(1) Background: The objective of this study was to evaluate the urine of dairy cows for presence of metabolites with the potential to be used as screening biomarkers for lameness as well as to characterize pre-lame, lame, and post-lame cows from the metabolic
[...] Read more.
(1) Background: The objective of this study was to evaluate the urine of dairy cows for presence of metabolites with the potential to be used as screening biomarkers for lameness as well as to characterize pre-lame, lame, and post-lame cows from the metabolic prospective. (2) Methods: Six lame and 20 control healthy cows were used in this nested case-control study. Urinary 1H-NMR analysis was used to identify and measure metabolites at five time points including −8 and −4 weeks prepartum, lameness diagnosis week (1–3 weeks postpartum) as well as at +4 and +8 weeks after calving. (3) Results: A total of 90 metabolites were identified and measured in the urine. At −8 and −4 weeks, 27 prepartum metabolites were identified as altered, at both timepoints, with 19 and 5 metabolites excreted at a lower concentration, respectively. Additionally, a total of 8 and 22 metabolites were found at greater concentration in pre-lame cows at −8 and −4 weeks, respectively. Lame cows were identified to excrete, at lower concentrations, seven metabolites during a lameness event with the top five most important metabolites being Tyr, adipate, glycerate, 3-hydroxy-3-methylglutarate, and uracil. Alterations in urinary metabolites also were present at +4 and +8 weeks after calving with N-acetylaspartate, glutamine, imidazole, pantothenate, beta-alanine and trimethylamine, with the greatest VIP (variable importance in projection) score at +4 weeks; and hipurate, pantothenate 1,3-dihydroxyacetone, galactose, and Tyr, with the greatest VIP score at +8 weeks postpartum. (4) Conclusions: Overall, results showed that urine metabotyping can be used to identify cows at risk of lameness and to better characterize lameness from the metabolic prospective. However, caution should be taken in interpretation of the data presented because of the low number of replicates.