Predicting metabolic health status using milk fatty acid concentrations in cows – a review
Keywords:
milk fatty acids, metabolic disorder, negative energy balance, ketosis, prediction, herd health monitoringAbstract
The extent of a metabolic disorder (e.g. ketosis) is not necessarily reflected by the concentration of ß-hydroxybutyrate (BHB) in the blood, which is currently held as the gold standard in diagnosis. Also, for both economic and work-efficiency reasons, analysing blood is currently not applicable as a routine monitoring method for cows in the critical phase. Aim of this review was to examine the possibility of using milk fatty acids (FAs) and fatty acid (FA) ratios to predict negative energy balance (NEB), ketosis or metabolic disorders. After searching in two pertinent databases, eleven studies matched the relevant criteria. FA profiles were examined for correlations with the concentration of non-esterified fatty acids (NEFA) in blood in three studies, concentration of BHB in blood in five studies and different indicators of energy balance in four studies. One study developed linear regression models using FAs and FA ratios. Most studies found that short and medium-chained FAs (C4 – C14 and C5 – C15) are decreased during NEB, increased BHB or NEFA concentrations, whereas long-chained FAs (> C16) increase, especially cis-9 C18:1. A few single FAs and FA ratios such as cis-9 C16:1, cis-9 C16:1 to C15:0, C17:0 to C15:0 and C18:1 to C15:0 are correlated with a more severe NEB, elevated blood BHB or NEFA concentrations. Some might be useful in routine herd health monitoring despite having only moderate correlation coefficients. More promising than using single FAs or FA ratios to detect cows suffering from excessive NEB or metabolic disorders might be the implementation of refined prediction models in order to use all available information to predict the health status of both individual cows as well as the whole herd as exactly as possible.
References
Oetzel GR. Monitoring and testing dairy herds for metabolic disease. Vet Clin North Am Food Anim Pract. 2004;20(3):651-74. https://doi.org/10.1016/j.cvfa.2004.06.006.
Duffield TF, Kelton DF, Leslie K, Lissemore KD, Lumsden JH. Use of test day milk fat and milk protein to detect subclinical ketosis in dairy cattle in Ontario. Can Vet J. 1997;38:713 - 8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1576823/pdf/canvetj00096-0043.pdf.
Herdt TH. Ruminant adaptation to negative energy balance. Influences on the etiology of ketosis and fatty liver. Vet Clin North Am Food Anim Pract. 2000;16(2):215-30, v. https://doi.org/10.1016/S0749-0720(15)30102-X.
Duffield TF, Lissemore KD, McBride BW, Leslie KE. Impact of hyperketonemia in early lactation dairy cows on health and production. Journal of dairy science. 2009;92(2):571-80. https://doi.org/10.3168/jds.2008-1507.
Tremblay M, Kammer M, Lange H, Plattner S, Baumgartner C, Stegeman JA, et al. Identifying poor metabolic adaptation during early lactation in dairy cows using cluster analysis. Journal of dairy science. 2018;101(8):7311-21. https://doi.org/10.3168/jds.2017-13582.
Jorritsma R, Wensing T, Kruip TAM, Vos P, Noordhuizen J. Metabolic changes in early lactation and impaired reproductive performance in dairy cows. Veterinary Research. 2003;34(1):11-26. https://www.vetres.org/articles/vetres/abs/2003/01/02/02.html.
McArt JAA, Nydam DV, Oetzel GR, Overton TR, Ospina PA. Elevated non-esterified fatty acids and β-hydroxybutyrate and their association with transition dairy cow performance. The Veterinary Journal. 2013;198(3):560-70. https://doi.org/10.1016/j.tvjl.2013.08.011.
Ospina PA, McArt JA, Overton TR, Stokol T, Nydam DV. Using Nonesterified Fatty Acids and beta-Hydroxybutyrate Concentrations During the Transition Period for Herd-Level Monitoring of Increased Risk of Disease and Decreased Reproductive and Milking Performance. Veterinary Clinics of North America-Food Animal Practice. 2013;29(2):387-412. https://doi.org/10.1016/j.cvfa.2013.04.003.
