Supplementary Materials - Serum 1H NMR-based metabolomics of sole lesion development in Holstein cows
Supplementary Methods. Details regarding NMR spectra acquisition and processing, and approach to statistical analysis. Supplementary Table 1. Details of the spectral bins selected as representative of each annotated metabolite and used in statistical analysis, including the Bovine Metabolome database identification number (BMDB ID). Supplementary Table 2. Details of the unlabeled spectral bins (not annotated to a metabolite) used in the statistical analysis. Supplementary Table 3. Results of univariable analysis with Wilcoxon signed-rank tests. Data were analyzed in 17 prespecified subsets split by time point, parity, and outcome definition; the control group in all cases were animals without sole lesions, outcomes were either cases of sole new hemorrhage (New SH), cases of new sole ulcers (New SU), those two groups combined (New SH/SU) or all cases of sole ulcers (All SU). Supplementary Table 4. Variable selection stability results including the mean log (base 2) fold-change (Log2FC) and the baseline stability thresholds (T99 and T100, equivalent to an expected 1% and 0% false positive rate, respectively). Data were analyzed in 17 prespecified subsets split by time point, parity, and outcome definition; the control group in all cases were animals without sole lesions, outcomes were either cases of sole new hemorrhage (New SH), cases of new sole ulcers (New SU), those two groups combined (New SH/SU) or all cases of sole ulcers (All SU).
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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.