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. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: Neuroscience. 2021 Feb 13;459:118–128. doi: 10.1016/j.neuroscience.2021.02.014

Sex-related differences in stress reactivity and cingulum white matter

MD Wheelock a,I, AM Goodman a,II, NG Harnett a,III, KH Wood a,IV, S Mrug a, DA Granger b,c, DC Knight a
PMCID: PMC7965343  NIHMSID: NIHMS1673850  PMID: 33588003

Abstract

The prefrontal cortex and limbic system are important components of the neural circuit that underlies stress and anxiety. These brain regions are connected by white matter tracts that support neural communication including the cingulum, uncinate fasciculus, and the fornix/stria-terminalis. Determining the relationship between stress reactivity and these white matter tracts may provide new insight into factors that underlie stress susceptibility and resilience. Therefore, the present study investigated sex differences in the relationship between stress reactivity and generalized fractional anisotropy (GFA) of the white matter tracts that link the prefrontal cortex and limbic system. Diffusion weighted images were collected and deterministic tractography was completed in 104 young adults (55 men, 49 women; mean age = 18.87 SEM = 0.08). Participants also completed self-report questionnaires (e.g., Trait Anxiety) and donated saliva (later assayed for cortisol) before, during, and after the Trier Social Stress Test. Results revealed that stress reactivity (area under the curve increase in cortisol) and GFA of the cingulum bundle varied by sex. Specifically, men demonstrated greater cortisol reactivity and greater GFA within the cingulum than women. Further, an interaction between sex, stress reactivity, and cingulum GFA was observed in which men demonstrated a positive relationship while women demonstrated a negative relationship between GFA and cortisol reactivity. Finally, trait anxiety was positively associated with the GFA of the fornix/stria terminalis - the white matter pathways that connect the hippocampus/amygdala to the hypothalamus. These findings advance our understanding of factors that underlie individual differences in stress reactivity.

Keywords: cortisol, sex, stress, DTI, cingulum, anxiety

Introduction

The prefrontal cortex (PFC), hippocampus, and amygdala are important components of the neural circuit that mediates stress reactivity (Goodman et al., 2016; Orem et al., 2019; Pruessner et al., 2008; Wheelock et al., 2016; Wheelock et al., 2018). Specifically, the PFC, amygdala, and hippocampus modulate hypothalamic-pituitary-adrenal (HPA) axis activity (Herman et al., 2005; Ziegler and Herman, 2002), with the subsequent release of cortisol (measurable in saliva), as the end-result of such activation (Granger et al., 2012). Although prior research has clearly demonstrated the importance of these brain regions in stress-related processes, the role of the white matter that connects these brain regions has received less empirical attention. In contrast, many studies have investigated the relationship between stress reactivity and functional brain connectivity. For instance, functional connectivity between the amygdala and dorsomedial PFC (dmPFC) and ventromedial PFC (vmPFC) is greater after completing a stressful task (van Marle et al., 2010; Veer et al., 2011). The increased functional connectivity between these brain regions suggests that analogous structural connections (e.g., the cingulum bundle and uncinate fasciculus) between these brain regions may play an important role in stress-related processes.

Although a number of prior studies have investigated the brain regions that mediate stress reactivity (Goodman et al., 2016; Orem et al., 2019; Pruessner et al., 2008; van Marle et al., 2010; Veer et al., 2011; Wheelock et al., 2016; Wheelock et al., 2018), few studies have investigated the microstructure of the white matter tracts (i.e., the fiber architecture of white matter) that connect these brain regions. Fractional anisotropy (FA) is one of several measures of tract-specific microstructural constraints on water diffusion that indexes axonal density and myelination (Mori and Zhang, 2006). Other related measures of diffusion (e.g., mean, axial, and radial diffusivity) index mean water diffusion or diffusion parallel and perpendicular to fiber tracts (Soares et al., 2013). Additional metrics, such as generalized FA (GFA), model fiber orientation resulting in superior diffusion tracking along crossing fibers (Tuch, 2004). The limited prior research that has assessed the relationship between FA and cortisol reactivity is equivocal. Specifically, some prior work suggests that low FA within the white matter adjacent to the rostral anterior cingulate is associated with high stress reactivity (Sheikh et al., 2014). However, two later studies did not observe an association between stress reactivity and the white matter of the fornix, cingulum, or uncinate fasciculus (Cox et al., 2015; Nugent et al., 2015). However, these prior studies were limited by a small sample size (Nugent et al., 2015) or only recruited male participants (Cox et al., 2015). Although other research has not focused explicitly on stress reactivity, a relationship has been observed between the cortisol awakening response and uncinate fasciculus and cingulum FA (Madsen et al., 2012). Similarly, higher levels of early morning cortisol have been associated with reduced cingulum FA (Echouffo-Tcheugui et al., 2018). Taken together, prior work suggests the microstructure of the white matter tracts that connect the PFC and limbic system may influence the expression and regulation of the emotional response to stress.

