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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.

Background: Early trauma predicts poor psychological and physical health. Glutamatergic synaptic processes offer one avenue for understanding this relationship, given glutamate’s abundance and involvement in reward and stress sensitivity, emotion, and learning. Trauma-induced glutamatergic excitotoxicity may alter neuroplasticity and approach/avoidance tendencies, increasing risk for psychiatric disorders. Studies examine upstream or downstream effects instead of glutamatergic synaptic processes in vivo, limiting understanding of how trauma affects the brain. Objective: In a pilot study using a previously published data set, we examine associations between early trauma and a proposed measure of synaptic strength in vivo in one of the largest human samples to undergo Carbon-13 (13C MRS) magnetic resonance spectroscopy. Participants were 18 healthy controls and 16 patients with PTSD (male and female). Method: Energy per cycle (EPC), which represents the ratio of neuronal oxidative energy production to glutamate neurotransmitter cycling, was generated as a putative measure of glutamatergic synaptic strength. Results: Results revealed that early trauma was positively correlated with EPC in individuals with PTSD, but not in healthy controls. Increased synaptic strength was associated with reduced behavioural inhibition, and EPC showed stronger associations between reward responsivity and early trauma for those with higher EPC. Conclusion: In the largest known human sample to undergo 13C MRS, we show that early trauma is positively correlated with EPC, a direct measure of synaptic strength. Our study findings have implications for pharmacological treatments thought to impact synaptic plasticity, such as ketamine and psilocybin.

Posttraumatic stress disorder (PTSD) is a devastating condition, for which there are few pharmacological agents, often with a delayed onset of action and poor efficacy. Trauma-focused psychotherapies are further limited by few trained providers and low patient engagement. This frequently results in disease chronicity as well as psychiatric and medical comorbidity, with considerable negative impact on quality of life. As such, off-label interventions are commonly used for PTSD, particularly in chronic refractory cases. Ketamine, an N -methyl-D-aspartate (NDMA) receptor antagonist, has recently been indicated for major depression, exhibiting rapid and robust antidepressant effects. It also shows transdiagnostic potential for an array of psychiatric disorders. Here, we synthesize clinical evidence on ketamine in PTSD, spanning case reports, chart reviews, open-label studies, and randomized trials. Overall, there is high heterogeneity in clinical presentation and pharmacological approach, yet encouraging signals of therapeutic safety, efficacy, and durability. Avenues for future research are discussed.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

A stressor-related disorder wherein traumatic experience precipitates protracted disruptions to mood and cognition, post-traumatic stress disorder (PTSD) is associated with wide-ranging abnormalities across the body. While various methods have investigated these deviations, only proton magnetic resonance spectroscopy ( 1 H MRS) enables noninvasive measurement of small-molecule metabolites in the living human. 1 H MRS has correspondingly been employed to test hypotheses about the composition and function of multiple brain regions putatively involved in PTSD. Here we systematically review methodological considerations and reported findings, both positive and negative, of the current 1 H-MRS literature in PTSD (N = 32 studies) to communicate the brain regional metabolite alterations heretofore observed, providing random-effects model meta-analyses for those most extensively studied. Our review suggests significant PTSD-associated decreases in N-acetyl aspartate in bilateral hippocampus and anterior cingulate cortex with less evident effect in other metabolites and regions. Model heterogeneities diverged widely by analysis (I 2

