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Posttraumatic stress disorder (PTSD) is a chronic psychiatric condition that follows exposure to a traumatic stressor. Though previous in vivo proton (1H) MRS) research conducted at 4 T or lower has identified alterations in glutamate metabolism associated with PTSD predisposition and/or progression, no prior investigations have been conducted at higher field strength. In addition, earlier studies have not extensively addressed the impact of psychiatric comorbidities such as major depressive disorder (MDD) on PTSD‐associated 1H‐MRS‐visible brain metabolite abnormalities. Here we employ 7 T 1H MRS to examine concentrations of glutamate, glutamine, GABA, and glutathione in the medial prefrontal cortex (mPFC) of PTSD patients with MDD (PTSD+MDD+; N = 6) or without MDD (PTSD+MDD−; N = 5), as well as trauma‐unmatched controls without PTSD but with MDD (PTSD−MDD+; N = 9) or without MDD (PTSD−MDD−; N = 18). Participants with PTSD demonstrated decreased ratios of GABA to glutamine relative to healthy PTSD−MDD− controls but no single‐metabolite abnormalities. When comorbid MDD was considered, however, MDD but not PTSD diagnosis was significantly associated with increased mPFC glutamine concentration and decreased glutamate:glutamine ratio. In addition, all participants with PTSD and/or MDD collectively demonstrated decreased glutathione relative to healthy PTSD−MDD− controls. Despite limited findings in single metabolites, patterns of abnormality in prefrontal metabolite concentrations among individuals with PTSD and/or MDD enabled supervised classification to separate them from healthy controls with 80+% sensitivity and specificity, with glutathione, glutamine, and myoinositol consistently among the most informative metabolites for this classification. Our findings indicate that MDD can be an important factor in mPFC glutamate metabolism abnormalities observed using 1H MRS in cohorts with PTSD. [ABSTRACT FROM AUTHOR]

The article discusses the use of multimodal neuroimaging to map the depressed brain under stress. It highlights the challenges of replicating brain-behavior associations in small cohorts and proposes new approaches to address this issue, such as using generative artificial intelligence models and conducting multimodal experimental studies. The article presents a specific study that examines the neural mechanisms and correlates of stress responses in individuals with major depressive disorder (MDD) and remitted MDD. The study finds disruptions in cortisol signaling, GABA levels, and large-scale brain network dynamics in individuals with MDD, providing insights into the maladaptive stress responses in depression. The article also discusses the potential implications of these findings for identifying biomarkers, developing interventions, and understanding sex differences in depression. [Extracted from the article]

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We assessed the interrater reliability, convergent validity, and discriminant validity of the Self-Injurious Thoughts and Behaviors Interview-Short Form (SITBI-SF) in a sample of 1,944 active duty service members and veterans seeking services for posttraumatic stress disorder (PTSD) and related conditions. The SITBI-SF demonstrated high interrater reliability and good convergent and discriminant validity. The measurement properties of the SITBI-SF were comparable across service members and veterans. Approximately 8% of participants who denied a history of suicidal ideation on the SITBI-SF reported suicidal ideation on a separate self-report questionnaire (i.e., discordant responders). Discordant responders reported significantly higher levels of PTSD symptoms than those who denied suicidal ideation on both response formats. Findings suggest that the SITBI-SF is a reliable and valid interview-based measure of suicide-related thoughts and behaviors for use with military service members and veterans. Suicide risk assessment might be optimized if the SITBI-SF interview is combined with a self-report measure of related constructs. [ABSTRACT FROM AUTHOR]

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 (1H MRS) enables noninvasive measurement of small-molecule metabolites in the living human. 1H 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 1H-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 (I2 < 0.01% to 90.1%) and suggested regional dependence on quantification reference (creatine or otherwise). While observed variabilities in methods and reported findings suggest that 1H-MRS explorations of PTSD could benefit from methodological standardization, informing this standardization by quantitative assessment of the existing literature is currently hampered by its small size and limited scope. [ABSTRACT FROM AUTHOR]

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 13C-acetate magnetic resonance spectroscopy (MRS) scans to estimate prefrontal EPC, which is the ratio of neuronal energetic needs per glutamate neurotransmission cycle (VTCA/VCycle). 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 13C-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 FROM AUTHOR]

An editorial is presented on standard of care in the clinic nor leading the way in providing precision medicine. Topics include fascinated neuroscientists serving as a foundation for a large body of neuroimaging research aiming to identify associations between localized brain regions; and longitudinal interventional design, and comparison of neural predictors of response in adults and adolescents.

