Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Resilience after combat: A prospective, longitudinal study of Marines and Navy Corpsmen.

Resilience is common, yet our understanding of key biopsychosocial and environmental correlates is limited. Additionally, perceived resilience is often conflated with absence of psychiatric symptoms. Here we leverage prospective, longitudinal data from 1835 Marines and Navy Corpsmen to examine predictors of perceived resilience 3 months after a combat deployment, while controlling for pre-deployment and concurrent psychiatric symptoms. Marines and Corpsmen did not differ significantly on psychosocial or clinical factors, and 50.4% reported high perceived resilience after deployment. Across groups, the strongest predictors of post-deployment perceived resilience were pre-deployment perceived resilience, positive emotions, and social support. Concurrent depression was the only clinical symptom negatively associated with perceived resilience. Our findings suggest that perceived resilience is a multi-dimensional construct that involves both psychosocial and personality factors, including but not limited to low psychopathology. Notably, establishing strong social support networks and encouraging positive emotions may help promote resilience following deployment.

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.

Inflammation in Posttraumatic Stress Disorder: Dysregulation or Recalibration?

Despite ample experimental data indicating a role of inflammatory mediators in the behavioral and neurobiological manifestations elicited by exposure to physical and psychologic stressors, causative associations between systemic low-grade inflammation and central nervous system inflammatory processes in posttraumatic stress disorder (PTSD) patients remain largely conceptual. As in other stress-related disorders, pro-inflammatory activity may play an equivocal role in PTSD pathophysiology, one that renders indiscriminate employment of anti-inflammatory agents of questionable relevance. In fact, as several pieces of preclinical and clinical research convergingly suggest, timely and targeted potentiation rather than inhibition of inflammatory responses may actually be beneficial in patients who are characterized by suppressed microglia function in the face of systemic low-grade inflammation. The deleterious impact of chronic stress-associated inflammation on the systemic level may, thus, need to be held in context with the - often not readily apparent - adaptive payoffs of low-grade inflammation at the tissue level.

High executive functioning is associated with reduced posttraumatic stress after trauma exposure among male U.S. military personnel.

Introduction: Evidence suggests that executive function (EF) may play a key role in development of PTSD, possibly influenced by factors such as trauma type and timing. Since EF can be improved through intervention, it may be an important target for promoting resilience to trauma exposure. However, more research is needed to understand the relation between trauma exposure, EF, and PTSD. The goal of this study was to improve understanding of EF as a potential antecedent or protective factor for the development of PTSD among military personnel. Method: In a cohort of U.S. Marines and Navy personnel (N = 1,373), the current study tested the association between exposure to traumatic events (pre-deployment and during deployment) and PTSD severity, and whether EF moderated these associations. Three types of pre-deployment trauma exposure were examined: cumulative exposure, which included total number of events participants endorsed as having happened to them, witnessed, or learned about; direct exposure, which included total number of events participants endorsed as having happened to them; and interpersonal exposure, which included total number of interpersonally traumatic events participants' endorsed. EF was measured using the Penn Computerized Neurocognitive Battery. Results: EF was associated with less PTSD symptom severity at pre-deployment, even when adjusting for trauma exposure, alcohol use, traumatic brain injury, and number of years in the military. EF also moderated the relation between cumulative trauma exposure and interpersonal trauma exposure and PTSD, with higher EF linked to a 20 and 33% reduction in expected point increase in PTSD symptoms with cumulative and interpersonal trauma exposure, respectively. Finally, higher pre-deployment EF was associated with reduced PTSD symptom severity at post-deployment, independent of deployment-related trauma exposure and adjusting for pre-deployment PTSD. Conclusion: Our results suggest that EF plays a significant, if small role in the development of PTSD symptoms after trauma exposure among military personnel. These findings provide important considerations for future research and intervention and prevention, specifically, incorporating a focus on improving EF in PTSD treatment.

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders.

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies.

Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.

Efficacy and Safety of Mifepristone in the Treatment of Male US Veterans With Posttraumatic Stress Disorder: A Phase 2a Randomized Clinical Trial.

