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

Profound Perturbation in the Metabolome of a Canine Obesity and Metabolic Disorder Model

Canine models are increasingly being used in metabolic studies due to their physiological similarity with humans. The present study aimed to identify changes in metabolic pathways and biomarkers with potential clinical utility in a canine model of obesity and metabolic disorders induced by a high-fat diet (HFD). Eighteen male beagles were included in this study, 9 of which were fed a HFD for 24 weeks, and the remaining 9 were fed normal chow (NC) during the same period. Plasma and urine samples were collected at weeks 12 and 24 for untargeted metabolomic analysis. Dogs fed a HFD showed a gradual body weight increase during the feeding period and had hyperlipidemia, increased leukocyte counts, and impaired insulin sensitivity at week 24. Plasma and urine metabonomics analysis displayed clear separations between the HFD-fed and NC-fed dogs. A total of 263 plasma metabolites varied between the two groups, including stearidonic acid, linolenic acid, carnitine, long-chain ceramide, 3-methylxanthine, and theophylline, which are mainly engaged in fatty acid metabolism, sphingolipid metabolism, and caffeine metabolism. A total of 132 urine metabolites related to HFD-induced obesity and metabolic disorders were identified, including 3-methylxanthine, theophylline, pyridoxal 5'-phosphate, and harmine, which participate in pathways such as caffeine metabolism and vitamin digestion and absorption. Eight metabolites with increased abundance (e.g., 3-methylxanthine, theophylline, and harmine) and 4 metabolites with decreased abundance (e.g., trigonelline) in both the plasma and urine of the HFD-fed dogs were identified. In conclusion, the metabolomic analysis revealed molecular events underlying a canine HFD model and identified several metabolites as potential targets for the prevention and treatment of obesity-related metabolic disorders.

Effects of Weight Loss and Moderate-Protein, High-Fiber Diet Consumption on the Fasted Serum Metabolome of Cats

Feline obesity elicits a plethora of metabolic responses leading to comorbidities, with potential reversal during weight loss. The specific metabolic alterations and biomarkers of organ dysfunction are not entirely understood. Untargeted, high-throughput metabolomic technologies may allow the identification of biological components that change with weight status in cats, increasing our understanding of feline metabolism. The objective of this study was to utilize untargeted metabolomic techniques to identify biomarkers and gain mechanistic insight into the serum metabolite changes associated with reduced food intake and weight loss in overweight cats. During a four-wk baseline period, cats were fed to maintain body weight. For 18 wk following baseline, cats were fed to lose weight at a rate of ~1.5% body weight/wk. Blood serum metabolites were measured at wk 0, 1, 2, 4, 8, 12, and 16. A total of 535 named metabolites were identified, with up to 269 of them being altered (p- and q-values < 0.05) at any time point. A principal component analysis showed a continual shift in metabolite profile as weight loss progressed, with early changes being distinct from those over the long term. The majority of lipid metabolites decreased with weight loss; however, ketone bodies and small lipid particles increased with weight loss. The majority of carbohydrate metabolites decreased with weight loss. Protein metabolites had a variable result, with some increasing, but others decreasing with weight loss. Metabolic mediators of inflammation, oxidative stress, xenobiotics, and insulin resistance decreased with weight loss. In conclusion, global metabolomics identified biomarkers of reduced food intake and weight loss in cats, including decreased markers of inflammation and/or altered macronutrient metabolism.

Serum metabolomics analysis reveals that weight loss in obese dogs results in a similar metabolic profile to dogs in ideal body condition

INTRODUCTION

The study of metabolic profile can be an important tool to better understand, at a systemic level, metabolic alterations caused by different pathological conditions, such as obesity. Furthermore, it allows the discovery of metabolic biomarkers, which may help to diagnose alterations caused by obesity.

OBJECTIVE

To investigate the metabolic profile of blood serum of obese dogs, control dogs, and dogs that were subjected to a weight loss program.

METHODS

Ten obese adult spayed female dogs were included, and their body composition was determined by the deuterium isotope dilution method. The dogs were subjected to a weight loss program and formed a new experimental group after losing 20% of the initial body weight. A third experimental group was composed of ten lean adult spayed female dogs. The metabolic profile of blood serum was evaluated through nuclear magnetic resonance (NMR). Principal Component Analyses (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) models were constructed using Pareto scaling pre-processing. Pathway analysis was also performed using the MetaboAnalist online tool.