Psychological traits such as anxiety have also been associated with the microstructure of white matter pathways (e.g., uncinate fasciculus, cingulum bundle, and fornix/stria terminalis) that connect the PFC, hippocampus, amygdala, and hypothalamus (Clewett et al., 2014; Eden et al., 2015; Kim and Whalen, 2009; Modi et al., 2013; Montag et al., 2012; Olson et al., 2015; Von Der Heide et al., 2013). Cumulatively these prior findings suggest the white matter that connects brain regions supporting emotion regulation is compromised by anxiety. However, there are important inconsistencies in this prior work. Specifically, while some of these studies found greater trait anxiety was associated with higher FA, others have found the opposite - lower trait anxiety associated with higher anisotropy (Clewett et al., 2014; Eden et al., 2015; Kim and Whalen, 2009; Kim et al., 2016; Modi et al., 2013; Montag et al., 2012). Thus, further research is necessary to establish the relationship between white matter microstructure and trait anxiety.

Sex differences in the emotional response to stress have been frequently observed in prior research and may underlie sex-related differences in the vulnerability to stress-related psychiatric disorders (Balodis et al., 2010; Het et al., 2012; Kirschbaum et al., 1999; Schoofs et al., 2013; Shalev et al., 2009). For example, the lifetime prevalence of depression, panic disorder, and generalized anxiety is greater in women than men (Eaton et al., 2012). Given that brain regions that include the PFC and amygdala appear to regulate the cortisol response and are implicated in depression and anxiety, it is likely that individual differences in stress reactivity play an important role in psychiatric disorders. Therefore, understanding the neural underpinnings of sex differences in stress reactivity may provide new insight into the susceptibility to stress-related psychiatric disorders. Prior studies that have investigated sex differences in stress reactivity suggest that the stress-elicited cortisol response is greater in men than women (Reschke-Hernandez et al., 2017), even after controlling for menstrual cycle phase (Stephens et al., 2016). Further, women on contraceptives/estrodial treatment also show a stress-elicited cortisol response that is lower than men (Merz and Wolf, 2015) as well as lower than women not taking oral contraceptives (Liu et al., 2017). Although prior research has demonstrated sex differences in white matter microstructure (Inano et al., 2011; Kim et al., 2017; Menzler et al., 2011; Oh et al., 2007; Ritchie et al., 2018; van Hemmen et al., 2017), limited research has investigated whether white matter microstructure varies with contraceptive use (De Bondt et al., 2013) or sex differences in stress-reactivity.

The present study investigated the GFA of white matter tracts that connect brain regions that support emotion expression and regulation processes to determine whether white matter varies with stress reactivity, trait anxiety, and sex. Diffusion weighted images were collected to determine whether white matter GFA varies with salivary cortisol in response to the Trier Social Stress Test (TSST) (Kirschbaum et al., 1993), State-Trait Anxiety Inventory (Spielberger, 1983), and sex. The present study estimated white matter microstructure using GFA, a more accurate measure of the direction of water diffusion within complex tissue structures and regions of crossing fibers than FA (Glenn et al., 2015). We hypothesized that the GFA of the cingulum bundle (connecting the dorsal cingulate to the vmPFC and temporal lobe), uncinate fasciculus (connecting the vmPFC and temporal lobe), and the fornix/stria terminalis (connecting the temporal lobe to the hypothalamus) would vary with stress reactivity, trait anxiety, and sex. More specifically, we hypothesized that greater stress reactivity and trait anxiety would be linked to 1) greater cingulum GFA given the dmPFC’s role in top down control of emotion-related processes (Montag et al., 2012; Shackman et al., 2011; Wheelock et al., 2014; Wood et al., 2012), 2) reduced uncinate fasciculus GFA given the vmPFC’s role in emotion regulation (Baur et al., 2011; Eden et al., 2015; Ochsner et al., 2012; Sheikh et al., 2014; Tromp et al., 2012), and 3) increased stria terminalis GFA given the amygdala’s excitatory impact on HPA axis activity (Herman et al., 2005; Modi et al., 2013). We hypothesized these white matter relationships would be stronger in men than women given men typically show greater stress reactivity than women (Reschke-Hernandez et al., 2017; Stephens et al., 2016). Determining the relationship stress reactivity, trait anxiety, and sex have with the microstructure of these white matter tracts will offer important new insights into the neurobiology of emotion.

