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.

Influence of affective instability on suicidal ideation beyond traumatic brain injury and posttraumatic stress disorder in veterans

OBJECTIVE

Mild traumatic brain injury (TBI) is associated with long-term consequences, including greater risk for posttraumatic stress disorder (PTSD) and suicidal ideation. Affective instability is also independently related to PTSD and suicidality, which may explain why some individuals continue to experience chronic psychiatric complaints following mild TBI. The purpose of the present study was to evaluate affective instability as a key factor for PTSD and suicidal ideation among Veterans with and without TBI.

METHOD

Participants (N = 299 Veterans; 86.96% male) completed the Personality Assessment Inventory (PAI) and structured clinical interviews for TBI and psychiatric diagnoses. Hierarchical linear regression was used to evaluate main and interaction effects.

RESULTS

There were no significant differences in affective instability (p = 0.140) or suicidal ideation (p = 0.453) between Veterans with or without TBI. Individuals with TBI were more likely to have a PTSD diagnosis (p = 0.001). Analyses evaluating PTSD diagnosis as an outcome indicated a main effect of affective instability (p < 0.001), but not TBI (p = 0.619). Analyses evaluating suicidal ideation as an outcome demonstrated an interaction effect between PTSD and affective instability beyond the effects of TBI (p = 0.034).

CONCLUSIONS

Severe Affective instability appears to be a key factor in suicidal ideation among Veterans beyond TBI or PTSD history. PTSD was more strongly associated with suicidality at lower and moderate levels of affective instability. At severe levels of affective instability, however, Veterans with and without PTSD experienced suicidal ideation at similar rates. Findings suggests that high levels of affective instability not better explained by other psychiatric conditions confers similar suicidality risk to that of PTSD in a Veteran population.

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

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

Intermittent theta burst stimulation and functional connectivity in people living with HIV/AIDS who smoke tobacco cigarettes: a preliminary pilot study

Background

People living with HIV (PLWHA) smoke at three times the rate of the general population and respond poorly to cessation strategies. Previous studies examined repetitive transcranial magnetic stimulation (rTMS) over left dorsolateral prefrontal cortex (L. dlPFC) to reduce craving, but no studies have explored rTMS among PLWHA who smoke. The current pilot study compared the effects of active and sham intermittent theta-burst stimulation (iTBS) on resting state functional connectivity (rsFC), cigarette cue attentional bias, and cigarette craving in PLWHA who smoke.

Methods

Eight PLWHA were recruited (single-blind, within-subject design) to receive one session of iTBS (n=8) over the L. dlPFC using neuronavigation and, four weeks later, sham iTBS (n=5). Cigarette craving and attentional bias assessments were completed before and after both iTBS and sham iTBS. rsFC was assessed before iTBS (baseline) and after iTBS and sham iTBS.

Results

Compared to sham iTBS, iTBS enhanced rsFC between the L. dlPFC and bilateral medial prefrontal cortex and pons. iTBS also enhanced rsFC between the right insula and right occipital cortex compared to sham iTBS. iTBS also decreased cigarette craving and cigarette cue attentional bias.

Conclusion

iTBS could potentially offer a therapeutic option for smoking cessation in PLWHA.

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

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

The Genetic Architecture of Amygdala Nuclei

BACKGROUND

Whereas genetic variants influencing total amygdala volume have been identified, the genetic architecture of its distinct nuclei has yet to be explored. We aimed to investigate whether increased phenotypic specificity through nuclei segmentation aids genetic discoverability and elucidates the extent of shared genetic architecture and biological pathways with related disorders.

METHODS

T1-weighted brain magnetic resonance imaging scans (N = 36,352, 52% female) from the UK Biobank were segmented into 9 amygdala nuclei with FreeSurfer (version 6.1). Genome-wide association analyses were performed on the entire sample, a European-only subset (n = 31,690), and a generalization (transancestry) subset (n = 4662). We estimated single nucleotide polymorphism-based heritability; derived polygenicity, discoverability, and power estimates; and investigated genetic correlations and shared loci with psychiatric disorders.

RESULTS

The heritability of the nuclei ranged from 0.17 to 0.33. Across the whole amygdala and the nuclei volumes, we identified 28 novel genome-wide significant (padj < 5 × 10-9) loci in the European analysis, with significant en masse replication for the whole amygdala and central nucleus volumes in the generalization analysis, and we identified 10 additional candidate loci in the combined analysis. The central nucleus had the highest statistical power for discovery. The significantly associated genes and pathways showed unique and shared effects across the nuclei, including immune-related pathways. Shared variants were identified between specific nuclei and autism spectrum disorder, Alzheimer's disease, Parkinson's disease, bipolar disorder, and schizophrenia.

CONCLUSIONS

Through investigation of amygdala nuclei volumes, we have identified novel candidate loci in the neurobiology of amygdala volume. These nuclei volumes have unique associations with biological pathways and genetic overlap with psychiatric disorders.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium

Background

Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective.

Methods

Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated.

Results

rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group.

Conclusions

Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

BACKGROUND

Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.

METHODS

We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.

RESULTS

We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.

CONCLUSION

These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

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.

