Examining the applicability of virtual battle space for stress management training in military personnel-A validation study.

Military personnel are often exposed to high levels of both physical and psychological challenges in their work environment and therefore it is important to be trained on how to handle stressful situations. The primary aim of this study was to examine whether military-specific virtual battle space (VBS) scenarios could elicit a physiological and subjective stress response in healthy military personnel, as compared to that of a virtual reality height exposure (VR-HE) stress task that has shown to reliably increase stress levels. Twenty participants engaged in two VBS scenarios and the VR-HE during separate sessions, while measurements of heart rate (HR), heart rate variability (HRV), respiration rate, and subjective stress levels were collected. Contrary to our initial expectations, analysis revealed that neither of the VBS scenarios induced a significant stress response, as indicated by stable HR, HRV, and low subjective stress levels. However, the VR-HE task did elicit a significant physiological stress response, evidenced by increased HR and HRV changes, aligning with previous research findings. Moreover, no discernible alterations were detected in cognitive performance subsequent to these stressors. These results suggest that the current VBS scenarios, despite their potential, may not be effective for stress-related training activities within military settings. The absence of a significant stress response in the VBS conditions points to the need for more immersive and engaging scenarios. By integrating interactive and demanding elements, as well as physical feedback systems and real-time communication, VBS training might better mimic real-world stressors and improve stress resilience in military personnel. The findings of this study have broader implications for stress research and training, suggesting the need for scenario design improvements in virtual training environments to effectively induce stress and improve stress management across various high-stress professions.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. CONCLUSION: The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

Amygdala fMRI-A Critical Appraisal of the Extant Literature.

Even before the advent of fMRI, the amygdala occupied a central space in the affective neurosciences. Yet this amygdala-centred view on emotion processing gained even wider acceptance after the inception of fMRI in the early 1990s, a landmark that triggered a goldrush of fMRI studies targeting the amygdala in vivo. Initially, this amygdala fMRI research was mostly confined to task-activation studies measuring the magnitude of the amygdala's response to emotional stimuli. Later, interest began to shift more towards the study of the amygdala's resting-state functional connectivity and task-based psychophysiological interactions. Later still, the test-retest reliability of amygdala fMRI came under closer scrutiny, while at the same time, amygdala-based real-time fMRI neurofeedback gained widespread popularity. Each of these major subdomains of amygdala fMRI research has left its marks on the field of affective neuroscience at large. The purpose of this review is to provide a critical assessment of this literature. By integrating the insights garnered by these research branches, we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of affective neuroscience? Our findings show that serious questions can be raised with regard to both the reliability and validity of amygdala fMRI. These conclusions force us to cast doubt on the continued viability of amygdala fMRI as a core pilar of the affective neurosciences.

Epigenome-wide association studies identify novel DNA methylation sites associated with PTSD: A meta-analysis of 23 military and civilian cohorts.

Background: The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions. Methods: As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using either Illumina HumanMethylation450 or MethylationEPIC (850K) BeadChips. A common QC pipeline was applied. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress. Results: We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e-09 < p < 5.30e-08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB. Many of these loci exhibit blood-brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Methylation at most CpGs correlated with their annotated gene expression levels. Conclusions: This study identifies 11 PTSD-associated CpGs, also leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.

Heightened SAM- and HPA-axis activity during acute stress impairs decision-making: A systematic review on underlying neuropharmacological mechanisms.

Individuals might be exposed to intense acute stress while having to make decisions with far-reaching consequences. Acute stress impairs processes required for decision-making by activating different biological stress cascades that in turn affect the brain. By knowing which stress system, brain areas, and receptors are responsible for compromised decision-making processes, we can effectively find potential pharmaceutics that can prevent the deteriorating effects of acute stress. We used a systematic review procedure and found 44 articles providing information on this topic. Decision-making processes could be subdivided into 4 domains (cognitive, motivational, affective, and predictability) and could be referenced to specific brain areas, while mostly being impaired by molecules associated with the sympathetic-adrenal-medullar and hypothalamic-pituitary-adrenal axes. Potential drugs to alleviate these effects included α1 and ß adrenoceptor antagonists, α2 adrenoceptor agonists, and corticotropin releasing factor receptor1/2 antagonists, while consistent stress-like effects were found with yohimbine, an α2 adrenoceptor antagonist. We suggest possible avenues for future research.

