Abstract
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 3,049 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 1,446 individuals with PTSD and 1,603 controls (2152 males/897 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=−0.12, p=0.0021). The tapetum connects the left and right hippocampus, structures for which structure and function have been consistently implicated in PTSD. Results remained significant/similar 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.
Introduction
Posttraumatic stress disorder (PTSD) is a debilitating mental health condition with a lifetime prevalence varying globally between 1-9%1, with higher rates in women. Rates of PTSD are higher in populations exposed to greater levels of trauma, such as combat veterans2 and civilians in conflict zones3. In addition to trauma type, genetics, and other sociological, psychological, and biological factors, individual differences in brain structure and function may explain vulnerability to developing PTSD following exposure to trauma, may result from trauma, or may be exacerbated by PTSD4. Diffusion MRI (dMRI) is able to model white matter tracts and assess microstructural organization5. Fractional anisotropy (FA) is the most commonly used metric of microstructural organization, reflecting the degree to which water is diffusing along the axon (axially) as compared with across it (radially). Greater FA can reflect higher myelination, axonal diameter, or fiber density. Mean diffusivity (MD) reflects the average magnitude of diffusion across all directions, axial diffusivity (AD) is diffusion along the primary eigenvector (the dominant fiber direction), and radial diffusivity (RD) estimates diffusion perpendicular to the primary eigenvector. Altered microstructural organization is associated with several different psychiatric disorders and could constitute a risk factor and/or a consequence of the disorders.
There is a lack of mechanistic evidence on the effects of stress and trauma on white matter structure. Exposure to trauma could lead to white matter damage, as excessive glucocorticoid levels can be neurotoxic and can impact myelination6,7. Studies of white matter microstructure in PTSD have reported inconsistent results. The majority report that PTSD is associated with lower FA8–24, but some report higher FA25–31, higher and lower FA in different regions32, or null results33–35. Alterations in the cingulum bundle are frequently reported9–13,16,18,21,23–29,31,32,36, with differences also observed in the uncinate, corpus callosum, and corona radiata14,16,18,19,24,26,29. Inconsistent findings may be partially due to the use of hypothesis-driven rather than whole brain approaches, choice of analytic pipeline, selection of diffusion metrics, gender-specific studies, homogeneity of single cohort samples such as trauma-exposed vs. unexposed controls, and focus on military vs. civilian samples.
The PGC-ENIGMA PTSD working group is an international collaborative effort of the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium that aims to increase statistical power through meta- and mega-analyses of PTSD neuroimaging biomarkers. This collaborative approach has led to the largest PTSD neuroimaging study to date, reporting smaller hippocampal volume in PTSD37. Here, we applied this approach to investigate the microstructural organization of white matter in PTSD. The ENIGMA DTI workflow38, which has successfully identified white matter compromise in schizophrenia39, bipolar disorder40, major depression41, and 22q11.2 deletion syndrome42, among others, was used by 28 cohorts to process their DTI data locally. We hypothesized the largest effects of compromised microstructure will be evident in the fronto-limbic tracts, such as the cingulum, uncinate, fornix, and corpus callosum; these tracts are strongly implicated in behavioral deficits of PTSD such as emotion regulation, working memory, and episodic memory10,16,19,20,24,43.
Materials and Methods
Study Samples
The PGC-ENIGMA PTSD DTI analysis included 28 cohorts from 7 countries totaling 1,603 healthy controls and 1,446 individuals with PTSD (either formally diagnosed or with CAPS-4>40, see Supplementary Figure 1). The age range across cohorts was 18-83 years; all but two older Vietnam era cohorts had an average age between 29-50. Of the 3,049 participants included in these analyses, 2,073 (68%) were from military cohorts, which resulted in a disproportionate number of males (70%). The majority of cohorts included trauma-exposed controls (e.g., combat, community violence, intimate partner violence, N=1,603), although some included trauma-unexposed controls (N=122), and one included no control group. Table 1 contains demographic and clinical information for each cohort. All participants provided written informed consent approved by local institutional review boards. Quality control was completed by each site, with visual quality checking and outlier detection. Details on ENIGMA-DTI methods39, inclusion/exclusion criteria, and clinical information may be found in Supplementary Note 1, Supplementary Table 1, and Supplementary Note 2, respectively.
Image Acquisition and Processing
The acquisition parameters for each cohort are provided in Supplementary Table 2. Preprocessing, including eddy current correction, echo-planar imaging-induced distortion correction and tensor fitting, was carried out at each site. Recommended protocols and quality control procedures are available on the ENIGMA-DTI and NITRC (Neuroimaging Informatics Tools and Resources Clearinghouse) webpages. Harmonization of preprocessing schemes was not enforced across sites to accommodate site- and acquisition-specific pipelines. Once tensors were estimated, they were mapped to the ENIGMA DTI template and projected onto the ENIGMA-DTI template and were averaged within ROIs (http://enigma.ini.usc.edu/protocols/dti-protocols/). Further details and ROI abbreviations can be seen in Supplementary Note 1.
