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. 2014 Oct 11;2(1):cou044. doi: 10.1093/conphys/cou044

Enzyme immunoassays as a method for quantifying hair reproductive hormones in two felid species

C V Terwissen 1,*, G F Mastromonaco 2, D L Murray 1
PMCID: PMC4732485  PMID: 27293665

Enzyme immunoassays were validated for the quantification of reproductive hormones (estrogen, testosterone, and progesterone) in the hair of two felid species. The method provides a tool to potentially determine sex and pregnancy states in wild populations, therefore improving the monitoring of felids that often have low reproductive success in captivity.

Keywords: Canada lynx (Lynx canadensis); domestic cat (Felis catus); estrogen, hair reproductive hormones; progesterone; testosterone

Abstract

Non-invasive monitoring of wild felid reproductive states is important, given that many species reproduce poorly in captivity. Despite extensive work in faecal hormone analysis in felids, continued development of techniques is necessary, particularly with wild populations. In this study, our aims were as follows: (i) biochemical validation of enzyme immunoassays for estrogen, testosterone and progesterone in Canada lynx and domestic cat hair extracts; (ii) assessment of the use of hair reproductive hormones to differentiate between reproductive states (intact, estrus, pregnant and spayed/neutered), using domestic cats as a model; and (iii) assessment of the use of hair reproductive hormones to differentiate between age and sex, accounting for potential regional variability in wild lynx populations. Analysis of hair hormone levels showed prospective value in detecting pregnancy states, with pregnant domestic cats having higher levels of progesterone than spayed females. However, intact and pregnant cats did not differ in progesterone levels. Yet, two female domestic cats had higher levels of hair progesterone following a 38-day oral progestin treatment, perhaps providing a preliminary pharmacological validation of the method. Estrogen and testosterone did not differ statistically according to reproductive states of domestic cats, although intact males had higher levels of hair testosterone than neutered males. When we applied these techniques to lynx fur, we determined that hormone levels were not sufficiently precise to differentiate age classes. Hair reproductive hormone ratios differed between sexes, with the estrogen-to-progesterone ratio demonstrating the highest accuracy in differentiating males from females. Hair hormone levels differed regionally for wild lynx, indicating that spatial variability should be a consideration in wildlife hormone studies spanning large spatial scales. We conclude that use of hair hormone analysis by enzyme immunoassay may hold promise for differentiating sex in felids, but the technique will require further refinement and validation before it can be applied broadly and reliably.

Introduction

Wild cats are among the most endangered and vulnerable group of mammals in the world (Nowell and Jackson, 1996). Wild cats from the genus Lynx are monoestrous, seasonal breeders, with a short breeding season. Canada lynx (Lynx canadensis), which occupy the boreal forest of North America, breed from late February to early April (Quinn and Gardner, 1987; Fanson et al., 2010b). It is understood that lynx productivity is highly correlated with the abundance of their primary prey, snowshoe hare (Lepus americanus), and during periods of high hare density, female lynx can reach sexual maturity at an accelerated rate (Quinn and Gardner, 1987). Lynx productivity is highest when snowshoe hare populations are at the peak of their 10 year numerical cycle and lowest when hare populations are at their nadir (Brand et al., 1976). However, there is evidence that cyclic dynamics vary regionally in lynx, meaning that some populations can be numerically out of phase with other populations in other regions (Krebs et al., 2013). It follows that such variation means that at a given time there should be regional differences in lynx reproductive states. Canada lynx are an important species for conservation, but the variability in their population dynamics provides challenges to population management. In fact, local lynx populations can be overexploited during cyclic lows when recruitment is minimal or non-existent (Bailey et al., 1986; Poole, 2003), meaning that tools need to be developed to track their population status and trends effectively.

Hormone analysis can provide valuable information on the basic physiology and overall health of an animal, and specific hormones can be used to measure particular aspects of health (Sheriff et al., 2011). Enzyme immunoassays (EIAs) are one method used for hormone analysis, but pharmacological validation must be carried out for the substrate of choice before the assay is widely adopted (Buchanan and Goldsmith, 2004). For example, studies of reproductive hormones in domestic cats (Felis catus) reveal that oral progestin increases baseline progesterone levels in faeces (Stewart et al., 2010). To our knowledge, however, no similar validation has been attempted for hair reproductive hormone studies despite interest in the use of hair as a medium for hormone analysis.

Reproductive hormones have long been monitored through faecal analysis to provide information on reproductive function (Brown and Wildt, 1997; Dehnhard et al., 2010). These hormones have been used to differentiate between age classes, because juveniles should produce lower levels of hormones than adults. Ratios of reproductive hormones generally serve to determine sex, given that both sexes produce testosterone, progesterone and estrogen (Rolland et al., 2005). This framework has been applied to the determination of age and sex in the faeces of North Atlantic right whales (Eubalaena glacialis, Rolland et al., 2005) and barred owls (Strix varia, Wasser and Hunt, 2005). It follows that as these same hormones are present in hair, then hair hormone analysis can be used to monitor similar reproductive parameters.

Hair hormone analysis has shown increasing popularity in ecology (MacBeth et al., 2010; Brearley et al., 2012; Bryan et al., 2013), although to date the expansion from cortisol to additional steroid hormones, such as reproductive hormones, has been minimally exploited (Stalder and Kirschbaum, 2012). Hair provides a unique option for monitoring hormones, because concentrations in hair are representative of the level in the body during the period of hair growth, and thus, sampling can represent weeks to months of hormone production depending on the length of hair analysed (Sheriff et al., 2011). This provides a longer-term assessment of status than is available using existing methods with blood (day of secretion; Genaro et al., 2007) and faeces (lag of 24–48 h; Fanson et al., 2011). It is thought that hair hormones are incorporated into the hair shaft from the follicle cells via the blood (Gow et al., 2010; Russel et al., 2011), which may provide an additional advantage because increased intra-individual changes in faecal analysis can be attributed to the composition of the gut bacteria (Palme, 2005; Dehnhard et al., 2010). Reproductive hormones have been measured in the hair of rock hyrax (Procavia capensis, Koren et al., 2006), cattle (Bos taurus, Gleixner and Meyer, 1997), humans (Yang et al., 1998) and grizzly bears (Ursus arctos, Bryan et al., 2013), but the present study is the first to quantify these hormones in a felid species.