RESULTS

The PCA shows that the control and after weight loss groups presented a trend to negative PC1, indicating similarities between these two groups. In contrast, obese animals presented a tendency to appear on negative PC2 indicating a different metabolic profile. The OPLS-DA analysis of the serum indicated that healthy groups presented higher content of glucose, while animals that lost weight had higher levels of cholesterol and lactate than the control group. On the other hand, the analysis showed that lipid content, cholesterol, and branched-chain amino acids were highest in obese animals. Variable Influence on Projection (VIP) analysis demonstrated that Lactate is the most important metabolite for the OPLS-DA model and Hierarchical Cluster Analysis (HCA) corroborated the similarity between the control group and the obese after weight loss groups. Moreover, the pathway analysis indicated the most important metabolic pathways related to this dataset.

CONCLUSIONS

The metabolomic assessment based on NMR of blood serum differed between obese dogs and animals in optimal body condition. Moreover, the weight loss resulted in metabolic profiles similar to those observed in lean animals.

Untargeted metabolomic profiling of serum in dogs with hypothyroidism

Hypothyroidism is one of the most commonly diagnosed endocrine disease in dogs. The clinical signs are caused by a deficiency of the active thyroid hormones triiodothyronine (T3) and thyroxine (T4) and have a negative impact on dog's quality of life. We hypothesized that serum metabolic profile varies between healthy dogs and dogs with hypothyroidism. Twenty serum samples from dogs with hypothyroidism and 20 from healthy dogs were used for untargeted metabolomics analysis performed by LC/MS analysis. Fifteen metabolites showed significant changes between hypothyroid and healthy dogs, being the pentose phosphate pathway (PPP), aminoacyl-tRNA biosynthesis and pyrimidine metabolism the principal pathways altered in hypothyroidism. Specifically, metabolites such as D-gluconic acid and L-Isoleucine may potentially act as biomarkers of disease.

Urinary proteome and metabolome in dogs (Canis lupus familiaris): The effect of chronic kidney disease

Chronic kidney disease (CKD) is a progressive and irreversible disease. Although urine is an ideal biological sample for proteomics and metabolomics studies, sensitive and specific biomarkers are currently lacking in dogs. This study characterised dog urine proteome and metabolome aiming to identify and possibly quantify putative biomarkers of CKD in dogs. Twenty-two healthy dogs and 28 dogs with spontaneous CKD were selected and urine samples were collected. Urinary proteome was separated by SDS-PAGE and analysed by mass spectrometry, while urinary metabolome was analysed in protein-depleted samples by 1D ¹H NMR spectra. The most abundant proteins in urine samples from healthy dogs were uromodulin, albumin and, in entire male dogs, arginine esterase. In urine samples from CKD dogs, the concentrations of uromodulin and albumin were significantly lower and higher, respectively, than in healthy dogs. In addition, these samples were characterised by a more complex protein pattern indicating mixed glomerular (protein bands ≥65 kDa) and tubular (protein bands <65 kDa) proteinuria. Urine spectra acquired by NMR allowed the identification of 86 metabolites in healthy dogs, belonging to 49 different pathways mainly involved in amino acid metabolism, purine and aminoacyl-tRNA biosynthesis or tricarboxylic acid cycle. Seventeen metabolites showed significantly different concentrations when comparing healthy and CKD dogs. In particular, carnosine, trigonelline, and cis-aconitate, might be suggested as putative biomarkers of CKD in dogs. SIGNIFICANCE: Urine is an ideal biological sample, however few proteomics and metabolomics studies investigated this fluid in dogs and in the context of CKD (chronic kidney disease). In this research, applying a multi-omics approach, new insights were gained regarding the molecular changes triggered by this disease in canine urinary proteome and metabolome. In particular, the involvement of the tubular component was highlighted, suggesting uromodulin, trigonelline and carnosine as possible biomarkers of CKD in dogs.

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

The metabolic syndrome is a multifactorial disease developed due to accumulation and chronification of several risk factors associated with disrupted metabolism. The early detection of the biomarkers by NMR spectroscopy could be helpful to prevent multifactorial diseases. The exposure of each risk factor can be detected by traditional molecular markers but the current biomarkers have not been enough precise to detect the primary stages of disease. Thus, there is a need to obtain novel molecular markers of pre-disease stages. A promising source of new molecular markers are metabolomics standing out the research of biomarkers in NMR approaches. An increasing number of nutritionists integrate metabolomics into their study design, making nutrimetabolomics one of the most promising avenues for improving personalized nutrition. This review highlight the major five risk factors associated with metabolic syndrome and related diseases including carbohydrate dysfunction, dyslipidemia, oxidative stress, inflammation, and gut microbiota dysbiosis. Together, it is proposed a profile of metabolites of each risk factor obtained from NMR approaches to target them using personalized nutrition, which will improve the quality of life for these patients.

