyses were used to compare plasma metabolites (n = 370) from EN and CN cats. Age was the primary driver of variance in the plasma metabolome, including a developmental change independent of neuter group between 19 and 21 weeks in lysolipids and fatty acid amides. Changes associated with sexual development and its subsequent loss were also observed, with differences at some time points observed between EN and CN cats for 45 metabolites (FDR p<0.05). Pathway Enrichment Analysis also identified significant effects in 20 pathways, dominated by amino acid, sterol and fatty acid metabolism. Most changes were interpretable within the context of male sexual development, and changed following neutering in the CN group. Felinine metabolism in CN cats was the most significantly altered pathway, increasing during sexual development and decreasing acutely following neutering. Felinine is a testosterone-regulated, felid-specific glutathione derivative secreted in urine. Alterations in tryptophan, histidine and tocopherol metabolism observed in peripubertal cats may be to support physiological functions of glutathione following diversion of S-amino acids for urinary felinine secretion.

Innovations in Canine and Feline Nutrition: Technologies for Food and Nutrition Assessment

Pet owners have increasing concerns about the nutrition of their pets, and they desire foods and treats that are safe, traceable, and of high nutritive value. To meet these high expectations, detailed chemical composition characterization of ingredients well beyond that provided by proximate analysis will be required, as will information about host physiology and metabolism. Use of faster and more precise analytical methodology and novel technologies that have the potential to improve pet food safety and quality will be implemented. In vitro and in vivo assays will continue to be used as screening tools to evaluate nutrient quality and adequacy in novel ingredients prior to their use in animal diets. The use of molecular and high-throughput technologies allows implementation of noninvasive studies in dogs and cats to investigate the impact of dietary interventions by using systems biology approaches. These approaches may further improve the health and longevity of pets.

Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs

INTRODUCTION

Dog breeds are a consequence of artificial selection for specific attributes. These closed genetic populations have metabolic and physiological characteristics that may be revealed by metabolomic analysis.

OBJECTIVES

To identify and characterise the drivers of metabolic differences in the fasted plasma metabolome and then determine metabolites differentiating breeds.

METHODS

Fasted plasma samples were collected from dogs maintained under two environmental conditions (controlled and client-owned at home). The former (n = 33) consisted of three breeds (Labrador Retriever, Cocker Spaniel and Miniature Schnauzer) fed a single diet batch, the latter (n = 96), client-owned dogs consisted of 9 breeds (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese) consuming various diets under differing feeding regimens. Triplicate samples were taken from Beagle (n = 10) and Labrador Retriever (n = 9) over 3 months. Non-targeted metabolite fingerprinting was performed using flow infusion electrospray-ionization mass spectrometry which was coupled with multivariate data analysis. Metadata factors including age, gender, sexual status, weight, diet and breed were investigated.

RESULTS

Breed differences were identified in the plasma metabolome of dogs housed in a controlled environment. Triplicate samples from two breeds identified intra-individual variability, yet breed separation was still observed. The main drivers of variance in dogs maintained in the home environment were associated with breed and gender. Furthermore, metabolite signals were identified that discriminated between Labrador Retriever and Cocker Spaniels in both environments.

CONCLUSION

Metabolite fingerprinting of plasma samples can be used to investigate breed differences in client-owned dogs, despite added variance of diet, sexual status and environment.

Direct infusion ESI–MS analysis for metabolite profiling of human plasma using various fractionation techniques

Background: Metabolomics is a real challenge owing to the complexity and chemical heterogeneity of biological samples. In this study, a comparative analysis of metabolite profiling using ten metabolite extraction techniques were investigated on a pooled plasma sample followed by direct infusion ESI–MS analysis on both positive and negative modes. Methodology & Results: Metabolites from a pooled sample of 50 healthy volunteers were separated one- and two-dimensionally utilizing solvent precipitation, solid-phase extraction and molecular weight fractionation. Numbers of unique metabolites that are specific to a particular sample preparation approach were also identified by online available database, Metlin. The 1H NMR study of different extraction procedures were also recorded to elaborate the comparative profiling of the various fractionation procedures. Conclusion: The results of this study suggest that the metabolite extraction procedures based on 1- and 2-dimensions, followed by direct infusion ESI–MS analysis were able to detect endogenous metabolites belonging to different chemical classes.

Merits of random forests emerge in evaluation of chemometric classifiers by external validation

Real-world applications will inevitably entail divergence between samples on which chemometric classifiers are trained and the unknowns requiring classification. This has long been recognized, but there is a shortage of empirical studies on which classifiers perform best in 'external validation' (EV), where the unknown samples are subject to sources of variation relative to the population used to train the classifier. Survey of 286 classification studies in analytical chemistry found only 6.6% that stated elements of variance between training and test samples. Instead, most tested classifiers using hold-outs or resampling (usually cross-validation) from the same population used in training. The present study evaluated a wide range of classifiers on NMR and mass spectra of plant and food materials, from four projects with different data properties (e.g., different numbers and prevalence of classes) and classification objectives. Use of cross-validation was found to be optimistic relative to EV on samples of different provenance to the training set (e.g., different genotypes, different growth conditions, different seasons of crop harvest). For classifier evaluations across the diverse tasks, we used ranks-based non-parametric comparisons, and permutation-based significance tests. Although latent variable methods (e.g., PLSDA) were used in 64% of the surveyed papers, they were among the less successful classifiers in EV, and orthogonal signal correction was counterproductive. Instead, the best EV performances were obtained with machine learning schemes that coped with the high dimensionality (914-1898 features). Random forests confirmed their resilience to high dimensionality, as best overall performers on the full data, despite being used in only 4.5% of the surveyed papers. Most other machine learning classifiers were improved by a feature selection filter (ReliefF), but still did not out-perform random forests.

Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread

SCOPE

Understanding relationships between dietary whole grain and health is hindered by incomplete knowledge of potentially bioactive metabolites derived from these foods. We aimed to discover compounds in urine correlated with changes in amounts of whole grain rye consumption.

METHODS AND RESULTS

After a wash-out period, volunteers consumed 48-g whole grain rye foods per day for 4 wk and then doubled their intake for a further 4 wk. Samples of 24-h urines were analyzed by flow infusion electrospray MS followed by supervised multivariate data analysis. Urine samples from participants who reported high intakes of rye flakes, rye pasta, or total whole grain rye products could not be discriminated adequately from their wash-out samples. However, discrimination was seen in urine samples from participants who reported high whole grain sourdough rye bread consumption. Accurate mass analysis of explanatory signals followed by fragmentation identified conjugates of the benzoxazinoid lactam 2-hydroxy-1,4-benzoxazin-3-one and hydroxylated phenyl acetamide derivatives. Statistical validation showed sensitivities of 84-96% and specificities of 70-81% (p values < 0·05) for elevated concentrations of these signals after preferential whole grain sourdough rye bread consumption.

CONCLUSION

Several potentially bioactive alkaloids have been identified in humans consuming fermented whole grain sourdough rye bread.

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.

Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure

BACKGROUND

An understanding of causal relations between diet and health is hindered by the lack of robust biological markers of food exposure.

OBJECTIVE

We aimed to develop a data-driven procedure to discover urine biomarkers indicative of habitual exposure to different foods.

DESIGN

The habitual diet of 68 participants was assessed by using 4 food-frequency questionnaires over 3 mo, and participants were assigned to different consumption-frequency classes for 58 dietary components. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to determine whether the chemical composition of urine was related to specific differences in the consumption levels of each food.

RESULTS

Foods were eaten habitually in 1 of 5 basic patterns differing in range and distribution of consumption frequency. Overnight, 24-h, and fasting urine samples proved useful for biomarker lead discovery with habitual citrus exposure used as a paradigm. Exposure level discrimination robustness improved linearly as urine samples from low-frequency citrus consumers were compared with urine samples from participants reporting increasingly higher intakes. For all foods, distinctiveness and consumption-frequency range influenced the likelihood that differential dietary exposure could be detected. Model output statistics indicated foods for which biomarker lead discovery was feasible. Metabolites proposed previously as acute intake biomarkers of citrus (proline betaine), oily fish (methylhistidine), coffee (dihydrocaffeic acid derivatives), and tomato (phenolic metabolites) were also biomarkers of habitual exposure. A significance threshold in modeling output statistics was determined to guide the discovery of potential biomarkers for other foods.

CONCLUSION

This data-driven strategy can identify urinary metabolites associated with habitual exposure to specific foods. This trial has the UK registration number 4349 and was registered at isrtcn.org as CCT-NAPN-A13175.

Identification of intra- and inter-individual metabolite variation in plasma metabolite profiles of cats and dogs

The purpose of the present study was first to identify drivers of variance in plasma metabolite profiles of cats and dogs that may affect the interpretation of nutritional metabolomic studies. A total of fourteen cats and fourteen dogs housed in environmentally enriched accommodation were fed a single batch of diet to maintain body weight. Fasting blood samples were taken on days 14, 16 and 18 of the study. Gas chromatography-mass spectrometry (GC-MS), liquid chromatography (LC)-MS/MS and solid-phase extraction-LC-MS/MS analyses were used for metabolite profiling. Principal component (PC) analysis that indicated 31 and 27 % of the variance was explained in PC1 and PC2 for cats and dogs, respectively, with most individuals occupying a unique space. As the individual was a major driver of variance in the plasma metabolome, the second objective was to identify metabolites associated with the individual variation observed. The proportion of intra- and inter-individual variance was calculated for 109 cat and 101 dog metabolites with a low intra-individual variance (SD < 0.05). Of these, fifteen cat and six dog metabolites had inter-individual variance accounting for at least 90 % of the total variance. There were four metabolites common to both species (campesterol, DHA, a cholestenol and a sphingosine moiety). Many of the metabolites with >75 % inter-individual variance were common to both species and to similar areas of metabolism. In summary, the individual is an important driver of variance in the fasted plasma metabolome, and specific metabolites and areas of metabolism may be differentially regulated by individuals in two companion animal species.

Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods

BACKGROUND

The lack of robust biological markers of dietary exposure hinders the quantitative understanding of causal relations between diet and health.

OBJECTIVE

We aimed to develop an efficient procedure to discover metabolites in urine that may have future potential as biomarkers of acute exposure to foods of high public health importance.

DESIGN

Twenty-four participants were provided with a test breakfast in which the cereal component of a standardized breakfast was replaced by 1 of 4 foods of high public health importance; 1.5-, 3-, and 4.5-h postprandial urine samples were collected. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to discover signals resulting from consumption of each test food.

RESULTS

Fasted-state urine samples provided a universal comparator for food biomarker lead discovery in postprandial urine. The filtering of data features associated with consumption of the common components of the standardized breakfast improved discrimination models and readily identified metabolites that showed consumption of specific test foods. A combination of trimethylamine-N-oxide and 1-methylhistidine was associated with salmon consumption. Novel ascorbate derivatives were discovered in urine after consumption of either broccoli or raspberries. Sulphonated caffeic acid and sulphonated methyl-epicatechin concentrations increased dramatically after consumption of raspberries.

CONCLUSIONS

This biomarker lead discovery strategy can identify urinary metabolites associated with acute exposure to individual foods. Future studies are required to validate the specificity and utility of potential biomarkers in an epidemiologic context.