Ketamine-enhanced prolonged exposure therapy in veterans with PTSD: A randomized controlled trial protocol.

BACKGROUND: The 2023 VA/DoD Clinical Practice Guideline for the Management of PTSD recommends individual, manualized trauma-focused such as Prolonged Exposure (PE) over pharmacologic interventions for the primary treatment of PTSD. Unfortunately, clinical trials of trauma-based therapies in the military and veteran population showed that 30% to 50% of patients did not demonstrate clinically meaningful symptom change. Ketamine, an FDA-approved anesthetic with potent non-competitive glutamatergic N-methyl-d-aspartate antagonistic properties, has demonstrated to enhance the recall of extinction learning and decrease fear renewal without interference of extinction training in preclinical studies. METHODS: We plan to conduct a single site RCT comparing three ketamine treatment vs. active placebo (midazolam) adjunct to PE therapy among Veterans with PTSD. Pharmacological phase will start simultaneously with PE session 1. Infusions will be administered 24 h. prior to PE session for the first 3 weeks. After PE is completed (session 10), patients will be assessed during a 3-month follow-up period at various time points. We estimate that out of 100 veterans, 80 will reach time point for primary outcome measure and will be considered for primary analysis. Secondary outcomes include severity of depression and anxiety scores, safety and tolerability of ketamine-enhanced PE therapy, cognitive performance during treatment and early improvement during PE related to the rate of dropouts during PE therapy. DISCUSSION: Results of the proposed RCT could provide scientific foundation to distinguish the essential components of this approach, enhance the methodology, elucidate the mechanisms involved, and identify sub-PTSD populations that most likely benefit from this intervention.

The relationship between blast-related mild traumatic brain injury and executive function is moderated by white matter integrity.

Blast-related mild traumatic brain injury (BR mTBI) is a critical research area in recent combat veterans due to increased prevalence of survived blasts. Post-BR mTBI outcomes are highly heterogeneous and defining neurological differences may help in discrimination and prediction of cognitive outcomes. This study investigates whether white matter integrity, measured with diffusion tensor imaging (DTI), could influence how remote BR mTBI history is associated with executive control. The sample included 151 Veterans from the Minneapolis Veterans Affairs Medical Center who were administered a clinical/TBI assessment, neuropsychological battery, and DTI scan as part of a larger battery. From previous research, six white matter tracts were identified as having a putative relationship with blast severity: the cingulum, hippocampal cingulum, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus and uncinate. Fractional anisotropy (FA) of the a priori selected white matter tracts and report of BR mTBI were used as predictors of Trail-Making Test B (TMT-B) performance in a multiple linear regression model. Statistical analysis revealed that FA of the hippocampal cingulum moderated the association between report of at least one BR mTBI and poorer TMT-B performance (p < 0.008), such that lower FA value was associated with worse TMT-B outcomes in individuals with BR mTBI. No significant moderation existed for other selected tracts, and the effect was not observed with predictors aside from history of BR mTBI. Investigation at the individual-tract level may lead to a deeper understanding of neurological differences between blast-related and non-blast related injuries.

ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury.

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

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.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

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.

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.

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.

Evaluating resilience in response to COVID-19 pandemic stressors among veteran mental health outpatients.

There is a public health need to understand mental health vulnerabilities to COVID-19 pandemic-related stressors and promote resilience among high-risk populations with preexisting psychiatric conditions. Recent cross-sectional studies suggest increases in mental health distress (e.g., depression and anxiety) during the pandemic. The present study expands upon these emerging findings using longitudinal latent modeling and hierarchical linear regressions. Consistent with the developmental psychopathology literature on resilience, we distinguished between promotive or risk (i.e., main effect), and protective or vulnerability (i.e., moderation) effects on mental health during the pandemic. At a large medical center, 398 veterans receiving outpatient mental health care provided prepandemic (Time 1) and during pandemic (Time 2) assessments of mental and physical health-related distress. Additional Time 2 questionnaires assessed pandemic-related stressors and positive behavioral adaptations in the summer of 2020. As expected, total stressor scores predicted longitudinal worsening of self-reported mental (ß = -.205) and physical health (ß = -.217). Positive behavioral adaptations enacted during the pandemic moderated and protected against stressor effects on mental health (ß = .160). In addition, the presence of substance use disorders moderated and conferred vulnerability to stressor effects on physical health (ß = -.158). Thus, higher COVID-19 pandemic stressor exposure may have exacerbated mental and physical health distress among veterans with common forms of psychopathology. Nevertheless, behavioral activation, purposeful maintenance of social connections, and focused treatment for substance misuse may be important intervention targets for reducing the longitudinal impact of pandemic stressors and enhancing resilience among people with mental illness. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The role of posttraumatic stress symptoms on memory complaints and performance in active-duty service members.

OBJECTIVE: Memory complaints are the most common form of cognitive limitation reported by military service members, but prior research suggests that posttraumatic stress symptoms (PTSS) may account for the link between subjective cognitive complaints and objective cognitive performance. The mechanisms underlying this relationship are largely unknown, including whether the finding applies to memory complaints and performance, which clinical dimensions are involved, and how the association varies when memory complaints are non-credible. METHOD: Using a sample of 196 US military service members, the present study aims to address these gaps by modeling the relationship between objective memory performance and plausible/implausible subjective memory complaints, then evaluating how the association is influenced by PTSS and clinical traits commonly found within PTSS (e.g. depression, anxiety, and somatic concerns). RESULTS: Overall memory complaints were associated with immediate and delayed recall, but both associations were fully mediated by PTSS (95% CI -0.14, -0.01; 95% CI -0.14, -0.02, respectively). Implausible memory complaints, however, were inconsistently linked to memory performance, and no PTSS mediation was observed. Of the clinical traits, only depression moderated the impact of PTSS, specifically by influencing the link between PTSS and overall memory complaints (ß = -0.02, SE = 0.004, p < .001). CONCLUSIONS: These results corroborate the importance of assessment for PTSS and depression in service members who report subjective memory complaints and highlight how targeted intervention for these conditions may play a key role in the management of memory complaints.

Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins.

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach.

PURPOSE: Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. BASIC PROCEDURES: We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. MAIN FINDINGS: When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). PRINCIPAL CONCLUSIONS: These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.

Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury.

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q < 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age-dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans.

A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury.

Multi-modal biomarkers (e.g., imaging, blood-based, physiological) of unique traumatic brain injury (TBI) endophenotypes are necessary to guide the development of personalized and targeted therapies for TBI. Optimal biomarkers will be specific, sensitive, rapidly and easily accessed, minimally invasive, cost effective, and bidirectionally translatable for clinical and research use. For both uses, understanding how TBI biomarkers change over time is critical to reliably identify appropriate time windows for an intervention as the injury evolves. Biomarkers that enable researchers and clinicians to identify cellular injury and monitor clinical improvement, inflection, arrest, or deterioration in a patient's clinical trajectory are needed for precision healthcare. Prognostic biomarkers that reliably predict outcomes and recovery windows to assess neurodegenerative change and guide decisions for return to play or duty are also important. TBI biomarkers that fill these needs will transform clinical practice and could reduce the patient's risk for long-term symptoms and lasting deficits. This article summarizes biomarkers currently under investigation and outlines necessary steps to achieve short- and long-term goals, including how biomarkers can advance TBI treatment and improve care for patients with TBI.

Inefficient Attentional Control Explains Verbal-Memory Deficits Among Military Veterans With Posttraumatic Reexperiencing Symptoms.

Among individuals with posttraumatic stress disorder (PTSD), verbal learning and memory are areas of weakness compared with other cognitive domains (e.g., visuospatial memory). In this study, previously deployed military veterans completed clinical assessments of word memory and vocabulary (n = 243) and a laboratory task measuring encoding, free recall, repetition priming, and recognition of words (n = 147). Impaired verbal memory was selectively related to reexperiencing symptoms of PTSD but was not associated with other symptom groupings or blast-induced traumatic brain injury. Implicit priming of response times following word repetition was also unrelated to clinical symptoms. Instead, slowed response times during encoding explained associations between reexperiencing and memory performance. These findings are consistent with alterations in attentional control explaining PTSD-related verbal-memory deficits. Such findings have implications for understanding trauma-focused psychotherapy and recovery, which may depend on efficient attentional processing of words to alter posttraumatic reexperiencing symptoms.

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups.

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. METHOD: Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site. RESULTS: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. DISCUSSION: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.

The association of posttraumatic stress disorder, depression, and head injury with mid-life cognitive function in civilian women.

BACKGROUND: Despite evidence linking posttraumatic stress disorder (PTSD), depression, and head injury, separately, with worse cognitive performance, investigations of their combined effects on cognition are limited in civilian women. METHODS: The Cogstate Brief Battery assessment was administered in 10,681 women from the Nurses' Health Study II cohort, mean age 64.9 years (SD = 4.6). Psychological trauma, PTSD, depression, and head injury were assessed using online questionnaires. In this cross-sectional analysis, we used linear regression models to estimate mean differences in cognition by PTSD/depression status and stratified by history of head injury. RESULTS: History of head injury was prevalent (36%), and significantly more prevalent among women with PTSD and depression (57% of women with PTSD and depression, 21% of women with no psychological trauma or depression). Compared to having no psychological trauma or depression, having combined PTSD and depression was associated with worse performance on psychomotor speed/attention ( ß = -.15, p = .001) and learning/working memory ( ß = -.15, p < .001). The joint association of PTSD and depression on worse cognitive function was strongest among women with past head injury, particularly among those with multiple head injuries. CONCLUSIONS: Head injury, like PTSD and depression, was highly prevalent in this sample of civilian women. In combination, these factors were associated with poorer performance on cognitive tasks, a possible marker of future cognitive health. Head injury should be further explored in future studies of PTSD, depression and cognition in women.

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information.

BACKGROUND: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. RESULTS: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. CONCLUSIONS: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

Advancing Research on Mechanisms of Resilience (ARMOR) Longitudinal Cohort Study of New Military Recruits: Results from a Feasibility Pilot Study.

Psychological resilience as a longitudinal process is highly relevant for understanding the functioning outcomes of military populations. Here, we review the extant literature on resilience among military service members, focusing on National Guard Soldiers. Our specific project (Advancing Research on Mechanisms of Resilience, "ARMOR") aims to develop a comprehensive model of resilience using a multilevel perspective. We report results from our prospective pilot study (n = 103) conducted in preparation for our large-scale longitudinal cohort study of Basic Combat Training (BCT) and its impact on military recruits' wellbeing. Results support feasibility of the larger study, evidence for a new measure of BCT stressor exposure, and demonstrate preliminary associations with BCT-related stressors and longitudinal changes in adaptive functioning. Future directions for our larger study will utilize data from survey responses, structured clinical interviews, neurobehavioral tasks, and neurobiological measures (functional and structural MRI and electroencephalography [EEG]) to examine individual differences in self-regulation as a predictor of resilience-related processes. ARMOR is well positioned to elucidate mechanisms that could be targeted for promoting wellbeing, preventing psychopathology, and facilitating long-term recovery.

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume.

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.