Veterinary and Animal Health

Cats with chronic kidney disease (CKD) have trouble maintaining body weight due to muscle wasting. Betaine is known to protect the kidney from water imbalance and prebiotics can increase nutrient absorption and favorably modulate the gut microbiome. In this study, Hall and colleagues evaluated the combined effects of feeding betaine and prebiotics on body weight of both CKD and healthy cats¹.

All study animals were fed pre-trial food for 28 days then randomly assigned to control or test food for 8 weeks. After 8 weeks each group crossed over to the alternative food for 8 weeks. At the end of each feeding period biomarkers of kidney function were analyzed in plasma, urine, and fecal samples. Total body mass index was also measured. CKD cats that consumed the test food had significantly higher body weight than the control food group. Test food did not affect total body mass index of healthy cats.

Indole compounds produced by bacterial metabolism decreased in urine and increased in feces of CKD cats fed test food. Plasma concentrations were negatively correlated with the level of kidney function, indicating a potential benefit of consuming test food. Altogether, these results suggest that betaine and prebiotics may increase total body mass index of CKD cats by enhancing one-carbon metabolism.

Exocrine pancreatic insufficiency (EPI) is a digestive disease in dogs caused by insufficient secretion of digestive enzymes from the exocrine pancreas. This condition is treated with oral replacement exocrine pancreatic enzymes, but symptoms, especially diarrhea typically remain after treatment. To better understand underlying cause(s) of the phenomenon Barko and colleagues evaluated the global serum metabolomes of symptomatic EPI and healthy dogs².

Compared to controls, levels of fatty and amino acids were consistent with malnourishment and macronutrient deficiencies in EPI dogs. Alterations of gut microbes in EPI dogs indicated intestinal inflammation. Overall, this study helped to better characterize the metabolic underpinnings of symptomatic EPI, and further studies could determine whether metabolic perturbations are associated with pathophysiology of the disease, contribute to remaining symptoms in treated animals, or a combination of the two.

Exercise-induced hemolysis is caused by repeated muscle contractions from intense exercise leading to compressed capillaries and subsequent damage to and rupture of erythrocytes. Hemolysis is common in equine endurance racing, but few studies have studied exercise-induced hemolysis in horses using metabolomics.

In one study, Pakula and colleagues aimed to provide an in-depth characterization of the exercise-induced hemolysis in endurance horses to better understand this process and potentially prevent its consequences³. Plasma of 47 Arabian endurance horses was collected before and after running an 80, 100, or 120 km distance and analyzed for heme, bilirubin, and biliverdin. Each of these metabolites were significantly increased after the race, with an association between those parameters, average speed, and distance completed.

Hemolysis marker levels were highest in horses that were eliminated from the race for metabolic reasons in comparison to finishers. Overall, these findings draw a connection between hemolysis and exercise intensity in endurance horses and emphasize the importance of respecting horse limitations to avoid detrimental outcomes.

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats that mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Diagnosing and differentiating these conditions requires invasive procedures, including intestinal tissue biopsy. Studies in humans show that global metabolic changes accompany IBD, which may be useful for differentiating the IBD subtypes Crohn’s disease and ulcerative colitis. Such studies have not been performed in cats with CE. Here, Marsilio and colleagues hypothesized that metabolic perturbations in CE cats can distinguish IBD from SCL⁴.

36 cats were enrolled in the study, 14 healthy and 22 CE (11 with IBD and 11 with SCL). Untargeted metabolomics was performed on fecal samples collected from each study animal. Differences in the abundance of fecal metabolites between control and CE cats were evaluated using a Mann Whitney test. Differences between IBD and SCL subgroups were computed using Dunn’s test. Principal component analysis (PCA) and hierarchical clustering was performed, and Random Forest regression was used to evaluate how accurately metabolic differences classified disease subtypes.

Out of 856 metabolites detected 84 differed significantly between control and CE cats. PCA and hierarchical clustering indicated separation of controls from CE groups, but no visible separation between cats with IBD and SCL (Figure 1A, B). For controls vs. CE cats, random forest classification revealed a group prediction with 80% accuracy, while group prediction between IBD and SCL was 53%. A random forest importance plot showed 7 metabolites to be key in classifying control from CE cats: sphingomyelin (d18:1/14:0, d16:1/16:0), 3-(3-hydroxyphenyl)propionate, beta-cryptoxanthin, myristoleate (14:1n5), N1-methyl-4-pyridone-3-carboxamide, 2-oxindole-3-acetate, and 5-hydroxyindoleacetate (Figure 1C). Overall, these data provide a first time look at metabolic disturbances that occur in cats with CE, which resemble patterns found in humans and other animal models. Follow-up studies of the mucosal and serum metabolome of cats with CE could further elucidate the origin of metabolic perturbations and allow further insight into pathogenesis.

Figure 1. Multivariate analysis of the fecal microbiome of healthy cats and cats with chronic enterpathy. (a) Heat map showing metabolites that were significantly different between healthy cats and cats with inflammatory bowel disease (IBD) and alimentary small cell lymphoma (SCL). Groups are represented by the colored bars at the top of the figure as red (healthy, n=14), green (IBD, n=11), and blue (SCL, n=11). Clusters can be identified between healthy cats and cats with chronic enteropathy (CE) but not between the disease subgroups IBD and SCL. (b) PCA score blots of metabolites in feces from healthy cats (green) and cats with chronic enteropathy (CE, red). (c) Random Forest importance plot.