Psychoneuroendocrinology (2014) 41, 13—22

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Contributions of sex, testosterone, and androgen receptor CAG repeat number to virtual Morris water maze performance Nicole T. Nowak a,*, Michael P. Diamond b, Susan J. Land c, Scott D. Moffat d a

University of Wisconsin — Milwaukee, Department of Psychology, Milwaukee, WI, USA Georgia Regents University, Medical College of Georgia, Augusta, GA, USA c Wayne State University, Wayne State Applied Genomics Technology Center, Detroit, MI, USA d Georgia Institute of Technology, School of Psychology, Atlanta, GA, USA b

Received 27 June 2013; received in revised form 29 October 2013; accepted 3 December 2013

KEYWORDS Androgen receptor CAG repeat; Testosterone; Spatial cognition; Virtual Morris water task; Sex difference

Summary The possibility that androgens contribute to the male advantage typically found on measures of spatial cognition has been investigated using a variety of approaches. To date, evidence to support the notion that androgens affect spatial cognition in healthy young adults is somewhat equivocal. The present study sought to clarify the association between testosterone (T) and spatial performance by extending measurements of androgenicity to include both measures of circulating T as well as an androgen receptor-specific genetic marker. The aims of this study were to assess the contributions of sex, T, and androgen receptor CAG repeat number (CAGr) on virtual Morris water task (vMWT) performance in a group of healthy young men and women. The hypothesis that men would outperform women on vMWT outcomes was supported. Results indicate that CAGr may interact with T to impact navigation performance and suggest that consideration of androgen receptor sensitivity is an important consideration in evaluating hormone—behavior relationships. # 2013 Elsevier Ltd. All rights reserved.

1. Introduction Although the sexes differ negligibly on standardized tests of intelligence (e.g., Koscik et al., 2009) reviews and metaanalyses have documented a male advantage in spatial

* Corresponding author at: 2441 East Hartford Avenue, 224 Garland Hall, Milwaukee, WI 53211, USA. Fax: +1 414 229 5219. E-mail address: [email protected] (N.T. Nowak).

performance, such as mental rotation ability (e.g., Voyer et al., 1995). Men also tend to excel on tests of wayfinding, whether tested in real-world or computerized environments (for review, see Coluccia and Louse, 2004). One example of such a computerized environment is the virtual Morris water task (vMWT), modeled after the rodent spatial learning and memory test in which there is a moderate male advantage (for a meta-analysis, see Jonasson, 2005). In humans, men tend to perform better than women on vMW tasks (e.g., Astur et al., 1998; Sandstrom et al., 1998; Driscoll et al., 2005; Burkitt et al., 2007; Nowak and Moffat, 2011).

0306-4530/$ — see front matter # 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psyneuen.2013.12.003

14 One ongoing approach to investigating between- and within-sex variability in spatial cognition is to manipulate circulating androgen concentrations in animal models. Experiments with rodents generally support the idea that water maze performance is affected by T. For example, manipulations found to impair spatial learning and memory in adult male rodents include castration (e.g., Spritzer et al., 2008), intrahippocampal administration of the androgen receptor (AR) antagonist flutamide (Edinger and Frye, 2007), and intrahippocampal injection of T (Harooni et al., 2008). Administration of T to female rats has been shown to enhance navigation performance (e.g., Roof and Havens, 1992). Some experiments have not found an effect of castration or androgen administration on spatial performance (e.g., Isgor and Sengelaub, 1998). While several studies in humans have investigated the association between salivary T and psychometric measures of spatial cognition (for review, see Puts et al., 2010), few studies have related T to vMWT or any other navigational outcomes in humans. Studies relating T to measures of spatial cognition such as mental rotation ability have found positive, negative, and null correlations in samples of men; and positive and null correlations in samples of women; with some supporting the so-called ‘optimum level theory’ (i.e., moderate levels of T may optimize spatial performance). Considering vMWT performance specifically, Driscoll et al. (2005) reported that higher Twas associated with faster performance in the last block of hidden platform trials in men. There was no significant association between T and spatial navigation performance in women. Burkitt et al. (2007) found that higher T was correlated with faster performance in women during the final block of hidden platform trials, but not in men. The apparent inconsistency between these findings may be a result of including older men in the Driscoll et al. study in whom age-related T depletion (Harman et al., 2001) would have been apparent. In addition, other factors surely moderate the relationship between T and cognitive function and a likely candidate for the latter is individual differences in androgen receptor sensitivity. Androgen receptors are distributed throughout the body, including regions of the brain known to be integral to spatial learning and memory, such as the temporal cortex (Puy et al., 1995) and hippocampus (Beyenburg et al., 2000). The CAGr is a polyglutamine sequence located in exon 1 of the AR gene, which is located on the X chromosome (Quigley et al., 1995). The normal range of this repeat is between 9 and 36 (Lehman et al., 2003) with a mean of approximately 21 (La Spada et al., 1991). The number of repeats is inversely associated with AR transactivation (Chamberlain et al., 1994); therefore, it is possible that an individual with fewer repeats may demonstrate an enhanced biological and behavioral response to androgens. This AR polymorphism has been associated with reproductive health in men (Zitzmann, 2009) and women (Shah et al., 2008), androgen insensitivity (Choong et al., 1996), handedness in men (Hampson and Sankar, 2012), cognition in older men (Yaffe et al., 2003), and risk for Alzheimer’s disease in men (Lehman et al., 2003). The present study further investigated the association between T and vMWT performance by extending measurements of androgenicity to include measures of T as well as an AR-specific genetic marker. To our knowledge, this is the first study to investigate the interaction between T and CAGr on

