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. 2020 Aug 10;185(9-10):e1750–e1758. doi: 10.1093/milmed/usaa142

Testosterone and Resting State Connectivity of the Parahippocampal Gyrus in Men With History of Deployment-Related Mild Traumatic Brain Injury

Kristine M Knutson 1, Stephen J Gotts 2, Eric M Wassermann 1, Jeffrey D Lewis 1,3
PMCID: PMC7643124  PMID: 32776114

Abstract

Introduction

The purpose of this study was to explore the effect of low testosterone level on whole-brain resting state (RS) connectivity in male veterans with symptoms such as sleep disturbance, fatiguability, pain, anxiety, irritability, or aggressiveness persisting after mild traumatic brain injury (mTBI). Follow-up analyses were performed to determine if sleep scores affected the results.

Materials and Methods

In our cross-sectional design study, RS magnetic resonance imaging scans on 28 veterans were performed, and testosterone, sleep quality, mood, and post-traumatic stress symptoms were measured. For each participant, we computed the average correlation of each voxel’s time-series with the rest of the voxels in the brain, then used AFNI’s 3dttest++ on the group data to determine whether the effects of testosterone level on whole-brain connectivity were significant. We then performed follow-up region of interest-based RS analyses of testosterone, with and without sleep quality as a covariate. The study protocol was approved by the National Institute of Health’s Combined Neuroscience Institutional Review Board.

Results

Sixteen participants reported repeated blast exposure in theater, leading to symptoms; the rest reported exposure to a single blast or a nonblast TBI. Thirty-three percent had testosterone levels <300 ng/dL. Testosterone level was lower in participants who screened positive for post-traumatic stress disorder compared to those who screened negative, but it did not reach statistical significance. Whole-brain connectivity and testosterone level were positively correlated in the left parahippocampal gyrus (LPhG), especially in its connectivity with frontal areas, the lingual gyrus, cingulate, insula, caudate, and right parahippocampal gyrus. Further analysis revealed that the effect of testosterone on LPhG connectivity is only partially mediated by sleep quality. Sleep quality by itself had an effect on connectivity of the thalamus, cerebellum, precuneus, and posterior cingulate.

Conclusion

Lower testosterone levels were correlated with lower connectivity of the LPhG. Weaknesses of this study include a retrospective design based on self-report of mTBI and the lack of a control group without TBI. Without a control group or pre-injury testosterone measures, we were not able to attribute the rate of low testosterone in our participants to TBI per se. Also testosterone levels were checked only once. The high rate of low testosterone level that we found suggests there may be an association between low testosterone level and greater post-traumatic stress disorder symptoms following deployment, but the causality of the relationships between TBI and deployment stress, testosterone level, behavioral symptomatology, and LPhG connectivity remains to be determined. Our study on men with persistent symptoms postdeployment and post-mTBI may help us understand the role of low testosterone and sleep quality in persistent symptoms and may be important in developing therapeutic interventions. Our results highlight the role of the LPhG, as we found that whole-brain connectivity in that region was positively associated with testosterone level, with only a limited portion of that effect attributable to sleep quality.

INTRODUCTION

Following deployment, military service members often report symptoms such as sleep difficulties, fatigue, and low mood,1 each of which has been associated with testosterone.2–6 Symptoms have frequently been attributed to a mild traumatic brain injury (mTBI) or post-traumatic stress disorder (PTSD).1,7,8 The stress of the military environment, particularly during deployment, has mixed effects on serum hormone levels, including testosterone.9 For example, serum testosterone levels were significantly reduced after weeks-long military training, but recovered within 3 days.10–12 However, stress can also increase testosterone levels. For example, testosterone levels were significantly increased 1 and 6 months after return from deployment compared to pre-deployment levels.9 Another study of combat veterans13 reported no difference in plasma testosterone levels between those with combat-related PTSD and healthy controls, possibly reflecting endocrine levels in chronic, rather than acute, stress; however, men with depression were excluded from that study.