Precision functional MRI mapping reveals distinct connectivity patterns for depression associated with traumatic brain injury

Depression associated with traumatic brain injury (TBI) is believed to be clinically distinct from primary major depressive disorder (MDD) and may be less responsive to conventional treatments. Brain connectivity differences between the dorsal attention network (DAN), default mode network (DMN), and subgenual cingulate have been implicated in TBI and MDD. To characterize these distinctions, we applied precision functional mapping of brain network connectivity to resting-state functional magnetic resonance imaging data from five published patient cohorts, four discovery cohorts (n = 93), and one replication cohort (n = 180). We identified a distinct brain connectivity profile in TBI-associated depression that was independent of TBI, MDD, posttraumatic stress disorder (PTSD), depression severity, and cohort. TBI-associated depression was independently associated with decreased DAN-subgenual cingulate connectivity, increased DAN-DMN connectivity, and the combined effect of both. This effect was stronger when using precision functional mapping relative to group-level network maps. Our results support the possibility of a physiologically distinct "TBI affective syndrome," which may benefit from individualized neuromodulation approaches to target its distinct neural circuitry.

Harmonizing PTSD severity scales across instruments and sites

OBJECTIVE

The variety of instruments used to assess posttraumatic stress disorder (PTSD) allows for flexibility, but also creates challenges for data synthesis. The objective of this work was to use a multisite mega analysis to derive quantitative recommendations for equating scores across measures of PTSD severity.

METHOD

Empirical Bayes harmonization and linear models were used to describe and mitigate site and covariate effects. Quadratic models for converting scores across PTSD assessments were constructed using bootstrapping and tested on hold out data.

RESULTS

We aggregated 17 data sources and compiled an n = 5,634 sample of individuals who were assessed for PTSD symptoms. We confirmed our hypothesis that harmonization and covariate adjustments would significantly improve inference of scores across instruments. Harmonization significantly reduced cross-dataset variance (28%, p < .001), and models for converting scores across instruments were well fit (median R² = 0.985) with an average root mean squared error of 1.46 on sum scores.

CONCLUSIONS

These methods allow PTSD symptom severity to be placed on multiple scales and offers interesting empirical perspectives on the role of harmonization in the behavioral sciences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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

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

Altered lateralization of the cingulum in deployment-related traumatic brain injury: An ENIGMA military-relevant brain injury study

Traumatic brain injury (TBI) in military populations can cause disruptions in brain structure and function, along with cognitive and psychological dysfunction. Diffusion magnetic resonance imaging (dMRI) can detect alterations in white matter (WM) microstructure, but few studies have examined brain asymmetry. Examining asymmetry in large samples may increase sensitivity to detect heterogeneous areas of WM alteration in mild TBI. Through the Enhancing Neuroimaging Genetics Through Meta-Analysis Military-Relevant Brain Injury working group, we conducted a mega-analysis of neuroimaging and clinical data from 16 cohorts of Active Duty Service Members and Veterans (n = 2598). dMRI data were processed together along with harmonized demographic, injury, psychiatric, and cognitive measures. Fractional anisotropy in the cingulum showed greater asymmetry in individuals with deployment-related TBI, driven by greater left lateralization in TBI. Results remained significant after accounting for potentially confounding variables including posttraumatic stress disorder, depression, and handedness, and were driven primarily by individuals whose worst TBI occurred before age 40. Alterations in the cingulum were also associated with slower processing speed and poorer set shifting. The results indicate an enhancement of the natural left laterality of the cingulum, possibly due to vulnerability of the nondominant hemisphere or compensatory mechanisms in the dominant hemisphere. The cingulum is one of the last WM tracts to mature, reaching peak FA around 42 years old. This effect was primarily detected in individuals whose worst injury occurred before age 40, suggesting that the protracted development of the cingulum may lead to increased vulnerability to insults, such as TBI.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts

OBJECTIVE

A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia.

METHOD

Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA-Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior.

RESULTS

We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15-0.97; r range: 0.21-0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments.

CONCLUSIONS

Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Network Centrality and Modularity of Structural Covariance Networks in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study

Introduction: Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCNs) are represented as graphs with brain regions as nodes and correlations between nodes as edges. Methods: We built SCNs for PTSD and control groups using 148 CT and SA measures that were harmonized for site in n = 3439 subjects from Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA)-Psychiatric Genomics Consortium (PGC) PTSD. We compared centrality between PTSD and controls as well as interactions of diagnostic group with age, sex, and comorbid major depressive disorder (MDD) status. We investigated associations between network modularity and diagnostic grouping. Results: Nodes with higher CT-based centrality in PTSD compared with controls included the left inferior frontal sulcus, left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. Children (<10 years) and adolescents (10-21) with PTSD showed greater centrality in frontotemporal areas compared with young (22-39) and middle-aged adults (40-59) with PTSD, who showed higher centrality in occipital areas. The PTSD diagnostic group interactions with sex and comorbid MDD showed altered centrality in occipital regions, along with greater visual network (VN) modularity in PTSD subjects compared with controls. Conclusion: Structural covariance in PTSD is associated with centrality differences in occipital areas and VN modularity differences in a large well-powered sample. In the context of extensive structural covariance remodeling taking place before and during adolescence, the present findings suggest a process of cortical remodeling that commences with trauma and/or the onset of PTSD but may also predate these events.

Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans

Importance

Suicide is a leading cause of death; however, the molecular genetic basis of suicidal thoughts and behaviors (SITB) remains unknown.

Objective

To identify novel, replicable genomic risk loci for SITB.

Design, Setting, and Participants

This genome-wide association study included 633 778 US military veterans with and without SITB, as identified through electronic health records. GWAS was performed separately by ancestry, controlling for sex, age, and genetic substructure. Cross-ancestry risk loci were identified through meta-analysis. Study enrollment began in 2011 and is ongoing. Data were analyzed from November 2021 to August 2022.

Main Outcome and Measures

SITB.