N.T. Nowak et al. navigation performance. The aim of the current study was to examine the contributions of sex, T, and CAGr on vMWT performance in a group of healthy young men and women while controlling for variables shown by previous research to affect scores on tests of spatial cognition, such as sexual orientation, use of hormonal contraceptives, and phase of the menstrual cycle. In addition, we used highly sensitive liquid chromatography tandem mass spectrometry (LC—MS/ MS) to assay T in men and women.

2. Methods 2.1. Participants Participants were 58 men (n = 29) and women (n = 29) recruited through university announcements. Participants were heterosexual, right-handed, and free of self-reported psychiatric, neurological, and endocrine disorders. Women were not using any form of hormonal contraceptives, and were tested during menses. The mean age of the males was 22.97 (SD = 3.91) years and the females 22.62 (SD = 3.78) years. Men had a mean of 15.28 (SD = 1.58) years of education and women had a mean of 14.89 (SD = 1.47) years. Fifty-three percent of the sample identified as White or Caucasian; 17% as Black or African American; 14% as Arab; 7% as Indian; 3% as Asian; 3% as Hispanic; and 3% as mixed race or other.

2.2. Procedure Participants were scheduled to arrive at the laboratory at either 8:30AM or 10:00AM to control for daily fluctuation in T. After providing informed consent, participants completed a health and demographics form and a questionnaire regarding their computer and video game experience. Venipuncture was performed using a BD Vacutainer1 Safety-LokTM Blood Collection Set to obtain 24 mL of blood from the antecubital region. For genotyping purposes, 4 mL of blood was drawn into a plastic whole blood tube spray-coated with EDTA and delivered to the Applied Genomics Technology Center at Wayne State University Medical School. For the T assays, blood was collected into two 10 mL glass whole blood tubes, left to stand for 15—20 min, and centrifuged for 15 min at 3500 rpm (Thermo Scientific Sorvall Legend X1R). Serum was aliquoted into 2 mL cryovials and stored at 808 C (Thermo Scientific Revco Elite Plus). Participants then completed the vMWT.

2.3. vMWT All virtual environments were designed using Unreal Tournament 2003 and Unreal Editor software (Epic Games Inc., Rockville, MD, USA). Participants viewed all virtual assessments on a 27.500 flat panel LCD monitor, and controlled their movement through the virtual environments with a joystick. Software automatically collected (x, y) path coordinates every 10 ms, and computed distance to completion of each trial. In addition, path intersections were tallied each time a participant intersected an (x, y) coordinate space they had previously traversed. This variable was included to calculate the number of times a participant intercepted their own path, effectively returning to an identical point in space that

Contributions of sex, testosterone, and androgen receptor CAG repeat

15

they had already visited. Latency to complete each trial was also collected, but as this was correlated r = .83 with distance traveled, only the latter variable is reported in this manuscript.

requiring spatial learning and memory. The dependent measure was the average distance traveled across the three trials: the less distance traveled, the better the performance.

