Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-26T20:42:31.003Z Has data issue: false hasContentIssue false
  • English
  • Français

Mediation analysis to estimate direct and indirect milk losses associated with bacterial load in bovine subclinical mammary infections

Published online by Cambridge University Press:  29 February 2016

J. Detilleux ,
L. Theron ,
J.-N. Duprez ,
E. Reding ,
N. Moula ,
M. Detilleux ,
C. Bertozzi ,
C. Hanzen  and
J. Mainil
J. Detilleux*
Affiliation:
Department of Animal Production, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
L. Theron
Affiliation:
Large Animal Clinic, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
J.-N. Duprez
Affiliation:
Department of Parasitic and Infectious diseases, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
E. Reding
Affiliation:
Association Wallonne de l’Elevage, 4 rue de Champs Elysées, 5590 Ciney, Belgium
N. Moula
Affiliation:
Department of Animal Production, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
M. Detilleux
Affiliation:
Department of Animal Production, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
C. Bertozzi
Affiliation:
Association Wallonne de l’Elevage, 4 rue de Champs Elysées, 5590 Ciney, Belgium
C. Hanzen
Affiliation:
Large Animal Clinic, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
J. Mainil
Affiliation:
Department of Parasitic and Infectious diseases, Farah Research Centre from the Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, 4000 Liège, Belgium
*
†E-mail: jdetilleux@ulg.ac.be
Get access

Abstract

Milk losses associated with mastitis can be attributed to either effects of pathogens per se (i.e. direct losses) or to effects of the immune response triggered by the presence of mammary pathogens (i.e. indirect losses). Test-day milk somatic cell counts (SCC) and number of bacterial colony forming units (CFU) found in milk samples are putative measures of the level of immune response and of the bacterial load, respectively. Mediation models, in which one independent variable affects a second variable which, in turn, affects a third one, are conceivable models to estimate direct and indirect losses. Here, we evaluated the feasibility of a mediation model in which test-day SCC and milk were regressed toward bacterial CFU measured at three selected sampling dates, 1 week apart. We applied this method on cows free of clinical signs and with records on up to 3 test-days before and after the date of the first bacteriological samples. Most bacteriological cultures were negative (52.38%), others contained either staphylococci (23.08%), streptococci (9.16%), mixed bacteria (8.79%) or were contaminated (6.59%). Only losses mediated by an increase in SCC were significantly different from null. In cows with three consecutive bacteriological positive results, we estimated a decreased milk yield of 0.28 kg per day for each unit increase in log2-transformed CFU that elicited one unit increase in log2-transformed SCC. In cows with one or two bacteriological positive results, indirect milk loss was not significantly different from null although test-day milk decreased by 0.74 kg per day for each unit increase of log2-transformed SCC. These results highlight the importance of milk losses that are mediated by an increase in SCC during mammary infection and the feasibility of decomposing total milk loss into its direct and indirect components.

Keywords

tolerancebovinemediation analysismilk lossmastitis
Type
Research Article
Information
animal , Volume 10 , Issue 8 , August 2016 , pp. 1368 - 1374
Copyright
© The Animal Consortium 2016 

