Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-23T00:37:40.270Z Has data issue: false hasContentIssue false

Effects of herd and physiological status on variation of 16 immunological and inflammatory parameters in dairy cows during drying off and the transition period

Published online by Cambridge University Press:  22 May 2018

Alfonso Zecconi*
Affiliation:
Department of Veterinary Medicine, University of Milan, via Celoria 10, 20133 Milan, Italy
Francesca Albonico
Affiliation:
Department of Veterinary Medicine, University of Milan, via Celoria 10, 20133 Milan, Italy
Maria Elena Gelain
Affiliation:
Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, 35020, Agripolis, Legnaro (PD), Italy
Renata Piccinini
Affiliation:
Department of Veterinary Medicine, University of Milan, via Celoria 10, 20133 Milan, Italy
Micaela Cipolla
Affiliation:
Department of Veterinary Medicine, University of Milan, via Celoria 10, 20133 Milan, Italy
Michele Mortarino
Affiliation:
Department of Veterinary Medicine, University of Milan, via Celoria 10, 20133 Milan, Italy
*
*For correspondence; e-mail: [email protected]

Abstract

During drying off and transition period, cows are subject to changes in endocrine status, metabolic stressors and altered immune functions, which could lead to an increased risk of disease. To expand our knowledge on the immune/inflammatory status and to identify markers to define cow status during this interval, the pattern of 9 different cellular parameters, 5 cytokines, 2 enzymes and 3 cellular ratios in blood samples were assessed in 15 primiparous cows belonging to three different dairy herds in Lombardy. Our data showed that the variation of almost all parameters was influenced by the physiological period in which the samples were collected, except for apoptosis, IL-1β, IL-6, lysozyme and granulocyte/monocyte ratio. Several markers were directly correlated either to the herd alone (IL-1β, IL-6, lysozyme, granulocyte/lymphocyte ratio and granulocyte/monocyte ratio) or in association with the sampling time (white blood cell count, necrosis, lymphocytes count, CD4+ lymphocytes proportion). Hierarchical cluster analysis identified three herd-associated sample clusters showing different frequency along the follow-up period. The results of this field study highlight the importance of the herd factor in the immune/inflammatory response. Furthermore, these results suggest that cellular parameters are probably the most suitable markers to define cow status during drying-off and the peripartum period.