2.4. vMWT — practice trials

2.8. vMWT — overhead maps

Participants received training to familiarize them with the specific procedures of the vMWT. Participants were given three practice trials of the vMWT in which they were placed in a virtual pool of water enclosed within a larger room. The room had a ceiling, floor, five walls and four objects placed around the pool, which could serve as navigation cues. The walls could serve as distal geometric cues because they were asymmetric and did not all form 908 angles. Within the pool there was a hidden platform that the participants were instructed to find. When the person ‘‘swam’’ over the hidden platform, it raised them out of the water for 10 s rendering them immobile except for the ability to rotate 3608. The platform remained in the same location across all trials and participants were informed of this. They were instructed to find the platform, remember its location, and return to the platform as quickly as possible on each trial.

Following the vMWT trials, overhead diagrams of the vMWT environment were presented to participants. The first of the diagrams contained only the distal walls of the environment; and the second was of the vMWT arena with all distal and proximal cues. In each condition, participants were told to place an ‘‘x’’ in the pool where they believed the center of the platform was located during the vMWT trials. To assess spatial memory as a function of cue type, we used a template to measure error in millimeters between the center of their ‘‘x’’ and the true center point of the square platform for each of the overhead diagrams.

2.5. vMWT — learning trials Participants were introduced to a new vMWT environment with seven walls and six objects and were instructed to locate the hidden platform as quickly as possible (for overhead illustration, see Nowak and Moffat, 2011). They were informed that the platform would remain in a fixed location, although their starting point would change. They were instructed to find the platform as quickly and accurately as possible on all subsequent trials. Similar to the practice trials, they remained on the platform for 10 s each time they found it, and were able to rotate 3608 during this time, but they were not explicitly told to do this. There was a 3-min time limit applied to each of the 10 learning trials. Dependent variables included distance traveled to reach the hidden platform, and number of path intersections. Good performance on the learning task is operationalized as less distance needed to locate the hidden platform across the 10 trials.

2.6. vMWT — probe Following the 10 learning trials, there was a 60-s probe trial in which the platform was removed from the pool unbeknownst to participants. The dependent measures included distance traveled in the goal quadrant and number of platform area intersections. Good performance on the probe trial is operationalized as more distance traveled within the goal quadrant, along with a greater number of platform area crossings.

2.7. vMWT — visible platform In the final vMWT trial, participants were placed in the same pool they had been in for the learning and probe trials. In this trial, the platform location was marked with flags and the participants were told to locate it as quickly as possible across three trials. This trial served as an assessment of visuomotor control and joystick competency without

2.9. Genomic analysis Genomic analysis was performed at Wayne State University Applied Genomics Technology Center. DNA was isolated from blood using a Qiagen EZ1 Advanced. The outer amplification was carried out in a 15 mL reaction containing 20 mmol/L of the gene specific primers NED-gcgcgaagtgatccagaa and gttgctgttcctcatcca (Rosa et al., 2007), 1 True Allele PCR Mix (Applied Biosystems), and 25 ng genomic DNA. The amplification was performed on a Mastercycler Gradient thermocycler (Eppendorf). The reaction conditions were 95 8C for 10 min, and amplification was achieved by 40 cycles of 95 8C for 30 s, 60.6 8C for 30 s, and 72 8C for 30 s followed by a final extension of 72 8C for 10 min (Rosa et al., 2007). The NED-labeled PCR products were mixed with LIZ-labeled GeneScanTM 500 size standard (Applied Biosystems) and electrophoresed on AB3730 (Applied Biosystems). The data were analyzed with GeneMapper (Applied Biosystems). CEPH 134702 DNA (Applied Biosystems) was used as a standard DNA and amplified and electrophoresed on each 96-well plate. Male samples and female homozygous samples at the CAG gene were excluded from the X-inactivation analysis. The remaining heterozygous female samples were analyzed for X-inactivation by assessment of methylation status using the methylation sensitive restriction enzyme HpaII (New England BioLabs1 Inc., Ipswich, MA). 225 ng (25 ng/mL) genomic DNA aliquots were either digested with HpaII (5 U) or mock-digested in digestion buffer with no enzyme. Samples were digested for 1 h at 37 8C in a 20 ml reaction volume, with a heat inactivation step of 20 min at 65 8C. Aliquots of 1 ml were amplified by PCR and followed the above CAG method of analysis. Total peak heights for both alleles were calculated for digested and undigested samples. Differences in the ratios of the peak heights between the digested and undigested samples represent the degree to which one allele is more or less methylated than the other in a sample.