Long-term trajectories of depressive symptoms in deployed military personnel: A 10-year prospective study.

BACKGROUND: Military missions, especially those involving combat exposure, are associated with an increased risk of depression. Understanding the long-term course of depressive symptoms post-deployment is important to improve decision-making regarding deployment and mental health policies in the military. This study investigates trajectories of depressive symptoms in the Dutch army, exploring the influence of factors such as demographics, early-life trauma, posttraumatic stress disorder (PTSD) symptoms, and deployment stressors. METHODS: A cohort of 1032 military men and women deployed to Afghanistan (2005-2008) was studied from pre- to 10 years post-deployment. Depressive and PTSD symptoms were assessed using the Symptom CheckList-90 and the Self-Rating Inventory for PTSD. Demographics, early trauma, and deployment experiences were collected at baseline and after deployment, respectively. Latent Class Growth Analysis was used to explore heterogeneity in trajectories of depressive symptoms over time. RESULTS: Four trajectories were found: resilient (65%), intermediate-stable (20%), symptomatic-chronic (9%), and late-onset-increasing (6%). The resilient group experienced fewer deployment stressors, while the symptomatic-chronic group reported more early life traumas. Trajectories with elevated depressive symptoms consistently demonstrated higher PTSD symptoms. LIMITATIONS: Potential nonresponse bias and missing information due to the longitudinal design and extensive follow-up times. CONCLUSIONS: This study identified multiple trajectories of depressive symptoms in military personnel up to 10 years post-deployment, associated with early trauma, deployment stressors, adverse life events and PTSD symptoms. The prevalence of the resilient trajectory suggests a substantial level of resilience among deployed military personnel. These findings provide valuable insights and a foundation for further research.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

Background: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Pre-trauma memory contextualization as predictor for PTSD-like behavior in male rats.

While many people experience potentially threatening events during their life, only a minority develops posttraumatic stress disorder (PTSD). The identification of individuals at risk among those exposed to trauma is crucial for PTSD prevention in the future. Since re-experiencing trauma elements outside of the original trauma-context is a core feature of PTSD, we investigate if the ability to bind memories to their original encoding context (i.e. memory contextualization) predicts PTSD vulnerability. We hypothesize that pre-trauma neutral memory contextualization (under stress) negatively relates to PTSD-like behavior, in a prospective design using the cut-off behavioral criteria rat model for PTSD. 72 male Sprague Dawley rats were divided in two experimental groups to assess the predictive value of 1) memory contextualization without acute stress (NS-group) and 2) memory contextualization during the recovery phase of the acute stress-response (S-group) for susceptibility to PTSD-like behavior. A powerful extension to regression analysis -path analysis-was used to test this specific hypothesis, together with secondary research questions. Following traumatic predator scent stress, 19.4% of the rats displayed PTSD-like behavior. Results showed a negative relation between pre-trauma memory contextualization and PTSD-like behavior, but only in the NS-group. Pre-trauma memory contextualization was positively related to fear association in the trauma environment, again only in the NS group. If the predictive value of pre-trauma contextualization of neutral information under non-stressful conditions for PTSD susceptibility is replicated in prospective studies in humans, this factor would supplement already known vulnerability factors for PTSD and improve the identification of individuals at risk among the trauma exposed, especially those at high trauma risk such as soldiers deployed on a mission.

Impaired learning, memory, and extinction in posttraumatic stress disorder: translational meta-analysis of clinical and preclinical studies.