The objectives of this study were as follows: (i) to validate EIAs biochemically for estrogen (E), testosterone (T) and progesterone (P) in Canada lynx and domestic cat hair extracts; (ii) to assess the use of hair reproductive hormones to differentiate between known reproductive states (intact, estrus, pregnant and spayed/neutered) using domestic cats as a model; and (iii) to assess the use of hair reproductive hormones to differentiate between age and sex, accounting for potential regional variability in wild lynx populations.

Materials and methods

Assay validation

Assay validation was conducted using methods previously described (see Terwissen et al., 2013), with some exceptions. For precision, interassay coefficients of variation were evaluated using faecal extract controls, at 30 and 55–70% binding, loaded in duplicate on each plate. The efficiency of the extraction procedure was analysed using recovery of exogenous hormone at the following concentrations for lynx and domestic cats (E, 5 µl at 48 pg/μl; T, 5 µl at 32 pg/μl; and P, 10 µl at 6 pg/μl).

Study animals

Wild hair samples were collected from lynx pelts at North American Fur Auctions (NAFA) in Toronto and Fur Harvesters Auction (FHA) in North Bay, Canada. All pelts were legally harvested by licensed trappers in the 2008–2009 trapping season and not tanned prior to collection. Peterborough Veterinary Clinic (PVC) in Peterborough, ON, Canada, and Cincinnati Zoo and Botanical Garden, in Cincinnati, OH, USA, provided domestic cat samples. Samples were collected with permission from the cat owners. Animals from PVC were privately owned pets, while those at Cincinnati Zoo were included in studies on felid reproductive biology (see Conforti et al., 2013 for details). Two females were given oral progestin for 38 days as part of these studies. Samples (3 cm × 3 cm; cut down to the skin) were taken from a standardized location for each species (a hindlimb on lynx and a forelimb on domestic cats) using clean gloves and scissors. All samples were placed in envelopes and stored at room temperature until analysis.

Reproductive states: domestic cat

The owners provided the age (6 months to 12 years) and sex of the domestic cats (12 males, of which seven were neutered and five intact; and 27 females, of which 10 were spayed, five intact, five in behavioural estrus and seven pregnant). Individuals that had been spayed or neutered at least 1 year prior to EIA analysis were used to ensure a minimal period of hair growth since castration. Females were classified as in estrus using signs of behavioural estrus (i.e. rolling, peddling of hindfeet, vocalizing; Conforti et al., 2013). Pregnancy was determined during spays performed by a licensed veterinarian or when kittens were reported by owners.

Age, sex and region: lynx

The age of lynx pelts was determined using pelt length (28 juveniles and 45 adults), with juveniles (or kits) having a pelt length <90.5 cm in the west and <81 cm in the east, while adults (or yearlings) had a pelt length >90.5 cm in the west and >82 cm in the east (Quinn and Gardner, 1984; Slough, 1996). The sex of lynx pelts (37 female and 36 male) was determined by amplifying the Y-chromosome-specific Sry locus and Zfx fragment on the X-chromosome (Woods et al., 1999; Ortega et al., 2004; Zigouris et al., 2012). DNA extraction and amplification was performed as per Row et al. (2012), and allele sizes were scored manually with Genemarker version 1.7 (Softgenetics, State College, PA, USA). Lynx samples were classified into region by trap line location (37 east, in Quebec, Ontario and Manitoba; and 36 west, in Yukon and Alaska).

Hair hormone analysis

Hair samples were extracted using methods previously described; see Terwissen et al. (2013). First, hair samples were washed with 100% methanol for 20 s using a spray bottle. Dried samples weighing between 10.4 and 68.0 mg were cut into 0.5 cm pieces into glass scintillation vials. To this, 100% methanol was added proportionally for 0.01 g/ml and extracted for 24 h on a rotator (Argos RotoFlex R2000, Elgin, IL, USA). Following centrifugation (10 min at 2629 g) 750 or 1500 µl of the extracted solution was transferred to a new glass vial and dried down in a fume hood. Samples were reconstituted in 150 µl EIA buffer (0.1 mm sodium phosphate buffer, pH 7.0, containing 9 g of NaCl and 1 g of bovine serum albumin per litre) for a 5-fold concentration for lynx hair E, T and P and domestic cat P, and a 10-fold concentration for domestic cat E and T. Reconstituted samples were sonicated for 20 s in an Elmasonic waterbath (Elma GmbH & Co. KG, Germany) before hormone analysis.

Estrogen, testosterone and progesterone values were quantified using EIAs based on the protocols from C. Munro, UC Davis, and described in detail by Kummrow et al. (2011). The following antibodies were used: estradiol-17β R4972/R0008, pregnane CL425 and testosterone R156/R157 (C. Munro, UC Davis). In brief, microtitre plates were coated with 50 µl of antiserum diluted in coating buffer (50 mm bicarbonate buffer, pH 9.6) and incubated overnight at 4°C. Unbound antiserum was washed from coated plates with 0.15 m NaCl solution containing 0.05% Tween 20. Immediately, 50 µl of reconstituted hair extracts, hormone standards and controls diluted in EIA buffer were added in duplicate, followed by 50 µl of horseradish peroxidase conjugate diluted in EIA buffer. Plates were incubated for 2 h at room temperature. Following incubation, the plates were washed, and 100 µl of substrate solution (50 mm citrate, 1.6 mm hydrogen peroxide and 0.4 mm 2,20-azino-di(3-ethylbenzthiazoline sulfonic acid) diammonium salt, pH 4.0) was added. Absorbance was measured at 405 nm using a spectrophotometer (MRX microplate reader, Dynex Technologies, Chantilly, VA, USA). Hormone levels are presented as mass per gram dry weight.