2.10. T quantification Testosterone quantification was provided by Quest Diagnostics using turbulent flow liquid chromatography tandem mass

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N.T. Nowak et al.

spectrometry (LC—MS/MS). This method of quantitating T shows no cross-reactivity with 30 steroid compounds biochemically similar to T, has an analytical sensitivity of 1.0 ng/dL, and a reportable range of 1.0 ng/dL to 2000 ng/ dL. Free Twas calculated based on total and percent unbound to sex hormone binding globulin and albumin. The intra- and inter-assay coefficients of variation for the total and free T tests are less than 15% (Salameh et al., 2010).

3. Results 3.1. vMWT Distance traveled across the 10 learning trials was entered into a repeated measures ANOVA with sex as the between subjects factor. A main effect of trial; F(9, 495) = 44.87, p < .001 on distance traveled across the learning trials was observed. Performance improved across trials. Men traveled less distance than women to complete the learning trials, but this group difference was only marginally significant, F(1,55) = 3.61, p = .06. Men traveled a greater distance in the goal quadrant of the pool; F(1, 55) = 17.37, p < .001, and crossed the platform area more frequently, F(1, 55) = 14.38, p = .001. Adding video game experience as a covariate did not diminish the significance of the sex effect on any of these variables. Distance traveled to complete the visible platform control trials did not differ by sex, F(1, 55) = 2.72, p = .14. When participants were shown overhead maps of the vMWT and asked to place an ‘‘x’’ where they thought the center of the platform area was located, a main effect of map type on accuracy of platform area demarcation was observed, F(1,54) = 44.69, p < .001. Post hoc comparisons revealed that participants were more accurate on the map with all of the cues (M error = 7.88 mm, SD = 4.65 mm), than the map that contained only distal room cues (M error = 22.66 mm, SD = 16.86 mm). The sexes did not differ in accuracy on the map with all of the cues available, F(1,54) = .45, p = .51, nor on the map containing only distal cues, F(1,54) = 1.84, p = .14.

Table 1

3.2. Testosterone concentrations and CAGr Men (M = 474.18, SD = 146.56) had higher total T (ng/dL) than women (M = 23.32, SD = 7.37), t(27.14) = 16.26, p < .001. Free T (pg/mL) concentration was also greater in men (M = 87.62, SD = 23.71) than women (M = 2.28, SD = 1.14), t(28.13) = 19.36, p < .001. Number of CAG repeats ranged from 12 to 30 with a mean of 20.88 (SD = 3.39) and a median and mode of 21. There was no sex difference in CAGr, t(55) = .27, p = .79. Because CAGr is known to vary by ethnic ancestry (e.g., Irvine et al., 1995; Nelson and Witte, 2002), we tested for effects of race on CAGr in our sample. In our sample of men, there were 18 who identified as white/Caucasian, one as black/African American, and 10 as Asian, Arab, Indian, more than one race, or other. We compared the 18 white/Caucasian men to the other 11 and found no effect of race, F(1,26) = .17, p = .68. Our female sample included 14 women who identified as white/Caucasian, seven as black/African American, and eight as Arab, Hispanic or Indian. We categorized race as black, white, and other, and found an effect of race on CAGr, F(2,26) = 5.7, p = .01. Pairwise comparisons revealed that black women (M = 17.86, S.E. = 1.09) had fewer repeats than white (M = 21.57, S.E. = .77), p = .01, and other women (M = 22.63, S.E. = 1.02), p = .004. The difference between white and other was not significant, p = .42.

3.3. Bivariate and partial correlations between CAGr, testosterone, and vMWT Table 1 displays bivariate and partial correlations between CAGr, T, and vMWT in men and women. Correlations between the three biological variables and navigation performance range from negligible to moderate in both sexes. In women, CAGr was significantly correlated with free T, r(28) = .46, p = .01, which indicates that a greater number of CAG repeats (i.e., less active androgen receptors as measured by CAGr) is associated with higher free T concentration. Because of the effect of race on CAGr in women, we

Bivariate and partial correlations between T, CAGr, and vMWT in men and women. CAGr

CAGr Total T Free T Learning distance Goal distance Platform crossings Map all Map distal

Total T .07

.17 .46* * .13

Free T

Learning distance

Goal distance

Platform crossings

Map all

Map distal

.07 .75*** (.71***)

.40 * .31 (.43*) .05 (.00)

.05 .12 (.02) .13 (.05) .05

.15 .19 (.02) .20 (.09) .08

.24 .09 (.01) .15 (.09) .15

.19 .26 (.15) .24 (.06) .03

.26 .04

.19 .10

.48** (.42*) .02 (.01)

.03 (.10)

.24 .21

.01 (.05) .21 (.16)

.10 (.01) .14 (.05)

.08 .18

.55

.10 .21

.14 (.15) .16 (.13)

.31 (.36) .38* (.33)

.11 .16

.09 .15

.74 *** **

.07 .11

.28 .32

Note. Men above and women below the diagonal. In parentheses are the partial correlations between T and vMWT controlling for CAGr. * p  .05. ** p  .01. *** p  .001.