Materials and Methods

Participants

One hundred twenty right-handed volunteers participated in this study as part of a larger longitudinal study of a community sample (MH098348). Participants were initially recruited from 5th grade classrooms in local public schools and were interviewed four times between the ages of 11 and 20 years. Following the completion of the final interview, participants were invited to return for a magnetic resonance imaging (MRI) study. Women were administered a pregnancy test and were excluded from the MRI study if pregnant. Additionally, women responded to a verbal self-report measure about their use of contraceptives and the number of days since the beginning of their last menstruation. Five participants were excluded from the present study due to a self-reported diagnosis of anxiety, depression, or obsessive compulsive disorder. An additional nine participants were excluded from the present analysis due to insufficient quantity of saliva samples (n=2) or poor quality/missing diffusion tensor imaging (DTI) data (n=7). Two additional participants were identified as extreme outliers (greater than 3 SD above the mean) on more than two raw cortisol values and were excluded from further analyses. Thus, a total of 104 participants (55 men, 49 women, mean age=18.87, SEM=0.08, age range 17–22 years, 59 Black American, 45 White American) were included in the present analyses. All participants provided written informed consent as approved by the University of Alabama at Birmingham Institutional Review Board.

Psychosocial Stress

The TSST was completed outside the scanning environment on a separate day prior to the DTI scan (Gossett et al., 2018). The TSST consisted of a five-minute speech preparation period, a five-minute mock job interview, and a five-minute mental arithmetic task involving serial subtraction (Kirschbaum et al., 1999). During the mock job interview, participants were instructed to pretend that they were a job applicant delivering a speech in front of an evaluation panel in hopes of being hired. While giving the speech, participants sat approximately three meters away from a desk behind which sat two judges wearing white lab coats. The judges did not provide any positive feedback during the task including any emotionally supportive gestures or dialogue. Participants were also told that the judges were trained to detect verbal and non-verbal stress signals, and that their performance was being video recorded for later analysis. If participants ended their speech early, they were told to continue until the full five minutes had elapsed. Following the mock job interview, participants completed the arithmetic (i.e., serial subtraction) portion of the test. Participants were instructed to subtract backwards from 996 in increments of 13 as quickly and accurately as possible. After every mistake, one of the judges instructed participants to stop and start again at 996.

Trait Anxiety

Participants completed the State Trait Anxiety Inventory (STAI form Y, Spielberger, 1983) prior to the imaging session. Scores on the trait anxiety scale were used as an index of participants’ negative affect.

Saliva Collection and Determination of Cortisol

Participants were interviewed and acclimated to the lab environment for approximately 60 minutes prior to collecting the baseline cortisol sample. Saliva samples were collected five minutes prior to the speech preparation portion of the TSST (pre-stress), 10 minutes after the serial subtraction portion of the TSST (post-stress), and 45 minutes after the TSST ended (recovery), following the procedures described in previously published work (Guo et al., 2017). Each salivary sample (1.0 ml) was collected using passive drool through a short straw into 2.0 ml cryovials, then stored at −80C. All saliva collections were scheduled in the afternoon (Mean=16:06, SEM=0:05, Range=13:37–18:06 hours) to avoid the cortisol awakening response and steep decline in cortisol levels across the morning.

Samples were shipped on dry-ice to the Institute for Interdisciplinary Salivary Bioscience Research. Samples were thawed and centrifuged at 3,000 rpm for 15 minutes to remove mucins. Samples were assayed for cortisol in duplicate using a commercially available enzyme immunoassay kit (Salimetrics, LLC in State College, PA) following the manufacturers recommended protocol. The test volume was 25 μl, range of sensitivity was from 0.007 to 3 μg/dl. On average, intra- and inter-assay coefficients of variation were less than 10% and 15%. The average of the duplicate assays for each sample were used in the statistical analysis.

Diffusion Weighted Imaging

Whole brain diffusion weighted imaging (DWI) data were acquired on a 3T Siemens Allegra scanner using a single channel head coil in 60 directions with one b0 image (TR=4600ms, TE=79ms, slices=41, FOV=24cm, voxel dimensions=2.5 mm isotropic, b-value=1000 s/mm2, acquisition time=4 minutes and 45 seconds). A 6 minute and 25 second T1 magnetization prepared-rapid gradient echo image was acquired for registration of DWI images (TR = 2300 ms, TE = 3.9 ms, flip angle = 12°, FOV = 25.6 cm, matrix = 256×256, slice thickness = 1 mm, 160 slices, 0.5 mm gap).