Our study was part of a broader study of postdeployment symptoms in U.S. service members and veterans experiencing at least one deployment-related concussion occurring during deployment in Iraq and Afghanistan in support of Operation Enduring Freedom (2001–2014), Operation Iraqi Freedom (2003–2010), and Operation New Dawn (2010–2011). In light of the known effects of TBI on testosterone, and testosterone’s beneficial effects on mood, functional improvement post-TBI, behavior (especially aggression and competition), and cognition (including spatial cognition),14–18 we performed an exploratory, data-driven analysis of the effects of testosterone level on whole-brain resting state (RS) connectivity. RS functional connectivity is a measure of the correlation between the fluctuations in blood oxygen level dependent signals from two brain areas while the subject is at rest, and it is considered to be a measure of the strength of the neural connection between them.19 Correlational analyses can be performed between connectivity and behavioral or clinical measures to explore for regions whose connectivity is related to those measures. Following an exploratory analysis, a detected region can be used as a seed to determine more specifically which regions drove the connectivity results.20,21 As sleep quality is related to depression and likely contributes to the onset of PTSD, we wanted to explore its effects on our RS connectivity results.8 Our RS connectivity analyses looked primarily at the effects of testosterone alone, and secondarily with sleep quality as an additional covariate, and with sleep quality alone. We also tested for correlations among testosterone, sleep quality, and depression to better understand the effects of testosterone on symptoms persisting after mTBI. We also split participants into a positive PTSD screen group and a negative one to compare mean testosterone levels, and we performed voxel-based morphometry (VBM) to find associations between gray matter volume (GMV) and testosterone level.

MATERIALS AND METHODS

Participants

We enrolled 28 male active duty U.S. service members and veterans with a history of deployment-related mTBI including blast exposure meeting the definition in the Department of Veterans Affairs/Department of Defense Clinical Practice Guidelines for the Management of Concussion, 2009, occurring at least 6 months prior. Recruitment occurred between 2012 and 2015. Initial contact with prospective TBI participants was made by members of the Defense and Veterans Brain Injury Center network of sites at military treatment facilities and the Department of Veterans Affairs medical centers, and their associated staff. The study protocol was approved by the National Institute of Health’s Combined Neuroscience Institutional Review Board. Written informed consent was obtained from all participants after the procedures had been fully explained. Inclusion criteria included self-report of any of the following somatic or behavioral symptoms, not present before, but developing within 3 months after mTBI, and may or may not have been present at enrollment: sleep disturbance, easy fatiguability, headache or other chronic widespread pain unrelated to physical injury; emotional lability, apathy or lack of spontaneity; lack of motivation; feelings of anxiety; personality change noticed by self or others; and irritability or aggressiveness. Exclusion criteria were inability to tolerate magnetic resonance imaging (MRI); daily use of psychomotor stimulants, narcotics, hypnotics, or anxiolytics; diagnosis of sleep apnea, thyroid disorder, or rheumatoid arthritis; history of brain injury associated with loss of consciousness lasting longer than 24 hours; daily use of more than five cups of coffee; or more than one headache per month before deployment.

Mean age was 34.4 ± 7.5 (range 26–49). Educational level ranged from 13 to 18 years (mean = 14.6). All participants were right-handed. Sixteen reported repeated blast exposure in theater leading to symptoms; the rest reported exposure to a single blast or a non-blast TBI. See Supplementary Table S1 for details on participants’ head and body injuries. Clinical MRI scans were interpreted by a board-certified neuroradiologist. One participant did not complete the RS scanning session because of claustrophobia and another’s RS dataset was unusable because of excessive motion/scanner artifact, resulting in a total of 26 participants for RS analysis; however, serum testosterone levels were not obtained for two other participants, leaving a total of 24 participants for RS analysis using testosterone measures (see Fig. 1). Anatomical images were available for all 28, so those with testosterone measures (n = 26) were included in the VBM analysis.

FIGURE 2.

FIGURE 2

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Boxplots Comparing Serum Testosterone Levels for the Group of Subjects Who Screened Negative for PTSD (n = 20) vs. Those Who Screened Positive (n = 6).

FIGURE 1.

FIGURE 1

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Enrollment Numbers at Each Step.