Results

A total of 633 778 US military veterans were included in the analysis (57 152 [9%] female; 121 118 [19.1%] African ancestry, 8285 [1.3%] Asian ancestry, 452 767 [71.4%] European ancestry, and 51 608 [8.1%] Hispanic ancestry), including 121 211 individuals with SITB (19.1%). Meta-analysis identified more than 200 GWS (P < 5 × 10-8) cross-ancestry risk single-nucleotide variants for SITB concentrated in 7 regions on chromosomes 2, 6, 9, 11, 14, 16, and 18. Top single-nucleotide variants were largely intronic in nature; 5 were independently replicated in ISGC, including rs6557168 in ESR1, rs12808482 in DRD2, rs77641763 in EXD3, rs10671545 in DCC, and rs36006172 in TRAF3. Associations for FBXL19 and AC018880.2 were not replicated. Gene-based analyses implicated 24 additional GWS cross-ancestry risk genes, including FURIN, TSNARE1, and the NCAM1-TTC12-ANKK1-DRD2 gene cluster. Cross-ancestry enrichment analyses revealed significant enrichment for expression in brain and pituitary tissue, synapse and ubiquitination processes, amphetamine addiction, parathyroid hormone synthesis, axon guidance, and dopaminergic pathways. Seven other unique European ancestry-specific GWS loci were identified, 2 of which (POM121L2 and METTL15/LINC02758) were replicated. Two additional GWS ancestry-specific loci were identified within the African ancestry (PET112/GATB) and Hispanic ancestry (intergenic locus on chromosome 4) subsets, both of which were replicated. No GWS loci were identified within the Asian ancestry subset; however, significant enrichment was observed for axon guidance, cyclic adenosine monophosphate signaling, focal adhesion, glutamatergic synapse, and oxytocin signaling pathways across all ancestries. Within the European ancestry subset, genetic correlations (r > 0.75) were observed between the SITB phenotype and a suicide attempt-only phenotype, depression, and posttraumatic stress disorder. Additionally, polygenic risk score analyses revealed that the Million Veteran Program polygenic risk score had nominally significant main effects in 2 independent samples of veterans of European and African ancestry.

Conclusions and Relevance

The findings of this analysis may advance understanding of the molecular genetic basis of SITB and provide evidence for ESR1, DRD2, TRAF3, and DCC as cross-ancestry candidate risk genes. More work is needed to replicate these findings and to determine if and how these genes might impact clinical care.

Adolescent alcohol use is linked to disruptions in age-appropriate cortical thinning: an unsupervised machine learning approach

Cortical thickness changes dramatically during development and is associated with adolescent drinking. However, previous findings have been inconsistent and limited by region-of-interest approaches that are underpowered because they do not conform to the underlying spatially heterogeneous effects of alcohol. In this study, adolescents (n = 657; 12-22 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study who endorsed little to no alcohol use at baseline were assessed with structural magnetic resonance imaging and followed longitudinally at four yearly intervals. Seven unique spatial patterns of covarying cortical thickness were obtained from the baseline scans by applying an unsupervised machine learning method called non-negative matrix factorization (NMF). The cortical thickness maps of all participants' longitudinal scans were projected onto vertex-level cortical patterns to obtain participant-specific coefficients for each pattern. Linear mixed-effects models were fit to each pattern to investigate longitudinal effects of alcohol consumption on cortical thickness. We found in six NMF-derived cortical thickness patterns, the longitudinal rate of decline in no/low drinkers was similar for all age cohorts. Among moderate drinkers the decline was faster in the younger adolescent cohort and slower in the older cohort. Among heavy drinkers the decline was fastest in the younger cohort and slowest in the older cohort. The findings suggested that unsupervised machine learning successfully delineated spatially coordinated patterns of vertex-level cortical thickness variation that are unconstrained by neuroanatomical features. Age-appropriate cortical thinning is more rapid in younger adolescent drinkers and slower in older adolescent drinkers, an effect that is strongest among heavy drinkers.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites

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.

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium

BACKGROUND

Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA).

METHODS

Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks.

RESULTS

Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks.

CONCLUSIONS

Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD.

ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data

The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized Analysis of Functional MRI pipeline), an open-source, containerized, user-friendly tool that facilitates reproducible analysis of task-based and resting-state fMRI data through uniform application of preprocessing, quality assessment, single-subject feature extraction, and group-level statistics. It provides state-of-the-art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to rate the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post-processing functions at the individual subject level, including calculation of task-based activation, seed-based connectivity, network-template (or dual) regression, atlas-based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low-frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed-effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post-processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe.

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

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

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

BACKGROUND

Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs).

METHODS

A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms.

RESULTS

GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program.

CONCLUSIONS

Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

The impact of climate change on the prevalence of mental illness symptoms

BACKGROUND

The repercussions of climate change threaten the population with an increased prevalence of extreme climate events. We explored the impact of climate change induced sea level rise (SLR) and tropical cyclone (TC) exposure on mental illness symptom prevalence.

METHODS

Using three datasets, TC exposure scores were calculated for each subject to determine how exposure affects posttraumatic stress disorder (PTSD), anxiety, and major depressive disorder (MDD) symptom prevalence. Inundation mapping of various SLR and storm surge (SS) scenarios were performed for the susceptible region of Miami-Dade and Broward counties to determine the population impact of flooding.

RESULTS

We found an elevated risk of mental illness symptoms from exposure to more high- intensity TCs and identified demographic variables that may contribute to this risk. Furthermore, inundation mapping demonstrated severe and widespread impact of SLR and SS on the mental health of communities.

LIMITATIONS

This study did not include data directly measuring comorbidity, resilience, preparedness, or ability to adapt to climate change. Also, multiple imputation using chained equations may have been imperfect. Furthermore, there is uncertainty in predicting and mapping SLR and TC intensity, which limits complete confidence in our SS predictions.