Tractography

Tractography was completed using DSI Studio (December 2015 build). DWI data were first eddy current corrected and then the fiber orientation density function (ODF) was estimated. The ODFs were reconstructed into MNI space using Q-space diffeomorphic reconstruction (Yeh and Tseng, 2011) to obtain the spin distribution function, and were resampled to 2mm resolution. A diffusion connectometry dataset was constructed that contained ODFs for all subjects (Yeh et al., 2016). Six tracts of interest were identified based on the neural network that supports emotion expression and regulation. The tracts of interest included bilateral cingulum bundle, uncinate fasciculus, and fornix/stria terminalis (6 tracts bilaterally). The fornix and stria terminalis comprised one seed region due to limitations in the resolution of the DTI data. The tracts for these regions were generated using seeds from the Johns Hopkins University (JHU) DTI atlas (Mori et al., 2008) included in DSI Studio.

Statistical Analysis

Confirmatory Statistical Analysis of Cortisol Reactivity and Sex.

Cortisol data were transformed to nmol/L and cortisol reactivity outliers were assessed prior to statistical analyses (defined as a z-score greater than 3.29). Following transformation and exclusion of outliers, cortisol reactivity was calculated using area under the curve with respect to increase (AUCi) (Pruessner et al., 2003). Preliminary analyses were performed to confirm the expected effect of stress on cortisol levels for the full sample using a one-way repeated measures ANOVA. ANOVA and an independent samples t-test were used to confirm sex differences in cortisol reactivity (i.e., AUCi). Violations of sphericity in the repeated measures ANOVA assessing cortisol were corrected using Greenhouse-Geisser adjusted degrees of freedom. All post-hoc tests were corrected for multiple comparisons using Bonferroni correction (p<0.05 corrected).

Comparison of White Matter Microstructure to Cortisol Reactivity, Trait Anxiety, and Sex.

The relationship between the independent measures (AUCi, trait anxiety, and sex) and the 6 tracts of interest were assessed using multiple linear regression within DSI Studio. A nominal correlation effect size of 5% was used to threshold the voxelwise data and a deterministic fiber tracking algorithm with a seeding density of 1 seed per mm3 (Yeh et al., 2013) was used to identify tracts that varied with AUCi and trait anxiety. To estimate the false discovery rate (FDR), a total of 2000 randomized permutations were applied to obtain the null distribution of the track length. GFA was calculated by min-max scaling the normalized diffusion orientation distribution function (Tuch, 2004) and was used to assess tract microstructure. GFA is an extension of the FA metric and is similarly scaled from 0 to 1, but is more resilient to crossing fibers (Glenn et al., 2015). White matter tract streamlines that demonstrated a significant association with one or more of the independent variables (FDR p≤0.05) were turned into ROI and the average GFA values were extracted from each subject for follow-up analysis of these tracts using SPSS. All post-hoc tests were corrected for multiple comparisons using Bonferroni correction (p≤0.05 corrected).

Comparison of White Matter Microstructure to Cortisol Reactivity and Contraceptive use.

Women participants responded to a verbal self-report measure about their use of contraceptives and the number of days since the beginning of their last menstruation. Sixteen women reported using contraceptives (12 oral contraceptive, 3 depo shot, 1 implant). Baseline cortisol, cortisol reactivity, and GFA were compared between men, naturally cycling women, and women on contraceptives. A Shaprio-Wilk test of normality and Levene’s test for homogeneity of variance were run prior to ANOVA. Comparisons of baseline cortisol, cortisol reactivity, and contraceptive use were also completed. Finally, the relationship between cortisol reactivity and menstrual cycle phase was also assessed. Five naturally cycling women were excluded from analyses of menstrual cycle phase for reporting their last menstruation as greater than 40 days prior to the study, leaving 28 naturally cycling women in the analysis. Women reporting less than 13 days since menstruation were considered in the follicular phase (n=19). Women between 15 and 28 days since menstruation were considered in the luteal phase (n=10). Results from all exploratory analyses of contraceptive use and menstrual cycle phase are reported in the supplemental materials.

