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Prediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers

(2019) JOURNAL OF DAIRY SCIENCE. 102(3). p.2631-2644
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Abstract
The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and beta-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immuno-gamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbalanced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the "balanced" group (n = 43) and were compared with cows in what was referred to as the "other balanced" group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the "imbalanced" group (n = 19) and compared with cows in what was referred to as the "other imbalanced" group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids arid BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-beta-D-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, parity, milk yield featurs) were used to create predictive models for the metabolic clusters. Accuracy for prediction of balanced (80%) and imbalanced (88%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows.
Keywords
NONESTERIFIED FATTY-ACIDS, NEGATIVE-ENERGY BALANCE, GROWTH-FACTOR-I, BETA-HYDROXYBUTYRATE, BODY CONDITION, FLUOROMETRIC-DETERMINATION, PHYSIOLOGICAL IMBALANCE, PRODUCTION DISEASES, INSULIN-RESISTANCE, SOMATOTROPIC AXIS, metabolic clustering, dairy cow, prediction, milk biomarker

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Chicago
De Koster, Jenne, M. Salavati, C. Grelet, M. A. Crowe, E. Matthews, R. O’Flaherty, Geert Opsomer, et al. 2019. “Prediction of Metabolic Clusters in Early-lactation Dairy Cows Using Models Based on Milk Biomarkers.” Journal of Dairy Science 102 (3): 2631–2644.
APA
De Koster, J., Salavati, M., Grelet, C., Crowe, M. A., Matthews, E., O’Flaherty, R., Opsomer, G., et al. (2019). Prediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers. JOURNAL OF DAIRY SCIENCE, 102(3), 2631–2644.
Vancouver
1.
De Koster J, Salavati M, Grelet C, Crowe MA, Matthews E, O’Flaherty R, et al. Prediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers. JOURNAL OF DAIRY SCIENCE. New york: Elsevier Science Inc; 2019;102(3):2631–44.
MLA
De Koster, Jenne et al. “Prediction of Metabolic Clusters in Early-lactation Dairy Cows Using Models Based on Milk Biomarkers.” JOURNAL OF DAIRY SCIENCE 102.3 (2019): 2631–2644. Print.
@article{8606370,
  abstract     = {The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and beta-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immuno-gamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbalanced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the {\textacutedbl}balanced{\textacutedbl} group (n = 43) and were compared with cows in what was referred to as the {\textacutedbl}other balanced{\textacutedbl} group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the {\textacutedbl}imbalanced{\textacutedbl} group (n = 19) and compared with cows in what was referred to as the {\textacutedbl}other imbalanced{\textacutedbl} group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids arid BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-beta-D-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, parity, milk yield featurs) were used to create predictive models for the metabolic clusters. Accuracy for prediction of balanced (80\%) and imbalanced (88\%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows.},
  author       = {De Koster, Jenne and Salavati, M. and Grelet, C. and Crowe, M. A. and Matthews, E. and O'Flaherty, R. and Opsomer, Geert and Foldager, L. and Hostens, Miel and McLoughlin, Niamh and Fahey, Alan and Santoro, Andreia and Byrne, Colin and Rudd, Pauline and Hallinan, Sinead and Wathes, Claire and Cheng, Zhangrui and Fouladi, Ali and Pollott, Geoff and Werling, Dirk and Bernardo, Beatriz Sanz and Wylie, Alistair and Bell, Matt and Van Eetvelde, Mieke and Hermans, Kristof and Moerman, Sander and Bogaert, Hannes and Vandepitte, Jan and Vande Velde, Leila and Van Ranst, Bonifacius and Hoglund, Johanna and Dahl, Susanne and Ostergaard, Soren and Rothmann, Janne and Krogh, Mogens and Meyer, Else and Gaillard, Charlotte and Ettema, Jehan and Rousing, Tine and Signorelli, Federica and Napolitano, Francesco and Moioli, Bianca and Crisa, Alessandra and Buttazzoni, Luca and McClure, Jennifer and Matthews, Daragh and Kearney, Francis and Cromie, Andrew and McClure, Matt and Zhang, Shujun and Chen, Xing and Chen, Huanchun and Zhao, Junlong and Yang, Liguo and Hua, Guohua and Tan, Chen and Wang, Guiqiang and Bonneau, Michel and Pompozzi, Andrea and Pearn, Armin and Evertson, Arnold and Kosten, Linda and Fogh, Anders and Andersen, Thomas and Lucy, Matthew and Elsik, Chris and Conant, Gavin and Taylor, Jerry and Gengler, Nicolas and Georges, Michel and Colinet, Frederic and Pamplona, Marilou Ramos and Hammami, Hedi and Bastin, Catherine and Takeda, Haruko and Laine, Aurelie and Van Laere, Anne-Sophie and Schulze, Martin and Vera, Sergio Palma},
  issn         = {0022-0302},
  journal      = {JOURNAL OF DAIRY SCIENCE},
  language     = {eng},
  number       = {3},
  pages        = {2631--2644},
  publisher    = {Elsevier Science Inc},
  title        = {Prediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers},
  url          = {http://dx.doi.org/10.3168/jds.2018-15533},
  volume       = {102},
  year         = {2019},
}

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