Statistical Analysis
For each cohort/study, a linear model was fit using the ppcor and matrixStats packages in R 3.1.3, with the ROI FA as the response variable and PTSD and covariates as predictors. For cohorts/studies including more than one data collection site, site was included as a fixed dummy variable in the site-level analysis. As in prior ENIGMA disease working group meta-analyses39, a random-effects inverse-variance weighted meta-analysis was conducted at a central coordinating site (the University of Southern California Imaging Genetics Center) in R (metafor package, version 1.99– 118 http://www.metafor-project.org/) to combine individual cohort estimated effect sizes (see Figure 2). Cohen’s d for the main effect of group and unstandardized β coefficients (regression parameters) for continuous predictors were computed with 95% confidence intervals. We used the Cohen’s d calculation that accounts for covariates in the fixed effects model, using the following equation:
Heterogeneity scores (I2) for each test were computed, indicating the percent of total variance in effect size explained by heterogeneity across cohorts. Bilaterally averaged FA was the primary imaging measure, with corresponding MD, RD, and AD examined post hoc when FA was significant for an effect of diagnosis. Lateralized ROIs were examined post hoc when a significant association was found with the bilateral average. The corticospinal tract was not analyzed as it has poor reliability38. A conservative Bonferroni correction was used for multiple testing (p<0.05/24=0.0021; 18 bilateral ROIs, 5 midline ROIs, average FA). Non-linear age term: We first conducted analyses to examine whether a non-linear age term should be included in statistical models along with age and sex, as age has a non-linear effect on FA44. As this analysis did reveal a significant effect of non-linear age above and beyond linear age, age2 was included in all subsequent analyses. Primary – group comparison: We compared PTSD cases to all controls (both trauma-exposed and unexposed), PTSD cases to trauma-exposed controls only, and trauma-exposed to trauma un-exposed controls. Secondary – subgroups: We examined PTSD associations in males and females separately, and in military and civilian samples separately. These results may be found in Supplementary Note 3. Secondary – interactions: We examined potential interactions between PTSD and age or sex. These results can be seen in Supplementary Note 4. Secondary – additional covariates: We tested a model including ancestry, but as this was a meta-analysis and most cohorts were primarily composed of participants of white non-Hispanic descent, this had a very minimal impact, and we did not include this variable as a covariate in our analysis. We examined the impact of five potentially confounding covariates on the associations of PTSD with FA – childhood trauma, depression, alcohol dependence/abuse, traumatic brain injury (TBI, of any severity), and use of psychotropic medications. We compared the white matter microstructure of individuals with PTSD to that of controls with each covariate included individually in the model, and in the subset of sites that collected data on childhood trauma, depression, alcohol use disorders, TBI, or medication without that covariate in the model to determine whether differences in results were due to the inclusion of the covariate or the reduction in sample size. There were not enough participants with all five variables to simultaneously model these potential confounds in a single model. Details of these methods and results are provided in Supplementary Note 5. Briefly, binary variables were created for depression, TBI, and medication use. As depression was assessed using a variety of measures, we used published cut-offs to recode the data as categorical depression (see Supplementary Note 2 for more details). Alcohol use disorders and childhood trauma were coded as three-level ordinal variables based on evidence of dose-dependent effects on brain structure and clinical severity, respectively45,46: Alcohol use disorders: 0=no alcohol use disorder, 1=alcohol abuse, 2=alcohol dependence, as measured by the SCID or AUDIT47; childhood trauma (as measured by the Childhood Trauma Questionnaire): 0=no reported childhood trauma, 1=one type of childhood trauma exposure, 2=two or more types of childhood trauma exposure; PTSD severity: To examine PTSD severity, we conducted linear regressions on CAPS-4 score in the PTSD group for sites that collected CAPS-4. We examined linear associations with CAPS-4 score covarying for childhood trauma, depression, alcohol use disorders, TBI, and medication use, and we tested associations with CAPS-4 separately in military veterans and civilians as well as males and females (see Supplementary Note 5 for more details).
Results
Group differences
We found significantly lower FA in the PTSD group in the tapetum of the corpus callosum (d= −0.12, p=0.0021) when comparing PTSD (n=1,397) and all controls (n=1,603). Post hoc analysis revealed a larger effect in the left than in the right tapetum (left d=−0.14, p=0.00040; right d=−0.080, p=0.038). Post hoc analysis also revealed higher RD in the tapetum in the PTSD group (bilateral d=0.10, p=0.0085; left d=0.12, p=0.0016).