Results

Preliminary and Confirmatory Analyses of the Association Between Sex and Cortisol Reactivity

As expected, the TSST had a significant impact on cortisol levels (F[1.64,169.02]=18.60, p<0.001) (Figure 1). Cortisol levels increased from pre- (M=4.05, SEM=0.20) to post-stress (M=5.57, SEM=0.32; t[103]=−4.84, p<0.001), and decreased from post-stress to recovery (M=4.22, SEM=0.26; t[103]=6.66, p<0.001). Recovery period cortisol levels were not significantly different from pre-stress levels (t[103]=−0.61, p>0.05). There was a significant interaction between sex and time (i.e., pre-stress, post-stress, and recovery) for cortisol levels (F[1.65, 168.58]=3.76, p<0.033) (Figure1). Follow-up post hoc tests revealed that, while there were no sex difference in pre-stress cortisol, men had higher post-stress (p<0.001) and recovery (p<0.01) cortisol levels than women (Figure 1 and Table 1). Further, men demonstrated higher post-stress than pre-stress cortisol (p<0.001, Table 2), while women’s pre- and post-stress cortisol levels did not significantly differ (p>0.05, Table 2). Both men and women demonstrated greater post-stress cortisol than recovery cortisol (Table 2). A main effect of cortisol across time was also observed (F[1.65,168.58]=18.48, p<0.001) as well as a main effect of sex (F[1,102]=10.41, p=0.002). This finding was mirrored in the cortisol AUCi data. Specifically, men demonstrated greater cortisol AUCi than women (t[102]=2.21, p<0.05). AUCi did not vary by race (p>0.05) or age (p>0.05) and was not correlated with trait anxiety (p>0.05).

Figure 1.

Figure 1.

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Cortisol reactivity differed between men and women. A) There was a significant sex by time interaction (p<0.05) such that men demonstrated a greater cortisol response at post-stress and recovery than women. Error bars reflect standard error of the mean. B) Area under the curve increase (AUCi) in cortisol was greater for men than women. Boxes represent the 1st and 3rd quartiles and whiskers represent 1.5 times the interquartile range. **p<0.005 *p<0.05

Table 1.

Sex differences in cortisol reactivity and trait anxiety

Cortisol (nmol/L) Men (54) Women (50) df Cohen’s d t p
pre-stress 4.31±0.31 3.75±0.25 102 0.11 1.139 0.168
post-stress 6.56±0.40 4.51±0.47 102 0.33 3.342 0.001*
recovery 4.87±0.35 3.53±0.36 102 0.26 2.673 0.009*
AUCi 96.52±22.58 25.17±23.11 102 0.22 2.206 0.03*
Trait anxiety 35.00±1.19 33.08±1.21 102 0.11 1.132 0.26
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AUCi= Cortisol Area Under the Curve with respect to increase.

*

Significant after Bonferroni correction. Pre-stress, post-stress, and recovery contrasts were corrected for three tests. AUCi and trait anxiety were treated as a separate family of tests and corrections were not applied.

Table 2.

Within group differences in cortisol reactivity

Men Mean diff df Cohen’s d t p
pre vs post −2.24±0.42 53 −0.74 −5.367 <0.001*
post vs recovery 1.69±0.26 53 0.89 6.448 <0.001*
pre vs recovery −0.55±0.42 53 −0.18 −1.302 0.199
Women Mean diff df t p
pre vs post −0.76±0.46 49 −0.24 −1.658 0.104
post vs recovery 0.98±0.31 49 0.46 3.207 0.002*
pre vs recovery 0.23±0.39 49 0.08 0.582 0.563
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*

Significant after Bonferroni correction for six tests.

Hypothesized Association Between White Matter Microstructure and Cortisol Reactivity

Multiple regression was used to predict cortisol reactivity (AUCi) from the microstructure of the 6 fiber pathways of interest (i.e., bilateral cingulum, uncinate fasciculus, and fornix/stria terminalis) using DSI Studio. No significant relationship was observed between the GFA of these 6 tracts and AUCi (p>0.05).

Hypothesized Association between White Matter Microstructure and Trait Anxiety

Trait anxiety (Mean=34.07, SEM=0.83, Range=20–57) did not correlate with cortisol reactivity (AUCi) (p>0.05). Multiple regression revealed that trait anxiety varied with left fornix/stria terminalis GFA (p≤0.05) (Figure 2). GFA from the left fornix/stria terminalis was then extracted for each participant, and graphed to illustrate the positive correlation between trait anxiety level and GFA of the left fornix/stria terminalis (Figure 2). Sex and race did not explain significant variance in trait anxiety or fornix/stria terminalis anisotropy (p>0.05).

Figure 2.

Figure 2.