Importance: To date, no psychopharmacologic treatment has been found to be uniformly effective in veterans with posttraumatic stress disorder (PTSD); novel targets and approaches are needed to treat this disabling disorder. Objective: To examine whether treatment with the glucocorticoid receptor antagonist mifepristone yields a signal for clinical efficacy in male veterans with PTSD. Design, Setting, and Participants: This phase 2a, double-blind, parallel-group randomized clinical trial was conducted from November 19, 2012 (accrual started), through November 16, 2016 (final follow-up), within the US Department of Veterans Affairs. Participants were male veterans with chronic PTSD and a screening Clinician-Administered PTSD Scale score of 50 or higher. A total of 181 veterans consented to participation. Statistical analysis was conducted between August 2014 and May 2017. Interventions: Participants were randomized in a 1:1 ratio to mifepristone (600 mg) or matched placebo taken orally for 7 days. Main Outcomes and Measures: The clinical outcome was whether a veteran achieved a clinical response status (a reduction of ≥30% of total Clinician-Administered PTSD Scale score from baseline) at 4- and 12-week follow-up. On the basis of a binary statistical selection rule, a difference in the proportion of treatment vs control group responders of 15% would be a clinically relevant difference. Self-report measures of PTSD and associated symptoms were also obtained. Neuroendocrine outcomes and plasma levels of mifepristone were measured. Safety was assessed throughout the study. The primary analysis was based on a multiple imputation technique to address missing outcome data; thus, some participant numbers may not appear as whole numbers. Results: A total of 81 veterans were enrolled and randomized. Excluding 1 participant randomized in error, 80 were included in the modified intention-to-treat analysis (41 randomized to mifepristone and 39 to placebo). The mean (SD) age was 43.1 (13.7) years. A total of 15.6 (38.1%) in the mifepristone group and 12.1 (31.1%) in the placebo group were clinical responders at 4 weeks in the analysis using the multiple imputation technique. The group difference in the proportion of clinical responders (7.0%) was less than the predefined margin of 15% indicating signal for clinical efficacy. In an exploratory analysis, the difference in response to mifepristone vs placebo in the subgroup with no lifetime history of traumatic brain injury (TBI) (7.0 [50.0%] vs 3.0 [27.3%]; difference, 22.7%) exceeded the efficacy margin at 4 weeks and was sustained at 12 weeks. In contrast, in veterans with PTSD and lifetime TBI, the response rate to mifepristone was lower than placebo at 12 weeks (7.4 [27.4%] vs 13.5 [48.3%]; difference, -20.9%). Conclusions and Relevance: This study did not detect a signal for efficacy for mifepristone at 600 mg/d for 1 week in male veterans with chronic PTSD. Thus, this study does not support a phase 3 trial in this population. Future studies of mifepristone for the treatment of PTSD may be of interest in those without a history of TBI or in samples with a low base rate of lifetime head trauma. Trial Registration: ClinicalTrials.gov Identifier: NCT01946685.

Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning.

Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

Development and application of novel performance validity metrics for computerized neurocognitive batteries.

OBJECTIVES: Data from neurocognitive assessments may not be accurate in the context of factors impacting validity, such as disengagement, unmotivated responding, or intentional underperformance. Performance validity tests (PVTs) were developed to address these phenomena and assess underperformance on neurocognitive tests. However, PVTs can be burdensome, rely on cutoff scores that reduce information, do not examine potential variations in task engagement across a battery, and are typically not well-suited to acquisition of large cognitive datasets. Here we describe the development of novel performance validity measures that could address some of these limitations by leveraging psychometric concepts using data embedded within the Penn Computerized Neurocognitive Battery (PennCNB). METHODS: We first developed these validity measures using simulations of invalid response patterns with parameters drawn from real data. Next, we examined their application in two large, independent samples: 1) children and adolescents from the Philadelphia Neurodevelopmental Cohort (n = 9498); and 2) adult servicemembers from the Marine Resiliency Study-II (n = 1444). RESULTS: Our performance validity metrics detected patterns of invalid responding in simulated data, even at subtle levels. Furthermore, a combination of these metrics significantly predicted previously established validity rules for these tests in both developmental and adult datasets. Moreover, most clinical diagnostic groups did not show reduced validity estimates. CONCLUSIONS: These results provide proof-of-concept evidence for multivariate, data-driven performance validity metrics. These metrics offer a novel method for determining the performance validity for individual neurocognitive tests that is scalable, applicable across different tests, less burdensome, and dimensional. However, more research is needed into their application.

Exposure to unpredictability and mental health: Validation of the brief version of the Questionnaire of Unpredictability in Childhood (QUIC-5) in English and Spanish.

Unpredictability is increasingly recognized as a primary dimension of early life adversity affecting lifespan mental health trajectories; screening for these experiences is therefore vital. The Questionnaire of Unpredictability in Childhood (QUIC) is a 38-item tool that measures unpredictability in childhood in social, emotional and physical domains. The available evidence indicates that exposure to unpredictable experiences measured with the QUIC predicts internalizing symptoms including depression and anxiety. The purpose of the present study was to validate English and Spanish brief versions (QUIC-5) suitable for administration in time-limited settings (e.g., clinical care settings, large-scale epidemiological studies). Five representative items were identified from the QUIC and their psychometric properties examined. The predictive validity of the QUIC-5 was then compared to the QUIC by examining mental health in four cohorts: (1) English-speaking adult women assessed at 6-months postpartum (N = 116), (2) English-speaking male veterans (N = 95), (3) English-speaking male and female adolescents (N = 155), and (4) Spanish-speaking male and female adults (N = 285). The QUIC-5 demonstrated substantial variance in distributions in each of the cohorts and is correlated on average 0.84 (r's = 0.81-0.87) with the full 38-item version. Furthermore, the QUIC-5 predicted internalizing symptoms (anxiety and depression) in all cohorts with similar effect sizes (r's = 0.16-0.39; all p's < 0.05) to the full versions (r's = 0.19-0.42; all p's < 0.05). In sum, the QUIC-5 exhibits good psychometric properties and is a valid alternative to the full QUIC. These findings support the future use of the QUIC-5 in clinical and research settings as a concise way to measure unpredictability, identify risk of psychopathology, and intervene accordingly.