Urinary chemical fingerprint left behind by repeated NSAID administration: Discovery of putative biomarkers using artificial intelligence

Prediction and early detection of kidney damage induced by nonsteroidal anti-inflammatories (NSAIDs) would provide the best chances of maximizing the anti-inflammatory effects while minimizing the risk of kidney damage. Unfortunately, biomarkers for detecting NSAID-induced kidney damage in cats remain to be discovered. To identify potential urinary biomarkers for monitoring NSAID-based treatments, we applied an untargeted metabolomics approach to urine collected from cats treated repeatedly with meloxicam or saline for up to 17 days. Applying multivariate analysis, this study identified a panel of seven metabolites that discriminate meloxicam treated from saline treated cats. Combining artificial intelligence machine learning algorithms and an independent testing urinary metabolome data set from cats with meloxicam-induced kidney damage, a panel of metabolites was identified and validated. The panel of metabolites including tryptophan, tyrosine, taurine, threonic acid, pseudouridine, xylitol and lyxitol, successfully distinguish meloxicam-treated and saline-treated cats with up to 75–100% sensitivity and specificity. This panel of urinary metabolites may prove a useful and non-invasive diagnostic tool for monitoring potential NSAID induced kidney injury in feline patients and may act as the framework for identifying urine biomarkers of NSAID induced injury in other species.

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.

Tryptophan metabolism is differently regulated between large and small dogs

Companion dogs have recently been promoted as an animal model for the study of aging due to their similar disease profile to humans, the sophistication of health assessment and disease diagnosis, and the shared environments with their owners. In addition, dogs show an interesting life history trait pattern where smaller individuals are up to two-fold longer lived than their larger counterparts. While some of the mechanisms underlying this size and longevity trade-off are strongly suspected (i.e., growth hormone/IGF-I), there are likely a number of undiscovered mechanisms as well. Accordingly, we have completed a large-scale global metabolomic profiling of dogs encompassing a range of sizes and ages from three cities across the USA. We found a surprisingly strong location signal in the metabolome, stronger in fact than any signal related to age, breed, or sex. However, after controlling for the effects of location, tryptophan metabolism emerged as significantly associated with weight of the dogs, with small dogs having significantly higher levels of tryptophan pathway metabolites. Overall, our results point toward novel, testable hypotheses about the underlying physiological mechanisms that influence size and longevity in the companion dog and suggest that dogs may be useful in sorting out the complexities of the tryptophan metabolic network.

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.

Indication of metabolic inflexibility to food intake in spontaneously overweight Labrador Retriever dogs

Background

Obesity in dogs is an increasing problem associated with morbidity, shortened life span and poor life quality. Overweight dogs exhibit postprandial hyperlipidaemia, highlighting the need to identify potential dysregulations in lipid metabolism. This study investigated metabolites related to lipid metabolism (i.e. acylcarnitines and taurine) and phospholipids in a feed-challenge test and aimed to identify metabolic variations in spontaneously overweight dogs. Twenty-eight healthy male Labrador Retriever dogs 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 (14–17 h), fasting blood samples were collected and dogs were fed a high-fat meal followed by postprandial blood sample collection hourly for 4 h. Liquid chromatography-time of flight mass spectrometry (LC-TOFMS) was used to identify plasma metabolites and phospholipids. Multivariate models, mixed model repeated measures and linear regression analyses were used for data interpretation.

Results

In all dogs, propionylcarnitine, stearoylcarnitine and nine phospholipids increased in response to food intake, while vaccenylcarnitine decreased (P ≤ 0.005 for all). Overall, carnitine and acetylcarnitine signal areas in the feed-challenge test were lower in overweight dogs (P ≤ 0.004). Notably, fasting plasma acetylcarnitine was lower in overweight dogs than in lean dogs (P = 0.001) and it did not change in response to feeding. The latter finding was in contrast to the decreased acetylcarnitine signal area found in lean dogs at one hour postprandially (P < 0.0001). One fasting phosphatidylcholine (PCaa C38:4) was higher in prominently overweight dogs (BCS > 6) than in lean dogs (P < 0.05).

Conclusions

Plasma carnitine status was overall lower in spontaneously overweight dogs than in lean dogs in this cohort of healthy Labrador Retriever dogs, indicating a potential carnitine insufficiency in the overweight group. The acetylcarnitine response in overweight dogs indicated decreased fatty acid oxidation at fasting and metabolic inflexibility to food intake. Further studies on metabolic inflexibility and its potential role in the metabolism of overweight dogs are warranted.