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Relationship between trait anxiety and the fornix/stria terminalis. Tract color represents generalized fractional anisotropy (GFA). Trait anxiety increased as the GFA of the left fornix/stria terminalis increased (FDR p<0.05). Lines on either side of the fitted line represent the 95% individual prediction interval.

Hypothesized Association between White Matter Microstructure and Sex

The effect of sex on white matter microstructure was assessed using multiple regression within DSI studio with sex coded as a binary variable. Men demonstrated greater anisotropy within the bilateral cingulum than women (FDR p≤0.05) (Figure 3, Table 3). GFA of the fornix/stria terminalis and uncinate fasciculus did not vary by sex. Further, GFA of the cingulum did not vary with age (Right cingulum: r=0.02: Left cingulum: r=0.04; p>0.05). Given cortisol and cingulum white matter microstructure varied with sex, we extracted GFA values from the cingulum bundle to determine whether there was an interaction between sex and white matter microstructure on stress reactivity (i.e., cortisol AUCi). Because there was no significant relationship between sex and the white matter of the uncinate fasciculus and stria terminalis/fornix in DSI studio, GFA values for these structures could not be extracted and similar analyses could not be performed. Two linear regressions (one for each cingulum white matter tract) were performed in which GFA, sex, and an interaction term between GFA and sex were included in the model predicting stress reactivity. The variables were centered prior to generating the interaction term between cingulum GFA and sex. GFA for left and right cingulum were normally distributed and had equal variance. Standardized beta values are reported below.

Figure 3.

Figure 3.

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Sex differences in the bilateral cingulum. Tract color represents generalized fractional anisotropy (GFA). GFA of tracts within the cingulum bundle differed between sexes. Men had significantly greater GFA within the left and right cingulum than women (FDR p<0.05). Boxes represent the 1st and 3rd quartiles and whiskers represent 1.5 times the interquartile range. *Indicates p<0.01.

Table 3.

Sex differences in cingulum microstructure

Region Men (54) M±SEM Women (50) M±SEM Cohen’s d t p
Left 0.103±0.003 0.093±0.003 0.52 2.610 0.010*
Right 0.090±0.002 0.082±0.002 0.55 2.803 0.006*
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*

Significant after Bonferroni correction for two tests.

Results indicated that cortisol reactivity (AUCi) varied with sex (β = −0.20, p<0.05). Specifically, men showed a larger cortisol response than women. Cortisol reactivity (AUCi) did not vary with right (β = 0.04, p>0.05) or left (β = 0.01, p>0.05) cingulum GFA. However, the interaction between sex and right cingulum GFA did vary with cortisol reactivity (AUCi) (β = 0.218, p<0.05), suggesting that the effect of sex on cortisol reactivity depends on the GFA in the right cingulum (Figure 4; Table 4). Although the interaction between sex and GFA in the left cingulum was in the same direction as the right cingulum (Figure 4), the interaction of GFA and the left cingulum was not significantly associated with cortisol reactivity (β = .128, p>0.05).

Figure 4.

Figure 4.

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Sex and cingulum Generalized Fractional Anisotropy (GFA). A) An interaction was observed between sex, cortisol area under the curve with respect to increase (AUCi), and right cingulum GFA (p<0.05). B) While a similar pattern was observed between sex and left cingulum GFA, this relationship did not meet statistical significance (p>0.05).

Table 4.

Interaction between sex, cortisol reactivity, and cingulum microstructure

Region Men (54) r (p) Women (50) r (p) Cohen’s d F p
Left −0.116 (0.406) 0.148 (0.305) 0.18 1.75 0.189
Right −0.191 (0.166) 0.251 (0.079) 0.31 5.15 0.025*
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Pearson r values reported for each group. F and p values are reported for the interaction between sex and cingulum GFA predicting cortisol AUCi.

*

Significant after Bonferroni correction for two tests.

Exploratory Analyses of Associations between White Matter Microstructure, Cortisol Reactivity, Contraceptive use, and Menstrual Cycle Phase

Exploratory analyses were conducted to better understand the relationship between cortisol, white matter microstructure, menstrual cycle phase, and contraceptive use. Women were separated into groups that were either naturally cycling (n=29) or using contraceptives (n=16). Naturally cycling women were further divided into those that were in the follicular (n=19) and luteal (n=10) phase. Due to the limited sample size of the self-reported menstrual phase data, exploratory analyses of the effects of menstrual phase on cortisol reactivity and contraceptive use on cortisol and cingulum GFA are included in supplemental materials. Please see supplemental results and supplemental figures 1 – 3 for these analyses.