Contributions of sex, testosterone, and androgen receptor CAG repeat Table 2

Total testosterone and CAGr as predictors of vMWT performance in men and women. Men

Women

Learning distance

Probe goal distance

Simple effects Total T CAGr R2 F

.30 * .22 * .30 5.25 *

.06 .04 .01 .06

Interaction Total T  CAGr DR 2 F Total R 2

.12 .04 1.54 * .35

.25 .08 2.04 .09

* **

Probe platform crossings

Map all

Map distal walls

b .04 .11 .02 .29

.01 .15 .05 .61

.18 .15 .06 .73

.05 .01 .11 .03

.34 ** .26 8.19 * .31

.03 .00 .02 .06

3.4. Predicting vMWT scores from testosterone and CAGr All variables were z-standardized based on sex-specific means, and each of the following regression analyses were conducted separately for men and women. Hierarchical multiple regression was used to test the main effects of total T and CAGr, and the total T  CAGr interaction, on vMWT outcomes. Total Tand CAGr were entered as predictors in the first step, and the total T  CAGr interaction was entered as the predictor in the second step. A second set of regressions was conducted using the same entry method to test the main Table 3

Probe goal distance

Probe platform crossings

Map all

Map distal walls

.07 .13 .02 .28

.10 .22 .08 1.13

b .39 ** .09 .26 4.66 **

.08 .05 .01 .16

.10 .19 .06 .79

.01 .00 .00 .02

.10 .01 .32 .09

.03 .00 .03 .27

.27 * .15 4.49 * .16

.01 .00 .01 .06

effects of free Tand CAGr, and the free T  CAGr interaction, on the outcome variables. To visualize and interpret the interactions, we followed the methods described by Cohen and Cohen (1983) and Aiken and West (1991) to plot the interactions of our continuous predictors on the vMWT outcome variables, and test whether each simple slope was different from zero. It is conventional to use one standard deviation above (‘‘high’’) and below (‘‘low’’) each predictor to plot these interactions and to perform simple slope testing. As a final step, simple slope testing was performed on all of the significant interactions to determine whether the relationship between T and vMWT performance depended on the level of androgen receptor activity as measured by CAGr. To this end, hierarchical regressions were run using total or free T and one standard deviation above CAGr as predictors in the first step, and the T  one standard deviation above CAGr interaction in the second step. The regression process was repeated using one standard deviation below CAGr. Results are reported in the text, Tables 2 and 3, and Figs. 1 and 2.

Free testosterone and CAGr as predictors of vMWT performance in men and women. Men

Women

Learning distance

Probe goal distance

Probe platform crossings

Simple effects Free T CAGr R2 F

.01 .24 * .16 2.46

.09 .04 .01 .12

Interaction Free T  CAGr DR 2 F Total R 2

.00 .00 .00 .16

.37 * .18 5.46 * .19

*

Learning distance

p  .05. p  .01.

examined correlations between CAGr, T, and vMWT separately by race. Since no difference was found in CAGr between the white and ‘‘other’’ groups, these two were combined for analyses. Larger sample sizes are necessary to make any conclusions about the possible moderating effect of race.

**

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p  .05. p  .01.

Map all

Map distal walls

Learning distance

Probe goal distance

Probe platform crossings

Map all

Map distal walls

b .12 .11 .03 .42

.02 .15 .05 .67

.16 .15 .05 .68

.15 .20 .03 .32

.01 .22 .06 .74

b .06 .13 .05 .62

.35 .14 .13 1.81

.47 .04 .15 2.12

.17 .05 1.20 .08

.31 * .20 6.19 .25

.02 .00 .01 .05

.11 .01 .18 .03

.26 .06 1.76 .12

.03 .00 .04 .05

.30 * .15 4.98 * .28

.52 ** .22 8.05 ** .36

N.T. Nowak et al.