Background Trauma and chronic stress are believed to induce and exacerbate psychopathology by disrupting glutamate synaptic strength. However, in vivo in human methods to estimate synaptic strength are limited. In this study, we established a novel putative biomarker of glutamatergic synaptic strength, termed energy-per-cycle (EPC). Then, we used EPC to investigate the role of prefrontal neurotransmission in trauma-related psychopathology. Methods Healthy controls (n = 18) and patients with posttraumatic stress (PTSD; n = 16) completed 13 C-acetate magnetic resonance spectroscopy (MRS) scans to estimate prefrontal EPC, which is the ratio of neuronal energetic needs per glutamate neurotransmission cycle (V TCA /V Cycle ). Results Patients with PTSD were found to have 28% reduction in prefrontal EPC ( t = 3.0; df = 32, P = .005). There was no effect of sex on EPC, but age was negatively associated with prefrontal EPC across groups ( r = –0.46, n = 34, P = .006). Controlling for age did not affect the study results. Conclusion The feasibility and utility of estimating prefrontal EPC using 13 C-acetate MRS were established. Patients with PTSD were found to have reduced prefrontal glutamatergic synaptic strength. These findings suggest that reduced glutamatergic synaptic strength may contribute to the pathophysiology of PTSD and could be targeted by new treatments.

Abstract 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.

Background Our behavioral traits, and subsequent actions, could affect the risk of exposure to the coronavirus disease of 2019 (COVID-19). The current study aimed to determine whether unique brain networks are associated with the COVID-19 infection risk. Methods This research was conducted using the UK Biobank Resource. Functional magnetic resonance imaging scans in a cohort of general population (n = 3662) were used to compute the whole-brain functional connectomes. A network-informed machine learning approach was used to identify connectome and nodal fingerprints that are associated with positive COVID-19 status during the pandemic up to February fourth, 2021. Results The predictive models successfully identified 6 fingerprints that were associated with COVID-19 positive, compared to negative status (all p values < 0.005). Overall, lower integration across the brain modules and increased segregation, as reflected by internal within module connectivity, were associated with higher infection rates. More specifically, COVID-19 positive status was associated with 1) reduced connectivity between the central executive and ventral salience, as well as between the dorsal salience and default mode networks; 2) increased internal connectivity within the default mode, ventral salience, subcortical and sensorimotor networks; and 3) increased connectivity between the ventral salience, subcortical and sensorimotor networks. Conclusion Individuals are at increased risk of COVID-19 infections if their brain connectome is consistent with reduced connectivity in the top-down attention and executive networks, along with increased internal connectivity in the introspective and instinctive networks. These identified risk networks could be investigated as target for treatment of illnesses with impulse control deficits.

Epidemiologic studies recognize that trauma and posttraumatic stress are associated with heightened suicidal behavior severity, yet examination of these associations from a genetic perspective is limited. We performed a multivariate gene-by-environment genome-wide interaction study (GEWIS) of suicidality in 123,633 individuals using a covariance matrix based on 26 environments related to traumatic experiences, posttraumatic stress, social support, and socioeconomic status. We discovered five suicidality risk loci, including the male-associated rs2367967 (CWC22), which replicated in an independent cohort. All GEWIS-significant loci exhibited interaction effects where at least 5% of the sample had environmental profiles conferring opposite SNP effects from the majority. We identified PTSD as a primary driving environment for GxE at suicidality risk loci. The male suicidality GEWIS was enriched for three middle-temporal-gyrus inhibitory neuron transcriptomic profiles: SCUBE- and PVALB-expressing cells (β = 0.028, p = 3.74 × 10−4), OPRM1-expressing cells (β = 0.030, p = 0.001), and SPAG17-expressing cells (β = 0.029, p = 9.80 × 10−4). Combined with gene-based analyses (CNTN5 passociation = 2.38 × 10−9, pinteraction = 1.51 × 10−3; PSMD14 passociation = 2.04 × 10−7, pinteraction = 7.76 × 10−6; HEPACAM passociation = 2.43 × 10−6, pinteraction = 3.82 × 10−7) including information about brain chromatin interaction profiles (UBE2E3 in male neuron p = 1.07 × 10−5), our GEWIS points to extracellular matrix biology and synaptic plasticity as biological interactors with the effects of potentially modifiable lifetime traumatic experiences on genetic risk for suicidality. Characterization of molecular basis for the effects of traumatic experience and posttraumatic stress on risk of suicidal behaviors may help to identify novel targets for which more effective treatments can be developed for use in high-risk populations.

