Search

Abstract Background Metabolic profiles differ between healthy humans and those with inflammatory bowel disease. Few studies have examined metabolic profiles in dogs with chronic enteropathy (CE). Hypothesis Serum metabolic profiles of dogs with CE are significantly different from those of healthy dogs. Animals Fifty‐five dogs with CE and 204 healthy controls. Methods A cross‐sectional study. The serum concentrations of 99 metabolites measured using a canine‐specific proton nuclear magnetic resonance spectroscopy platform were studied. A 2‐sample unpaired t‐test was used to compare the 2 study samples. The threshold for significance was set at P

Abstract Hepatopathies can cause major metabolic abnormalities in humans and animals. This study examined differences in serum metabolomic parameters and patterns in left-over serum samples from dogs with either congenital portosystemic shunts (cPSS, n = 24) or high serum liver enzyme activities (HLEA, n = 25) compared to control dogs (n = 64). A validated targeted proton nuclear magnetic resonance spectroscopy platform was used to assess 123 parameters. Principal component analysis of the serum metabolome demonstrated distinct clustering among individuals in each group, with the cluster of HLEA being broader compared to the other groups, presumably due to the wider spectrum of hepatic diseases represented in these samples. While younger and older adult control dogs had very similar metabolomic patterns and clusters, there were changes in many metabolites in the hepatopathy groups. Higher phenylalanine and tyrosine concentrations, lower branched-chained amino acids (BCAAs) concentrations, and altered fatty acid parameters were seen in cPSS dogs compared to controls. In contrast, dogs with HLEA had increased concentrations of BCAAs, phenylalanine, and various lipoproteins. Machine learning based solely on the metabolomics data showed excellent group classification, potentially identifying a novel tool to differentiate hepatopathies. The observed changes in metabolic parameters could provide invaluable insight into the pathophysiology, diagnosis, and prognosis of hepatopathies.

Abstract Background Metabolic profiling identifies seasonal variance of serum metabolites in humans. Despite the presence of seasonal disease patterns, no studies have assessed whether serum metabolites vary seasonally in dogs. Hypothesis There is seasonal variation in the serum metabolite profiles of healthy dogs. Animals Eighteen healthy, client‐owned dogs. Methods A prospective cohort study. Serum metabolomic profiles were assessed monthly in 18 healthy dogs over a 12‐month period. Metabolic profiling was conducted using a canine‐specific proton nuclear magnetic resonance spectroscopy platform, and the effects of seasonality were studied for 98 metabolites using a cosinor model. Seasonal component was calculated, which describes the seasonal variation of each metabolite. Results We found no evidence of seasonal variation in 93 of 98 metabolites. Six metabolites had statistically significant seasonal variance, including cholesterol (mean 249 mg/dL [6.47 mmol/L] with a seasonal component amplitude of 9 mg/dL [0.23 mmol/L]; 95% confidence interval [CI] 6‐13 mg/dL [0.14‐0.33 mmol/L], P

IntroductionReproduction causes major hormonal and physiological changes to the female body. However, the metabolic changes occurring during canine reproduction are scarcely studied.MethodsIn this cross-sectional study, we assessed the metabolic effects of canine reproductive status using a 1H NMR metabolomics platform optimized and validated for canine use. The study population consisted of a total of 837 healthy, intact female dogs in breeding age, of which 663 dogs were in anestrus, 78 in heat, 43 were pseudopregnant, 15 were pregnant, and 38 were lactating. The differences in metabolite profiles between these states were studied by the Kruskal-Wallis test with post-hoc tests performed using the Dunn's test, and visualized by box plots and a heatmap. The ability of the metabolite profile to differentiate pregnant dogs from non-pregnant ones was assessed by creating a multivariate Firth logistic regression model using forward stepwise selection.ResultsLactation, pregnancy and heat all were associated with distinct metabolic changes; pregnancy caused major changes in the concentrations of glycoprotein acetyls, albumin and creatinine, and smaller changes in several lipids, citrate, glutamine, and alanine. Pseudopregnancy, on the other hand, metabolically largely resembled anestrus. Lactation caused major changes in amino acid concentrations and smaller changes in several lipids, albumin, citrate, creatinine, and glycoprotein acetyls. Heat, referring to proestrus and estrus, affected cholesterol and LDL metabolism, and increased HDL particle size. Albumin and glycoprotein acetyls were the metabolites included in the final multivariate model for pregnancy detection, and could differentiate pregnant dogs from non-pregnant ones with excellent sensitivity and specificity.DiscussionThese results increase our understanding of the metabolic consequences of canine reproduction, with the possibility of improving maternal health and ensuring reproductive success. The identified metabolites could be used for confirming canine pregnancy.

