Hair cortisol concentrations were not impacted by collection region in cross-bred Angus steers

Hair cortisol has been used to evaluate long-term stress in cattle. However, hair sample collection regions vary between studies. The objective of this experiment was to evaluate hair cortisol concentrations in four different anatomical locations on cattle to determine if cortisol concentrations differed between sampling regions or sides. Sixteen crossbred black Angus steers (≥ 24 months of age, 800 ± 10 kg) were utilized in this experiment. Hair samples were collected from 1) left hip, 2) left shoulder, 3) right hip, and 4) right shoulder of each steer (4 samples/animal). Hair samples were analyzed for cortisol using an ELISA kit. A linear mixed effect model and type III analysis of variance were fitted for statistical analysis using R software, with steer being the whole plots and location of hair collection being the split plots. Hair cortisol concentration was similar (P > 0.10) across different collection regions. However, the study had a lower statistical power and therefore results should be interpreted cautiously. Hair cortisol analysis is a useful tool to evaluate long-term stress in animals; understanding the consistency of hair cortisol concentrations between body regions can influence how sample collection occurs in future studies. The current study indicated that hair sampled from left hip, left shoulder, right hip, and right shoulder of the cattle have similar hair cortisol levels under these conditions. The present study was limited by sample size, and more studies that assess variations in hair cortisol to due sampling location, age, and breed are needed.

1 Introduction

An animal’s well-being and stress conditions are important factors when considering optimal welfare and are often difficult to quantify (Staufenbiel et al., 2013). A well-known physiological response to stress is the secretion of adrenocorticotropic hormone by the anterior pituitary gland, which stimulates the adrenal cortex and results in the secretion of cortisol (Roth, 1985). The adrenal cortex releases cortisol into the blood, and most cortisol is bound to corticosteroid-binding globulin and albumins, and only 3-5% of cortisol remains unbound in the blood (Bozovic et al., 2013). Unbound cortisol traveling in the blood can diffuse through the basolateral membrane of the salivary gland acini and be secreted with saliva (Bozovic et al., 2013). The release of cortisol in blood and the diffusion of cortisol into saliva allow for the evaluation of cortisol concentration from serum and saliva to characterize stress response (Bozovic et al., 2013; Hellhammer et al., 2009; Saco et al., 2008). In general, saliva has a much lower cortisol concentration than blood, but it can well represent the change in unbound cortisol concentration in the blood (Ljubijankić et al., 2008; Vining et al., 1983). However, cortisol concentration in serum and saliva is only suitable for testing acute changes in cortisol concentrations as it only captures the cortisol concentration at the time of collection (Russell et al., 2012). In addition, the acute stress that was introduced to the animals during saliva and blood collection can elevate salivary and serum cortisol concentrations, which may influence the reliability of the analysis (Hopster et al., 1999; van Eerdenburg et al., 2021).

To evaluate chronic stress in animals, hair sample collection and cortisol analysis have been proposed to reflect long-term stress (Russell et al., 2012). Hair cortisol concentrations were first assessed by Koren et al. (2002) in rock hyrax and have emerged to be one of the popular non-invasive tools to evaluate chronic/long-term stress (Greff et al., 2019; Russell et al., 2012; Staufenbiel et al., 2013). The mechanism of cortisol depositing in the hair was proposed by Boumba et al. (2006), where the unbound cortisol in the blood enters the medulla of the hair shaft via passive diffusion, so the hair cortisol can reflect the free cortisol concentration instead of the total cortisol in the serum (Boumba et al., 2006; Russell et al., 2012). This hypothesis was supported by another study conducted on Rhesus monkeys, where greater hair cortisol was observed in monkeys that experienced prolonged stressful experiences (Davenport et al., 2006). As free cortisol diffuses into hair and hair does grow at a constant rate, hair cortisol analysis can provide information on average long-term free cortisol concentrations (Staufenbiel et al., 2013).

Many studies have utilized hair cortisol concentration to evaluate long-term stress in cattle, but the hair collection region varies across studies (Heimbürge et al., 2020; Tallo-Parra et al., 2018; Vesel et al., 2020). Moya et al. (2013) reported that the cortisol concentrations in hair from the head, neck, and shoulder are lower than in hair from the tail, but no differences were found between the head, neck, and shoulder in beef steers. In dairy cattle, Burnett et al. (2014) reported that hair from the tail region has greater cortisol than hair from the shoulder region, but no differences in cortisol between the hip and top line areas were identified (Burnett et al., 2014). However, past experiments have not compared the cortisol concentrations between the hair samples on the left and right sides of the animal. When branding or restraining animals without a squeeze chute, obtaining hair samples from a specific fixed location can be challenging. Thus, the ability to evaluate hair cortisol concentrations on either side or region of an animal is valuable when conducting research in a field setting. We hypothesized that the side (left vs. right) and region (shoulder vs. hip) of hair samples would not impact hair cortisol concentration. Therefore, the objective of this study was to evaluate hair cortisol concentration in hair samples collected from four site-specific external anatomical regions in beef cattle.