CONCLUSION

The impacts of climate change have been frequently studied in terms of physical health, natural disaster prevalence, and economic impacts, but rarely on mental health burden. However, it is vital that national, state, and local governments develop and deploy plans to address mental health needs along with expenditures for protecting infrastructure, the economy, and physical health from the combined effects of SLR and climate change-induced natural disasters.

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

BACKGROUND

Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD.

METHOD

Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site.

RESULTS

BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages.

DISCUSSION

Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

The role of trauma, social support, and demography on veteran resilience

BACKGROUND

Historically, resilience has often been conceptualized as the sustained lack of symptoms following trauma exposure. In line with a novel conceptualization of resilience as being dynamic over lifespan, determined by interacting biological and environmental factors, we examined the VA Mid-Atlantic Post Deployment Mental Health Repository (PDMH) comprised of 3876 US Military Veterans with and without PTSD diagnoses.

METHODS

We performed regression modelling to study the relationship between resilience (measured with Connor Davidson Resilience Scale; CD-RISC), posttraumatic stress disorder (PTSD) severity (Davidson Trauma Scale; DTS), social support (Medical Outcome Study Social Support Survey; MOSSS), combat exposure (Combat Exposure Scale; CES), childhood trauma (Trauma Life Events Questionnaire; TLEQ), and demographic factors. CD-RISC was positively correlated with years of education and negatively correlated with DTS, CES and TLEQ scores.

RESULTS

We found an interaction between CD-RISC and CES in predicting PTSD severity (Davidson Trauma Scale). Specifically, high resilience predicted lower PTSD symptom severity than low resilience, this relationship was amplified with increasing levels of combat exposure. Structural equation modelling (SEM) identified an optimal latent variable that represents resilience and relationships between latent variables for resilience, trauma, and illness. We derived a resilience latent variable composed of age, education level, MOSSS and race.

CONCLUSIONS

Our results support a conceptualization of resilience as a multifactorial determinant that coexists with PTSD, a state rather than trait variable, and can be quantified by biological and behavioural metrics.

HIGHLIGHTS

• Historically, resilience has often been conceptualized as the sustained lack of symptoms following trauma exposure.• We examined the VA Mid-Atlantic Post Deployment Mental Health Repository (PDMH) comprised of 3876 US Military Veterans.• We found an interaction effect between CD-RISC and CES in predicting PTSD severity (Davidson Trauma Scale).

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

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

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.

The neurobiology of human fear generalization: meta-analysis and working neural model

Fear generalization to stimuli resembling a conditioned danger-cue (CS+) is a fundamental dynamic of classical fear-conditioning. Despite the ubiquity of fear generalization in human experience and its known pathogenic contribution to clinical anxiety, neural investigations of human generalization have only recently begun. The present work provides the first meta-analysis of this growing literature to delineate brain substrates of conditioned fear-generalization and formulate a working neural model. Included studies (K = 6, N = 176) reported whole-brain fMRI results and applied generalization-gradient methodology to identify brain activations that gradually strengthen (positive generalization) or weaken (negative generalization) as presented stimuli increase in CS+ resemblance. Positive generalization was instantiated in cingulo-opercular, frontoparietal, striatal-thalamic, and midbrain regions (locus coeruleus, periaqueductal grey, ventral tegmental area), while negative generalization was implemented in default-mode network nodes (ventromedial prefrontal cortex, hippocampus, middle temporal gyrus, angular gyrus) and amygdala. Findings are integrated within an updated neural account of generalization centering on the hippocampus, its modulation by locus coeruleus and basolateral amygdala, and the excitation of threat- or safety-related loci by the hippocampus.

Assessment of Neuropsychological Function in Veterans With Blast-Related Mild Traumatic Brain Injury and Subconcussive Blast Exposure

Objective: The majority of combat-related head injuries are associated with blast exposure. While Veterans with mild traumatic brain injury (mTBI) report cognitive complaints and exhibit poorer neuropsychological performance, there is little evidence examining the effects of subconcussive blast exposure, which does not meet clinical symptom criteria for mTBI during the acute period following exposure. We compared chronic effects of combat-related blast mTBI and combat-related subconcussive blast exposure on neuropsychological performance in Veterans. Methods: Post-9/11 Veterans with combat-related subconcussive blast exposure (n = 33), combat-related blast mTBI (n = 26), and controls (n = 33) without combat-related blast exposure, completed neuropsychological assessments of intellectual and executive functioning, processing speed, and working memory via NIH toolbox, assessment of clinical psychopathology, a retrospective account of blast exposures and non-blast-related head injuries, and self-reported current medication. Huber Robust Regressions were employed to compare neuropsychological performance across groups. Results: Veterans with combat-related blast mTBI and subconcussive blast exposure displayed significantly slower processing speed compared with controls. After adjusting for post-traumatic stress disorder and depressive symptoms, those with combat-related mTBI exhibited slower processing speed than controls. Conclusion: Veterans in the combat-related blast mTBI group exhibited slower processing speed relative to controls even when controlling for PTSD and depression. Cognition did not significantly differ between subconcussive and control groups or subconcussive and combat-related blast mTBI groups. Results suggest neurocognitive assessment may not be sensitive enough to detect long-term effects of subconcussive blast exposure, or that psychiatric symptoms may better account for cognitive sequelae following combat-related subconcussive blast exposure or combat-related blast mTBI.

Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

FreeSurfer ‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.