1.4 1.2 1 0.8 0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1 -1.2 -1.4

Low CAGr (i.e., high AR activity)

1.4

High CAGr (i.e., low AR activity)

1.2

Error on Map with Object Cues

Probe Trial Goal Distance

18

β = .03 Low Free T

High Free T

β = -.70*

1 0.6 0.4 0.2 0 -0.2

High Free T

β = -.04

-0.6 -0.8 -1 -1.2 -1.4 1.4

1.2

1.2

1

1

0.6

Learning Trials Total Distance

β = .52*

0.8

Error on Map with Object Cues

Low Free T

-0.4

1.4

0.4 0.2 0 -0.2

β = .58*

0.8

Low Total T

High Total T

-0.4

β = -.16

-0.6 -0.8 -1

β = .47*

0.8 0.6 0.4 0.2 0 -0.2

LowTotal T

High Total T

β = .23

-0.4 -0.6 -0.8 -1

-1.2

-1.2

-1.4

-1.4

Figure 1 Interactions between T and CAGr on vMWT dependent measures in men. Z-scores are shown on the y-axis. Lines represent the relationship between T and dependent measures for high CAGr (dashed) and low CAGr (solid).

1.4

1.2

1.2

β = .68*

Eorr on Map with All Object Cues

1 0.8 0.6 0.4 0.2 0 -0.2

Low Free T

-0.4

High Free T

β = .01

-0.6 -0.8 -1

Error on Map with Distal Wall Cues

1.4

0.6 0.4 0 -0.2

0.8 0.6

β = .35

0.4 0.2 0 Low Total T

High Total T

β = -.18

Probe Trial Number of Platform Crossings

1

-1

Low Total T

High Total T

-0.8 -1

1.4

1.2

-0.8

High Free T

-0.6

-1.4

-0.6

Low Free T

-0.4

-1.4

-0.4

β = .08

0.2

-1.2

1.4

Error on Map with Object Cues

1 0.8

-1.2

-0.2

β = 1.13**

1.2 1 0.8 0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1

-1.2

-1.2

-1.4

-1.4

β = -.35 β = -.27

Figure 2 Interactions between Tand CAGr on vMWT dependent measures in women. Z-scores are shown on the y-axis. Lines represent the relationship between T and dependent measures for high CAGr (dashed) and low CAGr (solid).

Contributions of sex, testosterone, and androgen receptor CAG repeat In men, total T (b = .30, p = .04) and CAGr (b = .22, p = .04) predicted total distance traveled to complete the learning trials, and accounted for a significant proportion of variance, R2 = .30, F(2, 24) = 5.25, p = .01. Total T and CAGr interacted to predict error on the overhead map with all cues, (b = .34, p = .01), and accounted for a significant proportion of variance, R2 = .31, DR2 = .26, F(1,22) = 8.19, p = .01. Simple slope testing revealed that the slope of this outcome on total T at high CAGr was significantly different from zero, (b = .52, p = .05). Free T and CAGr also interacted to predict error on the map with all cues, (b = .31, p = .02), and there was a main effect of CAGr (b = .29, p = .04). These effects accounted for a significant proportion of variance, R2 = .25, F(1,23) = 6.19, p = .02. Simple slope testing revealed that the slope of this outcome on free T at high CAGr was significantly different from zero, (b = .58, p = .04). Finally, free T and CAGr interacted to predict distance traveled in the goal quadrant during the probe trial, (b = .37, p = .03), and accounted for a significant proportion of variance, R2 = .19, DR2 = .18, F(1,24) = 5.46, p = .03. Simple slope testing revealed that the slope of this outcome on free T at high CAGr was significantly different from zero, (b = .70, p = .05). In women, total T (b = .39, p = .01) predicted number of platform area crossings during the probe trial, and accounted for a significant proportion of variance, R2 = .26, F(2, 26) = 4.66, p = .02. Total T and CAGr interacted to predict error in locating the platform on the overhead map which included all of the cues, (b = .27, p = .04), and accounted for a significant proportion of variance, R2 = .16, DR2 = .15, F(1,25) = 4.49, p = .04. Free T and CAGr also interacted to predict error on the map with all cues, (b = .30, p = .04), and accounted for a significant proportion of variance, R2 = .28, DR2 = .15, F(1,24) = 4.98, p = .04. Simple slope testing revealed that the slope of this outcome on free T at low CAGr was significantly different from zero, (b = .68, p = .01). Finally, free T and CAGr interacted to predict error on the overhead map with distal cues, (b = .52, p = .01), and accounted for a significant proportion of variance, R2 = .36, DR2 = .22, F(1,24) = 8.05, p = .01. Post hoc probing of this interaction between free T and CAGr in women revealed that the slope of the outcome on free T at low CAGr was significantly different from zero, (b = 1.13, p = .002). Due to the positive correlation between CAGr and free T in women, we assessed the possibility of multicollinearity in our regression models. The tolerance statistic for the hierarchical regressions was .93 (VIF = 1.07), and .38—.52 (VIF = 2.63—1.92) for the simple slope regressions. The values of these two diagnostic statistics indicate that multicollinearity was not a problem (Cohen et al., 2003, p. 423).