Consumption of medium-chain triglycerides (MCT) has been shown to improve seizure control, reduce behavioural comorbidities and improve cognitive function in epileptic dogs. However, the exact metabolic pathways affected by dietary MCT remain poorly understood. In this study, we aimed to identify changes in the metabolome and neurotransmitters levels relevant to epilepsy and behavioural comorbidities associated with the consuming of an MCT supplement (MCT-DS) in dogs with idiopathic epilepsy (IE). Metabolic alterations induced by a commercial MCT-DS in a population of 28 dogs with IE were evaluated in a 6-month multi-centre, prospective, randomised, double-blinded, controlled cross-over trial design. A metabolic energy requirement-based amount of 9% MCT or control oil was supplemented to the dogs' stable base diet for 3 months, followed by the alternative oil for another 3 months. A validated, quantitative nuclear magnetic resonance (NMR) spectroscopy platform was applied to pre- and postprandially collected serum samples to compare the metabolic profile between both DS and baseline. Furthermore, alterations in urinary neurotransmitter levels were explored. Five dogs (30%) had an overall reduction in seizure frequency of ≥50%, and were classified as MCT-responders, while 23 dogs showed a ≤50% reduction, and were defined as MCT non-responders. Amino-acid metabolism was significantly influenced by MCT consumption compared to the control oil. While the serum concentrations of total fatty acids appeared similar during both supplements, the relative concentrations of individual fatty acids differed. During MCT supplementation, the concentrations of polyunsaturated fatty acids and arachidonic acid were significantly higher than under the control oil. β-Hydroxybutyric acid levels were significantly higher under MCT supplementation. In total, four out of nine neurotransmitters were significantly altered: a significantly increased γ-aminobutyric acid (GABA) concentration was detected during the MCT-phase accompanied by a significant shift of the GABA-glutamate balance. MCT-Responders had significantly lowered urinary concentrations of histamine, glutamate, and serotonin under MCT consumption. In conclusion, these novel data highlight metabolic changes in lipid, amino-acid and ketone metabolism due to MCT supplementation. Understanding the metabolic response to MCT provides new avenues to develop better nutritional management with improved anti-seizure and neuroprotective effects for dogs with epilepsy, and other behavioural disorders.

Abstract Background The kidneys have many essential metabolic functions, and metabolic disturbances during decreased renal function have not been studied extensively. Objectives To identify metabolic changes in blood samples with increased serum creatinine concentration, indicating decreased glomerular filtration. Animals Clinical samples analyzed using a nuclear magnetic resonance (NMR) based metabolomics platform. The case group consisted of 23 samples with serum creatinine concentration >125 μmol/L, and the control group of 873 samples with serum creatinine concentration within the reference interval. Methods Biomarker association with increased serum creatinine concentration was evaluated utilizing 3 statistical approaches: Wilcoxon rank‐sum test, logistic regression analysis (false discovery rate (FDR)‐corrected P‐values), and random forest classification. Medians of the biomarkers were compared to reference intervals. A heatmap and box plots were used to represent the differences. Results All 3 statistical approaches identified similar analytes associated with increased serum creatinine concentrations. The percentages of citrate, tyrosine, branched‐chain amino acids, valine, leucine, albumin, linoleic acid and the ratio of phenylalanine to tyrosine differed significantly using all statistical approaches, acetate differed using the Wilcoxon test and random forest, docosapentaenoic acid percentage only using logistic regression (P