Current evidence-based treatments for post-traumatic stress disorder (PTSD) are efficacious in only part of PTSD patients. Therefore, novel neurobiologically informed approaches are urgently needed. Clinical and translational neuroscience point to altered learning and memory processes as key in (models of) PTSD psychopathology. We extended this notion by clarifying at a meta-level (i) the role of information valence, i.e. neutral versus emotional/fearful, and (ii) comparability, as far as applicable, between clinical and preclinical phenotypes. We hypothesized that cross-species, neutral versus emotional/fearful information processing is, respectively, impaired and enhanced in PTSD. This preregistered meta-analysis involved a literature search on PTSD+Learning/Memory+Behavior, performed in PubMed. First, the effect of information valence was estimated with a random-effects meta-regression. The sources of variation were explored with a random forest-based analysis. The analyses included 92 clinical (N = 6732 humans) and 182 preclinical (N = 6834 animals) studies. A general impairment of learning, memory and extinction processes was observed in PTSD patients, regardless of information valence. Impaired neutral learning/memory and fear extinction were also present in animal models of PTSD. Yet, PTSD models enhanced fear/trauma memory in preclinical studies and PTSD impaired emotional memory in patients. Clinical data on fear/trauma memory was limited. Mnemonic phase and valence explained most variation in rodents but not humans. Impaired neutral learning/memory and fear extinction show stable cross-species PTSD phenotypes. These could be targeted for novel PTSD treatments, using information gained from neurobiological animal studies. We argue that apparent cross-species discrepancies in emotional/fearful memory deserve further in-depth study; until then, animal models targeting this phenotype should be applied with utmost care.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Compassion apps for better mental health: qualitative review.

BACKGROUND: There is increasing empirical evidence for the positive mental health effects of compassion-based interventions. Although numerous smartphone apps offering compassion-based interventions ('compassion apps') are now available for the general public, the quality of these apps has not yet been reviewed. A qualitative review of existing compassion apps serves as a crucial first step toward testing the efficacy of these apps, by identifying good-quality compassion apps that might be worth the investment of a scientific trial. AIMS: The current study focuses on reviewing the quality of existing compassion apps. METHOD: Existing compassion apps were identified through searches in the Google Play Store and App Store. The 24 included apps were reviewed on their quality by using the Mobile App Rating Scale, and on their consistency with current evidence by comparing them to existing and studied compassion-based interventions. RESULTS: Of the 24 included apps, eight were identified that met the criteria of being consistent with existing and studied compassion-based interventions, and acceptable to good overall quality. The other 16 apps failed to meet one or both of these criteria. CONCLUSIONS: Good-quality compassion apps are available, but many of the available apps fail to meet certain quality criteria. In particular, many apps failed to offer sufficient relevant and correct information, or failed to offer this information in an entertaining and interesting way. It is recommended that future compassion apps are based on a clear definition of compassion, offer evidence- and theory-based exercises and implement tools for increasing engagement.

Pattern classification based on the amygdala does not predict an individual's response to emotional stimuli.

Functional magnetic resonance imaging (fMRI) studies have often recorded robust univariate group effects in the amygdala of subjects exposed to emotional stimuli. Yet it is unclear to what extent this effect also holds true when multi-voxel pattern analysis (MVPA) is applied at the level of the individual participant. Here we sought to answer this question. To this end, we combined fMRI data from two prior studies (N = 112). For each participant, a linear support vector machine was trained to decode the valence of emotional pictures (negative, neutral, positive) based on brain activity patterns in either the amygdala (primary region-of-interest analysis) or the whole-brain (secondary exploratory analysis). The accuracy score of the amygdala-based pattern classifications was statistically significant for only a handful of participants (4.5%) with a mean and standard deviation of 37% ± 5% across all subjects (range: 28-58%; chance-level: 33%). In contrast, the accuracy score of the whole-brain pattern classifications was statistically significant in roughly half of the participants (50.9%), and had an across-subjects mean and standard deviation of 49% ± 6% (range: 33-62%). The current results suggest that the information conveyed by the emotional pictures was encoded by spatially distributed parts of the brain, rather than by the amygdala alone, and may be of particular relevance to studies that seek to target the amygdala in the treatment of emotion regulation problems, for example via real-time fMRI neurofeedback training.

Mental health issues and illness and substance use disorder (non-)disclosure to a supervisor: a cross-sectional study on beliefs, attitudes and needs of military personnel.