Statistical analysis

Linear regression analysis was used to determine whether there was a significant relationship between the standard curve and serial dilutions for assay parallelism and hormone added vs. hormone recovered for assay accuracy.

Hair reproductive hormones (E, T and P) were used to determine whether differences in reproductive states (intact, estrus, pregnant and spayed/neutered) could be detected, using domestic cats as a model species, given that considerable reproductive hormone data exist for this species (Swanson et al., 1995; Brown et al., 1996; Brown, 2006). Females given oral progestin treatments were excluded from the analysis. Hormones were log transformed to achieve normality and homogeneity of variance. Comparisons were made using a one-way ANOVA and Tukey's post hoc HSD test. Given unequal sample sizes, each model was validated further using residual plots. Post hoc power analyses were completed using the R package ‘stats: anova.power.test’ (R Core Team, 2013). While there are limitations to the use of post hoc power analysis (Hoenig and Heisey, 2001), this method was used because we were unable to conduct a priori estimations of sample size due to opportunistic domestic cat sample collection.

Hair reproductive hormones (E, T and P) were used to determine whether differences in age could be detected, because juveniles generally produce lower levels of reproductive hormones than adults, particularly among males (Rolland et al., 2005; Fanson et al., 2010a). Hormones were log transformed to achieve normality and homogeneity of variance. Differences in E, T and P were compared across age (adult vs. juvenile), sex (male vs. female) and region (east vs. west), using a general linear fixed-effect model, from log-transformed estimates. While our focal interest was to differentiate between ages, we included sex in the analysis to assess interaction effects between age and sex.

Hair reproductive hormone ratios (T:E, T:P and E:P) were used to determine whether differences in sex could be detected, given that both sexes can produce testosterone, progesterone and estrogen (Rolland et al., 2005). Ratios were compared across sex, age and region using a general linear fixed-effect model. Hair reproductive hormone ratios were normally distributed (Shapiro–Wilk test, P > 0.05). Variances were homogeneous in all cases (Levene's test, P > 0.05), except with age and T:P ratio (F1,67 = 4.22, P = 0.044). However, given that this P-value is close to the threshold for determining homogeneity (P = 0.05), a parametric test was used.

The area under the curve (AUC) of a receiver operating characteristic (ROC) curve (Greiner et al., 2000) was used to quantify how accurately hair reproductive hormone ratios differentiated between sexes, taking into account the number of false positives (i.e. a known male is identified as female, based on hormone ratios). Receiver operating characteristic curves are built by calculating the sensitivity (true positive) and specificity (false negative) at various cut-off points for the data (Boyce et al., 2002); therefore, a plot with perfect discrimination would have an AUC of one, given it has a sensitivity of one and specificity of zero (Greiner et al., 2000). This method is commonly used in the medical and veterinary literature to determine the accuracy of disease diagnosis tests, using the number of true positives and false positives in the test (Greiner et al., 2000). In ecology, ROCs are used to determine the model performance of resource selection functions, using the probability that an animal is detected where it genuinely occurs (true positive) and detection where no animal is observed (false positive; Boyce et al., 2002). In general, AUC values are categorized as follows: 0.5 is considered to be non-informative; 0.7–0.9 is moderately accurate; and >0.9 is highly accurate at discriminating between groups of interest (Swets, 1988; Greiner et al., 2000; Boyce et al., 2002). The R package ‘pROC’ was used to calculate AUC values (Robin et al., 2012).

All statistical analyses were performed using R 2.15.1 (Foundation of Open Source Statistics, Boston, MA, USA).

Results

Assay validation: domestic cat

Extraction of exogenous E, T and P in domestic cat hair samples resulted in procedural efficiencies averaging 99.7 ± 9.8 (±SEM), 110.7 ± 3.8 and 90.3 ± 6.8%, respectively. The recoveries of known concentrations of E, T and P from domestic cat hair extracts were as follows: 85.8 ± 4.3, 76.4 ± 2.8 and 100.9 ± 3.8%, respectively. The measured hormone concentrations in the spiked samples correlated with the expected concentrations for all hormones (for E, T and P, r = 0.98; all P > 0.01; see Supplementary Data). Serial dilutions of pooled hair extracts showed parallel displacement with the standard curves (E, r = 0.99; T, r = 0.99; and P, r = 0.98; all P > 0.01; see Supplementary Data). Interassay coefficients of variation were 6.0, 7.4 and 13.0% at 30% binding for E, T and P, respectively, 6.5 and 7.3% at 50% binding for E and P, and 10.4% at 70% binding for T. Intra-assay coefficients of variation were 10.1 at 70% binding for E, and 5.9 and 12.1% at 50% binding for T and P, respectively.

Assay validation: Canada lynx

Extraction of exogenous E, T and P in lynx hair samples resulted in procedural efficiencies averaging 106.6 ± 10.7 (±SEM), 113.1 ± 13.1 and 96.8 ± 14.9%, respectively. The recoveries of known concentrations of E, T and P from lynx hair extracts were 84.1 ± 1.5, 89.9 ± 7.1 and 73.9 ± 4.1%, respectively. The measured hormone concentrations in the spiked samples correlated with the expected concentrations for all hormones (E, T and P, r = 0.99; all P > 0.01; see Supplementary Data). Serial dilutions of pooled hair extracts showed parallel displacement with the standard curves (E, r = 0.99; T, r = 0.98; and P, r = 0.99; all P > 0.01; see Supplementary Data).