2 Materials and methods

2.1 Ethical statement

Prior to the initiation of this experiment, all animal care, handling, and procedures described herein were approved by the Colorado State University Animal Care and Use Committee (IACUC #1555).

2.2 Sample size calculation

A sample size calculation was conducted using PROC POWER in SAS 9.4 (SAS, 2023). Using a power of 0.8, mean difference of 6, SD of 0.5, correlation of 0.2, and alpha of 0.5 (Burnett et al., 2014), the estimated n pairs required for this study is 11 (11 animals with paired measurements on each). The sample size was also evaluated using two different scenarios (poorly correlated: 0.2; highly correlated 0.9) and if the standard deviation was twice what previous literature has shown (Burnett et al., 2014). Given the lack of data available in beef cattle, we decided to utilize 16 cattle in this study.

2.3 Sample collection and cortisol analysis

Sixteen crossbred black Angus steers (greater than 24 months of age, 800 ± 10 kg) previously fitted with ruminal cannulas one year prior were utilized in this experiment. All steers were group housed in one unshaded steel-paneled pen equipped with automatic waterers, received medium grass hay diet, and were managed as a group for approximately 6 months prior to the initiation of this experiment. Upon experiment initiation, all steers were moved to a working facility and restrained in a hydraulic chute during sample collection. A split-plot design was used in this experiment, where individual steer is classified as the whole plot and hair collection locations are the split-plots. Hair samples were collected from each steer in July, 2022, according to procedures described by Baier et al. (2019) with slight modifications. Briefly, hair samples were collected from 4 different locations of the animal: 1) left hip, 2) left shoulder, 3) right hip, and 4) right shoulder (4 samples/animal; Figure 1). Before hair sample collection, regions of interest were cleaned using a curry comb. A 5 x 5 cm² of hair was collected from regions of interest using electric hair clippers fitted with a #40 blade. Sample collection took approximately 5 minutes per steer. Curry combs and clippers were cleaned with 70% isopropyl alcohol prior to use and between hair collections in different regions. Hair samples were kept in opaque containers at room temperature to avoid contact with direct sunlight until analysis.

Figure 1

Figure 1. Hair sample collection regions: left shoulder, left hip, right shoulder, and right hip.

Hair cortisol concentration was determined using methods described by Greff et al. (2019) with slight modification. Prior to cortisol analysis, hair samples were submerged in ultrapure water and agitated overnight to remove debris. Hair samples were then air-dried and washed with isopropanol 3 times. Hair samples were air dried again and ground to powder form using mortar and pestle. Approximately 40 mg of ground hair sample and 2 mL methanol were added into an 8 mL glass vial. The mixture was sonicated for 30 minutes and incubated in a hot water shaker at 50 °C and 300 rpm for 18 h. Supernatant was transferred to a 2 mL microcentrifuge tube and centrifuged at 13,000 x g for 5 minutes. The supernatant was then extracted and dried on a centrifugal vacuum concentrator (CentriVap, Labconco, Kansas City, MO) at 50 °C for 4–5 hours. Dried supernatant was reconstituted with 200 µL ELISA Buffer (Cayman 400060; Cayman Chemical Company, MI, USA). Cortisol analysis was conducted in triplicate per sample using Cortisol ELISA kit (Cayman 500360; Cayman Chemical Company, MI, USA). In brief, 100 µL of ELISA Buffer, 50 µL of sample, 50 µL of Cortisol-AChE Tracer, and 50 µL of Cortisol ELISA Monoclonal Antibody were added into the well and incubated overnight at 4 °C with cover. Cortisol ELISA Standard (Cayman 400363; Cayman Chemical Company, MI, USA) was used as an internal standard and the recovery rates ranging between 95-99%. The wells were emptied and rinsed with wash buffer 5 times. 200 µL of Ellman’s Reagent was added into each well and the plate was incubated in the dark at room temperature for 90–120 minutes. The plate was read at 405 nm wavelength using plate reader.