Type
Research Article
Copyright
Copyright © Hannah Dairy Research Foundation 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amadori, M, Fusi, F, Bilato, D, Archetti, IL, Lorenzi, V & Bertocchi, L 2015 Disease risk assessment by clinical immunology analyses in periparturient dairy cows. Research in Veterinary Science 102 2526Google Scholar
Bertoni, G, Trevisi, E, Han, X & Bionaz, M 2008 Effects of inflammatory conditions on liver activity in puerperium period and consequences for performance in dairy cows. Journal of Dairy Science 91 33003310Google Scholar
Bionaz, M, Trevisi, E, Calamari, L, Librandi, F, Ferrari, A & Bertoni, G 2007 Plasma paraoxonase, health, inflammatory conditions, and liver function in transition dairy cows. Journal of Dairy Science 90 17401750Google Scholar
Comazzi, S, Gelain, ME, Martini, V, Riondato, F, Miniscalco, B, Marconato, L, Stefanello, D & Mortarino, M 2011 Immunophenotype predicts survival time in dogs with chronic lymphocytic leukemia. Journal of Veterinary Internal Medicine 25 100106Google Scholar
Danicke, S, Meyer, U, Winkler, J, Ulrich, S, Frahm, J, Kersten, S, Valenta, H, Rehage, J, Haussler, S, Sauerwein, H & Locher, L 2016 Haematological and immunological adaptations of non-pregnant, non-lactating dairy cows to a high-energetic diet containing mycotoxins. Archives of Animal Nutrition 70 116Google Scholar
Drackley, JK 1999 Biology of dairy cows during the transition period: the final frontier? Journal of Dairy Science 82 22592273Google Scholar
Drackley, JK, Dann, HM, Douglas, GN, Guretzky, NAJ, Litherland, NB, Underwood, JP & Loor, JJ 2005 Physiological and pathological adaptations in dairy cows that may increase susceptibility to periparturient diseases and disorders. Italian Journal of Animal Science 4 323344Google Scholar
Goff, JP & Horst, RL 1997 Physiological changes at parturition and their relationship to metabolic disorders. Journal of Dairy Science 80 12601268Google Scholar
Hailemariam, D, Mandal, R, Saleem, F, Dunn, SM, Wishart, DS & Ametaj, BN 2014 Identification of predictive biomarkers of disease state in transition dairy cows. Journal of Dairy Science 97 26802693CrossRefGoogle Scholar
Hatcher, L & Stepanski, EJ 1994 A Step-by-Step Approach to Using SAS System for Univariate e Multivariate Statistics. Cary, NC: SAS Institute IncGoogle Scholar
Jonsson, NN, Fortes, MRS, Piper, EK, Vankan, DM, de Cisneros, JPJ & Wittek, T 2013 Comparison of metabolic, hematological, and peripheral blood leukocyte cytokine profiles of dairy cows and heifers during the periparturient period. Journal of Dairy Science 96 22832292CrossRefGoogle ScholarPubMed
Karcher, EL, Beitz, DC & Stabel, JR 2008 Modulation of cytokine gene expression and secretion during the periparturient period in dairy cows naturally infected with Mycobacterium avium subsp paratuberculosis. Veterinary Immunology and Immunopathology 123 277288Google Scholar
Kitchen, BJ, Middleton, G & Salmon, M 1978 Bovine milk N-acetyl- beta -D-glucosaminidase and its significance in the detection of abnormal udder secretions. Journal of Dairy Research 45 1520Google Scholar
Leutenegger, CM, Alluwaimi, AM, Smith, WL, Perani, L & Cullor, JS 2000 Quantitation of bovine cytokine mRNA in milk cells of healthy cattle by real-time TaqMan (R) polymerase chain reaction. Veterinary Immunology and Immunopathology 77 275287Google Scholar
Mehrzad, J & Zhao, X 2008 Tlymphocyte proliferative capacity and CD4(+)/CD8(+) ratio in primiparous and pluriparous lactating cows. Journal of Dairy Research 75 457465Google Scholar
Piccinini, R, Binda, E, Belotti, M, Casirani, G & Zecconi, A 2004 Evaluation of non-specific immune status of heifers in field conditions during the periparturient period. Veterinary. Research 35 539550Google Scholar
Piccinini, R, Binda, E, Belotti, M, Casirani, G & Zecconi, A 2005 Comparison of blood and milk non-specific immune parameters in heifers after calving in relation to udder health. Veterinary Research 36 747757Google Scholar
Prgomet, C, Sarikaya, H, Bruckmaier, RM & Pfaffl, MW 2005 Short-term effects on pro-inflammatory cytokine, lactoferrin and CD14 mRNA expression levels in bovine immunoseparated milk and blood cells treated by LPS. Journal of Veterinary Medicine Series a-Physiology Pathology Clinical Medicine 52 317324Google Scholar
Rivas, AL, Quimby, FW, Blue, J & Coksaygan, O 2001 Longitudinal evaluation of bovine mammary gland health status by somatic cell counting, flow cytometry, and cytology. Journal of Veterinary Diagnostic Investigation 13 399407CrossRefGoogle ScholarPubMed
Trevisi, E, Zecconi, A, Bertoni, G & Piccinini, R 2010 Blood and milk immune and inflammatory profiles in periparturient dairy cows showing a different liver activity index. Journal of Dairy Research 77 310317Google Scholar
Trevisi, E, Amadori, M, Cogrossi, S, Razzuoli, E & Bertoni, G 2012 Metabolic stress and inflammatory response in high-yielding, periparturient dairy cows. Research in Veterinary Science 93 695704Google Scholar
Waldvogel, AS, Hediger-Weithaler, BM, Eicher, R, Zakher, A, Zarlenga, DS, Gasbarre, LC & Heussler, VT 2000 Interferon-gamma and interleukin-4 mRNA expression by peripheral blood mononuclear cells from pregnant and non-pregnant cattle seropositive for bovine viral diarrhea virus. Veterinary Immunology and Immunopathology 77 201212Google Scholar
Supplementary material: PDF

Zecconi et al. supplementary material

Tables S1-S4

Download Zecconi et al. supplementary material(PDF)
PDF 471.9 KB