Mann S, Nydam DV, Lock AL, Overton TR, McArt JAA. Short communication: Association of milk fatty acids with early lactation hyperketonemia and elevated concentration of nonesterified fatty acids. Journal of dairy science. 2016;99(7):5851-7. https://doi.org/10.3168/jds.2016-10920.
Tatone EH, Gordon JL, Hubbs J, LeBlanc SJ, DeVries TJ, Duffield TF. A systematic review and meta-analysis of the diagnostic accuracy of point-of-care tests for the detection of hyperketonemia in dairy cows. Prev Vet Med. 2016;130:18-32. https://www.ncbi.nlm.nih.gov/pubmed/27435643.
McArt JAA, Nydam DV, Oetzel GR, Guard CL. An economic analysis of hyperketonemia testing and propylene glycol treatment strategies in early lactation dairy cattle. Preventive Veterinary Medicine. 2014;117(1):170-9. https://doi.org/10.1016/j.prevetmed.2014.06.017.
Enjalbert F, Nicot MC, Bayourthe C, Moncoulon R. Ketone bodies in milk and blood of dairy cows: relationship between concentrations and utilization for detection of subclinical ketosis. Journal of dairy science. 2001;84(3):583-9. https://doi.org/10.3168/jds.S0022-0302(01)74511-0.
Geishauser T, Leslie K, Tenhag J, Bashiri A. Evaluation of eight cow-side ketone tests in milk for detection of subclinical ketosis in dairy cows. Journal of dairy science. 2000;83(2):296-9. https://doi.org/10.3168/jds.S0022-0302(00)74877-6.
Andersson L. Subclinical ketosis in dairy cows. Vet Clin North Am Food Anim Pract. 1988;4(2):233-51. https://doi.org/10.1016/S0749-0720(15)31046-X.
Melendez P, Pinedo PJ, Bastias J, Marin MP, Rios C, Bustamante C, et al. The association between ß-hydroxybutyrate and milk fatty acid profile with special emphasis on cojugated linoleic acid in postpartum Holstein cows. BMC Veterinary Research. 2016;10. https://doi.org/10.1186/s12917-016-0679-7.
Dorea JRR, French EA, Armentano LE. Use of milk fatty acids to estimate plasma nonesterified fatty acid concentrations as an indicator of animal energy balance. Journal of dairy science. 2017;100(8):6164-76. https://doi.org/10.3168/jds.2016-12466.
Rukkwamsuk T, Geelen MJH, Kruip TAM, Wensing T. Interrelation of Fatty Acid Composition in Adipose Tissue, Serum, and Liver of Dairy Cows During the Development of Fatty Liver Postpartum. Journal of dairy science. 2000;83(1):52-9. https://doi.org/10.3168/jds.S0022-0302(00)74854-5.
Bauman DE, Griinari JM. Nutritional regulation of milk fat synthesis. Annu Rev Nutr. 2003;23:203-27. https://www.annualreviews.org/doi/abs/10.1146/annurev.nutr.23.011702.073408.
Nogalski Z, Wronski M, Sobczuk-Szul M, Mochol M, Pogorzelska P. The Effect of Body Energy Reserve Mobilization on the Fatty Acid Profile of Milk in High-yielding Cows. Asian-Australas J Anim Sci. 2012;25(12):1712-20. http://www.ajas.info/journal/view.php?number=22865.
Jorjong S, van Knegsel AT, Verwaeren J, Lahoz MV, Bruckmaier RM, De Baets B, et al. Milk fatty acids as possible biomarkers to early diagnose elevated concentrations of blood plasma nonesterified fatty acids in dairy cows. Journal of dairy science. 2014;97(11):7054-64. https://doi.org/10.3168/jds.2014-8039.