Reproductive states: domestic cat

Comparisons of hair hormone concentrations for domestic cats of known reproductive states are given in Figs 1–3. Hair E (intact, n = 4; estrus, n = 5; pregnant, n = 7; and spayed, n = 10) and T levels (intact, n = 5; and neutered, n = 7) did not differ significantly between known reproductive states (all P > 0.15). Female domestic cat (intact, n = 10; pregnant, n = 5; and spayed, n = 10) hair P levels differed according to reproductive states (F2,24  = 9.05, P < 0.01). Pregnant individuals had significantly higher P levels than spayed individuals (Tukey's HSD, P < 0.01). However, there was no difference between pregnant and intact or spayed and intact individuals (all P > 0.08). Incidentally, two female cats were given oral progestin for 38 days ∼6 months prior to analysis, and had discernably higher hair progesterone values (2.7 and 4.13 times the average).

Figure 2:

Figure 2:

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Mean ± SD hair testosterone concentrations (in nanograms per gram of hair) from male domestic cats of known reproductive status (neutered, n = 7; and intact, n = 5).

Figure 1:

Figure 1:

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Mean ± SD hair estrogen concentrations (in nanograms per gram of hair) from female domestic cats of known reproductive status (intact, n = 4; estrus, n =5; pregnant, n = 7; and spayed, n = 10).

Figure 3:

Figure 3:

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Mean ± SD hair progesterone concentrations (in nanograms per gram of hair) from female domestic cats of known reproductive status (intact, n = 10; pregnant, n = 5; and spayed, n = 10). The asterisks show the hair progesterone concentrations for two females that received a 38 day oral progestin treatment.

Post hoc power analysis indicated that E and P had sufficient power with a sample size of seven individuals per group (E = 0.96, P = 0.98), while T had low power (0.47). In order to achieve a power of 0.8 for T, a sample size of ∼9.5 per group (intact and neutered) would be necessary.

Age and sex: lynx pelts

Mean hair hormone values for age (adult vs. juvenile), sex (male vs. female) and region (east vs. west) of lynx are given in Table 1. Hair E levels differed between region (F1,64 = 7.55, P < 0.01) and age (F1,64 = 7.06, P < 0.01), but main effects of sex and age × sex were not significant (all P > 0.19). These hair E results were supported by AUC values, which revealed a poor ability to classify according to age (AUC, 0.62).

Table 1:

Mean values ± SD (n) of hair reproductive hormones (in nanograms per gram of hair) in lynx pelts according to age, sex and trap line region

Estrogen Testosterone Progesterone
Adult 3.32 ± 1.82 (45) 3.35 ± 1.65 (45) 4.10 ± 2.56 (44)
 Female 3.11 ± 1.50 (23) 3.41 ± 1.69 (23) 5.37 ± 2.86 (23)
 East 3.02 ± 1.63 (16) 3.16 ± 1.88 (16) 4.81 ± 3.05 (16)
 West 3.32 ± 1.26 (7) 3.96 ± 1.07 (7) 6.63 ± 2.01 (7)
 Male 3.53 ± 2.11 (22) 3.30 ± 1.65 (22) 2.72 ± 1.12 (21)
 East 2.83 ± 1.68 (16) 2.75 ± 1.15 (16) 2.42 ± 0.99 (16)
 West 5.43 ± 2.08 (6) 4.76 ± 1.98 (6) 3.69 ± 1.02 (5)
Juvenile 4.34 ± 2.66 (24) 4.06 ± 1.59 (25) 3.93 ± 1.36 (28)
 Female 3.85 ± 3.09 (12) 4.04 ± 1.96 (11) 3.89 ± 1.44 (14)
 East 3.01 ± 1.09 (11) 3.68 ± 1.63 (10) 3.71 ± 1.32 (13)
 West 13.08 (1) 7.67 (1) 6.27 (1)
 Male 4.84 ± 2.17 (12) 4.08 ± 1.32 (14) 3.96 ± 1.33 (14)
 East 4.79 ± 2.27 (11) 4.03 ± 1.36 (13) 3.94 ± 1.38 (13)
 West 5.38 (1) 4.70 (1) 4.27 (1)
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Data are not log transformed.

Lynx hair T levels differed between region (F1,65 = 8.96, P < 0.01) and age (F1,65 = 8.67, P < 0.01). However, the hair T values were again not accurate at differentiating age (AUC, 0.65). Differences in hair T were not detected between sex, and no age × sex interaction was found (all P > 0.61).

Analysis of hair P levels revealed significant main effects of region (F1,67 =  12.40, P < 0.01) and sex (F1,67 = 16.04, P < 0.01) and an age × sex interaction (F1,67 = 11.54, P < 0.01). However, lynx P levels did not differ between age groups (P = 0.14). The significant age × sex interaction term indicates that adult females had higher average hair P values than adult males, while juvenile males and females were not distinguishable (Fig. 4). The AUC values showed that hair P values were non-informative for categorizing age in lynx (AUC, 0.55), although they were moderately accurate at differentiating sex (AUC, 0.70).

Figure 4:

Figure 4:

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Interaction plot representing differential mean progesterone concentration (in nanograms per gram of hair) according to age class in Canada lynx. Error bars represent ±SD.