Procedure

Participants were evaluated over 2 days at the Clinical Research Center of the National Institutes of Health in Bethesda, Maryland, USA. On day 1, a clinical history, a neurological examination, and experimental neuropsychological testing were performed. MRI scans were performed in the afternoon. On day 2, serum testosterone levels were measured at 8 a.m. Samples were analyzed by the National Institutes of Health Clinical Research Center clinical pathology laboratory. Experimental neuropsychological testing continued on day 2.

MRI Acquisition

Each participant completed an MRI session on a Siemens 3T Biograph scanner provided by the Center for Neuroscience and Regenerative Medicine. We acquired a T1-weighted MPRAGE (TR = 2530, TE = 3.03, matrix size = 256 × 256, flip angle = 7, slices = 176, slice thickness = 1), along with a 7.5 minutes RS scan of 150 T2*-weighted echoplanar volumes (TR 3000 = ms, TE = 25 ms, flip angle = 90°, slice thickness = 3 mm, slices = 43, voxel size = 1.7188 × 1.7188 × 3 mm, FOV = 1540 × 1540 mm, matrix = 128 × 128), during which participants were asked to keep their eyes closed, but not to sleep. We did not verify wakefulness.

Neuropsychological Tests

As part of a larger neuropsychological test battery, participants completed the Pittsburgh Sleep Quality Index (PSQI), which indicates the likelihood of a sleep disorder22; The Center for Epidemiological Studies Depression scale (CES-D), a self-report measure of depressive symptoms23; and the PTSD Checklist (PCL), a brief screening checklist for PTSD.24

Statistical Analysis

MRI Analysis

Preprocessing of the RS MRI data included despiking, interpolation to correct for slice time acquisition differences, and spatial registration to the first volume to minimize effects of head motion using AFNI.25 The RS images were blurred using a FWHM of 6 mm and rescaled to percent signal change. Anatomical images were segmented into maps of gray matter (GM), white matter, and cerebral spinal fluid using FreeSurfer, Version 5.3.0.26 Next, we followed ANATICOR procedures to remove artifacts, including six motion parameters, average signal (within a radius of 15 mm) within eroded white matter and cerebral spinal fluid, along with respiration and cardiac signals (nine Retroicor regressors and five Respiration Volume per Time, regressors).27–29 Cardiac and respiration signals were not available for three participants; these participants were included in the analyses. The residual time-series data were then transformed into Talairach space and standardized to z scores using the Fisher transformation. Global GM was not regressed out to avoid potential distortion of the correlation values.30

Following preprocessing, we created whole-brain “connectedness” maps for each subject’s RS data. Whole-brain connectedness is the average correlation of each voxel’s time-series with the rest of the voxels in the brain. AFNI’s 3dttest++, which runs t-tests on groups of 3D datasets, was performed to determine the effect of the continuous covariate of each subject’s testosterone level while removing the effect of head motion on their whole-brain connectedness data at each voxel. This procedure included only voxels where at least 90% of participants had data. In follow-up analyses, we used the significant result from the first analysis as a seed region, computed the average RS time-series in that seed region and correlated it with that of all other voxels in the brain for each participant. This resulted in a voxelwise functional connectivity map from the seed region for each participant. Testosterone level was then correlated with the seed-based functional connectivity maps across subjects in each voxel. These voxelwise correlations with testosterone level were then thresholded, correcting for multiple comparisons using cluster size. The first follow-up analysis showed which brain regions contributed to the connectedness results for testosterone. We then added sleep quality with and without testosterone as a covariate in a second and third follow-up analysis. To control for different motion levels across participants, each participant’s measure of transient head motion across consecutive time points (AFNI’s @1dDiffMag), which is comparable to the average framewise displacement,31 was calculated and entered as a mean-centered covariate into each group-level analysis. Our analyses were two-tailed and used a voxelwise threshold of P < 0.005, corrected to an alpha of 0.05 using AFNI’s empirically modeled spatial auto-correlation function. This resulted in a cluster size threshold of 166 voxels to be considered significant in our RS analyses.

