Cortisol is the primary effector molecule of the hypothalamic–pituitary–adrenal (HPA) axis involved in the response to stressors (Kirovski et al. Reference Kirovski, Snoj, Nedic, Nedic, Cebulj-Kadunc and Kobal2014). The determination of cortisol in blood is a widely used method (Sgorlon et al. Reference Sgorlon, Fanzago, Guiatti, Gabai, Stradaioli and Stefanon2015), but for cows it is a highly invasive technique that may induce activation of the HPA axis, increasing plasma cortisol level (Rushen et al. Reference Rushen, de Passillé, von Keyserlingk and Weary2008).
It is known that steroid hormones can permeate cell membranes and may cross the epithelial blood-milk barrier of mammary gland alveoli (Rushen et al. Reference Rushen, de Passillé, von Keyserlingk and Weary2008), showing a high correlation between milk and plasma cortisol concentrations after ACTH administration (Thinh et al. Reference Thinh, Yoshida, Long, Yusuf and Nakao2011). Considering that milking for dairy cows is a routine process, milk might be a non-invasive alternative to blood in bovine HPA axis evaluation. However, the analysis of milk cortisol in field conditions is necessary before it could be claimed as a reliable biomarker of an animal's ability to cope with environmental stimuli. Therefore, in the present study the variations in milk cortisol concentrations in response to relocation stress were analysed.
Materials and methods
The measure of variations of milk cortisol concentrations in Holstein Friesian (HF) and Norwegian Red (NR) cows exposed or not to perturbations was performed in two experiments. In study 1 the inter-day variations of cortisol concentration were evaluated. For this, milk samples were collected for 3 consecutive days from 20 cows during morning (6:00 AM) and afternoon (6:00 PM) milking. In study 2, cows were relocated from the Post-partum group to the group of Fresh cows (relocation PF), from the group of Fresh cows to the High production group (relocation FH) and from the High production group to the Low production group (relocation HL). Milk samples from these animals were collected individually once a day during the evening milking (6:00 PM) for five consecutive days, starting from 2 d before the relocation, which occurred on the morning of day 3. Cortisol in milk was analysed as reported by Gabai et al. (Reference Gabai, Mollo, Marinelli, Badan and Bono2006). Detailed information about animals, experimental procedures, ethical statement and statistical analysis are reported in the Supplementary File as online Supplementary Materials and Supplementary Table S1.
Results and discussion
In study 1, when no apparent environmental perturbation occurred, significant variations of milk cortisol concentrations between- and within-day were not observed (Fig. 1, online Supplementary Table S2). Despite the demonstration that environmental conditions and management can affect the circadian rhythm of cortisol secretion others (Mormede et al. Reference Mormede, Andanson, Auperin, Beerda, Guemene, Mamkvist, Manteca, Manteuffel, Prunet, van Reenen, Richard and Veissier2007; Ogino et al. Reference Ogino, Matsuura, Yamazaki, Irimajiri, Suzuki, Kushibiki, Singu, Kasuya, Hasegawa and Hodate2014) did not detect a rhythm in cortisol release in well fed, free ranging cows, while they observed a clear circadian rhythm in cows under tie-stall and restricted feeding conditions. Under our experimental conditions, as in most commercial farms, animals were free ranging and nutritional requirements were adequately met. Likely, these conditions did not favour a circadian rhythm of cortisol release and, considering that milk cortisol reflects plasma free cortisol variations between two consecutive milking (Shutt & Fell, Reference Shutt and Fell1985), this led to the lack of difference in milk cortisol concentrations between morning and afternoon milking. However, these observations cannot be generalised and within-day cortisol release should be also analysed under different environmental and farming situations.
The significant increase (P < 0·01) in milk cortisol concentrations on days 3, 4 and 5 (Table 1), observed in Study 2, suggests that relocation is a trigger for the HPA axis in the bovine species. Indeed, Gupta et al. (Reference Gupta, Earley, Ting and Crowe2005) observed a significant increase in plasma cortisol in steers after repeated regrouping and relocation. In lactating cows, the increase in plasma cortisol induced by relocation is the most likely explanation for the subsequent increase in milk cortisol.
HF, Holstein Frisian; NR, Norwegian Red; PF: from postpartum to fresh cows; FH: from fresh to high production cows; HL: from high production to low production cows; Primiparous: first calving cows; Pluriparous: second and third calving cows; ns: not significant; values within columns with different letters A, B, C differ significantly, P < 0·01.