Hormone ratios were calculated to determine whether hormone profiles could be used to determine sex using lynx individuals of known sex. Mean hair hormone ratios for age, sex and region are given in Table 2. The T:E ratios did not differ between region or age, and no sex × age interaction was found (all P > 0.18); however, they did differ between sex (F1,61 = 4.82, P = 0.03). The AUC values showed that the T:E ratios were not accurate at differentiating between males and females (AUC, 0.65).

Table 2:

Mean ± SD (n) of hair reproductive hormone ratios (in nanograms per gram of hair) in lynx pelts according to age, sex and trap line region

T:E T:P E:P
Adult 1.08 ± 0.25 (45) 0.95 ± 0.39 (44) 0.92 ± 0.43 (44)
 Female 1.15 ± 0.28 (23) 0.73 ± 0.37 (23) 0.67 ± 0.39 (23)
 East 1.10 ± 0.29 (16) 0.74 ± 0.35 (16) 0.68 ± 0.25 (16)
 West 1.24 ± 0.23 (7) 0.70 ± 0.44 (7) 0.64 ± 0.62 (7)
 Male 1.01 ± 0.20 (22) 1.19 ± 0.25 (21) 1.20 ± 0.28 (21)
 East 1.06 ± 0.21 (16) 1.18 ± 0.25 (16) 1.14 ± 0.25 (16)
 West 0.88 ± 0.11 (6) 1.23 ± 0.29 (5) 1.38 ± 0.33 (5)
Juvenile 0.99 ± 0.32 (21) 1.03 ± 0.28 (25) 1.11 ± 0.44 (24)
 Female 1.08 ± 0.39 (9) 1.00 ± 0.33 (11) 0.99 ± 0.46 (12)
 East 1.14 ± 0.37 (8) 0.98 ± 0.33 (10) 0.89 ± 0.32 (11)
 West 0.59 (1) 1.22 (1) 2.09 (1)
 Male 0.92 ± 0.25 (12) 1.05 ± 0.25 (14) 1.23 ± 0.40 (12)
 East 0.93 ± 0.26 (11) 1.05 ± 0.26 (13) 1.23 ± 0.42 (11)
 West 0.87 (1) 1.10 (1) 1.26 (1)
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Abbreviations: E, estrogen, P, progesterone; and T, testosterone. Data are not log transformed.

Lynx hormone E:P ratios showed detectable differences between sex (F1,63 = 23.34, P < 0.01) and age (F1,63 = 5.02, P = 0.02), while there were no differences between region, and no sex × age interaction was found (P > 0.11). The 95% confidence intervals for adult E:P ratios were non-overlapping, indicating they can be used to distinguish sex (males, 95% confidence interval = 1.08–1.32; females, 95% confidence interval = 0.51–0.83; Fig. 5). The T:P ratios were comparable across region and between ages (all P > 0.33), while an effect of sex (F1,64 = 17.80, P < 0.01) and a sex × age interaction were detected (F1,64 = 6.94, P = 0.01). Although both E:P and T:P ratios showed differences in sex, further quantifiaction using AUC values showed that E:P ratios (AUC, 0.82) were moderately accurate and superior at differentiating between sexes when compared with T:P ratios (AUC, 0.75). Finally, the level of accuracy was increased for E:P ratios to highly accurate when only adults were used in the ROC analysis (AUC, 0.90).

Figure 5:

Figure 5:

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Relationship between progesterone and estrogen (in nanograms per gram of hair) for wild adult Canada lynx pelts of known sex. Open circles, female; and filled triangles, male.

Discussion

To our knowledge, this is the first study to validate an EIA for analysis of reproductive hormones (E, T and P) in the hair of a felid species. First, we used domestic cats as a model to determine whether hair reproductive hormones could differentiate between individuals having known reproductive states (intact, pregnant, estrus and spayed/neutered). Progesterone appeared to be the most discriminating hormone, because pregnant individuals had higher levels than spayed individuals. Elevation in progesterone levels is tied to formation of corpora lutea, and this increase persists through pregnancy (Verhage et al., 1976; Swanson et al., 1995). Progesterone also increases in non-pregnant cats, although the duration is half that of pregnant individuals, at 36–38 days (Brown, 2006). This may explain why pregnant individuals had the highest hair progesterone levels, followed by intact and spayed groups. In addition, administration of oral progestin for 38 days resulted in higher than average hair progesterone values in two females. This provides a preliminary pharmacological validation and indicates the potential of the method for detecting change in hormone levels. Faecal studies support this finding, because they have shown that baseline progesterone levels increase in domestic cats when given oral progestin (Stewart et al., 2010).

Estrogen did not show differences according to domestic cat reproductive states, despite having reasonable statistical power. Although studies have shown that domestic cats are polyestrous and experience brief estrogen surges during estrus (Verhage et al., 1976), cycle lengths are relatively short, 3–16 days at 21 day intervals (Brown, 2011), with only small increases (>10-fold) in estrogen above baseline levels (serum, Verhage et al., 1976; faeces, Graham et al., 1995). It is therefore possible that the small magnitude of estrogen surges is not detectable using hair hormone analysis, given that a longer period of several weeks or months is being measured and compared. These inconsistent results suggest that estrogen from hair may not hold strong potential for monitoring reproductive states.

Testosterone did not differ between neutered and intact domestic cats, although previous studies have shown that faecal testosterone values differ between intact and neutered male domestic cats (Brown et al., 1996). However, given our small sample size, it is possible that the detectable effect size was too low in our testosterone analysis. This may be confounded further by the fact that testosterone levels have high interindividual variation in domestic cats (serum, Johnston et al., 1996; faeces, Brown et al., 1996). These results indicate the potential for hair reproductive hormone analysis in other felids. It is important, however, to validate hormone analysis methods on a species-by-species basis, because felids exhibit large differences in reproductive characteristics, such as type of ovulation, seasonality and ovarian responses (Brown, 2006).