OBJECTIVES: Research suggests that military personnel frequently delay disclosing mental health issues and illness (MHI), including substance use disorder, to supervisors. This delay causes missed opportunities for support and workplace accommodations which may help to avoid adverse occupational outcomes. The current study aims to examine disclosure-related beliefs, attitudes and needs, to create a better understanding of personnel's disclosure decision making. DESIGN: A cross-sectional questionnaire study among military personnel with and without MHI. Beliefs, attitudes and needs regarding the (non-)disclosure decision to a supervisor were examined, including factors associated with (non-)disclosure intentions and decisions. Descriptive and regression (logistic and ordinal) analyses were performed. SETTING: The study took place within the Dutch military. PARTICIPANTS: Military personnel with MHI (n=324) and without MHI (n=554) were participated in this study. OUTCOME MEASURE: (Non-)disclosure intentions and decisions. RESULTS: Common beliefs and attitudes pro non-disclosure were the preference to solve one's own problems (68.3%), the preference for privacy (58.9%) and a variety of stigma-related concerns. Common beliefs and attitudes pro disclosure were that personnel wanted to be their true authentic selves (93.3%) and the desire to act responsibly towards work colleagues (84.5%). The most reported need for future disclosure (96.8%) was having a supervisor who shows an understanding for MHI. The following factors were associated both with non-disclosure intentions and decisions: higher preference for privacy (OR (95% CI))=(1.99 (1.50 to 2.65)intention, 2.05 (1.12 to 3.76)decision) and self-management (OR (95% CI))=(1.64 (1.20 to 2.23)intention, 1.79 (1.00 to 3.20)decision), higher stigma-related concerns (OR (95% CI))=(1.76 (1.12 to 2.77)intention, 2.21 (1.02 to 4.79)decision) and lower quality of supervisor-employee relationship (OR (95% CI))=(0.25 (0.15 to 0.42)intention, 0.47 (0.25 to 0.87)decision). CONCLUSION: To facilitate (early-)disclosure to a supervisor, creating opportunities for workplace support, interventions should focus on decreasing stigma and discrimination and align with personnels' preference for self-management. Furthermore, training is needed for supervisors on how to recognise, and effectively communicate with, personnel with MHI. Focus should also be on improving supervisor-employee relationships.

Workplace Mental Health Disclosure, Sustainable Employability and Well-Being at Work: A Cross-Sectional Study Among Military Personnel with Mental Illness.

Purpose Disclosure of mental illness to a supervisor can have positive (e.g. supervisor support) and negative consequences (e.g. stigma). However, research on the association between disclosure and sustainable employability and well-being at work is scarce. The aim of this study was to investigate the association between the disclosure decision (yes/no), experiences with the decision (positive/negative) and sustainable employment and well-being at work among military personnel with mental illness (N = 323). Methods A cross-sectional questionnaire study was conducted. Descriptive and regression (linear and ordinal) analyses were performed. Comparisons were made between those with positive and negative disclosure experiences. Results Disclosure decision (yes/no) was not significantly associated with any of the measures of sustainable employability and well-being at work. However, positive disclosure experiences were significantly associated with higher scores on almost all measures of sustainable employability and well-being at work. Those with negative disclosure experiences reported significantly more shame (Mpos = 2.42, Mneg = 2.78, p < .05) and discrimination (Mpos = 1.70, Mneg = 2.84, p < .001). Those with a positive disclosure experience, reported significantly more supervisor support (Mpos = 3.20, Mneg = 1.94, p < .001). Conclusion We did not find evidence that the disclosure decision itself is related to measures of sustainable employment and well-being at work. In contrast, how participants had experienced their (non-)disclosure decision was significantly related to almost all measures. This emphasizes the importance of the work environments reactions to disclosure and mental illness in the workplace. Future research and interventions should focus on increasing the likelihood of positive disclosure experiences through creating a more inclusive work environment, with more supervisor support and less stigma.

Long-term risk for mental health symptoms in Dutch ISAF veterans: the role of perceived social support.

BACKGROUND: Military personnel deployed to combat and peacekeeping missions are exposed to high rates of traumatic events. Accumulating evidence suggests an important association between deployment and the development of other mental health symptoms beyond post-traumatic stress disorder. METHODS: This study examined the prevalence of agoraphobia, anxiety, depression, and hostility symptoms in a cohort of Dutch ISAF veterans (N = 978) from pre-deployment up to 10 years after homecoming. The interaction of potential moderating factors with the change in mental health symptoms relative to pre-deployment was investigated at each time point. RESULTS: The probable prevalence of agoraphobia, anxiety, depression, and hostility symptoms significantly increased over time to respectively 6.5, 2.7, 3.5, and 6.2% at 10 years after deployment. Except for hostility symptoms, the probable prevalence at 10 years after deployment was the highest compared to all previous follow-up assessments. Importantly, less perceived social support after returning from deployment was found as a risk factor for all different mental health symptoms. Unit support was not associated with the development of mental health problems. CONCLUSIONS: This study suggests a probable broad and long-term impact of deployment on the mental health of military service members. Due to the lack of a non-deployed control group, causal effects of deployment could not be demonstrated. Continued effort should nevertheless be made in the diagnosis and treatment of a wide range of mental health symptoms, even a decade after deployment. The findings also underscore the importance of social support after homecoming and its potential for the prevention of long-term mental health problems.