Genetic predictors of hippocampal subfield volume in PTSD cases and trauma-exposed controls

Behavioural, structural, and functional neuroimaging have implicated the hippocampus as a critical brain region in posttraumatic stress disorder (PTSD) pathogenesis. Recent work in a normative, primarily European, sample identified 15 unique genetic loci contributing to structural variability in six hippocampal subfield volumes. We explored the relevance of these loci in two samples (Mental Illness Research Education and Clinical Centre [MIRECC] and Grady; n = 290) of trauma-exposed individuals enriched for PTSD and of diverse ancestry. Four of the previous loci demonstrated nominal evidence of replication in the MIRECC dataset, primarily within non-Hispanic whites (NHW). One locus replicated in the Grady cohort, which was composed exclusively of non-Hispanic blacks (NHB). Our data supported genetic interactions with diagnosis of lifetime PTSD and genetic interactions with childhood trauma in the MIRECC sample, but not the Grady sample. Given the racial, diagnostic, and trauma-exposure differences with the original genome-wide association study (GWAS) report, we conducted a full GWAS in the MIRECC and Grady datasets. Interactions between genetic variants and lifetime PTSD or childhood trauma were interrogated for single nucleotide polymorphisms (SNPs) with evidence of main effects. Genetic associations surpassed false discovery rate (FDR)-correction within hippocampal subfields in fimbria, subiculum, cornu ammonis-1 (CA1), and hippocampal amygdala transition area (HATA). One association was replicated in the Grady cohort (rs12880795 in TUNAR with left (L)-HATA volume). The most significant association in the MIRECC dataset was between rs6906714 in LINC02571 and right (R)-fimbria volume (p = 5.99×10-8, q = 0.0056). Interestingly, the effect of rs6906714 on R-fimbria volume increased with exposure to childhood trauma (gene*environment [G*E] interaction p = 0.022). These preliminary results argue for G*E interactions between genetic loci with PTSD and childhood trauma on hippocampal phenotypes. Our results underscore the need for larger neuroimaging-genetic studies in PTSD, trauma, and ancestrally diverse populations.

Neural correlates of conceptual-level fear generalization in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) may develop when mechanisms for making accurate distinctions about threat relevance have gone awry. Generalization across conceptually related objects has been hypothesized based on clinical observation in PTSD, but the neural mechanisms remain unexplored. Recent trauma-exposed military veterans (n = 46) were grouped into PTSD (n = 23) and non-PTSD (n = 23). Participants learned to generalize fear across conceptual categories (animals or tools) of semantically related items that were partially reinforced by shock during functional magnetic resonance imaging. Conditioned fear learning was quantified by shock expectancy and skin conductance response (SCR). Relative to veteran controls, PTSD subjects exhibited a stronger neural response associated with fear generalization to the reinforced object category in the striatum, anterior cingulate cortex, amygdala, occipitotemporal cortex, and insula (Z > 2.3; p < 0.05; whole-brain corrected). Based on SCR, both groups generalized the shock contingency to the reinforced conceptual category, but learning was not significantly different between groups. We found that PTSD was associated with an enhanced neural response in fronto-limbic, midline, and occipitotemporal regions to a learned representation of threat that is based on previously established conceptual knowledge of the relationship between basic-level exemplars within a semantic category. Behaviorally, veterans with PTSD were somewhat slower to differentiate threat and safety categories as compared with trauma-exposed veteran controls owing in part to an initial overgeneralized behavioral response to the safe category. These results have implications for understanding how fear spreads across semantically related concepts in PTSD.

Serum Neurosteroid Levels Are Associated With Cortical Thickness in Individuals Diagnosed With Posttraumatic Stress Disorder and History of Mild Traumatic Brain Injury

Posttraumatic stress disorder (PTSD) co-occurring with mild traumatic brain injury (mTBI) is common in veterans. Worse clinical outcome in those with PTSD has been associated with decreased serum neurosteroid levels. Furthermore, decreased cortical thickness has been associated with both PTSD and mTBI. However, it is not known whether decreased neurosteroids are associated with decreased cortical thickness in PTSD co-occurring with mTBI. This study included 141 individuals divided into the following groups: (a) mTBI group (n = 32 [10 female, 22 male] veterans with a history of mTBI); (b) PTSD + mTBI group (n = 41 [6 female, 35 male] veterans with current PTSD with a history of mTBI); and (c) control group (n = 68 [35 female, 33 male] control participants), which were acquired through the Injury and Traumatic Stress (INTRuST) Clinical Consortium. Subjects underwent clinical assessment, magnetic resonance imaging at 3 T, and serum neurosteroid quantifications of allopregnanolone (ALLO) and pregnenolone (PREGN). Group differences in cortical thickness and associations between serum neurosteroid levels and cortical thickness were investigated. Cortical thickness was decreased in the PTSD + mTBI group compared with the other groups. In the PTSD + mTBI group, decreased cortical thickness was also associated with lower serum ALLO (right superior frontal cortex) and lower serum PREGN (left middle temporal and right orbitofrontal cortex). Cortical thickness in the middle temporal and orbitofrontal cortex was associated with PTSD symptom severity. There were no significant associations between neurosteroids and cortical thickness in the mTBI or control groups. Decreased cortical thickness in individuals with PTSD + mTBI is associated with decreased serum neurosteroid levels and greater PTSD symptom severity. Causality is unclear. However, future studies might investigate whether treatment with neurosteroids could counteract stress-induced neural atrophy in PTSD + mTBI by potentially preserving cortical thickness.