Lynx of known age and sex were used to assess the potential of using hair reproductive hormones to differentiate between groups. Although we detected significant age-specific differences among hair estrogen and testosterone values in lynx pelts, further analysis with AUC showed these differences were not accurate at differentiating between adults and juveniles. Notably, progesterone was effective at differentiating only between the sexes of adult individuals. These findings are similar to faecal reproductive hormone studies that show similarities in estrogen and progesterone values among female lynx aged 2–12 years (Fanson et al., 2010b). However, the results are inconsistent with findings that faecal androgen values differed significantly between neutered males, intact juveniles and adult males (Fanson et al., 2010a). Our inability to distinguish between lynx age classes may be related to error in the age-class classification system, which relied on pelt length measurements (Quinn and Gardner, 1984; Slough, 1996). The method is widely used to distinguishing kits from yearlings and adults (Quinn and Gardner, 1984), meaning that peri-pubertal individuals may be incorrectly classified. Regardless, at this point it is not possible to confirm that these assays hold promise for distinguishing hair hormones by age.

Hair hormone values differed between regions (east and west) for the three hormones of interest. This pattern may be due to differences in the temperature during the time of active hair growth (or moult). For example, the average monthly temperatures from available weather stations were −4.68°C for Ontario and −13.41°C for the Yukon in November 2008 (Environment Canada, 2014); such differences in environmental conditions between areas are likely to persist year round. It is possible that this difference leads to differences in fur characteristics that translate to higher reproductive hormone values in the west. However, while the mechanism driving these regional differences is currently unknown, it is an important potential confounding factor that should be investigated further. Depending on the outcome of this investigation, the utility of hair reproductive hormone analysis should be reviewed carefully.

Hormone ratios showed differences that may be used to distinguish accurately between sexes, especially for adults. In particular, the E:P ratio holds promise for evaluating sex ratios, which is consistent with previous findings showing that faecal androgen-to-estrogen ratios can distinguish sexes in right whales (Rolland et al., 2005) and barred owls (Wasser and Hunt, 2005). Ultimately, this method may provide a cost-effective and reasonably accurate method for determining population sex ratios. Interestingly, these results did not show significant regional differences as observed in the E, T and P values.

We were able to detect reproductive hormones in the hair of other lynx species [Eurasian lynx (Lynx lynx) and bobcat (Lynx rufus)] and biochemically validated an EIA for lynx and domestic cats, which shows that the method holds promise for Lynx spp. (C. V. Terwissen, G. F. Mastromonaco and D. L. Murray, unpublished observations), as well as other felids. Our study should serve as a prompt for further investigation into the use of hair analysis for documenting reproductive states. This is particularly important given that felids tend not to reproduce well in captivity (Brown, 2006), making monitoring of wild populations critical. However, we stress that considerable further pharmacological validation should be conducted using methods to determine that biologically relevant changes are being detected (Brown et al., 1998; Axnér et al., 2008). Accordingly, further development and refinement of hair hormone-based tools will be necessary before these tools can be applied broadly to wild populations.

Supplementary material

Supplementary material is available at Conservation Physiology online.

Funding

This work was supported by the Toronto Zoo and by a Natural Sciences and Engineering Council of Canada Strategic Projects Grant to D.L.M.

Supplementary Material

Supplementary Data
supp_2_1_cou044__index.html (1KB, html)

Acknowledgements

We would like to thank North American Fur Auction and Fur Harvesters Auction for providing access to lynx pelts, as well as Dr Kris Young from Peterborough Veterinary Hospital and Helen Bateman from Cincinnati Zoo for providing samples from domestic cats. Finally, we thank Guillaume Bastille-Rousseau for assistance with statistical analysis, Christine Gilman for her hard work in processing samples at the Toronto Zoo and Erin Koen for providing sex data.