Pre-deployment threat learning predicts increased risk for post-deployment insomnia: Evidence from the Marine Resiliency Study.

Insomnia is a common and impairing consequence of military deployment, but little is known about pre-deployment risk factors for post-deployment insomnia. Abnormal threat learning tendencies are commonly observed in individuals with insomnia and maladaptive responses to stress have been implicated in the development of insomnia, suggesting that threat learning could be an important risk factor for post-deployment insomnia. Here, we examined pre-deployment threat learning as a predictor of post-deployment insomnia and the potential mechanisms underlying this effect. Male servicemembers (N = 814) completed measures of insomnia, psychiatric symptoms, and a threat learning task before and after military deployment. Threat learning indices that differentiated participants with versus withoutinsomnia at post-deployment were tested as pre-deployment predictors of post-deployment insomnia. Post-deployment insomnia was linked to elevations on several threat learning indices at post-deployment, but only higher threat conditioning, as indexed by higher threat expectancy ratings to the danger cue, emerged as a pre-deployment predictor of post-deployment insomnia. This effect was independent of combat exposure levels and partially mediated by greater post-deployment nightmares. The tendency to acquire stronger expectations of aversive events following encounters with danger cues may increase risk for post-deployment insomnia, in part due to the development of more severe nightmares.

Prospective longitudinal assessment of sensorimotor gating as a risk/resiliency factor for posttraumatic stress disorder.

Little is understood about cognitive mechanisms that confer risk and resiliency for posttraumatic stress disorder (PTSD). Prepulse Inhibition (PPI) is a measure of pre-attentional response inhibition that is a stable cognitive trait disrupted in many neuropsychiatric disorders characterized by poor behavioral or cognitive inhibition, including PTSD. Differentiating between PTSD-related phenotypes that are pre-existing factors vs. those that emerge specifically after trauma is critical to understanding PTSD etiology and can only be addressed by prospective studies. This study tested the hypothesis that sensorimotor gating performance is associated with risk/resiliency for combat-related PTSD. As part of a prospective, longitudinal study, 1226 active duty Marines and Navy Corpsman completed a PPI test as well as a clinical interview to assess PTSD symptoms both before,  and 3 and 6 months after a combat deployment. Participants that developed PTSD 6 months following deployment (N=46)  showed lower PPI across pre and post-deployment time points compared to participants who did not develop PTSD (N=1182) . Examination of the distribution of PTSD across PPI performance revealed a lower than expected number of cases in the highest performing quartile compared to the rest of the distribution (p < 0.04). When controlling for other factors that predict PTSD in this population, those in the top 25% of PPI performance showed a >50% reduction in chance to develop PTSD (OR = 0.32). Baseline startle reactivity and startle habituation were not significantly different between PTSD risk and control groups. These findings suggest that robust sensorimotor gating may represent a resiliency factor for development of PTSD following trauma.

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.

Contribution of early-life unpredictability to neuropsychiatric symptom patterns in adulthood.

BACKGROUND: Recent studies in both human and experimental animals have identified fragmented and unpredictable parental and environmental signals as a novel source of early-life adversity. Early-life unpredictability may be a fundamental developmental factor that impacts brain development, including reward and emotional memory circuits, affecting the risk for psychopathology later in life. Here, we tested the hypothesis that self-reported early-life unpredictability is associated with psychiatric symptoms in adult clinical populations. METHODS: Using the newly validated Questionnaire of Unpredictability in Childhood, we assessed early-life unpredictability in 156 trauma-exposed adults, of which 65% sought treatment for mood, anxiety, and/or posttraumatic stress disorder (PTSD) symptoms. All participants completed symptom measures of PTSD, depression and anhedonia, anxiety, alcohol use, and chronic pain. Relative contributions of early-life unpredictability versus childhood trauma and associations with longitudinal outcomes over a 6-month period were determined. RESULTS: Early-life unpredictability, independent of childhood trauma, was significantly associated with higher depression, anxiety symptoms, and anhedonia, and was related to higher overall symptom ratings across time. Early-life unpredictability was also associated with suicidal ideation, but not alcohol use or pain symptoms. CONCLUSIONS: Early-life unpredictability is an independent and consistent predictor of specific adult psychiatric symptoms, providing impetus for studying mechanisms of its effects on the developing brain that promote risk for psychopathology.