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Threat-induced anxiety during goal pursuit disrupts amygdala-prefrontal cortex connectivity in posttraumatic stress disorder

To investigate how unpredictable threat during goal pursuit impacts fronto-limbic activity and functional connectivity in posttraumatic stress disorder (PTSD), we compared military veterans with PTSD (n = 25) vs. trauma-exposed control (n = 25). Participants underwent functional magnetic resonance imaging (fMRI) while engaged in a computerized chase-and-capture game task that involved optimizing monetary rewards obtained from capturing virtual prey while simultaneously avoiding capture by virtual predators. The game was played under two alternating contexts-one involving exposure to unpredictable task-irrelevant threat from randomly occurring electrical shocks, and a nonthreat control condition. Activation in and functional connectivity between the amygdala and ventromedial prefrontal cortex (vmPFC) was tested across threat and nonthreat task contexts with generalized psychophysiological interaction (gPPI) analyses. PTSD patients reported higher anxiety than controls across contexts. Better task performance represented by successfully avoiding capture by predators under threat compared with nonthreat contexts was associated with stronger left amygdala-vmPFC functional connectivity in controls and greater vmPFC activation in PTSD patients. PTSD symptom severity was negatively correlated with vmPFC activation in trauma-exposed controls and with right amygdala-vmPFC functional connectivity across all participants in the threat relative to nonthreat contexts. The findings showed that veterans with PTSD have disrupted amygdala-vmPFC functional connectivity and greater localized vmPFC processing under threat modulation of goal-directed behavior, specifically related to successfully avoiding loss of monetary rewards. In contrast, trauma survivors without PTSD relied on stronger threat-modulated left amygdala-vmPFC functional connectivity during goal-directed behavior, which may represent a resilience-related functional adaptation.

Combat exposure, posttraumatic stress disorder, and head injuries differentially relate to alterations in cortical thickness in military Veterans

Combat-exposed Veterans are at increased risk for developing psychological distress, mood disorders, and trauma and stressor-related disorders. Trauma and mood disorders have been linked to alterations in brain volume, function, and connectivity. However, far less is known about the effects of combat exposure on brain health. The present study examined the relationship between severity of combat exposure and cortical thickness. Post-9/11 Veterans (N = 337; 80% male) were assessed with structural neuroimaging and clinically for combat exposure, depressive symptoms, prior head injury, and posttraumatic stress disorder (PTSD). Vertex-wide cortical thickness was estimated using FreeSurfer autosegmentation. FreeSurfer's Qdec was used to examine relationship between combat exposure, PTSD, and prior head injuries on cortical thickness (Monte Carlo corrected for multiple comparisons, vertex-wise cluster threshold of 1.3, p < 0.01). Covariates included age, sex, education, depressive symptoms, nonmilitary trauma, alcohol use, and prior head injury. Higher combat exposure uniquely related to lower cortical thickness in the left prefrontal lobe and increased cortical thickness in the left middle and inferior temporal lobe; whereas PTSD negatively related to cortical thickness in the right fusiform. Head injuries related to increased cortical thickness in the bilateral medial prefrontal cortex. Combat exposure uniquely contributes to lower cortical thickness in regions implicated in executive functioning, attention, and memory after accounting for the effects of PTSD and prior head injury. Our results highlight the importance of examining effects of stress and trauma exposure on neural health in addition to the circumscribed effects of specific syndromal pathology.

Widespread Cortical Thickness Is Associated With Neuroactive Steroid Levels

Background

Neuroactive steroids are endogenous molecules with regenerative and neuroprotective actions. Both cortical thickness and many neuroactive steroid levels decline with age and are decreased in several neuropsychiatric disorders. However, a systematic examination of the relationship between serum neuroactive steroid levels and in vivo measures of cortical thickness in humans is lacking.

Methods

Peripheral serum levels of seven neuroactive steroids were assayed in United States military veterans. All (n = 143) subsequently underwent high-resolution structural MRI, followed by parcellelation of the cortical surface into 148 anatomically defined regions. Regression modeling was applied to test the association between neuroactive steroid levels and hemispheric total gray matter volume as well as region-specific cortical thickness. False discovery rate (FDR) correction was used to control for Type 1 error from multiple testing.

Results

Neuroactive steroid levels of allopregnanolone and pregnenolone were positively correlated with gray matter thickness in multiple regions of cingulate, parietal, and occipital association cortices (r = 0.20–0.47; p < 0.05; FDR-corrected).

Conclusion

Positive associations between serum neuroactive steroid levels and gray matter cortical thickness are found in multiple brain regions. If these results are confirmed, neuroactive steroid levels and cortical thickness may help in monitoring the clinical response in future intervention studies of neuroregenerative therapies.

A Pilot Study of Neurocognitive Function and Brain Structures in Adolescents With Alcohol Use Disorders: Does Maltreatment History Matter?

Neurocognitive and brain structural differences are associated with adolescent onset alcohol use disorders (AUDs). Maltreatment histories may contribute to current results. To examine these issues, healthy adolescents (n = 31), adolescents without maltreatment and AUD (AUD - MAL, n = 28), and adolescents with AUDs with maltreatment (AUD + MAL, n = 17) underwent comprehensive neurocognitive assessments and MRI structural scans. Controls performed significantly better than the two AUD groups in math and language. The AUD + MAL group performed significantly lower in sustained attention compared to the AUD - MAL and control groups and lower in reading compared to controls. The AUD + MAL group had larger left pars triangularis, a region of the inferior frontal gyrus, compared to the AUD-MAL and control groups, and smaller anterior corpus callosum volumes versus the AUD - MAL group. There were no group differences in other prefrontal cortex, amygdala, hippocampus, and parahippocampal volumes. The AUD + MAL group showed an inverse correlation between hippocampal volumes and age. AUD variables were associated with lower performance in fine-motor and executive function. Cannabis use variables were associated with lower performance in fine-motor, language, visual-spatial, memory, and executive function. Parahippocampal volumes positively correlated with abstinence. The preliminary results suggest adolescent AUD studies should consider examinations of maltreatment history, comorbid substance use disorders, and recovery during abstinence in their analyses.