For VBM, T1 images were segmented, normalized, modulated, and smoothed using an 8 × 8 × 8 full width at half maximum Gaussian kernel using SPM12 and the CAT12 toolbox,32 running on MATLAB R2016a using the defaults unless otherwise specified. A positive multiple regression was performed on the segmented GMVs and level of testosterone (where significant results would mean higher levels of testosterone were associated with increased tissue volume). A negative test was also computed as a quality control check. An overall significance threshold of P = 0.001 with family-wise error correction for multiple comparisons was used. Age and total intracranial volume were included as covariates of no interest. In addition to the whole-brain VBM analysis, a VBM analysis was performed in the LPhG region of interest (ROI) that resulted from the RS analysis with testosterone to determine whether there were any structural changes within this ROI that correlated with testosterone levels.

Neuropsychological Tests Analysis

We used SPSS (Version 20) to calculate the means and standard deviations for PSQI, CES-D, and PCL scores. We also used SPSS to compute the Spearman rank order correlation coefficients between PSQI and CES-D scores with testosterone level at P < 0.05. We used Spearman’s Rho as the variables were not normally distributed. We split participants into two groups based on PCL scores, those with scores above the cut-off of 50 (positive PTSD screen) and those below (negative PTSD screen), then used an independent samples t-test to compare the mean testosterone level between groups.

RESULTS

Testosterone Level Results

The mean serum testosterone level for those participants with usable RS data (n = 24) was 376 ± 107 ng/dL. Thirty-three percent of those participants had testosterone levels below 300 ng/dL, a level the American Urological Society considers a reasonable cut-off for diagnosis of low testosterone.33 For comparison, the mean serum testosterone level for all 26 participants with testosterone measures was similar: 383 ± 107 ng/dL, with 30.77% below the cut-off. As expected for the age range of our participants, testosterone level was not significantly associated with age (Spearman’s one-tailed, P = 0.09).

Testosterone and Neuropsychological Test Results

The mean PSQI score was 11.3 ± 3.9, with 24 of 26 participants scoring higher than five, indicating the likelihood of a sleep disorder. The mean CES-D score was 15.9 ± 10.3, with 12 of 28 participants scoring above 16 and therefore considered at risk for depression. The mean PCL score for those participants who also had testosterone measures was 39.2 ± 15.4, with six out of 26 participants scoring higher than the cut-off of 50 for positive screening for PTSD. These six participants had lower testosterone levels than the group with a negative PTSD screen, but the difference did not quite reach statistical significance (312.0 vs. 404.6, t24 = 1.96, P = 0.06; see Fig. 2).

FIGURE 3.

FIGURE 3

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(a) Coronal View of Testosterone’s Effects on Whole-Brain RS Connectivity Overlaid on the AFNI TT_N27 Atlas. Warm Colors Indicate Significantly Increased Whole-Brain RS Connectivity with Increasing Testosterone Level in the LPhG (Peak at −25, −7, −22, Size = 196 Voxels), Indicating that Subjects With High Testosterone Levels Tended to Have More Whole Brain Connectivity to/from the LPhG. P < 0.005, Corrected to P < 0.05, Two-Tailed, Minimum Cluster Size = 166 Contiguous Voxels. (b) Scatterplot of Testosterone Level and LPhG Connectivity.

There was a significant negative correlation between testosterone and PSQI score (R = −0.36, P = 0.04), but not between testosterone and CES-D score (R = −0.18, P = 0.19). PSQI, CES-D, and PCL scores were all highly correlated (Rs > 0.58, Ps ≤ 0.001).

Imaging Results

As shown in Supplementary Table S1, some participants had microhemorrhages or small white matter lesions, but otherwise normal MRIs. As these regions were small and most affected white matter, we did not expect them to affect the results of RS analyses and did not remove any lesion areas from our analyses.

Whole Brain RS Results

Testosterone level had a significant positive association with whole-brain RS connectivity in the left parahippocampal gyrus (LPhG). No other area met the cluster size threshold (see Fig. 3a).

FIGURE 4.