Discussion

The present study investigated whether the GFA of white matter pathways (i.e., cingulum bundle, uncinate fasciculus, and stria terminalis/fornix) varied with stress reactivity, trait anxiety, and sex. Stress reactivity (indexed by the cortisol response to the TSST) varied with sex and contraceptive use. Although we did not observe a direct relationship between cortisol reactivity and white matter GFA, we did find that inter-individual variability in the GFA of the white matter of the fornix/stria terminalis varied with individual differences in trait anxiety. Further, we found that the GFA of the cingulum varied by sex. In fact, the interaction of sex and cingulum GFA explained significant variance in stress reactivity. Specifically, right cingulum GFA was positively related with stress reactivity in women, while right cingulum GFA was negatively related with stress reactivity in men. These findings suggest the white matter that connects the PFC and limbic system varies by sex and with individual differences in trait anxiety. These findings provide new insight into the relationship these white matter pathways (i.e., cingulum bundle) may have with stress reactivity.

Trait anxiety is associated with white matter microstructure

The prior research that has investigated normal, healthy variation of white matter and trait anxiety is inconclusive. For example, prior research has demonstrated a negative relationship between trait anxiety and the microstructure of the uncinate fasciculus (Eden et al., 2015; Kim and Whalen, 2009; Kim et al., 2017; Kim et al., 2016), while other studies have demonstrated a positive relationship between trait anxiety and white matter of the cingulum (Montag et al., 2012), uncinate fasciculus (Clewett et al., 2014; Modi et al., 2013; Montag et al., 2012), and fornix/stria terminalis (Modi et al., 2013). Further, research using probabilistic tractography between seed regions found that trait anxiety varies positively with the number of tracts that connect the amygdala and dorsal anterior cingulate cortex. In contrast, a negative relationship was observed between trait anxiety and the number of tracts that connect the amygdala, medial orbitofrontal cortex, and parahippocampal gyrus (i.e. regions that contain the uncinate and fornix/stria terminalis) (Greening and Mitchell, 2015). The discrepancies in the white matter findings across prior studies of trait anxiety may be driven by differences in sample size, DWI acquisition parameters, and probabilistic vs deterministic tractography. In the present study, we did not observe a relationship between trait anxiety and uncinate white matter GFA, which is inconsistent with some of the prior work on this topic. However, we did observe a positive relationship between trait anxiety and the fornix/stria terminalis. Our findings are supported by prior work (Modi et al., 2013), that has also observed a positive relationship between trait anxiety and the stria terminalis/fornix. Thus, the present findings in combination with prior research, suggest the microstructure of the white matter pathways that connect the amygdala, hippocampus, and hypothalamus play an important role in anxiety.

The relationship between white matter microstructure and stress reactivity

To our knowledge, this is the largest study to date to assess the relationship between white matter microstructure and psychosocial stress reactivity in young adults. Stress reactivity (indexed via AUCi salivary cortisol) did not vary with the GFA of the cingulum, uncinate fasciculus, and fornix/stria terminalis in the present study. Interestingly, the current findings are in contrast to prior psychosocial stress research that found decreased FA in the white matter adjacent to the rostral anterior cingulum in young elementary age girls with high stress reactivity (Sheikh et al., 2014). These discrepant findings may be due to differences in the age and sex of participants in the present as compared to the prior research, as both age and sex can influence white matter microstructure (Inano et al., 2011). Furthermore, the prior study separated participants into groups of high and low cortisol reactivity, while the present study assessed the relationship between cortisol reactivity and GFA as a continuous variable. Although there has been limited prior investigations of the relationship between white matter and stress reactivity, more studies have assessed the relationship between white matter and morning cortisol levels. However, the specific regions associated with morning cortisol as well as the direction of white matter changes in these prior studies have been inconsistent (Bierer et al., 2015; Madsen et al., 2012). Although prior research suggests that the brain regions connected by these white matter tracts play an important role in the emotional response to stress (Harnett et al., 2015; Herman et al., 2005; Wheelock et al., 2018; Wheelock et al., 2014; Wood et al., 2012), we found no relationship between stress reactivity and the GFA of the uncinate fasciculus or fornix/stria terminalis in the present study. Stress research in animal models suggests the fornix/stria terminalis plays an important role in the expression and regulation of the hormonal (e.g., cortisol) response to stress (Herman et al., 2005). However, given the limited human neuroimaging research that has compared white matter pathways and stress reactivity, more research is needed to establish the role of white matter microstructure in the expression of acute and chronic stress.

