Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom.
Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, United Kingdom; High Field NMR Facility, Liverpool Shared Research Facilities University of Liverpool, Liverpool, L69 7ZB, United Kingdom.
J Dairy Sci. 2023 Apr;106(4):2667-2684. doi: 10.3168/jds.2022-22681. Epub 2023 Mar 2.
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.
蹄底出血和溃疡,统称为蹄底病变,是奶牛跛行的重要原因。我们旨在比较在泌乳早期发生蹄底病变的奶牛与未受影响的奶牛的血清代谢组。我们前瞻性地招募了来自单个奶牛场的 1169 头荷斯坦奶牛队列,并在 4 个时间点评估了动物:产前、产后立即、泌乳早期和泌乳晚期。兽医在每个时间点记录蹄底病变,在头 3 个时间点采集血清样本。病例通过泌乳早期出现蹄底病变来定义,并根据之前是否记录到蹄底病变进一步细分;未受影响的对照组随机选择以匹配病例。对 228 例病例对照亚组的血清样本进行质子磁共振波谱分析。分析与时间点、胎次队列和蹄底病变结果相关的亚组中,与 34 个暂定注释代谢物和 51 个未标记代谢物对应的光谱信号。我们使用 3 种分析方法(偏最小二乘判别分析、最小绝对收缩和选择算子回归以及随机森林)来确定血清代谢组的预测能力并识别信息丰富的代谢物。我们应用引导选择稳定性、三角剖分和置换来支持变量选择的推断。根据子集的不同,类预测的平均平衡准确率在 50%到 62%之间。在所有 17 个子集中,有 20 个变量具有很高的信息量;与蹄底病变相关性最强的证据对应于苯丙氨酸和 4 个未标记的代谢物。我们得出结论,质子磁共振波谱分析的血清代谢组似乎无法预测蹄底病变的存在或病变的未来发展。尽管少数代谢物可能与蹄底病变有关,但鉴于预测准确率较低,这些代谢物可能只解释了受影响和未受影响动物之间差异的一小部分。未来的代谢组学研究可能会揭示奶牛蹄底病变发病机制的潜在代谢机制;然而,实验设计和分析需要有效地控制动物间和外部光谱变异的来源。