2.4 Statistical analysis

All data in this study were analyzed using R statistical software version 4.3.2 (R Core Team, 2023) in R studio version 2023.12.1 + 402. Three observations were removed from analysis due to a high coefficient of variation between triplicates (greater than 16% coefficient of variation) and falling outside of the linear range of the standard curve for cortisol analysis. One observation was removed from the study after normality test and Cook’s distance test, which indicated that the removed observation, which had a 1.0 Cook’s distance, was an outlier and highly influential to the statistical model (Dohoo et al., 2014). A linear mixed model (package lme4 ver. 1.1–32 and lmerTest ver 3.1-3; Bates et al., 2015; Kuznetsova et al., 2017) was fitted with REML to investigate the effect of side (left vs. right) and region (shoulder vs. hip) on hair cortisol concentration, with animal as random variable. The main effect of side and region, and the interaction between side and region, were analyzed using type III analysis of variance using Kenward-Roger’s method (package car ver 3.1-1; John and Sanford, 2019). Significant differences were determined at P-value ≤ 0.05.

3 Results and discussion

In a biological setting, the main function of cortisol release is to stimulate additional energy release and usage within the body to overcome a stressful event (Bozovic et al., 2013). The acute elevation of cortisol is generally harmless, but prolonged exposure to cortisol (e.g., during chronic stress) can shift the energy away from biological functions such as regulating fat and glucose metabolism and blood pressure, which can negatively affect animal welfare (Moberg, 2000; Staufenbiel et al., 2013). Additionally, stress in production animals negatively affects dry matter intake, immunity, and meat quality (Llonch et al., 2016; Braun et al., 2017; Xing et al., 2019). Therefore, cortisol quantification can be used as a tool to study stress in production animals to improve management practices for better animal welfare.

This experiment aimed to evaluate the hair cortisol concentration in four different anatomical locations on cattle to determine if cortisol concentrations differed between sampling regions and or sampling sides. The cortisol concentrations determined by ELISA, in this experiment, should be considered relative differences between variables rather than absolute concentrations (Saluti et al., 2022 and Castellani et al., 2025). The mean ± SEM hair cortisol concentrations (pg/mL) were 293.2 ± 20.5, 273.9 ± 20.5, 272.3 ± 20.4, 294.2 ± 20.4, for the left side, right side, hip, and shoulder regions, respectively (Figure 2). There was no difference in hair cortisol concentrations between the left and right sides of the animal under these study conditions (P = 0.25). Additionally, samples collected from the hip region did not differ from samples collected from the shoulder region (P = 0.19). The interaction between the side (left vs. right) and region (hip vs. shoulder) was not significant (P = 0.20). Burnett et al. (2014) evaluated hair cortisol concentration in dairy cattle and reported no difference among the shoulder, top line, and hip; the authors utilized 18 dairy cows in their study, with a mean ranging from 4.8-5.8 pg/mL, and a standard error mean of 1.1 (Burnett et al., 2014). The mean hair cortisol concentration in the current study was 283 pg/mL (or 1.4 pg/mg), which was higher compared to hair cortisol concentration reported in Burnett et al. (2014), but lower than cortisol concentration reported by Moya et al. (2.0 pg/mg; 2013), Creutzinger et al. (5 pg/mg; 2017), and Baier et al. (0.98-7.57 pg/mg; 2019). However, calves in the Creutzinger et al. (2017) study were 47 days, cattle in the Baier et al. (2019) study ranged from 1–9 years of age, and the Moya et al. (2013) study had 313 kg cattle. Although, the mean hair cortisol concentrations reported in the present study are within the range reported by Moya et al. (0.31-5.31 pg/mg; 2013). Observed differences in the present study versus previous studies may be due to a small sample size in the present study. However, it is worth noting that the difference in cattle age between studies makes it difficult to compare hair cortisol concentrations between studies, as hair cortisol concentrations can vary by age and the relationship is not always straightforward (Heimbürge et al., 2019). Previous studies in rabbits (26 body sites; n = 8, mean = 2.12 pg/mg, SEM = 0.05), polar bears (rump, neck, shoulder, and abdomen; n = 15, mean = 0.48 pg/mg, SEM = N/A), and coyotes (above tail, abdomen, hips, mid-back, neck, and shoulders; n = 12, mean = 16.6 ng/g, SEM = 0.5) also reported no differences in cortisol concentration in hair collected from different collection regions (Comin et al., 2012; Macbeth et al., 2012; Schell et al., 2017). Similar to our findings, these previous studies found that hair cortisol concentrations did not differ between collection regions and had smaller sample sizes (Comin et al., 2012; Macbeth et al., 2012; Schell et al., 2017); however, our study had a lower power. A post hoc power calculation was conducted using mean, SD, and correlation from the current study and determined that the power in the current study was 0.114. The difference between the ad hoc power and the post hoc power calculations in the present study was due to a larger standard deviation (approximately 90 pg/mL) in the current study compared to the SD (0.5 pg/mL) from Burnett et al. (2014), which was the study used for power calculation prior to the initiation of this experiment. In contrast, a study conducted by Moya et al. (2013) reported greater hair cortisol concentration in the tail compared to head and shoulder, and greater cortisol concentration in hair from neck compared to the shoulder in beef cattle (n = 12, mean = 2.35 pg/mg, SEM = 0.176). Another study conducted in pigs found greater hair cortisol concentrations in dorsolumbar compared to craniodorsal sampling regions (Casal et al., 2017). In horses, hair samples from the mane were reported to have greater hair cortisol concentrations than tail hair samples (Duran et al., 2017). The current study did not include hair from the tail and neck region for hair cortisol concentration evaluation, which is a limitation. To better understand hair cortisol concentration variation by region, future studies should include multiple anatomical locations. Although we did not find a difference in location or side in the present study, a larger sample size with multiple anatomical locations may be necessary to accurately encompass the population and account for the individual variation within animals, particularly given the variation observed in our study.