Mantysaari P, Mantysaari EA, Kokkonen T, Mehtio T, Kajava S, Grelet C, et al. Body and milk traits as indicators of dairy cow energy status in early lactation. Journal of dairy science. 2019;102(9):7904-16. https://doi.org/10.3168/jds.2018-15792.
Puppel K, Solarczyk P, Kuczynska B, Madras-Majewska B. Oleic acid as a biomarker for early diagnosis of elevated blood levels of non-esterified fatty acids and beta-hydroxybutyric acid in the early stages of lactation in high-yielding Polish Holstein cows. Animal Science Papers and Reports. 2017;35(4):387-96. http://www.ighz.pl/uploaded/FSiBundleContentBlockBundleEntityTranslatableBlockTranslatableFilesElement/filePath/986/str387-396.pdf.
Puppel K, Golebiewski M, Solarczyk P, Grodkowski G, Slosarz J, Kunowska-Slosarz M, et al. The relationship between plasma beta-hydroxybutyric acid and conjugated linoleic acid in milk as a biomarker for early diagnosis of ketosis in postpartum Polish Holstein-Friesian cows. Bmc Veterinary Research. 2019;15(1). https://bmcvetres.biomedcentral.com/articles/10.1186/s12917-019-2131-2.
Jorjong S, van Knegsel ATM, Verwaeren J, Bruckmaier RM, De Baets B, Kemp B, et al. Milk fatty acids as possible biomarkers to diagnose hyperketonemia in early lactation. Journal of dairy science. 2015;98(8):5211-21. https://doi.org/10.3168/jds.2014-8728.
Van Haelst YN, Beeckman A, Van Knegsel AT, Fievez V. Short communication: elevated concentrations of oleic acid and long-chain fatty acids in milk fat of multiparous subclinical ketotic cows. Journal of dairy science. 2008;91(12):4683-6. https://doi.org/10.3168/jds.2008-1375.
Nogalski Z, Pogorzelska P, Sobczuk-Szul M, Mochol M, Nogalska A. Influence of BHB concentration in blood on fatty acid content in the milk of high-yielding cows. Med Weter. 2015;71(8):493-6. http://www.medycynawet.edu.pl/images/stories/pdf/pdf2015/082015/201508493496.pdf.
Bach KD, Barbano DM, McArt JAA. Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows. Journal of dairy science. 2019;102(11):10129-39. https://doi.org/10.3168/jds.2019-16926.
Woolpert ME, Dann HM, Cotanch KW, Melilli C, Chase LE, Grant RJ, et al. Management, nutrition, and lactation performance are related to bulk tank milk de novo fatty acid concentration on northeastern US dairy farms. Journal of dairy science. 2016;99(10):8486-97. https://doi.org/10.3168/jds.2016-10998.
Woolpert ME, Dann HM, Cotanch KW, Melilli C, Chase LE, Grant RJ, et al. Management practices, physically effective fiber, and ether extract are related to bulk tank milk de novo fatty acid concentration on Holstein dairy farms. Journal of dairy science. 2017;100(6):5097-106. http://www.sciencedirect.com/science/article/pii/S0022030217302965.
Rottman LW, Ying Y, Zhou K, Bartell PA, Harvatine KJ. The daily rhythm of milk synthesis is dependent on the timing of feed intake in dairy cows. Physiol Rep. 2014;2(6). https://doi.org/10.14814/phy2.12049.
Bannon CD, Craske JD, Hilliker AE. Analysis of fatty acid methyl esters with high accuracy and reliability. IV. Fats with fatty acids containing four or more carbon atoms. Journal of the American Oil Chemists’ Society. 1985;62(10):1501-7. https://doi.org/10.1007/BF02541903.
Soyeurt H, Dardenne P, Dehareng F, Lognay G, Veselko D, Marlier M, et al. Estimating Fatty Acid Content in Cow Milk Using Mid-Infrared Spectrometry. Journal of dairy science. 2006;89(9):3690-5. https://doi.org/10.3168/jds.S0022-0302(06)72409-2.