References

  1. Axnér E, Gustavsson T, Ström Holst B. (2008) Estradiol measurement after GnRH-stimulation as a method to diagnose the presence of ovaries in the female domestic cat. Theriogenology 70: 186–191. [DOI] [PubMed] [Google Scholar]
  2. Bailey TN, Bangs EE, Portner MF, Malley JC, McAvinchey RJ. (1986) An apparent overexploited lynx population on the Kenai Peninsula Alaska. J Wildlife Manage 50: 279–290. [Google Scholar]
  3. Boyce MS, Vernier PR, Nielsen SE, Schmiegelow FKA. (2002) Evaluating resource selection functions. Ecol Model 157: 281–300. [Google Scholar]
  4. Brand CJ, Keith LB, Fischer CA. (1976) Lynx responses to changing snowshoe hare densities in central Alberta. J Wildlife Manage 40: 416–428. [Google Scholar]
  5. Brearley G, McAlpine C, Bell S, Bradley A. (2012) Influence of urban edges on stress in an arboreal mammal: a case study of squirrel gliders in southeast Queensland, Australia. Landscape Ecol 27: 1407–1419. [Google Scholar]
  6. Brown JL. (2006) Comparative endocrinology of domestic and nondomestic felids. Theriogenology 66: 25–36. [DOI] [PubMed] [Google Scholar]
  7. Brown JL. (2011) Female reproductive cycles of wild female felids. Anim Reprod Sci 124: 155–162. [DOI] [PubMed] [Google Scholar]
  8. Brown JL, Wildt DE. (1997) Assessing reproductive status in wild felids by noninvasive faecal steroid monitoring. Int Zoo Yearbook 35: 173–191. [Google Scholar]
  9. Brown JL, Terio KA, Graham LH. (1996) Fecal androgen metabolite analysis for noninvasive monitoring of testicular steroidogenic activity in felids. Zoo Biol 15: 425–434. [Google Scholar]
  10. Brown JL, Goodrowe KL, Simmons LG, Armstrong DL, Wildt DE. (1998) Evaluation of pituitary–gonadal response to GnRH, and adrenal status, in the leopard (Panthera pardus japonensis) and the tiger (Panthera tigris). J Reprod Fertil 82: 227–236. [DOI] [PubMed] [Google Scholar]
  11. Bryan HM, Darimont CT, Paquet PC, Wynne-Edwards KE, Smits JEG. (2013) Stress and reproductive hormones in grizzly bears reflect nutritional benefits and social consequences of a salmon foraging niche. PLoS ONE 8: e80537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Buchanan KL, Goldsmith AR. (2004) Noninvasive endocrine data for behavioural studies: the importance of validation. Anim Behav 67: 183–185. [Google Scholar]
  13. Conforti VA, Bateman HL, Schnook MW, Newsom J, Lyons LA, Grahn RA, Deddens JA, Swanson WF. (2013) Laparoscopic oviductal artificial insemination improves pregnancy success in exogenous gondatropin-treated domestic cats as a model for endangered felids. Biol Reprod 89: 1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dehnhard M, Fanson K, Frank A, Naidenko SV, Vargas A, Jewgenow K. (2010) Comparative metabolism of gestagens and estrogens in the four lynx species, the Eurasian (Lynx lynx), the Iberian (L. pardinus), the Canada lynx (L. canadensis) and the bobcat (L. rufus). Gen Comp Endocrinol 167: 287–296. [DOI] [PubMed] [Google Scholar]
  15. Environment Canada (2014) Climate, Monthly Climate Summaries. http://climate.weather.gc.ca/prods_servs/cdn_climate_summary_e.html (15 March 2014, date last accessed). [Google Scholar]
  16. Fanson KV, Wielebnowski NC, Shenk TM, Jakubas WJ, Squires JR, Lucas JR. (2010a) Patterns of testicular activity in captive and wild Canada lynx (Lynx canadensis). Gen Comp Endocrinol 169: 210–216. [DOI] [PubMed] [Google Scholar]
  17. Fanson KV, Wielebnowski NC, Shenk TM, Vashon JH, Squires JR, Lucas JR. (2010b) Patterns of ovarian and luteal activity in captive and wild Canada lynx (Lynx canadensis). Gen Comp Endocrinol 169: 217–224. [DOI] [PubMed] [Google Scholar]
  18. Fanson KV, Wielebnowski NC, Shenk TM, Lucas JR. (2011) Comparative patterns of adrenal activity in captive and wild Canada lynx (Lynx canadensis). J Comp Physiol B 181: 1–9. [DOI] [PubMed] [Google Scholar]
  19. Genaro G, Moraes W, Silva JC, Adania CH, Franci CR. (2007) Plasma hormones in neotropical and domestic cats undergoing routine manipulations. Can J Vet Res 75: 216–221. [DOI] [PubMed] [Google Scholar]
  20. Gleixner A, Meyer HHD. (1997) Detection of estradiol and testosterone in hair of cattle by HPLC/EIA. Fresenius J Anal Chem 357: 1198–1201. [Google Scholar]
  21. Gow T, Rieder S, Van Uum SM, Koren G. (2010) An assessment of cortisol analysis of hair and its clinical applications. Forensic Sci Int 196: 32–37. [DOI] [PubMed] [Google Scholar]
  22. Graham LH, Goodrowe KL, Raeside JI, Liptrap RM. (1995) Non-invasive monitoring of ovarian function in several felid species be measurement of fecal estradiol-17β and progestins. Zoo Biol 14: 223–237. [Google Scholar]
  23. Greiner M, Pfeiffer D, Smith RD. (2000) Principles and practical application of the receiver-operating characteristics analysis for diagnostic tests. Prev Vet Med 45: 23–41. [DOI] [PubMed] [Google Scholar]
  24. Hoenig JM, Heisey DM. (2001) The abuse of power: the pervasive fallacy of power calculations for data analysis. Am Stat 55: 19–24. [Google Scholar]
  25. Johnston SD, Root MV, Olson PNS. (1996) Ovarian and testicular function in the domestic cat: clinical management of spontaneous reproductive disease. Anim Reprod Sci 42: 261–274. [Google Scholar]
  26. Koren L, Mokady O, Geffen E. (2006) Elevated testosterone levels and social ranks in female rock hyrax. Horm Behav 49: 470–477. [DOI] [PubMed] [Google Scholar]
  27. Krebs CJ, Kielland K, Bryant J, O'Donoghue M, Doyle F, McIntyre C, DiFolco D, Berg N, Carriere S, Boonstra R, et al. (2013) Synchrony in the snowshoe hare (Lepus americanus) cycle in northwestern North America, 1970–2012. Can J Zool 91: 562–572. [Google Scholar]
