TY - JOUR
T1 - Metabolic clusters of early-lactating dairy cows based on blood β-hydroxybutyrate trajectories and predicted from milk compounds
AU - Girma, Muluken
AU - Heirbaut, Stijn
AU - Hertogs, Karolien
AU - Jing, X. P.
AU - Zhang, MQ
AU - Lutakome, P.
AU - Stevens, Els
AU - Geerinckx, Katleen
AU - Aernouts, B
AU - Vandaele, Leen
AU - Fievez, Veerle
PY - 2024/11
Y1 - 2024/11
N2 - High-yielding dairy cows encounter metabolic challenges in early lactation. Typically, BHB, measured at a specific time point, is employed to diagnose the metabolic status of cows based on a predetermined threshold. However, in early lactation, BHB is highly dynamic, with high interindividual variability in its time profile. This could limit the effectiveness of the single measurement and threshold-based diagnosis and could contribute to the disparities in reports linking metabolic status with productive and reproductive outcomes. This research examines the trajectories of BHB to unveil intercow variations and identify latent metabolic groups. We compiled a dataset from 2 observational studies involving a total of 195 lactations from multiparous Holstein Friesian cows. The dataset encompasses measurements of BHB, nonesterified fatty acids (NEFA), and insulin from blood samples collected at 3, 6, 9, and 21 DIM, along with weekly determinations of milk composition and fatty acids (FA) proportions in milk fat. In both experiments, milk yield (MY) and feed intake were recorded daily during the first month of lactation. We explored interindividual and intraindividual variations in metabolic responses using the trajectories of blood BHB and evaluated the presence of distinct metabolic groups based on such variations. For this purpose, we employed the growth mixture model, a trajectory clustering technique. Our findings unveil novel insights into the diverse metabolic responses among cows, encompassing both trajectory patterns and the magnitude of blood BHB concentrations. Specifically, we identified 3 latent metabolic groups: the quickly increasing BHB (QuiBHB) cluster (≈10%) exhibited a higher initial BHB concentration than other clusters, peaked on d 9 (average maximum BHB of 2.4 mM) and then declined by d 21; the slowly increasing BHB (SloBHB) cluster (≈23%) started with a lower BHB concentration, gradually increased until d 9, and reached the highest BHB concentration at d 21 (1.6 mM serum BHB at the end of the experimental period); and the low BHB (LoBHB) cluster (≈67%) began with the lowest serum BHB concentration (serum BHB <0.75 mM) and remained relatively stable throughout the sampling period. Notably, the 3 metabolic groups exhibited significant physiological disparities, which were evident in blood NEFA and insulin concentrations. The QuiBHB and SloBHB cows exhibited higher NEFA and lower insulin concentrations as compared with the LoBHB cows. Interestingly, these metabolic differences extended to MY and DMI during the first month of lactation. The elevated BHB concentrations observed in QuiBHB cows were linked with lower DMI and MY as compared with SloBHB and LoBHB cows. Accordingly, these animals were considered metabolically impaired. Conversely, SloBHB cows displayed higher MY along with increased DMI, and thus the elevated BHB might be indicative of an adaptive response for these cows. The QuiBHB cows also displayed higher proportions of UFA, MUFA, and total C18:1 FA in milk during the first week of lactation. Prediction of the QuiBHB cows using these FA and test day variables resulted in moderate predictive accuracy (area under the receiver operating characteristic curve >0.7). Given the limited sample size for the development of prediction models and the variation in DIM among samples in the same week, the result is indicative of the predictive potential of the model and room for model optimization. In summary, distinct metabolic groups of cows could be identified based on the trajectories of blood BHB in early lactation.
AB - High-yielding dairy cows encounter metabolic challenges in early lactation. Typically, BHB, measured at a specific time point, is employed to diagnose the metabolic status of cows based on a predetermined threshold. However, in early lactation, BHB is highly dynamic, with high interindividual variability in its time profile. This could limit the effectiveness of the single measurement and threshold-based diagnosis and could contribute to the disparities in reports linking metabolic status with productive and reproductive outcomes. This research examines the trajectories of BHB to unveil intercow variations and identify latent metabolic groups. We compiled a dataset from 2 observational studies involving a total of 195 lactations from multiparous Holstein Friesian cows. The dataset encompasses measurements of BHB, nonesterified fatty acids (NEFA), and insulin from blood samples collected at 3, 6, 9, and 21 DIM, along with weekly determinations of milk composition and fatty acids (FA) proportions in milk fat. In both experiments, milk yield (MY) and feed intake were recorded daily during the first month of lactation. We explored interindividual and intraindividual variations in metabolic responses using the trajectories of blood BHB and evaluated the presence of distinct metabolic groups based on such variations. For this purpose, we employed the growth mixture model, a trajectory clustering technique. Our findings unveil novel insights into the diverse metabolic responses among cows, encompassing both trajectory patterns and the magnitude of blood BHB concentrations. Specifically, we identified 3 latent metabolic groups: the quickly increasing BHB (QuiBHB) cluster (≈10%) exhibited a higher initial BHB concentration than other clusters, peaked on d 9 (average maximum BHB of 2.4 mM) and then declined by d 21; the slowly increasing BHB (SloBHB) cluster (≈23%) started with a lower BHB concentration, gradually increased until d 9, and reached the highest BHB concentration at d 21 (1.6 mM serum BHB at the end of the experimental period); and the low BHB (LoBHB) cluster (≈67%) began with the lowest serum BHB concentration (serum BHB <0.75 mM) and remained relatively stable throughout the sampling period. Notably, the 3 metabolic groups exhibited significant physiological disparities, which were evident in blood NEFA and insulin concentrations. The QuiBHB and SloBHB cows exhibited higher NEFA and lower insulin concentrations as compared with the LoBHB cows. Interestingly, these metabolic differences extended to MY and DMI during the first month of lactation. The elevated BHB concentrations observed in QuiBHB cows were linked with lower DMI and MY as compared with SloBHB and LoBHB cows. Accordingly, these animals were considered metabolically impaired. Conversely, SloBHB cows displayed higher MY along with increased DMI, and thus the elevated BHB might be indicative of an adaptive response for these cows. The QuiBHB cows also displayed higher proportions of UFA, MUFA, and total C18:1 FA in milk during the first week of lactation. Prediction of the QuiBHB cows using these FA and test day variables resulted in moderate predictive accuracy (area under the receiver operating characteristic curve >0.7). Given the limited sample size for the development of prediction models and the variation in DIM among samples in the same week, the result is indicative of the predictive potential of the model and room for model optimization. In summary, distinct metabolic groups of cows could be identified based on the trajectories of blood BHB in early lactation.
U2 - 10.3168/jds.2024-24762
DO - 10.3168/jds.2024-24762
M3 - A1: Web of Science-article
SN - 0022-0302
VL - 107
SP - 9719
EP - 9734
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 11
ER -