Here we present functional neuroimaging-based network data (focused on the default mode network) collected from a cohort of US Veterans with history of combat exposure, combined with clinical assessments for PTSD and other psychiatric comorbidities. The data has been processed and analyzed using several network construction methods (signed, thresholded, normalized to phase-randomized and rewired surrogates, functional and multimodal parcellation). An interpretation and discussion of the data can be found in the main NeuroImage article by Akiki et al. [51] Keywords: fMRI, PTSD, Functional connectivity, Graph theory, Veterans, Intrinsic connectivity networks, Default mode network

Background Major depressive disorder (MDD) treatment is characterized by low remission rate and often involves weeks to months of treatment. Identification of pretreatment biomarkers of response may play a critical role in novel drug development, in enhanced prognostic predictions, and perhaps in providing more personalized medicine. Using a network restricted strength predictive modeling (NRS-PM) approach, the goal of the current study was to identify pretreatment functional connectome fingerprints (CFPs) that (1) predict symptom improvement regardless of treatment modality and (2) predict treatment specific improvement. Methods Functional magnetic resonance imaging and behavioral data from unmedicated patients with MDD (n = 200) were investigated. Participants were randomized to daily treatment of sertraline or placebo for 8 weeks. NRS-PM with 1000 iterations of 10 cross-validation were implemented to identify brain connectivity signatures that predict percent improvement in depression severity at week-8. Results The study identified a pretreatment CFP that significantly predicts symptom improvement independent of treatment modality but failed to identify a treatment specific CFP. Regardless of treatment modality, improved antidepressant response was predicted by high pretreatment connectivity between modules in the default mode network and the rest of the brain, but low external connectivity in the executive network. Moreover, high pretreatment internal nodal connectivity in the bilateral caudate predicted better response. Conclusions The identified CFP may contribute to drug development and ultimately to enhanced prognostic predictions. However, the results do not assist with providing personalized medicine, as pretreatment functional connectivity failed to predict treatment specific response.

Background Considering the slow-acting properties of traditional antidepressants, an important challenge in the field is the identification of early treatment response biomarkers. Reduced cortical thickness has been reported in neuroimaging studies of depression. However, little is known whether antidepressants reverse this abnormality. In this brief report, we investigated early cortical thickness changes following treatment with sertraline compared to placebo. Methods Participants (n = 215) with major depressive disorder were randomized to a selective serotonin reuptake inhibitor, sertraline, or to placebo. Structural magnetic resonance imaging scans were acquired at baseline and one week following treatment. Response was defined as at least 50% improvement in Hamilton rating scale for depression score at week 8. In a vertex-wise approach, we examined the effects of treatment, response, and treatment × response. Results Following correction for multiple comparisons, we found a significant effect of treatment, with widespread increase in cortical thickness following sertraline compared to placebo. Clusters with increased thickness were found in the left medial prefrontal cortex, right medial and lateral prefrontal cortex, and within the right parieto-temporal lobes. There were no sertraline-induced cortical thinning, and no significant response effects or treatment × response interactions. Conclusion Our findings suggest that cortical thickness abnormalities may be responsive to antidepressant treatment. However, a relationship between these early cortical changes and later treatment response was not demonstrated. Future studies would be needed to investigate whether those early effects are maintained at eight weeks and are associated with enhanced response.