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

Resilience as a translational endpoint in the treatment of PTSD

Resilience is a neurobiological entity that shapes an individual's response to trauma. Resilience has been implicated as the principal mediator in the development of mental illness following exposure to trauma. Although animal models have traditionally defined resilience as molecular and behavioral changes in stress responsive circuits following trauma, this concept needs to be further clarified for both research and clinical use. Here, we analyze the construct of resilience from a translational perspective and review optimal measurement methods and models. We also seek to distinguish between resilience, stress vulnerability, and posttraumatic growth. We propose that resilience can be quantified as a multifactorial determinant of physiological parameters, epigenetic modulators, and neurobiological candidate markers. This multifactorial definition can determine PTSD risk before and after trauma exposure. From this perspective, we propose the use of an 'R Factor' analogous to Spearman's g factor for intelligence to denote these multifactorial determinants. In addition, we also propose a novel concept called 'resilience reserve', analogous to Stern's cognitive reserve, to summarize the sum total of physiological processes that protect and compensate for the effect of trauma. We propose the development and application of challenge tasks to measure 'resilience reserve' and guide the assessment and monitoring of 'R Factor' as a biomarker for PTSD.

Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder: A Mendelian Randomization Study

Importance

There is a well-established negative association of educational attainment (EA) and other traits related to cognitive ability with posttraumatic stress disorder (PTSD), but the underlying mechanisms are poorly understood.

Objectives

To investigate the association of PTSD with traits related to EA.

Design, Setting, and Participants

Genetic correlation, polygenic risk scoring, and mendelian randomization (MR) were conducted including 23 185 individuals with PTSD and 151 309 control participants from the Psychiatric Genomics Consortium for PTSD and up to 1 131 881 individuals assessed for EA and related traits from UK Biobank, 23andMe, and the Social Science Genetic Association Consortium. Data were analyzed from July 3 through November 19, 2018.

Main Outcomes and Measures

Genetic correlation obtained from linkage disequilibrium score regression, phenotypic variance explained by polygenic risk scores, and association estimates from MR.

Results

Summary association data from multiple genome-wide association studies were available for a total of 1 180 352 participants (634 391 [53.7%] women). Posttraumatic stress disorder showed negative genetic correlations with EA (rg = -0.26; SE = 0.05; P = 4.60 × 10-8). Mendelian randomization analysis, conducting considering a random-effects inverse-variance weighted method, indicated that EA has a negative association with PTSD (β = -0.23; 95% CI, -0.07 to -0.39; P = .004). Investigating potential mediators of the EA-PTSD association, propensity for trauma exposure and risk-taking behaviors were observed as risk factors for PTSD independent of EA (trauma exposure: β = 0.37; 95% CI, 0.19 to 0.52; P = 2.57 × 10-5; risk-taking: β = 0.76; 95% CI, 0.38 to 1.13; P = 1.13 × 10-4), while income may mediate the association of EA with PSTD (MR income: β = -0.18; 95% CI, -0.29 to -0.07; P = .001; MR EA: β = -0.23; 95% CI, -0.39 to -0.07; P = .004; multivariable MR income: β = -0.32; 95% CI, -0.57 to 0.07; P = .02; multivariable MR EA: β = -0.04; 95% CI, -0.29 to 0.21; SE, 0.13; P = .79).

Conclusions and Relevance

Large-scale genomic data sets add further evidence to the negative association of EA with PTSD, also supporting the role of economic status as a mediator in the association observed.

Resting-state brain fluctuation and functional connectivity dissociate moral injury from posttraumatic stress disorder

Moral injury is closely associated with posttraumatic stress disorder (PTSD) and characterized by disturbances in social and moral cognition. Little is known about the neural underpinnings of moral injury, and whether the neural correlates are different between moral injury and PTSD. A sample of 26 U.S. military veterans (two females: 28-55 years old) were investigated to determine how subjective appraisals of morally injurious events measured by Moral Injury Event Scale (MIES) and PTSD symptoms are differentially related to spontaneous fluctuations indexed by amplitude of low frequency fluctuation (ALFF) as well as functional connectivity during resting-state functional magnetic resonance imaging scanning. ALFF in the left inferior parietal lobule (L-IPL) was positively associated with MIES subscores of transgressions, negatively associated with subscores of betrayals, and not related with PTSD symptoms. Moreover, functional connectivity between the L-IPL and bilateral precuneus was positively related with PTSD symptoms and negatively related with MIES total scores. Our results provide the first evidence that morally injurious events and PTSD symptoms have dissociable neural underpinnings, and behaviorally distinct subcomponents of morally injurious events are different in neural responses. The findings increase our knowledge of the neural distinctions between moral injury and PTSD and may contribute to developing nosology and interventions for military veterans afflicted by moral injury.

Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder

BACKGROUND AND PURPOSE

Posttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here, we used a novel machine learning method - evolving partitions to improve classification (EPIC) - to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat-exposed military veterans.

METHODS

We used EPIC with repeated cross-validation (CV) to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (n = 40) versus controls (n = 57), and classification of ELS within the PTSD (ELS+ n = 16; ELS- n = 24) and control groups (ELS+ n = 16; ELS- n = 41). Additional inputs included intracranial volume, age, sex, adult trauma, and depression.