The differences in milk cortisol concentrations following the relocations can hardly be explained by differences in milk yield. Indeed, milk yield was affected (P < 0·01) by variables related to the stage of lactation (production group). On the contrary, none of the variables related to the stage of lactation showed any effect on milk cortisol concentrations. Fukasawa & Tsukada (Reference Fukasawa and Tsukada2010) reported that fresh cows showed significantly higher milk cortisol concentrations in comparison to mid and late lactating cows, thus suggesting that the stage of lactation can affect milk cortisol concentrations. However, in the study of Fukasawa & Tsukada (Reference Fukasawa and Tsukada2010) the group of fresh cows included animals between 7 and 90 DIM (days in milking), while in Study 2 of this paper all animals in the PF group were beyond 50 DIM.
In addition, our previous observations (Gabai, unpublished data), indicate that milk cortisol concentrations are significantly higher (P < 0·01) in the first week postpartum (1·52 ± 0·14 ng/ml), decrease by the second week of lactation (0·86 ± 0·12 ng/ml) and then remain stable as far as day 30 after parturition (0·83 ± 0·12 ng/ml). Moreover, potential effects on milk cortisol related to mammary inflammation can be excluded, as SCC in our animals was lower than 200 000 cells/ml and an increase in milk cortisol concentration can be only observed when SCC is higher than 400 000 cells/ml (Sgorlon et al. Reference Sgorlon, Fanzago, Guiatti, Gabai, Stradaioli and Stefanon2015). Thus, relocation was the prominent stimulus for HPA activation and milk cortisol increase.
Milk yield showed a significant (P < 0·01) increase on day 3 followed by a decrease on days 4 and 5 (Table 1). The transient increase in milk yield could be explained by the positive effect of cortisol on glycaemia (Sgorlon et al. Reference Sgorlon, Colitti, Asquini, Ferrarini, Pallavicini and Stefanon2012), possibly related to increased peripheral gluconeogenesis. However, this temporary increase in milk yield lasted only 1 d and then decreased. The effect of cortisol on milk yield is controversial, as most information derives from exogenous ACTH/glucocorticoids administration (van der Kolk, Reference Van der Kolk1990). However, stress and glucocorticoids may affect milk yield by different mechanisms (Silanikove et al. Reference Silanikove, Shamay, Shinder and Moran2000).
Despite the two breeds being present on the same farm under the same environmental conditions, breed differences in milk cortisol were not observed in either study. Neither Parity nor the Breed × Parity interaction influenced milk cortisol concentrations. However, we observed that the extent of the response to the environmental challenge was very variable among cows and, in our opinion, this observation deserves further consideration. Here, the reduced number of animals does not allow us to identify subpopulation of cows with different response intensity. In a previous work (Sgorlon et al. Reference Sgorlon, Fanzago, Guiatti, Gabai, Stradaioli and Stefanon2015), we observed a significant difference in milk cortisol concentrations between Italian Holstein and Italian Simmental cows and hypothesised that the different ability to cope with milk yield could explain, at least in part, that difference. It is important to consider that, in that previous work, milk cortisol was measured in animals belonging to fourteen farms, and that one breed only was present in each farm. Indeed, mean milk cortisol concentrations were different among farms and Holstein herds did not necessarily show the higher cortisol concentrations. This observation suggests that different environmental conditions can affect the ‘basal’ HPA axis activity, and superimpose the genetic background (Mormede et al. Reference Mormede, Andanson, Auperin, Beerda, Guemene, Mamkvist, Manteca, Manteuffel, Prunet, van Reenen, Richard and Veissier2007).
Up to now, the limited amount of data available on milk cortisol concentrations does not allow the identification of a threshold to define cows’ wellbeing. In cattle, the function of the HPA axis is not well characterised. Studies on rhythmicity, responses to pharmacological treatments and to chronic stress led to inconsistent results and available data are far from conclusive (Mormede et al. Reference Mormede, Andanson, Auperin, Beerda, Guemene, Mamkvist, Manteca, Manteuffel, Prunet, van Reenen, Richard and Veissier2007). Therefore, more studies are needed for better understanding of both environmental and genetic factors affecting milk cortisol concentrations. However, based on the results of this work, cortisol measurement in milk samples collected during consecutive days can be considered as a suitable biomarker to assess the individual HPA response of dairy cows to the same short/medium-term environmental challenge and the overall conditions of the herd.
Further studies are required to investigate if milk cortisol can be useful for prediction of animals with an increased risk of developing diseases and to aid the selection of more resilient animals.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0022029916000790.
This research was funded by the Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università di Udine. Project BRAIN. The study was supported by the EU COST Action FA1308 ‘DairyCare’.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
N. P. participated to the study design, sample collection, data analysis and manuscript preparation; G. G. participated in drafting the manuscript; B. S. participated in conceiving the study and drafting the manuscript; L. D. D. carried out the immunoassays; S. S. participated in conceiving and designing the study, collecting samples and had major responsibilities in data analysis and drafting the manuscript.