  28. Kummrow MS, Gilman C, Mackie P, Smith DA, Mastromonaco G. (2011) Noninvasive analysis of fecal reproductive hormone metabolits in female veiled chameleons (Chamaeleo calyptratus) by enzyme immunoassay. Zoo Biol 30: 95–115. [DOI] [PubMed] [Google Scholar]
  29. MacBeth BJ, Cattet MRL, Stenhouse GB, Gibeau ML, Janz DM. (2010) Hair cortisol concentrations as a noninvasive measure of long-term stress in free-ranging grizzly bears (Ursus arctos): considerations with implications for other wildlife. Can J Zool 88: 935–949. [Google Scholar]
  30. Nowell K, Jackson P. (1996) Wild Cats: Status Survey and Conservation Action Plan. IUCN Cat Specialist Group. IUCN, Gland, Switzerland. [Google Scholar]
  31. Ortega J, Franco M, Adams BA, Ralls K, Maldonado JE. (2004) A reliable, non-invasive method for sex determination in the endangered San Joaquin kit fox (Vulpes macrotis mutica) and other canids. Conserv Genet 5: 715–718. [Google Scholar]
  32. Palme R. (2005) Measuring fecal steroids: guidelines for practical application. Ann NY Acad Sci 1046: 75–80. [DOI] [PubMed] [Google Scholar]
  33. Poole KG. (2003) A review of the Canada lynx, Lynx canadensis, in Canada. Can Field Nat 117: 360–376. [Google Scholar]
  34. Quinn NWS, Gardner JF. (1984) Relationship of age and sex to lynx pelt characteristics. J Wildlife Manage 48: 953–956. [Google Scholar]
  35. Quinn NWS, Gardner JF. (1987) Lynx. In M Novak, J Baker, ME Obbard, B Mallock, eds, Wild Furbearer Management and Conservation in North America. Ontario Ministry of Natural Resources, Peterborough, ON, Canada, ppp 682–694. [Google Scholar]
  36. R Core Team and contributors worldwide (2013) Package ‘stats’: anova.power.test. Version 3.0.2. R Foundation for Statistical Computing, Vienna, Austria. [Google Scholar]
  37. Robin X, Turck N, Hainard A, Lisacek Tiberti N, Sanchez JC, Muller M. (2012) Package ‘pROC’: Display and analyze ROC curves. Version 1.5.4. BMC Bioinformatics 12: 77. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Rolland RM, Hunt KE, Kraus SD, Wasser SK. (2005) Assessing reproductive states of right whales (Eubalaena glacialis) using fecal hormone metabolites. Gen Comp Endocrinol 142: 308–317. [DOI] [PubMed] [Google Scholar]
  39. Row JR, Gomez C, Koen EL, Bowman J, Murray DL, Wilson PJ. (2012) Dispersal promotes high gene flow among Canada lynx populations across mainland North America. Conserv Genet 13: 1259–1268. [Google Scholar]
  40. Russel E, Koren G, Rieder M, Van Uum S. (2011) Hair cortisol as a biological marker of chronic stress: current states, future directions and unanswered questions. Psychoneuroendocrinology 37: 589–601. [DOI] [PubMed] [Google Scholar]
  41. Sheriff MJ, Dantzer B, Delehanty B, Palme R, Boonstra R. (2011) Measuring stress in wildlife: techniques for quantifying glucocorticoids. Oecologia 166: 869–887. [DOI] [PubMed] [Google Scholar]
  42. Slough BG. (1996) Estimating population age ratio with pelt-length data. Wildlife Soc Bull 24: 495–499. [Google Scholar]
  43. Stalder T, Kirschbaum C. (2012) Analysis of cortisol in hair – state of the art and future directions. Brain Behav Immun 26: 1019–1029. [DOI] [PubMed] [Google Scholar]
  44. Stewart RA, Pelican KM, Brown JL, Wildt DE, Ottinger MA, Howard JG. (2010) Oral progestin induces rapid, reversible suppression of ovarian activity in the cat. Gen Comp Endocrinol 166: 409–416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Swanson WF, Roth TL, Brown JL, Wildt DE. (1995) Relationship of circulating steroid hormones, luteal luteinizing hormone receptor and progesterone concentration, and embryonic mortality during early embryogenesis in the domestic cat. Biol Reprod 53: 1022–1029. [DOI] [PubMed] [Google Scholar]
  46. Swets JA. (2000) Measuring the accuracy of diagnostic systems. Science 240: 1285–1293. [DOI] [PubMed] [Google Scholar]
  47. Terwissen CV, Mastromonaco GF, Murray DL. (2013) Influence of adrenocorticotrophin hormone challenge and external factors (age, sex, and body region) on hair cortisol concentration in Canada lynx (Lynx canadensis). Gen Comp Endocrinol 194: 162–167. [DOI] [PubMed] [Google Scholar]
  48. Verhage HG, Beamer NB, Brenner RM. (1976) Plasma levels of estradiol and progesterone in the cat during polyestrus, pregnancy and pseudopregnancy. Biol Reprod 14: 579–585. [DOI] [PubMed] [Google Scholar]
  49. Wasser SK, Hunt KE. (2005) Noninvasive measures of reproductive function and disturbance in the barred owl, great horned owl, and northern spotted owl. Ann NY Acad Sci 1046: 109–137. [DOI] [PubMed] [Google Scholar]
  50. Woods JG, Paetkau D, Lewis D, McLellan BN, Proctor M, Strobeck C. (1999) Genetic tagging of free-ranging black and brown bears. Wildlife Soc Bull 27: 616–627. [Google Scholar]
  51. Yang ZH, Lan J, Meng YJ, Wan XJ, Han DW. (1998) A preliminary study of steroid reproductive hormones in human hair. J Steroid Biochem Mol Biol 67: 447–450. [DOI] [PubMed] [Google Scholar]
  52. Zigouris J, Dawson FN, Bowman J, Gillett RM, Schaefer JA, Kyle CJ. (2012) Genetic isolation of wolverine (Gulo gulo) populations at the eastern periphery of their North American distribution. Conserv Genet 13: 1543–1559. [Google Scholar]

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Supplementary Materials

Supplementary Data
supp_2_1_cou044__index.html (1KB, html)
supp_cou044_cou044supp_fig1.jpg (1.1MB, jpg)
supp_cou044_cou044supp_fig2.jpg (1.1MB, jpg)
supp_cou044_cou044supp_fig3.jpg (1.1MB, jpg)
supp_cou044_cou044supp_fig4.jpg (1.2MB, jpg)

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