FIGURE 4

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Regions Meeting the Cluster Size Threshold Where Whole-Brain Connectivity to/from the LPhG ROI was Significantly Correlated with Testosterone Level Across Subjects. The LPhG ROI Seed Used in This Analysis Resulted From the Whole-Brain Testosterone Analysis. P < 0.005, Corrected to P < 0.05, Two-Tailed, Minimum Cluster Size = 166 Contiguous Voxels.

ROI RS Results

In a follow-up seed-to-whole-brain RS analysis, we used the LPhG results from our first RS analysis as the seed ROI and testosterone level as a covariate. We found that testosterone level was significantly correlated with LPhG RS connectivity to many brain areas (see Supplementary Table S2; Fig. 4.

When we performed this ROI analysis again with testosterone level as a covariate, but removed the effects of PSQI score, some areas of connectivity were lost or attenuated, including the precuneus, cerebellum, caudate and left inferior and medial frontal gyri, but others remained, including the right anterior cingulate, right precuneus, left middle frontal gyrus, right lingual gyrus, bilateral superior parietal cortex, and the cerebellum (see Supplementary Table S3 and Supplementary Fig. S1).

When examining the effects of PSQI alone (without considering testosterone), significant negative correlations were observed in a bilateral cluster that included parts of the thalamus and cerebellum (size = 1590 voxels; peak 3, −7, −2) and the precuneus and cingulate gyrus (BA 31; size = 379 voxels, peak −1, −63, 28; see Supplementary Fig. S2). Disordered sleep, as indicated by the PSQI, was associated with weaker connectivity with the LPhG in these regions. Notably, the effects of PSQI alone did not overlap with the effects of testosterone that were lost when PSQI was added as a covariate. Taken together, these results suggest that a limited portion of the effect of testosterone on functional connectivity of the LPhG is attributable to sleep quality.

Testosterone and VBM Results

A significant positive association between testosterone level and GMV, which met the family-wise error correction for size, was found only in the posterior lobe of the right cerebellar hemisphere (39, −68, −26; 55 voxels). No significant negative correlations were found. The VBM analysis within the LPhG ROI did not produce any significant results.

DISCUSSION

Testosterone Levels

One-third of our participants had levels below the cut-off for low testosterone, which has been associated with PTSD.9 Our PTSD positive screen group had lower testosterone levels than the negative group, but the difference did not reach statistical significance (P = 0.06). We found that testosterone level was significantly and positively correlated with whole-brain RS functional connectivity of the LPhG, and we found a significant negative correlation between testosterone level and sleep problems. The effect of testosterone on the parahippocampal gyrus (PhG) and sleep quality is discussed below.

PHG and Testosterone

The PhG is considered a primary hub of the default mode network,34 and its connectivity and function are affected by testosterone. For example, the long-range functional connectivity of the PhG was found to be higher in men than women, possibly because of the effects of testosterone on this region.35 Also, supraphysiological testosterone doses in eugonadal elderly men were associated with decreased activity in the right entorhinal cortex/amygdala, and increased activity in left entorhinal cortex, RPhG, right posterior hippocampus, and bilateral prefrontal cortex.36 Both exogenous and endogenous testosterone affected bilateral PhG activation in men in response to affective stimuli.37

Studies of GMV in patients with medical conditions affecting testosterone level have revealed volume differences in the PhG compared to normal controls. For instance, an increase in GMV in familial male precocious puberty with its continuous unregulated testosterone secretion38 and a positive correlation between testosterone and GMV in bilateral parahippocampus in Klinefelter syndrome where testosterone is deficient39 were found. We found, however, that testosterone level did not affect LPhG GMV, but was associated with GMV only in the right cerebellum, which is consistent with the right cerebellum being larger in men than women.39 Our imaging results show that testosterone level has an effect on RS connectivity of the PhG, but not its volume.

Sleep Quality

We found a significant negative association between testosterone level and PSQI score, meaning that lower testosterone level was associated with disrupted sleep. Others have found similar relationships.5 Sleep disturbances may have contributed to our participants’ low testosterone levels, as well as their fatigue and mood complaints. Sleep complaints are common following deployment,40 as well as mTBI,41 and this was true for our participants. Even though we excluded those with sleep apnea, 24 of 26 participants scored greater than five on the PSQI and were therefore at risk for sleep problems.