4. Discussion The purpose of this study was to assess the influence of sex, T, and CAGr on vMWT performance in a group of healthy young adults. Commensurate with prior research, we found that men outperformed women on a number of navigation outcomes (Astur et al., 1998; Sandstrom et al., 1998; Driscoll et al., 2005; Burkitt et al., 2007; Nowak and Moffat, 2011). Men required less distance to locate the hidden platform across the 10 learning trials than women, although this

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advantage only approached significance in the present study. During the probe trial, men traveled a greater distance in the goal quadrant and crossed the platform area more frequently. The results of this investigation suggest that CAGr, a marker of AR activity, may interact with T to affect navigation performance. In considering our findings regarding T in isolation from CAGr, lower total T predicted better navigation performance: in men, less distance traveled to locate the hidden platform across the learning trials; and in women more frequent platform area crossings in the probe trial. Previous studies have documented a null correlation between free T and time to complete the vMWT learning trials in young men (Driscoll et al., 2005; Burkitt et al., 2007), and a negative correlation with time to complete learning trials in young women. While few studies have related T to vMWT outcomes, several have reported positive, negative, or null effects of T on other domains of spatial cognition such as mental rotation (for review, see Puts et al., 2010) — a cognitive domain which is modestly correlated with navigational skill (e.g., Moffat et al., 1998; Driscoll et al., 2005). It is possible that different domains of spatial cognition are selectively sensitive to T, and that inclusion of a receptor specific marker of androgenicity could be useful in explaining these hormone—behavior relationships. In the present study, we observed interactive relationships between T and vMWT performance. In men, low T was associated with better performance as measured by greater distance traveled in the goal quadrant of the probe trial, and less error on demarcation of the platform location on the overhead map which contained only proximal object cues. This effect of T on performance was significant at a low level of AR activity (i.e., greater number of CAGr). Thus, in young adult men who are at or near their lifetime peak in T levels, lower effective T (i.e., lower T and greater number of CAGr) was associated with better performance. These effects are similar to past studies which have suggested that optimal spatial performance (mental rotation or spatial visualization) is associated with a T level near the upper end of the female distribution and lower end of the male distribution (Shute et al., 1983; Gouchie and Kimura, 1991; Moffat and Hampson, 1996; Puts et al., 2008). This pattern of results is captured in the optimum T level theory — the notion that higher T young women and lower T young men have the best spatial performance, and our results in men are compatible with this theory. However, the results in women were more unexpected and cannot be easily captured by the optimum T level framework. In women, low Tcoupled with greater AR activity (i.e., fewer CAGr) predicted more accurate demarcation of the platform on the overhead maps. The interaction of low T and higher receptor activity suggests that a moderate level of androgenicity may be associated with optimal performance on these overhead mapping tasks which were designed to assess allocentric spatial memory. A number of factors may limit the degree to which these results can be related to previous studies on T and spatial cognition in women, including lack of correspondence between spatial measures; a more racially diverse sample than previous studies; and the fact that we tested women during menses when both T and E are low. These factors are discussed in more detail below.