Summary: More than six decades have passed since the discovery of monoaminergic antidepressants. Yet, it remains a mystery why these drugs take weeks to months to achieve therapeutic effects, although their monoaminergic actions are present rapidly after treatment. In an attempt to solve this mystery, rather than studying the acute neurochemical effects of antidepressants, here we propose focusing on the early changes in the brain functional connectome using traditional statistics and machine learning approaches. Capitalizing on three independent datasets (n = 1,261) and recent developments in data and network science, we identified a specific connectome fingerprint that predates and predicts response to monoaminergic antidepressants. The discovered fingerprint appears to generalize to antidepressants with differing mechanism of action. We also established a consensus whole-brain hierarchical connectivity architecture and provided a set of model-based features engineering approaches suitable for identifying connectomic signatures of brain function in health and disease. : Drugs; Medical Imaging; Clinical Neuroscience Subject Areas: Drugs, Medical Imaging, Clinical Neuroscience

Posttraumatic stress disorder (PTSD) is a chronic debilitating psychiatric disorder characterized by symptoms of re-experience, avoidance, and hyperarousal that can arise immediately or many years after exposure to a traumatic event and injury. Although extensive research has been done over the past 30 years, the etiology of PTSD remains largely unknown. Several neurobiological systems have been implicated in the pathophysiology and vulnerability for developing PTSD; however, first-line pharmacotherapies are limited. Less than 30% achieve full remission, and even then, approved pharmacological treatments often take weeks for therapeutic effect. This article aims to review the pathophysiology of PTSD within multiple neurobiological systems and how these mechanisms are used as pharmacologic targets of treatment, as well as their potential for future targets of intervention.

Background Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph-based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty U.S. Army soldiers with PTSD compared to controls. Methods A total of 102 participants with (n = 50) or without PTSD (n = 52) completed functional magnetic resonance imaging at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. Results In contrast to resting state, where there were no group differences, we found a significantly higher GBCr during symptom provocation, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal-ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. Conclusion In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

Background In soldiers with posttraumatic stress disorder, symptom provocation was found to induce increased connectivity within the salience network, as measured by functional magnetic resonance imaging and global brain connectivity with global signal regression (GBCr). However, it is unknown whether these GBCr disturbances would normalize following effective posttraumatic stress disorder treatment. Methods Sixty-nine US Army soldiers with (n = 42) and without posttraumatic stress disorder (n = 27) completed functional magnetic resonance imaging at rest and during symptom provocation using subject-specific script imagery. Then, participants with posttraumatic stress disorder received six weeks (12 sessions) of group cognitive processing therapy or present-centered therapy. At week 8, all participants repeated the functional magnetic resonance imaging scans. The primary analysis used a region-of-interest approach to determine the effect of treatment on salience GBCr. A secondary analysis was conducted to explore the pattern of GBCr alterations posttreatment in posttraumatic stress disorder participants compared to controls. Results Over the treatment period, present-centered therapy significantly reduced salience GBCr ( p = .02). Compared to controls, salience GBCr was high pretreatment (present-centered therapy, p = .01; cognitive processing therapy, p = .03) and normalized post-present-centered therapy ( p = .53) but not postcognitive processing therapy ( p = .006). Whole-brain secondary analysis found high GBCr within the central executive network in posttraumatic stress disorder participants compared to controls. Post hoc exploratory analyses showed significant increases in executive GBCr following cognitive processing therapy treatment ( p = .01). Conclusion The results support previous models relating cognitive processing therapy to central executive network and enhanced cognitive control while unraveling a previously unknown neurobiological mechanism of present-centered therapy treatment, demonstrating treatment-specific reduction in salience connectivity during trauma recollection.

Posttraumatic stress disorder is a chronic and debilitating psychiatric disorder with a complex clinical presentation. The last two decades have seen a proliferation of literature on the neurobiological mechanisms subserving affective processing in posttraumatic stress disorder. The current review will summarize the neuroimaging results of the most common experimental designs used to elucidate the affective signature of posttraumatic stress disorder. From this summary, we will provide a heuristic to organize the various paradigms discussed and report neural patterns of activations using this heuristic as a framework. Next, we will compare these results to the traditional functional neurocircuitry model of posttraumatic stress disorder and discuss biological and analytic variables which may account for the heterogeneity within this literature. We hope that this approach may elucidate the role of experimental parameters in influencing neuroimaging findings.