RESULTS

On average, EPIC classified PTSD with 69% accuracy (SD = 5%), and ELS with 64% accuracy in the PTSD group (SD = 10%), and 62% accuracy in controls (SD = 6%). EPIC selected unique sets of individual features that classified each group with 75-85% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas-defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS.

CONCLUSIONS

EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat-exposed military veterans, which may represent distinct biotypes of stress-related neuropathology.

Smaller hippocampal CA1 subfield volume in posttraumatic stress disorder

BACKGROUND

Smaller hippocampal volume in patients with posttraumatic stress disorder (PTSD) represents the most consistently reported structural alteration in the brain. Subfields of the hippocampus play distinct roles in encoding and processing of memories, which are disrupted in PTSD. We examined PTSD-associated alterations in 12 hippocampal subfields in relation to global hippocampal shape, and clinical features.

METHODS

Case-control cross-sectional studies of U.S. military veterans (n = 282) from the Iraq and Afghanistan era were grouped into PTSD (n = 142) and trauma-exposed controls (n = 140). Participants underwent clinical evaluation for PTSD and associated clinical parameters followed by MRI at 3 T. Segmentation with FreeSurfer v6.0 produced hippocampal subfield volumes for the left and right CA1, CA3, CA4, DG, fimbria, fissure, hippocampus-amygdala transition area, molecular layer, parasubiculum, presubiculum, subiculum, and tail, as well as hippocampal meshes. Covariates included age, gender, trauma exposure, alcohol use, depressive symptoms, antidepressant medication use, total hippocampal volume, and MRI scanner model.

RESULTS

Significantly lower subfield volumes were associated with PTSD in left CA1 (P = 0.01; d = 0.21; uncorrected), CA3 (P = 0.04; d = 0.08; uncorrected), and right CA3 (P = 0.02; d = 0.07; uncorrected) only if ipsilateral whole hippocampal volume was included as a covariate. A trend level association of L-CA1 with PTSD (F_{4, 221}  = 3.32, P = 0.07) is present and the other subfield findings are nonsignificant if ipsilateral whole hippocampal volume is not included as a covariate. PTSD-associated differences in global hippocampal shape were nonsignificant.

CONCLUSIONS

The present finding of smaller hippocampal CA1 in PTSD is consistent with model systems in rodents that exhibit increased anxiety-like behavior from repeated exposure to acute stress. Behavioral correlations with hippocampal subfield volume differences in PTSD will elucidate their relevance to PTSD, particularly behaviors of associative fear learning, extinction training, and formation of false memories.

White matter abnormalities in mild traumatic brain injury with and without post-traumatic stress disorder: a subject-specific diffusion tensor imaging study

Mild traumatic brain injuries (mTBIs) are often associated with posttraumatic stress disorder (PTSD). In cases of chronic mTBI, accurate diagnosis can be challenging due to the overlapping symptoms this condition shares with PTSD. Furthermore, mTBIs are heterogeneous and not easily observed using conventional neuroimaging tools, despite the fact that diffuse axonal injuries are the most common injury. Diffusion tensor imaging (DTI) is sensitive to diffuse axonal injuries and is thus more likely to detect mTBIs, especially when analyses account for the inter-individual variability of these injuries. Using a subject-specific approach, we compared fractional anisotropy (FA) abnormalities between groups with a history of mTBI (n = 35), comorbid mTBI and PTSD (mTBI + PTSD; n = 22), and healthy controls (n = 37). We compared all three groups on the number of abnormal FA clusters derived from subject-specific injury profiles (i.e., individual z-score maps) along a common white matter skeleton. The mTBI + PTSD group evinced a greater number of abnormally low FA clusters relative to both the healthy controls and the mTBI group without PTSD (p < .05). Across the groups with a history of mTBI, increased numbers of abnormally low FA clusters were significantly associated with PTSD symptom severity, depression, post-concussion symptoms, and reduced information processing speed (p < .05). These findings highlight the utility of subject-specific microstructural analyses when searching for mTBI-related brain abnormalities, particularly in patients with PTSD. This study also suggests that patients with a history of mTBI and comorbid PTSD, relative to those without PTSD, are at increased risk of FA abnormalities.

Genomic Approaches to Posttraumatic Stress Disorder: The Psychiatric Genomic Consortium Initiative

Posttraumatic stress disorder (PTSD) after exposure to a traumatic event is a highly prevalent psychiatric disorder. Heritability estimates from twin studies as well as from recent molecular data (single nucleotide polymorphism-based heritability) indicate moderate to high heritability, yet robust genetic variants for PTSD have not yet been identified and the genetic architecture of this polygenic disorder remains largely unknown. To date, fewer than 10 large-scale genome-wide association studies of PTSD have been published, with findings that highlight the unique challenges for PTSD genomics, including a complex diagnostic entity with contingency of PTSD diagnosis on trauma exposure and the large genetic diversity of the study populations. The Psychiatric Genomics Consortium PTSD group has brought together more than 200 scientists with the goal to increase sample size for genome-wide association studies and other genomic analyses to sufficient numbers where robust discoveries of molecular signatures can be achieved. The sample currently includes more than 32,000 PTSD cases and 100,000 trauma-exposed control subjects, and collection is ongoing. The first results found a significant shared genetic risk of PTSD with other psychiatric disorders and sex-biased heritability estimates with higher heritability in female individuals compared with male individuals. This review describes the scope and current focus of the Psychiatric Genomics Consortium PTSD group and its expansion from the initial genome-wide association study group to nine working groups, including epigenetics, gene expression, imaging, and integrative systems biology. We further briefly outline recent findings and future directions of "omics"-based studies of PTSD, with the ultimate goal of elucidating the molecular architecture of this complex disorder to improve prevention and intervention strategies.