In the analysis comparing participants with PTSD (n=1,339) to trauma-exposed controls (n=1,481), we found lower FA and higher RD in the tapetum in PTSD, although the bilateral tapetum was marginally significant (FA: bilateral d=−0.11, p=0.0044; left d=−0.14, p=0.00065; RD: bilateral d=0.090, p=0.027; left d=0.12, p=0.0026) (see Table 2 and Figure 1, and see Figure 2 for site-specific effects). PTSD participants from cohorts that only included trauma-unexposed controls were not included.
Comparing trauma-exposed (n=200) to trauma un-exposed controls (n=93) from 6 sites, we found marginally lower FA in exposed controls in the tapetum, splenium of corpus callosum, and fornix/stria-terminalis (d=−0.41, p=0.014; d=−0.48, p=0.0042; d=−0.36, p=0.019, respectively), along with significantly higher MD and RD in the splenium (d=0.48, p=0.0017; d=0.56, p=0.00023, respectively) and marginally higher RD in the tapetum (d=0.32, p=0.036).
Subgroups
We examined military vs. civilian cohorts, and male vs. female participants separately. All subgroups showed non-significant associations with PTSD, but there were marginal associations with tapetum FA in the military-only and male-only subgroups separately (see Supplementary Note 3 and Supplementary Figure 3 for more details). Results of group-by-sex and group-by-age interactions were not significant and are shown in Supplementary Note 4 and Supplementary Figure 4.
Additional Covariates
The role of potentially confounding variables on the association between PTSD and the tapetum was tested in several post hoc analyses focused on left, right, and bilateral tapetum FA (see Supplementary Figure 2). As these analyses were considered post hoc and limited to the tapetum, we used a test-wise significance threshold of p<0.05. Results generally remained significant across all models. Including dichotomous depression as a covariate (696 PTSD vs. 825 controls) resulted in lower left tapetum FA in the PTSD group (left d=−0.15, p=0.0090) and borderline lower bilateral tapetum FA (d=−0.11, p=0.090). Including AUD as a covariate (691 PTSD vs. 623 controls) resulted in lower bilateral and left tapetum FA in the PTSD group (bilateral d=−0.14, p=0.012; left d=−0.16, p=0.0061) and borderline lower right tapetum FA (d=−0.10, p=0.066). Including a binary TBI variable (849 PTSD vs. 1,016 controls) resulted in lower left tapetum FA (d=−0.12, p=0.015). Including a dichotomous psychotropic medication covariate (713 PTSD vs. 679 controls) resulted in lower bilateral and left tapetum FA in the PTSD group (bilateral d=−0.11, p=0.050; left d=−0.014, p=0.013). Including childhood trauma as a covariate (367 PTSD vs. 598 controls) did not yield any significant results, but neither did the analysis in the reduced sample, suggesting that the sample reduction impacted these results. To control for covariate- and cohort-dependent changes in sample size, each analysis was repeated in a smaller sample that corresponded to omitting the relevant covariate. The tapetum results remained consistent in nearly all reduced sample analyses – significant effects survived covariate adjustment and effects that disappeared (such as with childhood trauma) were also absent in the reduced sample. Thus, covariates had minimal impact beyond the reduction in sample size (see Supplementary Note 5 and Supplementary Figures 5–9). A table showing how many participants at each site had information on these potentially confounding variables may be found in Supplementary Table 3.
PTSD Severity
PTSD symptom severity in the PTSD group (measured by the CAPS-4, N=979 from 18 sites) was not associated with FA (Figure 3). Subgroup analyses yielded marginal associations between CAPS-4 score and tapetum FA in the military cohorts, but no other subgroup. Results were similar when potentially confounding variables were included, with no significant associations, although the tapetum was marginally significant when psychotropic medication use was included. Detailed analyses of PTSD severity and covariates within subgroups are in Supplementary Note 5 and Supplementary Figures 10 and 11.