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

Albert, JM and Nelson, S 2011. Generalized causal mediation analysis. Biometrics 67, 1028–1038.Google Scholar
Burton, JL and Erskine, RJ 2003. Immunity and mastitis. Some new ideas for an old disease. The Veterinary Clinics Food Animal Practice 19, 1–45.Google Scholar
Burvenich, C, Paape, MJ, Hill, AW, Guidry, AJ, Miller, RH, Heyneman, R, Kremer, WD and Brand, A 1994. Role of the neutrophil leucocyte in the local and systemic reactions during experimentally induced E. coli mastitis in cows immediately after calving. Veterinary Quartely 16, 45–50.Google Scholar
Capuco, AV, Paape, MJ and Nickerson, SC 1986. In vitro study of polymorphonuclear leukocyte damage to mammary tissue of lactating cows. American Journal of Veterinary Research 47, 663–669.Google Scholar
Daniel, RM, De Stavola, BL, Cousens, SN and Vansteelandt, S 2015. Causal mediation analysis with multiple mediators. Biometrics 71, 1–14.Google Scholar
de Haas, Y, Barkema, HW and Veerkamp, RF 2002. The effect of pathogen specific clinical mastitis on the lactation curve for somatic cell count. Journal of Dairy Science 85, 1314–1323.Google Scholar
Detilleux, J, Kastelic, JP and Barkema, HW 2015. Mediation analysis to estimate direct and indirect milk losses due to clinical mastitis in dairy cattle. Preventive Veterinary Medicine 118, 449–456.Google Scholar
Detilleux, JC, Kehrli, ME Jr., Stabel, JR, Freeman, AE and Kelley, DH 1995. Study of immunological dysfunction in periparturient Holstein cattle selected for high and average milk production. Veterinary Immunology and Immunopathology 44, 251–267.Google Scholar
Detilleux, J, Theron, L, Duprez, J-N, Reding, E, Humblet, M-F, Planchon, V, Delfosse, C, Bertozzi, C, Mainil, J and Hanzen, C 2013. Structural equation models to estimate risk of infection and tolerance to bovine mastitis. Genetics Selection Evolution, doi: 10.1186/1297-9686-45-6, Published online by BioMed Central 6 March 2013.Google Scholar
Dohoo, I 2001. Setting SCC cut points for cow and herd interpretation. Paper present at the 40th Annual Meeting of the National Mastitis Council, 11 to 14 February 2001, Reno, Nevada.Google Scholar
Fritz, MS and MacKinnon, DP 2007. Required sample size to detect the mediated effect. Psychological Science 18, 233–239.Google Scholar
Gröhn, YT, Wilson, DJ, Gonzalez, RN, Hertl, JA, Schulte, H, Bennett, G and Schukken, YH 2003. Effect of pathogen-specific clinical mastitis on milk yield in dairy cows. Journal of Dairy Science 87, 3358–3374.Google Scholar
Hagnestam-Nielsen, C, Emanuelson, U, Berglund, B and Strandberg, E 2009. Relationship between somatic cell count and milk yield in different stages of lactation. Journal of Dairy Science 92, 3124–3133.Google Scholar
Halasa, T, Nielen, M, De Roos, APW, Van Hoorne, R, de Jong, G and Lam, TJGM 2009. Production loss due to new subclinical mastitis in Dutch dairy cows estimated with a test-day model. Journal of Dairy Science 92, 599–606.Google Scholar
Hertl, JA, Schukken, YH, Welcome, FL, Tauer, LW and Gröhn, YT 2014. Pathogen-specific effects on milk yield in repeated clinical mastitis episodes in Holstein dairy cows. Journal of Dairy Science 97, 1465–1480.Google Scholar
Judd, CM and Kenny, DA 1981. Process analysis: estimating mediation in treatment evaluations. Evaluation Review 5, 602–619.Google Scholar
Kause, A, van Dalen, S and Bovenhuis, H 2012. Genetics of ascites resistance and tolerance in chicken: a random regression approach. G3 Genes Genomes Genetics 2, 527–535.Google Scholar
Kenny, DA and Judd, CM 2014. Power anomalies in testing mediation. Psychological Science 25, 334–339.Google Scholar
Lauzon, K, Zhao, X, Bouetard, A, Delbecchi, L, Paquette, B and Lacasse, P 2005. Antioxidants to prevent bovine neutrophil-induces mammary epithelial cell damage. Journal of Dairy Science 88, 4295–4303.Google Scholar
Leitner, G, Yadlin, B, Glickman, A, Chaffer, M and Saran, A 2000. Systemic and local immune response of cows to intramammary infection with Staphylococcus aureus . Research in Veterinary Science 2000 (69), 181–184.Google Scholar
Lin, LK 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255–268.Google Scholar
McDougall, S, Bryan, MA and Tiddly, RM 2009. Effect of treatment with the nonsteroidal anti-inflammatory meloxicam on milk production, somatic cell count, probability of re-treatment, and culling of dairy cows with mild clinical mastitis. Journal of Dairy Science 92, 4421–4431.Google Scholar
Mehrzad, J, Duchateau, L and Burvenich, C 2005. High milk neutrophil chemiluminescence limits the severity of bovine coliform mastitis. Veterinary Research 36, 101–116.Google Scholar
Preacher, KJ and Kelley, K 2011. Effect size measures for mediation models: quantitative strategies for communicating indirect effects. Psychological Methods 16, 93–115.Google Scholar
Reding, E, Theron, L, Detilleux, J, Bertozzi, C and Hanzen, C 2011. LAECEA: un outil fédérateur à la décision pour le suivi de la santé mammaire dans les élevages bovins laitiers wallons. Paper presented at the 18th Annual Meeting of the 3R Rencontres Recherches Ruminants, Paris, 3 to 4 December 2011, Paris, France.Google Scholar
Reksen, O, Solverod, L and Osteras, O 2007. Relationships between milk culture results and milk yield in Norwegian dairy cattle. Journal of Dairy Science 90, 4670–4678.Google Scholar
Schneider, DS and Aires, JS 2008. Two ways to survive infection: what resistance and tolerance can teach us about treating infectious diseases. Nature Reviews Immunology 8, 889–995.Google Scholar
Seegers, H, Fourichon, C and Beaudeau, F 2003. Production effects related to mastitis and mastitis economics in dairy herds. Veterinary Research 34, 475–491.Google Scholar
Sharma, N, Singh, NK and Bhadwal, MS 2011. A relationship of somatic cell counts and mastitis: an overview. Asian-Australian Journal of Animal Science 24, 429–438.Google Scholar
Ten Have, TR and Joffe, MM 2012. A review of causal estimation of effects in mediation analyses. Statistical Methods in Medical Research 21, 77–107.Google Scholar
Thompson-Crispi, KA, Sewalem, A, Miglior, F and Mallard, BA 2012. Genetic parameters of adaptive immune response traits in Canadian Holsteins. Journal of Dairy Science 95, 401–409.Google Scholar
Tofighi, D and MacKinnon, DP 2011. RMediation: an R package for mediation analysis confidence intervals. Behavior Research Methods 42, 692–700.Google Scholar
VanderWeele, TJ 2012. Invited commentary: structural equation models and epidemiologic analysis. American Journal of Epidemiology 176, 608–612.Google Scholar
VanderWeele, TJ and Vansteelandt, S 2014. Mediation analysis with multiple mediators. Epidemiological Methods 2, 95–115.Google Scholar
Vansteelandt, S and VanderWeele, TJ 2012. Natural direct and indirect effects on the exposed: effect decomposition under weaker assumptions. Biometrics 6, 1019–1027.Google Scholar
Zhao, X and Lacasse, P 2008. Mammary tissue damage during bovine mastitis: causes and control. Journal of Animal Science 86, 57–65.Google Scholar