Altered lateralization of the cingulum in deployment-related traumatic brain injury: An ENIGMA military-relevant brain injury study.

Traumatic brain injury (TBI) in military populations can cause disruptions in brain structure and function, along with cognitive and psychological dysfunction. Diffusion magnetic resonance imaging (dMRI) can detect alterations in white matter (WM) microstructure, but few studies have examined brain asymmetry. Examining asymmetry in large samples may increase sensitivity to detect heterogeneous areas of WM alteration in mild TBI. Through the Enhancing Neuroimaging Genetics Through Meta-Analysis Military-Relevant Brain Injury working group, we conducted a mega-analysis of neuroimaging and clinical data from 16 cohorts of Active Duty Service Members and Veterans (n = 2598). dMRI data were processed together along with harmonized demographic, injury, psychiatric, and cognitive measures. Fractional anisotropy in the cingulum showed greater asymmetry in individuals with deployment-related TBI, driven by greater left lateralization in TBI. Results remained significant after accounting for potentially confounding variables including posttraumatic stress disorder, depression, and handedness, and were driven primarily by individuals whose worst TBI occurred before age 40. Alterations in the cingulum were also associated with slower processing speed and poorer set shifting. The results indicate an enhancement of the natural left laterality of the cingulum, possibly due to vulnerability of the nondominant hemisphere or compensatory mechanisms in the dominant hemisphere. The cingulum is one of the last WM tracts to mature, reaching peak FA around 42 years old. This effect was primarily detected in individuals whose worst injury occurred before age 40, suggesting that the protracted development of the cingulum may lead to increased vulnerability to insults, such as TBI.

Effects of Multisession Transcranial Direct Current Stimulation on Stress Regulation and Emotional Working Memory: A Randomized Controlled Trial in Healthy Military Personnel.

OBJECTIVES: Top-down stress regulation, important for military operational performance and mental health, involves emotional working memory and the dorsolateral prefrontal cortex (DLPFC). Multisession transcranial direct current stimulation (tDCS) applied over the DLPFC during working memory training has been shown to improve working memory performance. This study tested the hypothesis that combined tDCS with working memory training also improves top-down stress regulation. However, tDCS response differs between individuals. Resting-state electrophysiological brain activity was post hoc explored as a possible predictor of tDCS response. The predictive value of the ratio between slow-wave theta oscillations and fast-wave beta oscillations (theta/beta ratio) was examined, together with the previously identified tDCS response predictors age, education, and baseline working memory performance. MATERIALS AND METHODS: Healthy military service members (n = 79) underwent three sessions of real or sham tDCS over the right DLPFC (anode: F4, cathode: behind C2) at 2 mA for 20 minutes during emotional working memory training (N-back task). At baseline and within a week after the tDCS training sessions, stress regulation was assessed by fear-potentiated startle responses and subjective fear in a threat-of-shock paradigm with instructed emotional downregulation. Results were analyzed in generalized linear mixed-effects models. RESULTS: Threat-of-shock responses and emotional working memory performance showed no significant group-level effects of the real vs sham tDCS training intervention (p > 0.07). In contrast, when considering baseline theta/beta ratios or the other tDCS response predictors, exploratory results showed a trait-dependent beneficial effect of tDCS on emotional working memory training performance during the first session (p < 0.01). CONCLUSIONS: No evidence was found for effectivity of the tDCS training intervention to improve stress regulation in healthy military personnel. The emotional working memory training results emphasize the importance of studying the effects of tDCS in relation to individual differences. CLINICAL TRIAL REGISTRATION: This study was preregistered on September 16, 2019, at the Netherlands Trial Register (www.trialregister.nl) with ID: NL8028.

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking.

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.

Rare copy number variation in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24-71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10-8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further.