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Pharmacometabolomics with a combination of PLS-DA and random forest algorithm analyses reveal meloxicam alters feline
Liam E Broughton-Neiswanger1, Sol M Rivera-Velez2, Martin A Suarez3
1Program in Individualized Medicine, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA.
Abstract:
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.
Insights
Repeated meloxicam use in cats alters plasma metabolites, including organic acids and amino acids, within days. Seventeen specific molecules identified may help predict and manage adverse effects, enabling personalized treatment for feline health.
Area of Science:
- Veterinary Pharmacology
- Metabolomics
- Biomarker Discovery
Background:
- Repeated meloxicam administration in cats can cause organ damage, limiting its use.
- Identifying predictive molecules for meloxicam's adverse effects is crucial for safe and effective feline treatment.
- Individualized monitoring can maximize therapeutic benefits while minimizing risks.
Purpose of the Study:
- To investigate alterations in the feline plasma metabolome following repeated meloxicam administration.
- To identify specific plasma metabolites that can serve as biomarkers for monitoring meloxicam treatment in cats.
- To explore potential mechanisms underlying non-steroidal anti-inflammatory drug (NSAID)-induced side effects.
Main Methods:
- An untargeted metabolomics approach was applied to plasma samples from purpose-bred cats treated with meloxicam or saline.
- Machine-learning algorithms, including partial least squares discriminant analysis (PLS-DA) and random forest (RF), were used for biomarker refinement.
- Statistical analysis included 74 identified metabolites from samples collected at various time points.
Main Results:
- Repeated meloxicam administration significantly altered plasma metabolites, including nonvolatile organic acids, aromatic amino acids, monosaccharides, and inorganic compounds.
- Metabolomic changes were detectable as early as four days after initiating meloxicam treatment.
- Seventeen distinct plasma molecules were identified as capable of differentiating meloxicam-treated cats from controls.
Conclusions:
- Meloxicam treatment induces significant and early changes in the plasma metabolome of cats.
- Identified plasma metabolites show potential as biomarkers for monitoring meloxicam therapy and predicting adverse events.
- These findings may contribute to understanding NSAID-induced toxicity and developing personalized treatment strategies for cats.
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