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Serum 1H nuclear magnetic resonance–based metabolomics of sole lesion development in Holstein cows

Barden, Matthew; Phelan, Marie M.; Hyde, Robert; Anagnostopoulos, Alkiviadis; Griffiths, Bethany E.; Bedford, Cherry; Green, Martin; Psifidi, Androniki; Banos, Georgios; Oikonomou, Georgios

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Authors

Matthew Barden

Marie M. Phelan

Mr ROBERT HYDE Robert.Hyde4@nottingham.ac.uk
ASSISTANT PROFESSOR IN COMPUTATIONAL BIOLOGY

Alkiviadis Anagnostopoulos

Bethany E. Griffiths

Cherry Bedford

Martin Green

Androniki Psifidi

Georgios Banos

Georgios Oikonomou



Abstract

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.

Citation

Barden, M., Phelan, M. M., Hyde, R., Anagnostopoulos, A., Griffiths, B. E., Bedford, C., Green, M., Psifidi, A., Banos, G., & Oikonomou, G. (2023). Serum 1H nuclear magnetic resonance–based metabolomics of sole lesion development in Holstein cows. Journal of Dairy Science, 106(4), 2667-2684. https://doi.org/10.3168/jds.2022-22681

Journal Article Type Article
Acceptance Date Nov 15, 2022
Online Publication Date Mar 2, 2023
Publication Date 2023-04
Deposit Date May 27, 2023
Publicly Available Date May 30, 2023
Journal Journal of Dairy Science
Print ISSN 0022-0302
Electronic ISSN 1525-3198
Publisher American Dairy Science Association
Peer Reviewed Peer Reviewed
Volume 106
Issue 4
Pages 2667-2684
DOI https://doi.org/10.3168/jds.2022-22681
Keywords Lameness; Claw horn lesions; Metabolomics; Nuclear magnetic resonance (NMR) spectroscopy
Public URL https://nottingham-repository.worktribe.com/output/17947552
Publisher URL https://www.journalofdairyscience.org/article/S0022-0302(23)00097-8/fulltext

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