20 There are clearly still major gaps in our knowledge about the possible mechanisms by which T and AR sensitivity could affect human navigation behavior, brain structure and function. In order for androgens to directly affect spatial learning and memory through the classical nuclear mechanism, ARs must be present and functional in the brain to interact with T and dihydrotestosterone. Androgen receptors have been found in human brain regions known to facilitate spatial navigation, such as the temporal cortex (Puy et al., 1995) and hippocampus (Beyenburg et al., 2000). Both of these findings highlight the importance of the interaction between circulating T, which varies substantially within the individual, and the receptor specific CAGr, which is a stable intraindividual measure of lifelong androgen sensitivity. Inclusion of CAGr in future research has the potential to expand our knowledge regarding the hormone—gene relationships which affect the brain, spatial and other behaviors. A growing body of work is documenting the importance of this polymorphism in predicting normal and pathophysiological human conditions. For example, the length of the CAG polymorphism, or the interaction of it with T, is predictive of reproductive health conditions in men (Zitzmann, 2009) and women (Shah et al., 2008); self-reported dominance and prestige in men (Simmons & Roney, 2011); handedness and negative affect in men (Hampson & Sankar, 2012; Sankar & Hampson, 2012); white matter volume in adolescent males (Perrin et al., 2008); and risk for Alzheimer’s disease in men (Lehman et al., 2003, 2004). The strengths of our study lie in the concurrent investigation of T and an AR receptor polymorphism and our control of several possible confounding factors. Sexual orientation may affect spatial scores, so we included only heterosexual participants in our analyses. Heterosexual men tend to perform better than homosexual men on measures of spatial cognition such as mental rotation and spatial perception (Sanders and Ross-Field, 1986; Gladue et al., 1990; McCormick and Witelson, 1991; Wegesin, 1998; Neave et al., 1999; Rahman and Wilson, 2003). Homosexual men have been found to use more landmarks on a map navigation task than heterosexual men, which is a navigation strategy that is more often employed by women (Rahman et al., 2005). On a test of object location memory, a spatial task which often favors females, homosexual men had better scores than heterosexual men (Rahman et al., 2003). Less is known about the possible influence of sexual orientation on navigation in women. Secondly, the debate surrounding specimen collection (saliva vs. blood) and quantitation of T (radioimmunoassay vs. LC—MS/MS) is ongoing; we collected blood samples in order to quantify T by LC—MS/MS, the ‘‘gold standard’’ for T measurement (Rosner et al., 2007). Finally, women in our sample were not taking hormonal contraceptives, some of which are known to suppress T levels by up to 60% (Wiegratz et al., 1995) and have been observed to impact spatial performance (for review, see Hampson, 2008; Griksiene and Ruksenas, 2011). The present study also has some limitations. The primary limitation was the relatively small sample size. It is possible that some of the effects represent type I error, just as it is possible that true effects were not detected within the sample. Our sample was likely more racially diverse than most other studies (many previous studies have not reported the racial composition of their samples). Mean CAGr has been

N.T. Nowak et al. found to differ by race (Irvine et al., 1995; Nelson and Witte, 2002) and this was true in our sample in which the average CAGr for women who identified as black or African American was lower than the group average for white/Caucasian women. However, the small samples within each race precluded any conclusions about the possible moderating nature of race on the relationships between T, CAGr, and navigation. The racial heterogeneity of our sample will help generalize the results to the general population but limits the comparison to previous studies based on more homogeneous samples. Testing women during menses had both advantages and disadvantages. The advantage was that it met our goal of controlling for possible menstrual cycle effects on spatial cognition (e.g., see Hampson, 2008). However, T is low during menses, so capturing only this phase may have resulted in a narrow distribution of T. The reference range for women age 18—69 years for the free T test we used is .1—6.4 pg/mL, and our observed range was from .7 to 5.1 pg/mL. For total T, the reference range for the test is 2—45 ng/dL and our observed values ranged from 10 to 44. Thus it could be argued that we under sampled women at the very high and low normal ends of the T distribution.

5. Conclusion The innovation of this study lies in the measurement of both T and CAGr as measures of androgenicity, in assessing the association between androgens and spatial navigation. The results suggest that effects of T on spatial navigation may depend on the number of CAGr. For men with low and women with high AR activity, lower T predicted better vMWT performance. This investigation should be considered a preliminary one which may motivate reconsideration of reported associations between T and a number of behavioral outcomes. Given the novelty of this approach, it will be important to confirm whether these interactions between CAGr and T are upheld in separate and larger samples and across different cognitive domains.

Role of the funding source None.

Conflict of interest None declared.

Acknowledgements We thank Dr. Michael P. Diamond for his expertise, and donation of laboratory space; Dr. Susan J. Land from the Wayne State Applied Genomics Technology Center (supported, in part, by NIH Center grant P30 CA022453) for quantification of the CAGr; all of the staff at the Wayne State Clinical Research Center for their time; Victoria Good for her work as a research assistant; and all of our participants.

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