Soyeurt H, Dehareng F, Gengler N, McParland S, Wall E, Berry DP, et al. Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries. Journal of dairy science. 2011;94(4):1657-67. https://doi.org/10.3168/jds.2010-3408.
Gonzalez FD, Muino R, Pereira V, Campos R, Benedito JL. Relationship among blood indicators of lipomobilization and hepatic function during early lactation in high-yielding dairy cows. Journal of veterinary science. 2011;12(3):251-5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3165154/.
Tremblay M, Kammer M, Lange H, Plattner S, Baumgartner C, Stegeman JA, et al. Prediction model optimization using full model selection with regression trees demonstrated with FTIR data from bovine milk. Prev Vet Med. 2019;163:14-23. https://doi.org/10.1016/j.prevetmed.2018.12.012.
Stoop WM, Bovenhuis H, Heck JM, van Arendonk JA. Effect of lactation stage and energy status on milk fat composition of Holstein-Friesian cows. Journal of dairy science. 2009;92(4):1469-78. https://doi.org/10.3168/jds.2008-1468.
Knegsel ATMv, Brand Hvd, Dijkstra J, Tamminga S, Kemp B. Effect of dietary energy source on energy balance, production, metabolic disorders and reproduction in lactating dairy cattle. Reprod Nutr Dev. 2005;45(6):665-88. https://doi.org/10.1051/rnd:2005059.
van Knegsel AT, van den Brand H, Dijkstra J, Tamminga S, Kemp B. Effect of dietary energy source on energy balance, production, metabolic disorders and reproduction in lactating dairy cattle. Reproduction, nutrition, development. 2005;45(6):665-88. https://doi.org/10.1051/rnd:2005059.
Gross J, van Dorland HA, Bruckmaier RM, Schwarz FJ. Milk fatty acid profile related to energy balance in dairy cows. J Dairy Res. 2011;78(4):479-88. https://doi.org/10.1017/S0022029911000550.
Gillis AT, Eskin NAM, Cliplef RL. Fatty acid composition of bovine intramuscular and subcutaneaous fat as related to breed and sex. Journal of Food Science. 1973;38(3):408-11. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2621.1973.tb01441.x.
Muth M. Beziehungen zwischen peripartal gemessenen Fettsäurekonzentrationen im Blut und postpartalen Gebärmuttererkrankungen bei Milchkühen. München: Ludwig-Maximilians-Universität München; 2011.http://nbn-resolving.de/urn:nbn:de:bvb:19-133331.
Gross J, van Dorland HA, Bruckmaier RM, Schwarz FJ. Performance and metabolic profile of dairy cows during a lactational and deliberately induced negative energy balance with subsequent realimentation. Journal of dairy science. 2011;94(4):1820-30. https://doi.org/10.3168/jds.2010-3707.
Vrankovic L, Aladrovic J, Octenjak D, Bijelic D, Cvetnic L, Stojevic Z. Milk fatty acid composition as an indicator of energy status in Holstein dairy cows. Arch Anim Breed. 2017;60(3):205-12. https://www.arch-anim-breed.net/60/205/2017/.
Chandler TL, Pralle RS, Dorea JRR, Poock SE, Oetzel GR, Fourdraine RH, et al. Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early-lactation Holstein and Jersey cows. Journal of dairy science. 2018;101(3):2476-91. https://doi.org/10.3168/jds.2017-13209.
Luke TDW, Rochfort S, Wales WJ, Bonfatti V, Marett L, Pryce JE. Metabolic profiling of early-lactation dairy cows using milk mid-infrared spectra. Journal of dairy science. 2019;102(2):1747-60. https://doi.org/10.3168/jds.2018-15103.
van der Drift SGA, Jorritsma R, Schonewille JT, Knijn HM, Stegeman JA. Routine detection of hyperketonemia in dairy cows using Fourier transform infrared spectroscopy analysis of beta-hydroxybutyrate and acetone in milk in combination with test-day information. Journal of dairy science. 2012;95(9):4886-98. https://doi.org/10.3168/jds.2011-4417.