Background: Although the ε4 allele of the apolipoprotein E (APOE) gene and posttraumatic stress disorder (PTSD) have been linked to cognitive dysfunction and dementia risk, it is unknown whether they interact to predict cognitive dysfunction.Methods: We analyzed data from European-American (EA) veterans who participated in the National Health and Resilience in Veterans Study (NHRVS): main sample (n = 1,386) and primary replication sample (n = 509). EAs from the Yale-Penn Study cohort (n = 948) served as a second replication sample. Multivariable analyses were conducted to evaluate the predictive effects of ε4 carrier status and PTSD on cognitive functioning, with a focus on whether PTSD moderates the effect of ε4 carrier status.Results: APOE ε4 allele carrier status (d = 0.15 and 0.17 in the main and primary replication NHRVS samples, respectively) and PTSD (d = 0.31 and 0.17, respectively) were independently associated with lower cognitive functioning. ε4 carriers with PTSD scored lower than those without PTSD (d = 0.68 and 1.29, respectively) with the most pronounced differences in executive function (d's = 0.75-1.50) and attention/concentration (d's = 0.62-1.33). A significant interaction was also observed in the Yale-Penn sample, with ε4 carriers with PTSD making more perseverative errors on a measure of executive function than those without PTSD (24.7% vs. 17.6%; d = 0.59).Conclusions: APOE ε4 allele carriers with PTSD have substantially greater cognitive difficulties than ε4 carriers without PTSD. These results underscore the importance of assessing, monitoring, and treating PTSD in trauma-affected individuals who are at genetic risk for cognitive decline and dementia. [ABSTRACT FROM AUTHOR]

Posttraumatic stress disorder (PTSD) is a debilitating disorder with limited medication treatment options. Recent reports have described the dearth of research on new drug development as a crisis in the pharmacotherapy of PTSD. There are only two PTSD medications approved by the U.S. Food and Drug Administration, and both are serotonergic antidepressants. Therefore, there is a tremendous need to identify more effective and more rapidly acting pharmacotherapies for PTSD that work through novel neural mechanisms. Pilot evidence and case reports provided preliminary evidence supporting the safety and utility of investigating the therapeutic effects of ketamine in PTSD. However, the efficacy of this drug for PTSD has not yet been tested in active duty military or veteran populations. Here, we report the design and methods of a study funded under the Consortium to Alleviate PTSD. The study is a multisite, placebo-controlled, double–blind, randomized clinical trial to examine the dose-related efficacy of ketamine, as compared to placebo, in producing a rapid and sustained reduction in PTSD symptomatology in veterans and active duty military populations with antidepressant-resistant PTSD. Approximately 198 eligible participants who meet criteria for PTSD will be randomized to the study drug (i.e., ketamine 0.5 mg/kg, ketamine 0.2 mg/kg, or placebo). The study drug will be administered intravenously twice per week for 4 weeks, followed by a 4-week follow-up period. This ongoing study is the only trial of therapeutic effects of ketamine for PTSD and the first placebo-controlled trial to determine the dose-related effects of repeated ketamine on PTSD. [ABSTRACT FROM AUTHOR]

The authors convey their concerns on the optimism about ketamine's rapid-acting antidepressant impacts in stress-related psychopathology. They mentioned that rapid-acting antisuicidal effects take place within a day and persist around one week. They added that the behavioral activation of joining a clinical trial seems to be highly therapeutic. Most health insurance firms do not cover the high costs of off-label ketamine dosing.