As an individual's metabolism reflects health and disease states well, metabolomics holds a vast potential in biomedical applications. However, normal physiological factors, such as age, can also influence metabolism, challenging the establishment of disease-specific metabolic aberrations. Here, we examined how physiological and diet-related factors drive variance in the metabolism of healthy pet dogs. We analysed 2068 serum samples using a canine nuclear magnetic resonance (NMR) spectroscopy-based metabolomics platform. With generalized linear models, we discovered that age, breed, sex, sterilization, diet type and fasting time significantly affected the canine metabolite profiles. Especially, breed and age caused considerable variation in the metabolite concentrations, and breeds with very different body conformations systematically differed in several lipid measurands. Our results enhance the understanding how normal physiological factors influence canine metabolism, aid accurate interpretation of the NMR results, and suggest the NMR platform might be applied in identifying aberrations in nutrient absorption and metabolism.

The adrenal glands play a major role in metabolic processes, and both excess and insufficient serum cortisol concentrations can lead to serious metabolic consequences. Hyper- and hypoadrenocorticism represent a diagnostic and therapeutic challenge. Serum samples from dogs with untreated hyperadrenocorticism (n = 27), hyperadrenocorticism undergoing treatment (n = 28), as well as with untreated (n = 35) and treated hypoadrenocorticism (n = 23) were analyzed and compared to apparently healthy dogs (n = 40). A validated targeted proton nuclear magnetic resonance (1H NMR) platform was used to quantify 123 parameters. Principal component analysis separated the untreated endocrinopathies. The serum samples of dogs with untreated endocrinopathies showed various metabolic abnormalities with often contrasting results particularly in serum concentrations of fatty acids, and high- and low-density lipoproteins and their constituents, which were predominantly increased in hyperadrenocorticism and decreased in hypoadrenocorticism, while amino acid concentrations changed in various directions. Many observed serum metabolic abnormalities tended to normalize with medical treatment, but normalization was incomplete when compared to levels in apparently healthy dogs. Application of machine learning models based on the metabolomics data showed good classification, with misclassifications primarily observed in treated groups. Characterization of metabolic changes enhances our understanding of these endocrinopathies. Further assessment of the recognized incomplete reversal of metabolic alterations during medical treatment may improve disease management.

[This corrects the article DOI: 10.1371/journal.pgen.1007361.].

Knowledge on the genetic epidemiology of disorders in the dog population has implications for both veterinary medicine and sustainable breeding. Limited data on frequencies of genetic disease variants across breeds exists, and the disease heritage of mixed breed dogs remains poorly explored to date. Advances in genetic screening technologies now enable comprehensive investigations of the canine disease heritage, and generate health-related big data that can be turned into action. We pursued population screening of genetic variants implicated in Mendelian disorders in the largest canine study sample examined to date by examining over 83,000 mixed breed and 18,000 purebred dogs representing 330 breeds for 152 known variants using a custom-designed beadchip microarray. We further announce the creation of MyBreedData (www.mybreeddata.com), an online updated inherited disorder prevalence resource with its foundation in the generated data. We identified the most prevalent, and rare, disease susceptibility variants across the general dog population while providing the first extensive snapshot of the mixed breed disease heritage. Approximately two in five dogs carried at least one copy of a tested disease variant. Most disease variants are shared by both mixed breeds and purebreds, while breed- or line-specificity of others is strongly suggested. Mixed breed dogs were more likely to carry a common recessive disease, whereas purebreds were more likely to be genetically affected with one, providing DNA-based evidence for hybrid vigor. We discovered genetic presence of 22 disease variants in at least one additional breed in which they were previously undescribed. Some mutations likely manifest similarly independently of breed background; however, we emphasize the need for follow up investigations in each case and provide a suggested validation protocol for broader consideration. In conclusion, our study provides unique insight into genetic epidemiology of canine disease risk variants, and their relevance for veterinary medicine, breeding programs and animal welfare.