OBJECTIVE To evaluate the plasma disposition of mycophenolic acid (MPA) and its derivatives MPA glucuronide and MPA glucoside after twice-daily infusions of mycophenolate mofetil (MMF) in healthy cats for 3 days and to assess the effect of MMF administration on peripheral blood mononuclear cell (PBMC) counts and CD4+-to-CD8+ ratios. ANIMALS 5 healthy adult cats. PROCEDURES MMF was administered to each cat (10 mg/kg, IV, q 12 h for 3 days). Each dose of MMF was diluted with 5% dextrose in water and then administered over a 2-hour period with a syringe pump. Blood samples were collected for analysis. A chromatographic method was used to quantitate concentrations of MPA and its metabolites. Effects of MMF on PBMC counts and CD4+-to-CD8+ ratios were assessed by use of flow cytometry. RESULTS All cats biotransformed MMF into MPA. The MPA area under the plasma concentration–time curve from 0 to 14 hours ranged from 14.6 to 37.6 mg·h/L and from 14.4 to 22.3 mg·h/L after the first and last infusion, respectively. Total number of PBMCs was reduced in 4 of 5 cats (mean ± SD reduction, 25.9 ± 15.8% and 26.7 ± 19.3%) at 24 and 48 hours after the end of the first infusion of MMF, respectively. CONCLUSIONS AND CLINICAL RELEVANCE Plasma disposition of MPA after twice-daily IV infusions for 3 days was variable in all cats. There were no remarkable changes in PBMC counts and CD4+-to-CD8+ ratios.

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 NSAIDinduced 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.

Non-steroidal anti-inflammatories (NSAIDs), such as meloxicam, are the mainstay for treating painful and inflammatory conditions in animals and humans; however, the repeated administration of NSAIDs can cause adverse effects, limiting the long-term administration of these drugs to some patients. The primary aim of this study was to determine the effects of repeated meloxicam administration on the feline plasma and urine lipidome. Cats (n = 12) were treated subcutaneously with either saline solution or 0.3 mg/kg body weight of meloxicam daily for up to 31 days. Plasma and urine lipidome were determined by LC-MS before the first treatment and at 4, 9 and 13 and 17 days after the first administration of meloxicam. The repeated administration of meloxicam altered the feline plasma and urine lipidome as demonstrated by multivariate statistical analysis. The intensities of 94 out of 195 plasma lipids were altered by the repeated administration of meloxicam to cats (p < 0.05). Furthermore, we identified 12 lipids in plasma and 10 lipids in urine that could serve as biomarker candidates for discriminating animals receiving NSAIDs from healthy controls. Expanding our understanding about the effects of NSAIDs in the body could lead to the discovery of mechanism(s) associated with intolerance to NSAIDs.

Repeated administration of meloxicam can cause kidney damage in cats by mechanisms that remain unclear. Metabolomics and lipidomics are powerful, noninvasive approaches used to investigate tissue response to drug exposure. Thus, the objective of this study was to assess the effects of meloxicam on the feline kidney using untargeted metabolomics and lipidomics approaches. Female young‐adult purpose‐breed cats were allocated into the control (n = 4) and meloxicam (n = 4) groups. Cats in the control and meloxicam groups were treated daily with saline and meloxicam at 0.3 mg/kg subcutaneously for 17 days, respectively. Renal cortices and medullas were collected at the end of the treatment period. Random forest and metabolic pathway analyses were used to identify metabolites that discriminate meloxicam‐treated from saline‐treated cats and to identify disturbed metabolic pathways in renal tissue. Our results revealed that the repeated administration of meloxicam to cats altered the kidney metabolome and lipidome and suggest that at least 40 metabolic pathways were altered in the renal cortex and medulla. These metabolic pathways included lipid, amino acid, carbohydrate, nucleotide and energy metabolisms, and metabolism of cofactors and vitamins. This is the first study using a pharmacometabonomics approach for studying the molecular effects of meloxicam on feline kidneys.

Repeated administration of meloxicam to cats is often limited by the potential damage to multiple organ systems. Identifying molecules that predict the adverse effects of meloxicam would help to monitor and individualize its administration, maximizing meloxicam's beneficial effects. The objectives of this study were to (a) determine if the repeated administration of meloxicam to cats alters the plasma metabolome and (b) identify plasma metabolites that may serve to monitor during the administration of meloxicam in cats. Purpose bred young adult cats (n = 12) were treated with meloxicam at 0.3 mg/kg or saline subcutaneously once daily for up to 17 days. An untargeted metabolomics approach was applied to plasma samples collected prior to and at designated time points after meloxicam or saline administration. To refine the discovery of biomarkers, the machine‐learning algorithms, partial least squares discriminant analysis (PLS‐DA) and random forest (RF), were trained and validated using a separate unrelated group of meloxicam‐ and saline‐treated cats (n = 8). A total of 74 metabolites were included in the statistical analysis. Metabolomic analysis shows that the repeated administration of meloxicam alters multiple substances in plasma, including nonvolatile organic acids, aromatic amino acids, monosaccharides, and inorganic compounds as early as four days following administration of meloxicam. Seventeen plasma molecules were able to distinguish meloxicam‐treated from saline‐treated cats. The metabolomic changes discovered in this study may help to unveil unknown mechanisms of NSAID‐induced side effects. In addition, some metabolites could be valuable for individualizing the administration of meloxicam to cats to mitigate adverse effects.