When we removed the effect of PSQI score in our LPhG ROI-to-whole-brain connectivity analysis with testosterone level, we found fewer areas of connectivity than when only testosterone level was included. The results show that in our participants, sleep quality had an effect on LPhG functional connectivity which was different from that of testosterone level. Others have also found that the PhG is associated with sleep quality. For example, reduced GM volume in the LPhG was found in people with obstructive sleep disorder and GM volume increased after treatment.42 Also, significantly decreased fractional anisotropy in PhG was found bilaterally in patients with mTBI and sleep disturbance, compared to those with histories of mTBI but without sleep disturbance.43

LIMITATIONS

Limitations of this study include a retrospective design based on self-report of mTBI—many could not quantify their number of blast exposures—and the lack of a control group without TBI. Importantly, without a control group or pre-injury testosterone measures, we were not able to attribute the rate of low testosterone in our participants to TBI per se, although several studies have found low testosterone to be common after TBI, even in the chronic stage.14,15,44 Another limitation is that testosterone levels were checked only once during the study. Also, since sleep problems, depression and PTSD symptoms were highly correlated, we cannot separate their effects. There is a need to determine whether changes in LPhG connectivity associated with testosterone level cause changes in learning and sensitivity to reward45 or emotional memory,46,47 or increased fatigue,16 and to help untangle the complex relationships between testosterone, LPhG connectivity, and persistent symptoms after mTBI, but we were not able to do so because of correction for multiple comparisons considerations. The causality of the relationships between TBI and deployment stress, testosterone level, behavioral symptomatology, and LPhG connectivity remains to be determined. In addition to TBI, all of our participants were exposed to the stress of prolonged deployment in a conflict zone. Deployment stress affects the prevalence and severity of postconcussive symptoms and may have other effects which are difficult to distinguish from those of mTBI.48 To dissociate the effects of physical trauma and stress in this population would require study of previously deployed service members with equal stress exposure but no histories of TBI, and individuals with comparable histories of TBI, but no deployment stress, groups which are difficult to recruit. However, the aim of this study was to explore the physiological basis of a commonly recognized and socially important syndrome48 and develop hypotheses relevant to treatment, rather than to determine its ultimate causation.

CONCLUSION

In this exploratory study, we found that testosterone level wassignificantly and positively correlated with whole-brain RS functional connectivity of the LPhG in male service members/veterans with history of deployment-related mTBI and persistent complaints, and that only a limited portion of that effect was attributable to sleep quality. We also found an association between low testosterone level and sleep problems. These results might suggest that testosterone level be considered when making treatment recommendations for patients with persistent complaints after TBI. However, as there have been only a few studies of testosterone therapy after TBI,6,49,50 further research is needed to determine whether low testosterone and the associated lowered LPhG connectivity contribute to persistent symptoms following TBI. Our connectivity results are intriguing given the role of the PhG in the default mode network, and further investigation should be performed to determine whether PhG connectivity could be used to monitor treatment efficacy.

Supplementary Material

Figure_S1_usaa142
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Figure_S2_usaa142
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Table_S1_usaa142
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Table_S2_usaa142
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Table_S3_usaa142
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ACKNOWLEDGMENTS

We appreciate the technical support of the Center for Neuroscience and Regenerative Medicine, and we gratefully acknowledge the generous time and effort the service members made in supporting this study.

A poster summarizing this work was presented at the Organization of Human Brain Mapping Conference, Vancouver, Canada, June 28, 2017.

The work was performed at the Behavioral Neurology Unit, National Institute of Neurological Disorders and Stroke Clinical Neuroscience Program, National Institutes of Health, Bethesda, Maryland, USA. Funding came from the Clinical Neuroscience Program of the National Institute of Neurological Disorders and Stroke, National Institutes of Health (1ZIANS002977). Dr Gotts is supported by the National Institute of Mental Health, Division of Intramural Research (1ZIAMH002588).

The view(s) expressed herein are those of the authors and do not reflect the official policy or position of the Department of the Air Force, Department of Defense, or the US Government. The authors declare they have no financial relationships with commercial interests.

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