Correlation between metabolomic profile constituents and feline pancreatic lipase immunoreactivity

Abstract

Abstract Background Feline pancreatic lipase immunoreactivity (fPLI) is commonly used to diagnose pancreatitis in cats (FP). Untargeted metabolomics has been extensively applied in human and veterinary medicine, but no metabolomic studies regarding FP have been conducted. Objectives To identify metabolites significantly associated with increased fPLI. Animals Forty‐nine client‐owned cats: 11 clinically healthy and 38 with various clinical conditions. Methods Analytical cross‐sectional study with convenience sampling. A panel of 630 metabolites belonging to 26 biochemical classes was quantified in plasma using a commercial metabolomic assay. The correlation between plasma metabolite concentrations and serum fPLI was evaluated using Spearman's rank correlation coefficient (Rs) with Bonferroni correction. Multivariable analysis then was performed to control for glomerular filtration rate, liver damage, and blood glucose concentration. The accuracy of selected metabolites in discriminating between cats with normal (≤3.5 μg/L) and increased (>5.3 μg/L) fPLI was estimated using the area under the receiver operating characteristic curve (AUROC). Results Four hundred and seven of 630 metabolites (64.6%) were quantified in all cats. When controlled for potential confounders only 3 sphingolipids were significantly positively correlated with fPLI: 2 cerebrosides: HexCer(d18:1/24:0); (Rs = .56), and HexCer(d18:1/24:1); (Rs = .58) and 1 sphingomyelin: SM C18:0 (Rs = .55). Their AUROCs in identifying cats with increased fPLI were 82% (95% confidence interval [CI 95%], 70%‐94%), 84% (CI 95%, 72%‐96%), and 78% (CI 95%, 65%‐92%), respectively. Conclusions and Clinical Importance Selected sphingolipids are moderately positively correlated with fPLI and appear to have fair to moderate diagnostic accuracy in discriminating between cats with normal and increased fPLI.

Keywords

• cerebrosides
• feline pancreatitis
• fPLI
• sphingolipids
• sphingomyelins
• untargeted metabolomics