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Between- and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation

Published online by Cambridge University Press:  07 November 2019

M. A. Krogh Open the ORCID record for M. A. Krogh [Opens in a new window] ,
M. Hostens Open the ORCID record for M. Hostens [Opens in a new window] ,
M. Salavati Open the ORCID record for M. Salavati [Opens in a new window] ,
C. Grelet Open the ORCID record for C. Grelet [Opens in a new window] ,
M. T. Sorensen ,
D. C. Wathes Open the ORCID record for D. C. Wathes [Opens in a new window] ,
C. P. Ferris Open the ORCID record for C. P. Ferris [Opens in a new window] ,
C. Marchitelli Open the ORCID record for C. Marchitelli [Opens in a new window] ,
F. Signorelli  and
F. Napolitano
...Show all authors
M. A. Krogh*
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allé 20, TjeleDK8830, Denmark
M. Hostens
Affiliation:
Department of Reproduction, Obstetrics and Herd Health, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
M. Salavati
Affiliation:
Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield AL9 7TA, United Kingdom
C. Grelet
Affiliation:
Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
M. T. Sorensen
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allé 20, TjeleDK8830, Denmark
D. C. Wathes
Affiliation:
Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield AL9 7TA, United Kingdom
C. P. Ferris
Affiliation:
Agri-Food and Biosciences Institute, Largepark, Hillsborough BT26 6DR, Northern Ireland, UK
C. Marchitelli
Affiliation:
Research Center for Animal Production and Aquaculture, Via Salaria 31, 00015 Monterotondo, Roma, Italy
F. Signorelli
Affiliation:
Research Center for Animal Production and Aquaculture, Via Salaria 31, 00015 Monterotondo, Roma, Italy
F. Napolitano
Affiliation:
Research Center for Animal Production and Aquaculture, Via Salaria 31, 00015 Monterotondo, Roma, Italy
F. Becker
Affiliation:
Institute for Reproductive Biology, Leibniz Institute for Farm Animal Biology, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
T. Larsen
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allé 20, TjeleDK8830, Denmark
E. Matthews
Affiliation:
School of Veterinary Medicine, University College Dublin, Veterinary Science Centre Belfield, Dublin 4, Ireland
F. Carter
Affiliation:
School of Veterinary Medicine, University College Dublin, Veterinary Science Centre Belfield, Dublin 4, Ireland
A. Vanlierde
Affiliation:
Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
G. Opsomer
Affiliation:
Department of Reproduction, Obstetrics and Herd Health, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
N. Gengler
Affiliation:
Gembloux Agro-Bio Tech, University of Liège, Passage des Déportés 2, B-5030 Gembloux, Belgium
F. Dehareng
Affiliation:
Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
M. A. Crowe
Affiliation:
School of Veterinary Medicine, University College Dublin, Veterinary Science Centre Belfield, Dublin 4, Ireland
K. L. Ingvartsen
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allé 20, TjeleDK8830, Denmark
L. Foldager
Affiliation:
Department of Animal Science, Aarhus University, Blichers Allé 20, TjeleDK8830, Denmark Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, Aarhus DK8000, Denmark
*
†E-mail: mogenskrogh@anis.au.dk
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Abstract

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

Keywords

dairybiomarkerphysiological imbalancevariancemonitoring
Type
Research Article
Information
animal , Volume 14 , Issue 5 , May 2020 , pp. 1067 - 1075
Copyright
© The Animal Consortium 2019

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Footnotes

a

Present address: Genetics and Genomics Division, The Roslin Institute, Easter Bush Campus, Midlothian EH25 9RG, United Kingdom.

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