Electronic supplementary material

The online version of this article (10.1186/s12917-019-1845-5) contains supplementary material, which is available to authorized users.

Plasma metabolomics reveals lower carnitine concentrations in overweight Labrador Retriever dogs

Background

The prevalence of overweight is increasing in dogs, but the metabolic events related to this condition are still poorly understood. The purpose of the study was to investigate the postprandial response of plasma metabolites using a meal-challenge test and to identify metabolic variations related to spontaneous overweightness in privately owned dogs.

Results

Twenty-eight healthy male intact Labrador Retriever dogs 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 an overnight fast (14–17 h), blood samples were collected and dogs were thereafter fed a high-fat meal. Postprandial blood samples were collected hourly four times. Plasma metabolites were identified by nuclear magnetic resonance. Postprandial metabolomes differed from the fasting metabolome in multivariate discriminant analysis (PLS-DA: Q²Y = 0.31–0.63, cross-validated ANOVA: P ≤ 0.00014) Eleven metabolites, all amino acids, contributed to the separations. Carnitine was identified as a metabolite related to overweight (stepwise logistic regression analysis P ≤ 0.03) and overweight dogs had overall lower carnitine response (mixed model repeated measures analysis P = 0.005) than lean dogs. Notably, mean fasting carnitine concentration in overweight dogs (9.4 ± 4.2 µM) was close to a proposed reference limit for carnitine insufficiency.

Conclusions

A postprandial amino acid response was detected but no time-dependent variations with regards to body condition groups were found. Lower carnitine concentrations were found in overweight compared to lean dogs. The latter finding could indicate a carnitine insufficiency related to spontaneous adiposity and altered lipid metabolism in overweight dogs in this cohort of otherwise healthy Labrador Retrievers.

Electronic supplementary material

The online version of this article (10.1186/s13028-019-0446-4) contains supplementary material, which is available to authorized users.

Untargeted metabolomic analysis in non-fasted diabetic dogs by UHPLC-HRMS

INTRODUCTION

We recently identified variances in serum metabolomic profiles between fasted diabetic and healthy dogs, some having similarities to those identified in human type 1 diabetes.

OBJECTIVES

Compare untargeted metabolomic profiles in the non-fasted state.

METHODS

Serum from non-fasted diabetic (n = 6) and healthy control (n = 6) dogs were analyzed by liquid chromatography-high resolution mass spectrometry.

RESULTS

Clear clustering of metabolites between groups were observed, with multiple perturbations identified that were similar to those previously observed in fasted diabetic dogs.

CONCLUSION

These findings further support the development of targeted assays capable of detecting metabolites that may be useful as biomarkers of canine diabetes.

A Comparative Study of Serum Biochemistry, Metabolome and Microbiome Parameters of Clinically Healthy, Normal Weight, Overweight, and Obese Companion Dogs

The aim of this study was to compare fecal microbiome, plasma, fecal and urine metabolomes, and serum biochemistry of adult companion dogs according to body condition scores. Blood, serum/plasma, urine, and fecal samples were collected from 66 clinically healthy, adult companion dogs of either normal weight (NW), overweight (OW), or obese dogs (OB). analyses included fecal microbiome analyses via 16S ribosomal RNA gene amplicon; sequencing, nontargeted plasma, fecal, and urine metabolomics using liquid chromatography/gas chromatography-mass; spectrometry, and serum biochemistry for each dog. Few significant differences in serum biochemistry and fecal microbiome Operational Taxonomic Unit (OTU) were found between weight groups and there was high OTU variation between individual dogs. NW dogs had higher relative abundance of the genus Eubacterium (log-fold change 4.3, adjusted P value = .003) and lower relative abundance of the family Bifidobacteriaceae (log-fold change -3.6, adjusted P value = .02) compared to OB dogs. The microbiome of NW dogs had higher OTU richness compared with OB dogs. Metabolome analysis showed 185 plasma, 37 fecal, and 45 urine metabolites that significantly differed between NW and OW or OB dogs. There were notable significant differences in relative abundance of several plasma phospholipid moieties and fecal volatile fatty acids between weight phenotypes. The combinations of host and gut microbiota and metabolic shifts suggest a pattern that could help detection of early metabolic changes in overweight dogs before the development of obesity related disease. The results of this study support the need for continued investigation into sensitive measures of metabolic aberrancies in overweight dogs.