Alteration of the Canine Metabolome After a 3-Week Supplementation of Cannabidiol (CBD) Containing Treats: An Exploratory Study of Healthy Animals

Despite the increased interest and widespread use of cannabidiol (CBD) in humans and companion animals, much remains to be learned about its effects on health and physiology. Metabolomics is a useful tool to evaluate changes in the health status of animals and to analyze metabolic alterations caused by diet, disease, or other factors. Thus, the purpose of this investigation was to evaluate the impact of CBD supplementation on the canine plasma metabolome. Sixteen dogs (18.2 ± 3.4 kg BW) were utilized in a completely randomized design with treatments consisting of control and 4.5 mg CBD/kg BW/d. After 21 d of treatment, blood was collected ~2 h after treat consumption. Plasma collected from samples was analyzed using CIL/LC-MS-based untargeted metabolomics to analyze amine/phenol- and carbonyl-containing metabolites. Metabolites that differed — fold change (FC) ≥ 1.2 or ≤ 0.83 and false discovery ratio (FDR) ≤ 0.05 — between the two treatments were identified using a volcano plot. Biomarker analysis based on receiver operating characteristic (ROC) curves was performed to identify biomarker candidates (area under ROC ≥ 0.90) of the effects of CBD supplementation. Volcano plot analysis revealed that 32 amine/phenol-containing metabolites and five carbonyl-containing metabolites were differentially altered (FC ≥ 1.2 or ≤ 0.83, FDR ≤ 0.05) by CBD; these metabolites are involved in the metabolism of amino acids, glucose, vitamins, nucleotides, and hydroxycinnamic acid derivatives. Biomarker analysis identified 24 amine/phenol-containing metabolites and 1 carbonyl-containing metabolite as candidate biomarkers of the effects of CBD (area under ROC ≥ 0.90; P < 0.01). Results of this study indicate that 3 weeks of 4.5 mg CBD/kg BW/d supplementation altered the canine metabolome. Additional work is warranted to investigate the physiological relevance of these changes.

Canine Carboxyl- and Hydroxyl-Containing Metabolites Altered after a Three-Week Supplementation of Cannabidiol (CBD)-Containing Treats in an Exploratory Study

Untargeted metabolomics has been increasingly used to evaluate metabolic alterations caused by diet, disease, or other factors in animals. The purpose of this exploratory study was to evaluate the impact of Cannabidiol (CBD) supplementation on the canine carboxyl and hydroxyl submetabolomes. Sixteen dogs (18.2 ± 3.4 kg BW) were utilized in a completely randomized design with treatments consisting of control and 4 mg CBD/kg BW/d. After 21 d of treatment, blood was collected approximately 2 h after morning treat consumption. Plasma collected from samples was analyzed using CIL/LC-MS-based untargeted metabolomics to analyze carboxyl- and hydroxyl-containing metabolites. Metabolites that differed (fold change (FC) ≥ 1.2 or ≤ 0.83 and FDR ≤ 0.05) between the two treatments were identified using a volcano plot. Biomarker analysis based on Receiver Operating Characteristic (ROC) curves was performed to identify biomarker candidates (area under ROC ≥ 0.90) of the effects of CBD supplementation. Volcano plot analysis revealed that 42 carboxyl-containing metabolites and 32 hydroxyl-containing metabolites were differentially altered (FC ≥ 1.2 or ≤ 0.83, FDR ≤ 0.05) by CBD; these metabolites were involved in the metabolism of lipids, amino acids, carbohydrates, and more. Biomarker analysis identified 23 carboxyl-containing metabolites and 15 hydroxyl-containing metabolites as candidate biomarkers of the effects of CBD (area under ROC ≥ 0.90; P<0.01). Results of this study indicate that 4 mg CBD/kg BW/d supplemented for 3-weeks altered the canine carboxyl and hydroxyl submetabolomes and may indicate potential mechanisms by which CBD exerts some of its effects. Future work is warranted to investigate these potential mechanisms.

Plasma Carboxyl-Metabolome Is Associated with Average Daily Gain Divergence in Beef Steers