New approaches to the neurobiology of posttraumatic stress disorder (PTSD) are needed to address the reported crisis in PTSD drug development. These new approaches may require the field to move beyond a narrow fear-based perspective, as fear-based medications have not yet demonstrated compelling efficacy. Antidepressants, particularly recent rapid-acting antidepressants, exert complex effects on brain function and structure that build on novel aspects of the biology of PTSD, including a role for stress-related synaptic dysconnectivity in the neurobiology and treatment of PTSD. Here, we integrate this perspective within a broader framework—in other words, a dual pathology model of (a) stress-related synaptic loss arising from amino acid–based pathology and (b) stress-related synaptic gain related to monoamine-based pathology. Then, we summarize the standard and experimental (e.g., ketamine) pharmacotherapeutic options for PTSD and discuss their putative mechanism of action and clinical efficacy. [ABSTRACT FROM AUTHOR]

Purpose Of Review: Although a fine-grained understanding of the neurobiology of posttraumatic stress disorder (PTSD) is yet to be elucidated, the last two decades have seen a rapid growth in the study of PTSD using neuroimaging techniques. The current review summarizes important findings from functional and structural neuroimaging studies of PTSD, by primarily focusing on their relevance towards an emerging network-based neurobiological model of the disorder.Recent Findings: PTSD may be characterized by a weakly connected and hypoactive default mode network (DMN) and central executive network (CEN) that are putatively destabilized by an overactive and hyperconnected salience network (SN), which appears to have a low threshold for perceived saliency, and inefficient DMN-CEN modulation. There is considerable evidence for large-scale functional and structural network dysfunction in PTSD. Nevertheless, several limitations and gaps in the literature need to be addressed in future research. [ABSTRACT FROM AUTHOR]

Purpose Of Review: Studies of the neurobiology and treatment of PTSD have highlighted many aspects of the pathophysiology of this disorder that might be relevant to treatment. The purpose of this review is to highlight the potential clinical importance of an often-neglected consequence of stress models in animals that may be relevant to PTSD: the stress-related loss of synaptic connectivity.Recent Findings: Here, we will briefly review evidence that PTSD might be a "synaptic disconnection syndrome" and highlight the importance of this perspective for the emerging therapeutic application of ketamine as a potential rapid-acting treatment for this disorder that may work, in part, by restoring synaptic connectivity. Synaptic disconnection may contribute to the profile of PTSD symptoms that may be targeted by novel pharmacotherapeutics. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented which discusses cross-sectional study related to amygdala-hippocampal volume and the phenotypic heterogeneity of post-traumatic stress disorder.

Background: Posttraumatic stress disorder (PTSD) is a debilitating mental illness that is thought to be associated with brain white matter (WM) alterations. Individual diffusion tensor imaging (DTI) studies to date have reported inconsistent alterations in FA across different brain regions in patients with PTSD. Here, we aimed to investigate FA in PTSD using both region-of-interest (ROI)-based and whole-brain-based meta-analytic approaches.Objectives: Individual ROI-based meta-analysis was carried out in each eligible white matter tract and seed-based D mapping (SDM) meta-analysis was conducted in the whole brain to identify the convergence of FA alterations in PTSD relative to controls.Results: Seventeen studies were included in ROI-based meta-analysis (≥ 3 studies were included for each ROI, NPTSD ≥ 80 and Ncontrol ≥ 103 per ROI). Fourteen studies with a total of 322 PTSD and 335 controls were included in whole-brain based meta-analysis. Both ROI and whole-brain meta-analyses showed that patients with PTSD have significantly higher FA in the inferior fronto-occipital fasciculus and lower FA in the genu of corpus callosum. Whole-brain meta-analyses also identified higher FA in the left inferior temporal gyrus and lower FA in the anterior cingulum and left corticospinal tract.Limitations: A small number of studies were included in some ROI tracts. Thus the results should be interpreted with caution.Conclusions: Our results suggest that PTSD patients have increased FA in areas related to visual processing, but decreased FA in anterior brain regions critical to cognition association and fear regulation. [ABSTRACT FROM AUTHOR]