Effects of intranasal (S)-ketamine on Veterans with co-morbid treatment-resistant depression and PTSD: A retrospective case series.

Background: (S)-ketamine is a glutamatergic drug with potent and rapid acting effects for the treatment of depression. Little is known about the effectiveness of intranasal (S)-ketamine for treating patients with comorbid depression and post-traumatic stress disorder (PTSD). Methods: We performed a retrospective case series analysis of clinical outcomes in 35 Veterans with co-morbid depression and PTSD who were treated with intranasal (S)-ketamine treatments at the VA San Diego Neuromodulation Clinic between Jan 2020 and March 2021. Veterans were not randomized or blinded to treatment. The primary outcome measured was a change in patient health questionnaire-9 (PHQ-9) and PTSD Checklist for DSM-5 (PCL-5) scores across the first 8 treatments (induction period) using a repeated measures analysis of variance (ANOVA). In a smaller sub-group (n = 19) of Veterans who received at least 8 additional treatments, we analyzed whether intranasal (S)-ketamine continued to show treatment effects. Finally, we performed a sub-group and correlation analyses to understand how changes in PHQ-9 and PCL-5 scores were related across treatments. Findings: During the induction phase of treatment there was an absolute reduction of 5.1 (SEM 0.7) on the patient health questionnaire-9 (PHQ-9) rating scale for depression, from 19.8 (SEM 0.7) at treatment 1 to 14.7 (SEM 0.8) at treatment 8 (week 4) (F(7238) = 8.3, p = 1e-6, partial η2 = 0.2). Five Veterans (14%) showed a clinically meaningful response (50% reduction in PHQ-9 score) at treatment 8. There was an absolute reduction of 15.5 +/- 2.4 on the patient checklist 5 (PCL-5) rating scale for PTSD, from 54.8 (SEM 2) at treatment 1 down to 39.3 (SEM 2.5) at treatment 8 (F(7238) = 15.5, p = 2e-7, partial η2 = 0.31). Sixteen Veterans (46%) showed a clinically meaningful response (reduction in PCL-5 of > 30%) in PTSD. Change in PHQ-9 correlated with change in PCL-5 at treatment 8 (r = 0.47, p = 0.005), but a decrease in PTSD symptoms were observable in some individuals with minimal anti-depressant response. Interpretations: While this is an open-label retrospective analysis, our results indicate that both depression and PTSD symptoms in Veterans with dual-diagnoses may improve with repeated intranasal (S)-ketamine treatment. The effects of (S)-ketamine on PTSD symptoms were temporally and individually distinct from those on depression, suggesting potentially different modes of action on the two disorders. This work may warrant formal randomized controlled studies on the effects of intranasal (S)-ketamine for individuals with co-morbid MDD and PTSD. Funding: VA Center of Excellence in Stress and Mental Health, VA ORD (Career Development Award to DSR), Burroughs-Wellcome Fund Award (DSR), NIMH (EL).

Non-invasive cervical vagus nerve stimulation effects on reaction time and valence image anticipation response.

BACKGROUND: Norepinephrine (NE) driven noninvasive vagus nerve stimulation (nVNS), which improves attention and reduces reaction time, augments learning. Equally important, endogenous NE mediated arousal is highly dependent on the valence (positive or negative) of the exogenous stimulus. But to date, no study has measured valence specific effects of nVNS on both functional magnetic resonance imaging (fMRI) anticipation task response and reaction time in healthy individuals. Therefore, the aim of this pilot study was to assess whether nVNS vs sham modulates valence cortical anticipation task response and reaction time in a normative sample. METHODS: Participants received right sided transcutaneous cervical nVNS (N = 12) or sham (N = 12) stimulation during a 3T fMRI scan. Subjects first performed a continuous performance task (CPT) and then a cued anticipation task to images of positively and negatively valenced events during fMRI. Reaction times to cues and Blood oxygen level dependent (BOLD) response were examined over phase to identify effects of nVNS/sham over time. RESULTS: nVNS reduced reaction time for all valenced image anticipation trials. With the fMRI anticipation task, we observed a valence-specific effect; nVNS increased responsivity to images with negative valence and decreased responsivity to images with positive valence, whereas sham showed an inverse valence response. CONCLUSIONS: nVNS was linked to reduced reaction time during the anticipation task. In tandem, nVNS consistently enhanced responsivity to negatively valenced images and diminished responsivity to positively valenced images, suggesting specific nVNS driven endogenous neurotransmitter signaling may contribute.

Detection of Chronic Blast-Related Mild Traumatic Brain Injury with Diffusion Tensor Imaging and Support Vector Machines.

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions.