Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress.

Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.

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.

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.

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.

Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury.

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep-learning neural network method, 3D-MEGNET, and applied it to resting-state magnetoencephalography (rs-MEG) source-magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat-deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All-frequency model, which combined delta-theta (1-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D-MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver-operator-characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta-theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta-theta and gamma-band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta-band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source-imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all-frequency model offered more discriminative power than each frequency-band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.

Marked Increases in Resting-State MEG Gamma-Band Activity in Combat-Related Mild Traumatic Brain Injury.

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30-80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.

MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury.

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained cognitive impairment in military service members and Veterans. However, the mechanism of persistent cognitive deficits including working memory (WM) dysfunction is not fully understood in mTBI. Few studies of WM deficits in mTBI have taken advantage of the temporal and frequency resolution afforded by electromagnetic measurements. Using magnetoencephalography (MEG) and an N-back WM task, we investigated functional abnormalities in combat-related mTBI. Study participants included 25 symptomatic active-duty service members or Veterans with combat-related mTBI and 20 healthy controls with similar combat experiences. MEG source-magnitude images were obtained for alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. Compared with healthy combat controls, mTBI participants showed increased MEG signals across frequency bands in frontal pole (FP), ventromedial prefrontal cortex, orbitofrontal cortex (OFC), and anterior dorsolateral prefrontal cortex (dlPFC), but decreased MEG signals in anterior cingulate cortex. Hyperactivations in FP, OFC, and anterior dlPFC were associated with slower reaction times. MEG activations in lateral FP also negatively correlated with performance on tests of letter sequencing, verbal fluency, and digit symbol coding. The profound hyperactivations from FP suggest that FP is particularly vulnerable to combat-related mTBI.

Brain Amygdala Volume Increases in Veterans and Active-Duty Military Personnel With Combat-Related Posttraumatic Stress Disorder and Mild Traumatic Brain Injury.

OBJECTIVE: To identify amygdalar volumetric differences associated with posttraumatic stress disorder (PTSD) in individuals with comorbid mild traumatic brain injury (mTBI) compared with those with mTBI-only and to examine the effects of intracranial volume (ICV) on amygdala volumetric measures. SETTING: Marine Corps Base and VA Healthcare System. PARTICIPANTS: A cohort of veterans and active-duty military personnel with combat-related mTBI (N = 89). DESIGN: Twenty-nine participants were identified with comorbid PTSD and mTBI. The remaining 60 formed the mTBI-only control group. Structural images of brains were obtained with a 1.5-T MRI scanner using a T1-weighted 3D-IR-FSPGR pulse sequence. Automatic segmentation was performed in Freesurfer. MAIN MEASURES: Amygdala volumes with/without normalizations to ICV. RESULTS: The comorbid mTBI/PTSD group had significantly larger amygdala volumes, when normalized to ICV, compared with the mTBI-only group. The right and left amygdala volumes after normalization to ICV were 0.122% ± 0.012% and 0.118% ± 0.011%, respectively, in the comorbid group compared with 0.115% ± 0.012% and 0.112% ± 0.009%, respectively, in the mTBI-only group (corrected P < .05). CONCLUSIONS: The ICV normalization analysis performed here may resolve previous literature discrepancies. This is an intriguing structural finding, given the role of the amygdala in the challenging neuroemotive symptoms witnessed in casualties of combat-related mTBI and PTSD.

Direct and indirect relationships among posttraumatic stress disorder, depression, hostility, anger, and verbal and physical aggression in returning veterans.

Hostility, anger, and aggression are conceptually related but unique constructs found to occur more often among veterans with posttraumatic stress disorder (PTSD) than among civilians or veterans without PTSD. However, the pathways between PTSD, depression, hostility, anger, and aggression have not been comprehensively characterized. Therefore, drawing on a sample of returning Operation Enduring Freedom/Operation Iraqi Freedom combat veterans ( N = 175; 95% male; mean age 30 years), this study sought to examine the direct and indirect relationships among PTSD, depression, hostility, anger, and four types of aggression: verbal, and physical toward self, others, and objects. Functional modeling of direct effects was done using multiple least-squares regression and bootstrapped mediation analyses were carried out to test indirect effects. Results indicate that PTSD is not the overall direct contributor to different forms of aggression, supporting the mediating role of depression and trait anger. Depression symptoms explain part of the relationships between PTSD and verbal aggression, physical aggression toward objects, and physical aggression toward self and trait anger explains part of the relationships between PTSD and verbal aggression, physical aggression toward objects, and physical aggression toward others. Our findings support the importance of assessing for anger, depression, and different types of aggression among veterans presenting for PTSD treatment to develop individualized treatment plans that may benefit from early incorporation of interventions.

COMT val158met polymorphism links to altered fear conditioning and extinction are modulated by PTSD and childhood trauma.

BACKGROUND: Risk for posttraumatic stress disorder (PTSD) is thought to be mediated by gene × environment (G × E) interactions that affect core cognitive processes such as fear learning. The catechol-O-methyltransferase (COMT) val158met polymorphism has been associated with risk for PTSD and impaired fear inhibition. We used a large, relatively homogenous population to (1) replicate previous findings of poor fear inhibition in COMT Met/Met carriers with PTSD; (2) determine if COMT association with fear inhibition is moderated by childhood trauma (CT), an environmental risk factor for PTSD; and (3) determine if COMT is associated with altered fear processes after recent exposure to combat trauma. METHODS: Male Marines and Navy Corpsmen of European-American ancestry were assessed prior to (n = 714) and 4-6 months after deployment to Afghanistan (n = 452). Acquisition and extinction of fear-potentiated startle, childhood and combat trauma history, and PTSD diagnosis were assessed at both time points. RESULTS: Before deployment, Met/Met genotype was associated with fear inhibition deficits in participants with current PTSD; however, this association was dependent on CT exposure. After deployment, combat trauma was associated with a modest reduction in fear extinction in Met/Met compared with Val/Val carriers. There were no associations of COMT genotype with fear extinction within healthy and non-traumatized individuals. CONCLUSIONS: These findings support the hypothesis that G × E interactions underlie associations of COMT val158met with fear inhibition deficits. These studies confirm that Met/Met carriers with PTSD have poor fear inhibition, and support further research in understanding how this polymorphism might impact response to extinction-based therapies.