We applied an untargeted metabolomics technique to analyze the plasma carboxyl-metabolome of beef steers with divergent average daily gain (ADG). Forty-eight newly weaned Angus crossbred beef steers were fed the same total mixed ration ad libitum for 42 days. On day 42, the steers were divided into two groups of lowest (LF: n = 8) and highest ADG (HF: n = 8), and blood samples were obtained from the two groups for plasma preparation. Relative quantification of carboxylic-acid-containing metabolites in the plasma samples was determined using a metabolomics technique based on chemical isotope labeling liquid chromatography mass spectrometry. Metabolites that differed (fold change (FC) ≥ 1.2 or ≤ 0.83 and FDR ≤ 0.05) between LF and HF were identified using a volcano plot. Metabolite set enrichment analysis (MSEA) of the differential metabolites was done to determine the metabolic pathways or enzymes that were potentially altered. In total, 328 metabolites were identified. Volcano plot analysis revealed 43 differentially abundant metabolites; several short chain fatty acids and ketone bodies had greater abundance in HF steers. Conversely, several long chain fatty acids were greater in LF steers. Five enzymatic pathways, such as fatty acyl CoA elongation and fatty-acid CoA ligase were altered based on MSEA. This study demonstrated that beef steers with divergent ADG had altered plasma carboxyl-metabolome, which is possibly caused by altered abundances and/or activities of enzymes involved in fatty acid oxidation and biosynthesis in the liver.

VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots

Comparative genome- and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a user-defined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/Shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots (https://huygens.science.uva.nl/VolcaNoseR). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome- and proteome-wide datasets.

Plasma Proteomic Profile Associated with Platelet Dysfunction after Trauma

Background. Coagulopathic bleeding is a major cause of mortality after trauma, and platelet dysfunction contributes to this problem. The causes of platelet dysfunction are unknown, but a great deal can be learned from the plasma environment after injury, which may directly alter platelet function. Studying the changes in plasma using untargeted proteomics would provide unbiased insight into the presence of possible inhibitors of platelet function, changes to their major ligands, or other previously unknown pathways affecting platelet function. Methods. Citrated blood was collected from severely injured trauma patients at the time of their arrival to the Emergency Department. Platelet testing was performed immediately, and plasma was frozen for analysis. Samples were collected from 110 patients, and a subset of 24 patients was identified by a preserved (n=12) or severely impaired (n=12) platelet aggregation response to five different agonists (adenosine diphosphate, arachidonic acid, collagen, thrombin receptor-activating peptide, and ristocetin). Untargeted proteomics was performed by nanoflow liquid chromatography tandem mass spectrometry to determine the plasma protein profile associated with platelet dysfunction. Protein abundance levels for each patient were normalized to total protein concentration to control for hemodilution by crystalloid fluid infusion prior to blood draw. Results were compared by Wilcoxon rank-sum test, and a two-tailed p value less than 0.05 was considered significant. No adjustment was made for multiple comparisons, as the risk of a type II error was felt to outweigh that of a type I error in this exploratory analysis. Results. Patients with platelet dysfunction were more severely injured (median Injury Severity Score 29.5 vs. 13.5, p=0.002) but otherwise demographically similar to those with retained platelet function. Of 232 proteins identified, twelve were significantly different in the low- vs. high-platelet function groups: gelsolin (median peak intensity 9.70E+6 vs. 1.48 E+7, p=0.002), transketolase (2.86E+4 vs. 9.36E+3, p=0.003), protein S100-A8 (4.60E+4 vs. 2.64E+4, p=0.006) and -A9 (5.83E+4 vs. 4.07E+4, p=0.012), histone H4 (5.72E+4 vs. 8.47E+6, p=0.007), histidine-rich glycoprotein (HRG) (5.00E+6 vs. 8.30E+6, p=0.008), factor XIII B chain (1.09E+6 vs. 1.61E+6, p=0.020), apolipoprotein A-IV (2.30E+7 vs. 3.28E+7, p=0.024), alpha-enolase (1.02E+5 vs. 4.15E+4, p=0.024), heat shock protein 90-alpha (1.41E+4 vs. 4.08E+3, p=0.045), alpha-2-HS-glycoprotein (2.83E+7 vs. 3.68E+7, p=0.045), and neutrophil gelatinase-associated lipocalin (3.44E+4 vs. 1.36E+4, p=0.045). These results are summarized in the figure, which shows one group of proteins that decreased in abundance (on the left side of the volcano plot) and another that increased (on the right side) in the patients with low platelet function. The twelve proteins that changed the most fall into several categories related to platelet function. Low gelsolin and high histone levels are each associated with microvascular obstruction by release of intracellular material that accumulates in small vessels and activates platelets. Low HRG and high damage-associated molecular pattern (DAMP) protein levels are consistent with massive innate immune activation, which can impair platelet function in many ways. Conclusion. This study provides an unbiased description of the change in proteomic profile associated with platelet dysfunction after trauma and identifies twelve proteins with the most profound changes. The pathways involving these proteins are salient targets for immediate investigation to better understand platelet dysfunction after trauma and identify targets for intervention. Figure Legend. Volcano plot depicting fold-change and statistical significance of individual proteins in patients with low vs. high platelet function. Dotted horizontal line represents p = 0.05. Twelve proteins showed a statistically significant p value. Figure Disclosures No relevant conflicts of interest to declare.