Figure 2

Figure 2. Hair cortisol concentrations (pg/mL) from four different anatomical locations in 16 crossbred Angus steers.

Other than the location of hair collection, many factors can also contribute to the differences in hair cortisol concentration. Multiple intrinsic and external conditions such as breed, sex class, age, environment, hair color, and physiological state can influence cortisol concentrations (Burnett et al., 2014; Braun et al., 2017; Baier et al., 2019; Idris et al., 2021). Baier et al. (2019) reported a positive correlation between hair cortisol concentration and hair length in cattle, with a mean of 6.47 pg/mg, n = 18, and SEM = 1.15. Furthermore, Baier et al. (2019) also found that older cattle had higher hair cortisol concentrations. In contrast, the hair cortisol concentrations were similar across different portions of the hair shaft and different hair segments in monkeys (n = 20, mean = 110.3 pg/mg, SEM = 10.2; Davenport et al., 2006). The absence of a difference could also be age dependent. Hayashi et al. (2021) reported that hair from the hip had a higher cortisol concentration than the shoulder in six-week-old calves; however, this difference was not detected in 24-week-old calves (n = 21, mean = 5.2 pg/mg, SEM = 0.2). Moreover, it has been reported that time of sampling and hair color can influence hair cortisol concentration (Baier et al., 2019). Management practices have also been shown to influence hair cortisol concentrations. For example, high-concentrate diets have been associated with decreased ruminal pH, which, in extreme cases, may induce stress, as indicated by elevated stress biomarkers in blood serum in feedlot conditions (Chen et al., 2021). Conversely, high-fiber diets have been observed to reduce overall serum cortisol levels, likely due to delayed peaks in glucose and insulin throughout the day, as reported in studies on gilts (Rushen et al., 1999). Additionally, heat stress has been shown to significantly elevate cortisol levels, with cattle exposed to high ambient temperatures displaying increased concentrations of cortisol metabolites in various body fluids, including hair (Idris et al., 2021). Poor handling practices exacerbate these cortisol spikes (Hemsworth et al., 2011). Moreover, reduced water consumption and feed intake due to heat stress can further elevate cortisol levels and other metabolic markers (Marques et al., 2019). Thus, several management factors can influence total cortisol concentrations and may therefore influence hair cortisol levels, although further research is needed to confirm this. These studies underlined the complexity involved when quantifying cortisol, thus it is critical to acknowledge that the quantification of cortisol as an indicator of stress requires the consideration of multiple internal and external conditions.

4 Applications

Evaluation of stress is essential to assess the well-being of the animals, and utilizing proper analysis tools is important to determine the stress status in the animals. Cortisol concentrations from hair sampled from different sides of the cattle, as well as hip and shoulder regions, did not differ in this experiment. The present study did not find a statistical difference in average hair cortisol concentrations between the left hip, right hip, left shoulder, and right shoulder in 24-month-old crossbreed Angus steers under these study conditions; however, results should be interpreted with caution due to low statistical power. More studies investigating hair sampling location, age, and breed are necessary to validate the use of hair cortisol concentrations as an indicator of chronic stress in livestock. Given the small sample size and individual animal variation in the present study, more studies to validate location should be conducted.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The animal study was approved by Colorado State University Institutional Animal Care and Use Committee. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

HL: Formal Analysis, Writing – original draft, Writing – review & editing. CO: Writing – original draft, Writing – review & editing. DV: Writing – original draft, Writing – review & editing. LK: Investigation, Writing – review & editing. JC: Investigation, Resources, Writing – review & editing. LE-C: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing. TE: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing. MC: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. The authors would like to thank the Patten-Davis Foundation Y-Cross funds for making this project possible.

Acknowledgments

The authors acknowledge the ARDEC Livestock Experimental Staff for excellent husbandry and care of animals, as well as for all the practical help throughout the experiment.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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