Background Identifying the neural correlates of ketamine treatment may facilitate and expedite the development of novel, robust, and safe rapid-acting antidepressants. Prefrontal cortex (PFC) global brain connectivity with global signal regression (GBCr) was recently identified as a putative biomarker of major depressive disorder. Accumulating evidence have repeatedly shown reduced PFC GBCr in major depressive disorder, an abnormality that appears to normalize following ketamine treatment. Methods Fifty-six unmedicated participants with major depressive disorder were randomized to intravenous placebo (normal saline; n = 18), ketamine (0.5 mg/kg; n = 19), or lanicemine (100 mg; n = 19). PFC GBCr was computed using time series from functional magnetic resonance imaging scans that were completed at baseline, during infusion, and at 24-h posttreatment. Results Compared to placebo, ketamine significantly increased average PFC GBCr during infusion ( p = 0.01) and at 24-h posttreatment ( p = 0.02). Lanicemine had no significant effects on GBCr during infusion ( p = 0.45) and at 24-h posttreatment ( p = 0.23) compared to placebo. Average delta PFC GBCr (during minus baseline) showed a pattern of positively predicting depression improvement in participants receiving ketamine ( r = 0.44; p = 0.06; d = 1.0) or lanicemine ( r = 0.55; p = 0.01; d = 1.3) but not those receiving placebo ( r = −0.1; p = 0.69; d = 0.02). Follow-up vertex-wise analyses showed ketamine-induced GBCr increases in the dorsolateral, dorsomedial, and frontomedial PFC during infusion and in the dorsolateral and dorsomedial PFC at 24-h posttreatment ( corrected p

Introduction Using proton magnetic resonance spectroscopy imaging, the effects of early life stress on nonhuman primate striatal neuronal integrity were examined as reflected by N -acetyl aspartate (NAA) concentrations. NAA measures were interrogated through examining their relationship to previously documented early life stress markers—cerebrospinal fluid corticotropin-releasing factor concentrations, hippocampal volume, body mass, and behavioral timidity. Rodent models of depression exhibit increases in neurotrophic effects in the nucleus accumbens. We hypothesized that rearing under conditions of early life stress (variable foraging demand, VFD) would produce persistent elevations of NAA concentrations (in absolute or ratio form) in ventral striatum/caudate nucleus (VS/CN) with altered correlation to early life stress markers. Methods Eleven bonnet macaque males reared under VFD conditions and seven age-matched control subjects underwent proton magnetic resonance spectroscopy imaging during young adulthood. Voxels were placed over VS/CN to capture nucleus accumbens. Cisternal cerebrospinal fluid corticotropin-releasing factor concentrations, hippocampal volume, body mass, and response to a human intruder had been previously determined. Results VFD-reared monkeys exhibited significantly increased NAA/creatine concentrations in right VS/CN in comparison to normally reared controls, controlling for multiple comparisons. In comparison to controls, VFD cerebrospinal fluid corticotropin-releasing factor concentrations were directly associated with right VS/CN absolute NAA. Left hippocampal volume was inversely associated with left VS/CN NAA/creatine in VFD reared but not in controls. Disruption of a normative inverse correlation between left VS/CN NAA and body mass was noted in VFD. Only non-VFD subjects exhibited a direct relationship between timidity response to an intruder and right VS/CN NAA. Conclusion Early life stress produced persistent increases in VS/CN NAA, which demonstrated specific patterns of association (or lack thereof) to early life stress markers in comparison to non-VFD subjects. The data are broadly consistent with a stable nonhuman primate phenotype of anxiety and mood disorder vulnerability whereby in vivo indicators of neuronal integrity, although reduced in hippocampus, are increased in striatum. The findings may provide a catalyst for further studies in humans and other species regarding a reciprocal hippocampal/nucleus accumbens relationship in affective disorders.