• Classifying PTSD from trauma-unexposed healthy controls (HC) using three imaging modalities performed well (∼75 % AUC), but performance suffered markedly when classifying PTSD from trauma-exposed healthy controls (TEHC) using three imaging modalities (∼60 % AUC). • Using deep learning for feature reduction (denoising variational auto-encoder; DVAE) dramatically reduced the number of features with no concomitant performance degradation. • Utilizing denoising variational autoencoder (DVAE) models improves generalizability across heterogeneous multi-site data compared with the traditional machine learning frameworks. 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics. [ABSTRACT FROM AUTHOR]

We investigated the extent of cortical thinning in U.S. Veterans exposed to combat who varied in the severity of their posttraumatic stress disorder (PTSD) symptoms. In addition, we explored the neural correlates of PTSD symptom dimensions and the interactive effects of combat exposure and PTSD upon cortical thickness. Sixty-nine combat exposed Veterans completed high-resolution magnetic resonance imaging (MRI) scans to estimate cortical thickness. The Clinician Administered PTSD Scale (CAPS) and Combat Exposure Scale (CES) assessments were completed to measure current PTSD and historical combat severity, respectively. PTSD symptom dimensions (numbing, avoidance, reexperiencing, anxious arousal, and dysphoric arousal) were studied. Vertex-wise whole cerebrum analyses were conducted. We found widespread negative correlations between CAPS severity and cortical thickness, particularly within the prefrontal cortex. This prefrontal correlation remained significant after controlling for depression severity, medication status, and other potential confounds. PTSD dimensions, except anxious arousal, negatively correlated with cortical thickness in various unique brain regions. CES negatively correlated with cortical thickness in the left lateral prefrontal, regardless of PTSD diagnosis. A significant interaction between CES and PTSD diagnosis was found, such that CES negatively correlated with cortical thickness in the non-PTSD, but not in the PTSD, participants. The results underscore the severity of cortical thinning in U.S. Veterans suffering from high level of PTSD symptoms, as well as in Veterans with no PTSD diagnosis but severe combat exposure. The latter finding raises considerable concerns about a concealed injury potentially related to combat exposure in the post-9/11 era. [ABSTRACT FROM AUTHOR]

The STRONG STAR Consortium (South Texas Research Organizational Network Guiding Studies on Trauma and Resilience) and the Consortium to Alleviate PTSD are interdisciplinary and multi-institutional research consortia focused on the detection, diagnosis, prevention, and treatment of combat-related posttraumatic stress disorder (PTSD) and comorbid conditions in military personnel and veterans. This manuscript outlines the consortia's state-of-the-science collaborative research model and how this can be used as a roadmap for future trauma-related research. STRONG STAR was initially funded for 5 years in 2008 by the U.S. Department of Defense's (DoD) Psychological Health and Traumatic Brain Injury Research Program. Since the initial funding of STRONG STAR, almost 50 additional peer-reviewed STRONG STAR-affiliated projects have been funded through the DoD, the U.S. Department of Veterans Affairs (VA), the National Institutes of Health, and private organizations. In 2013, STRONG STAR investigators partnered with the VA's National Center for PTSD and were selected for joint DoD/VA funding to establish the Consortium to Alleviate PTSD. STRONG STAR and the Consortium to Alleviate PTSD have assembled a critical mass of investigators and institutions with the synergy required to make major scientific and public health advances in the prevention and treatment of combat PTSD and related conditions. This manuscript provides an overview of the establishment of these two research consortia, including their history, vision, mission, goals, and accomplishments. Comprehensive tables provide descriptions of over 70 projects supported by the consortia. Examples are provided of collaborations among over 50 worldwide academic research institutions and over 150 investigators. [ABSTRACT FROM AUTHOR]