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

Guanshi Zhang, Qilan Deng, Rupasri Mandal, David S. Wishart, Burim N. Ametaj

Research output: Contribution to journalArticle

12 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)8510-8521
Number of pages12
JournalJournal of Agricultural and Food Chemistry
Volume65
Issue number38
DOIs
StatePublished - Sep 27 2017
Externally publishedYes

Keywords

  • amino acids
  • biomarkers
  • dairy cow
  • metabolomics
  • metritis
  • sphingolipids

ASJC Scopus subject areas

  • Chemistry(all)
  • Agricultural and Biological Sciences(all)

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