The societal burden of psychiatric disorders that result after exposure to psychological trauma is enormous. The study of trauma-related disorders using neurobiological and public health approaches is often disjointed. It is critical to emphasize the translational potential of neurobiological work and its relevance to the public health burden of psychological trauma. Applying a public health model to traumatology that includes primary, secondary, and tertiary levels, we highlight ways in which advancing the field of neurobiology can pave the way for scalable interventions that can improve outcomes and help to address the public health problem.

Background Two decades of human neuroimaging research have associated volume reductions in the hippocampus with posttraumatic stress disorder. However, little is known about the distribution of volume loss across hippocampal subfields. Recent advances in neuroimaging methods have made it possible to accurately delineate 10 gray matter hippocampal subfields. Here, we apply a volumetric analysis of hippocampal subfields to data from a group of combat-exposed Veterans. Method Veterans (total, n = 68, posttraumatic stress disorder, n = 36; combat control, n = 32) completed high-resolution structural magnetic resonance imaging. Based on previously validated methods, hippocampal subfield volume measurements were conducted using FreeSurfer 6.0. The Clinician-Administered PTSD Scale assessed posttraumatic stress disorder symptom severity; Beck Depression Inventory assessed depressive symptom severity. Controlling for age and intracranial volume, partial correlation analysis examined the relationship between hippocampal subfields and symptom severity. Correction for multiple comparisons was performed using false discovery rate. Gender, intelligence, combat severity, comorbid anxiety, alcohol/substance use disorder, and medication status were investigated as potential confounds. Results In the whole sample, total hippocampal volume negatively correlated with Clinician-Administered PTSD Scale and Beck Depression Inventory scores. Of the 10 hippocampal subfields, Clinician-Administered PTSD Scale symptom severity negatively correlated with the hippocampus–amygdala transition area (HATA). Beck Depression Inventory scores negatively correlated with dentate gyrus, cornu ammonis 4 (CA4), HATA, CA2/3, molecular layer, and CA1. Follow-up analysis limited to the posttraumatic stress disorder group showed a negative correlation between Clinician-Administered PTSD Scale symptom severity and each of HATA, CA2/3, molecular layer, and CA4. Conclusion This study provides the first evidence relating posttraumatic stress disorder and depression symptoms to abnormalities in the HATA, an anterior hippocampal region highly connected to prefrontal-amygdala circuitry. Notably, dentate gyrus abnormalities were associated with depression severity but not posttraumatic stress disorder symptoms. Future confirmatory studies should determine the extent to which dentate gyrus volume can differentiate between posttraumatic stress disorder- and depression-related pathophysiology.

Background The hippocampus and amygdala have been repeatedly implicated in the psychopathology of posttraumatic stress disorder (PTSD). While numerous structural neuroimaging studies examined these two structures in PTSD, these analyses have largely been limited to volumetric measures. Recent advances in vertex-based neuroimaging methods have made it possible to identify specific locations of subtle morphometric changes within a structure of interest. Methods In this cross-sectional study, we used high-resolution magnetic resonance imaging to examine the relationship between PTSD symptomatology, as measured using the Clinician Administered PTSD Scale for the DSM-IV, and structural shape of the hippocampus and amygdala using vertex-wise shape analyses in a group of combat-exposed U.S. Veterans (N = 69). Results Following correction for multiple comparisons and controlling for age and cranial volume, we found that participants with more severe PTSD symptoms showed an indentation in the anterior half of the right hippocampus and an indentation in the dorsal region of the right amygdala (corresponding to the centromedial amygdala). Post hoc analysis using stepwise regression suggest that among PTSD symptom clusters, arousal symptoms explain most of the variance in the hippocampal abnormality, whereas reexperiencing symptoms explain most of the variance in the amygdala abnormality. Conclusion The results provide evidence of localized abnormalities in the anterior hippocampus and centromedial amygdala in combat-exposed U.S. Veterans suffering from PTSD symptoms. This novel finding provides a more fine-grained analysis of structural abnormalities in PTSD and may be informative for understanding the neurobiology of the disorder.

Background Chronic stress and related physiological responses are known to have deleterious effects on neural integrity. Combat exposure is a notoriously pathogenic stressor, and with over 2 million U.S. troops deployed to active combat zones since 2001, there is an urgent need to advance our understanding of its potential neural impact. Previous evidence suggests structural alterations in posttraumatic stress disorder (PTSD) and more recent studies have explored cortical thinning specifically. This preliminary study investigates the impact of combat exposure on cortical thickness, controlling for history of early life stress and age. Methods Twenty-one combat-exposed Veterans with PTSD and 20 non-PTSD combat-exposed controls (mean age 32.7) completed the Combat Exposure Scale, Childhood Trauma Questionnaire, and structural magnetic resonance imaging in a Siemens 3T TIM trio system. General linear model was used to examine the effect of combat exposure on cortical thickness, controlling for early life trauma exposure and age using cluster-wise correction ( p

Transforming growth factor-β1 (TGF-β1) is a multifunctional cytokine with anti-inflammatory, immunosuppressive, and neuroprotective properties. The hypothalamic-pituitary-adrenal axis and immune system exert bidirectional influences on each other, via cortisol and TGF-β1, but the exact nature of the interaction is not well characterized. The current study examined the effects, in bonnet macaques ( Macaca radiata ), of two consecutive acute confinement stress periods in an unfamiliar room while mildly restrained, first without and then with dexamethasone pretreatment (0.01 mg/kg intramuscular). Preceding the confinement studies, a non-stress control condition obtained contemporaneous levels of cortisol and TGF-β1 in both plasma and cerebrospinal fluid to match the confinement stress studies. Subjects were reared under either normative or variable foraging demand conditions. Since there were no rearing effects at baseline or for any of the conditions tested—either for cortisol or TGF-β—the study analyses were conducted on the combined rearing groups. The stress condition increased both plasma and cerebrospinal fluid cortisol levels whereas dexamethasone pretreatment decreased cortisol concentrations to below baseline levels despite stress. The stress condition decreased TGF-β1 concentrations only in cerebrospinal fluid but not in serum. Together, the data suggested that stress-induced reductions of a centrally active neuroprotective cytokine occur in the face of hypothalamic-pituitary-adrenal axis activation, potentially facilitating glucocortoid-induced neurotoxicity. Stress-induced reductions of neuroprotective cytokines prompt exploration of protective measures against glucocorticoid-induced neurotoxicity.

Objective: We previously demonstrated an inverse relationship between both dentate gyrus neurogenesis – a form of neuroplasticity – and expression of the antiapoptotic gene marker, BCL-2 and adult macaque body weight. We therefore explored whether a similar inverse correlation existed in humans between body mass index (BMI) and hippocampal N-acetyl-aspartate (NAA), a marker of neuronal integrity and putatively, neuroplasticity. We also studied the relationship of a potentially neurotoxic process, worry, to hippocampal NAA in patients with generalized anxiety disorder (GAD) and control subjects (CS). Methods: We combined two previously studied cohorts of GAD and control subjects. Using proton magnetic resonance spectroscopy imaging (1H MRSI) in medication-free patients with GAD (n = 29) and a matched healthy control group (n = 22), we determined hippocampal concentrations of (1) NAA (2) choline containing compounds (CHO), and (3) Creatine + phosphocreatine (CR). Data were combined from 1.5 T and 3 T scans by converting values from each cohort to z-scores. Overweight and GAD diagnosis were used as categorical variables while the Penn State Worry Questionnaire (PSWQ) and Anxiety Sensitivity Index (ASI) were used as dependent variables. Results: Overweight subjects (BMI ≥ 25) exhibited lower NAA levels in the hippocampus than normal-weight subjects (BMI