DI/LC-MS/MS-Based Metabolic Profiling for Identification of Early Predictive Serum Biomarkers of Metritis in Transition Dairy Cows

J Agric Food Chem. 2017 Sep 27;65(38):8510-8521. doi: 10.1021/acs.jafc.7b02000. Epub 2017 Sep 18.

Abstract

The objectives of this study were to evaluate alterations of metabolites in the blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected from both healthy and metritic cows during -8, -4, disease diagnosis, +4, and +8 wks relative to parturition. Results indicated that cows with metritis experienced altered concentrations of serum amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the entire experimental period. Moreover, two sets of predictive biomarker models and one set of diagnostic biomarker models for metritis were developed, and all of them showed high sensitivity and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for metritis in transition dairy cows.

Keywords: amino acids; biomarkers; dairy cow; metabolomics; metritis; sphingolipids.

Publication types

  • Evaluation Study

MeSH terms

  • Animals
  • Biomarkers / blood*
  • Cattle
  • Cattle Diseases / blood*
  • Cattle Diseases / diagnosis
  • Chromatography, High Pressure Liquid / methods*
  • Female
  • Metabolomics
  • Tandem Mass Spectrometry / methods*
  • Uterine Diseases / blood*
  • Uterine Diseases / diagnosis

Substances

  • Biomarkers