The influence of sex on stress reactivity

Cortisol reactivity also varied by sex. Specifically, men demonstrated greater cortisol reactivity than women. This finding is consistent with prior research that has demonstrated sex differences in cortisol reactivity (Balodis et al., 2010; Het et al., 2012; Kirschbaum et al., 1999; Schoofs et al., 2013; Shalev et al., 2009). Further, we observed greater cingulum GFA in men than women. Prior research has also demonstrated greater whole brain white matter anisotropy in men than women (Inano et al., 2011; Manzouri and Savic, 2018; Menzler et al., 2011; Rametti et al., 2011; van Hemmen et al., 2017). However, no prior study has attempted to link sex differences in white matter microstructure to psychosocial stress reactivity. In the present study an interaction between sex and cingulum GFA was observed when predicting individual reactivity to stress. This finding suggests that the effect of sex on cortisol reactivity depends on the microstructure of the cingulum. While men have higher cingulum FA than women on average (Inano et al., 2011; Menzler et al., 2011), prior research suggests that this difference is due to sex hormones rather than sex chromosomes as women born XY with androgen insensitivity have FA similar to women born XX (van Hemmen et al., 2017). In addition to cortisol, molecular precursors to sex hormones are released in response to stress (Lennartsson et al., 2012), and prior work has demonstrated variations in stress reactivity across the menstrual cycle which vary with fluctuations in hormones (Goldstein et al., 2010). Taken together with prior work, the present research suggests that the emotional response to stress may, in part, be a product of individual variability in cingulum connectivity, which itself is shaped, over the course of development, by environmental and hormonal factors. Brain regions connected by the cingulum have been implicated in stress-related disorders including depression, anxiety, and panic disorders (Blair et al., 2012; Caetano et al., 2006; Etkin and Wager, 2007; Han et al., 2008) and the higher prevalence of these stress-related disorders in women is consistent with a neurohormonal mechanism (Balodis et al., 2010; Eaton et al., 2012; Het et al., 2012; Kirschbaum et al., 1999; Schoofs et al., 2013; Shalev et al., 2009). The present findings suggest that the cingulum plays an important role in the moderation of sex-related emotional reactions to psychosocial stressors.

Conclusions

The present study found sex differences in bilateral cingulum white matter and stress reactivity. Further, we observed an interaction between sex and stress reactivity in the right cingulum. Finally, the present study found a relationship between trait anxiety and the white matter of the left fornix/stria terminalis. Taken together, these results suggest that individual differences in white matter structure may impact trait anxiety and cortisol reactivity. These observations, which are based on healthy variability in white matter, trait anxiety, and cortisol reactivity, may inform future studies exploring the neural basis of stress-related psychopathology.

Strengths and Limitations

In the present study, trait anxiety, stress reactivity, and white matter GFA were assessed in young adults. Strengths of this study include the large sample size, robust stress response across participants, and investigation of individual differences in a community sample. The use of a large community sample has the advantage of better reflecting relationships between trait anxiety, cortisol, sex, and white matter in the broader community. However, it may also limit the generalizability of the present findings to clinical populations given only a small number of clinically diagnosed (n =5) individuals participated in this study and their data were excluded from the present analyses. Further, methodological differences may contribute to the discrepancies observed in the relationships between trait anxiety, stress reactivity, and white matter reported in the present study compared to prior work. For example, many prior studies of anxiety, stress reactivity, and white matter have utilized ROI or voxelwise tensor estimation analysis approaches. In contrast, the present study utilized a seed-based deterministic tractography approach. Additional work is needed to better understand the full impact that different analysis approaches may have on estimates of white matter tract associations with stress reactivity and anxiety.

Supplementary Material

1

Highlights.

  • The relationship between stress reactivity, white matter, and sex was assessed

  • Stress-elicited cortisol reactivity was greater in men than women

  • Generalized fractional anisotropy of the cingulum bundle was greater in men than women

  • Trait anxiety varied with the generalized fractional anisotropy of the fornix/stria terminalis

  • An interaction was observed between sex, stress reactivity, and cingulum generalized fractional anisotropy

Acknowledgements

This research was supported by National Institutes of Health [grant number MH098348 to SM & DCK and MDW received support from a T32 fellowship MH100019].

Footnotes

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Disclosure Statement

In the interest of full disclosure DAG is Founder and Chief Scientific and Strategy Advisor at Salimetrics LLC and SalivaBio LLC and these relationships are managed by the policies of the committees on conflict of interest at the Johns Hopkins University School of Medicine and the University of California at Irvine. All authors have approved the final manuscript.

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