Discussion
We present DTI results from a multi-cohort study conducted by the PGC-ENIGMA PTSD consortium. In a meta-analysis of 3,049 participants from 28 sites, we found lower FA and higher RD in the tapetum among adults with PTSD (neuroanatomical figure – Supplementary Figure 12), which remained after accounting for several potentially confounding factors. The tapetum is a major tract within the corpus callosum that serves as a conduit between right and left hippocampus. Prior studies of white matter disruption in PTSD have found alterations in other hippocampal tracts, but were generally hindered by small sample sizes leading to inconsistent findings across studies. Our results add to the existing literature in identifying structural disruptions that compromise putative hippocampal functions, which are known to play a central role in PTSD symptomatology48,49. The tapetum is a segment of the corpus callosum that connects the temporal lobes, in particular the left and right hippocampus50. It is one of the last corpus callosum segments to develop and experiences rapid growth around age 14, which may make it vulnerable to the effects of trauma for a longer period of time51. Along with the inferior longitudinal fasciculus, cingulum, fornix, spino-limbic tracts (not studied here), and the anterior commissure, the tapetum is a dominant hippocampal pathway50. Structural and functional alterations in the hippocampus are frequently reported in PTSD, with smaller volumes37, decreased activation, and disrupted functional connectivity with the medial and lateral prefrontal cortices52,53. Here we report microstructural evidence that structural connectivity between the left and right hippocampus may also be disrupted in PTSD. While many studies have reported that PTSD is associated with alterations in the cingulum bundle9–13,16,18,21,23–29,31,32,36, which has a hippocampal component, the tapetum has not yet emerged for several possible reasons. Many prior studies took an ROI approach, which limited analyses to pre-determined regions that frequently omitted the tapetum, a small region often grouped with other tracts such as the splenium or posterior thalamic radiation. Critically, in 2013, an error was uncovered in the JHU atlas used as part of the TBSS pipeline, with the uncinate incorrectly identified as the inferior fronto-occipital fasciculus, and the tapetum incorrectly identified as the uncinate54. Thus, the tapetum was simply not examined in prior studies, with one very recent exception showing that tapetum abnormalities are associated with lower major depressive disorder remission55. Finally, the precise role of the tapetum in connecting the left and right hippocampus was only recently elucidated by mapping the subcortical connectome with exquisitely high-resolution mapping capable of discerning the intermingling of tapetum and other corpus callosum fibers. Super-resolution DTI conducted by the Chronic Diseases Connectome Project that acquired 1150-direction single-subject and 391-direction 94-subject data made this ultra-structural mapping possible50.
Childhood trauma is the greatest single risk factor for future vulnerability to PTSD56; numerous studies show significant alterations in brain structure and function in individuals who had experienced significant early life stress46,57. Some of these alterations likely contribute to a higher risk for psychopathology, but childhood trauma exposure did not explain the association between tapetum white matter disruption and PTSD that we report here. Depression is frequently comorbid with PTSD58 and is associated with disrupted white matter organization, although the affected tracts are broadly distributed59. Accounting for depression in group comparisons did not significantly alter our results, suggesting that tapetum white matter disruption is specific to PTSD. Particularly in military populations, which formed the majority of our sample, PTSD is often comorbid with traumatic brain injury (TBI)60. White matter is particularly vulnerable to TBI, which produces stretching and shearing of axons and altered neurometabolism61. Accounting for TBI also did not significantly change our results, indicating that TBI was associated with white matter damage generally, but not specifically within the tapetum. Psychotropic medications are another potential confound, given their neurotrophic and neuroprotective effects62. The result in the tapetum persisted after covarying for psychotropic medication, indicating that our findings are unlikely to be explained by medication. Lastly, PTSD can be comorbid with alcohol use disorders, which have a poorer clinical prognosis63,64. alcohol use disorders have been associated with significant changes in white matter organization65,66 but did not influence the present results.
We found a marginally significant association of PTSD with FA in the tapetum in male and military subgroups separately. Although results were non-significant in female or civilian subgroups, the effect size was slightly larger and in the same direction. The female and civilian subgroups were smaller and therefore the analyses had lower power than in male and military subgroups. Most prior dMRI studies in civilians report lower FA in PTSD9,10,12–14,16,17,21–25,30–32,67. Studies of military cohorts have been mixed, reporting higher FA26–29,36, lower FA8,15,18–20, and null results33–35. This discrepancy may be due to differences in age, chronicity, and type of trauma exposure, although military personnel often also experience civilian trauma. Combat-related PTSD is often comorbid with TBI, which is also associated with white matter disruption, constituting a potentially confounding factor for studies68.
In the absence of longitudinal data, our analysis cannot make causal inferences about the direction of the relationship between PTSD and tapetum white matter organization. Disrupted white matter of the tapetum may represent a vulnerability that predates the onset of PTSD, or a pathological response to trauma. In twins discordant for exposure to combat stress, the unexposed twins of combat veterans with PTSD have smaller hippocampal volume than the unexposed twins of combat veterans without PTSD69. Individuals with two risk alleles of the FKBP5 gene have demonstrated lower cingulum FA above and beyond the association of cingulum FA with PTSD11,67. These studies suggest that heritable differences in brain structure may influence risk of developing PTSD. Evidence that alterations are caused by PTSD was observed in Israeli Defense Force recruits with reduced structural connectivity between the hippocampus and ventromedial prefrontal cortex, but only after exposure to military stress70. With the varying developmental trajectories of brain structure, function, and connectivity, along with the varying distribution of stress hormone receptors in the brain, the complex question of vulnerability vs. consequence will require prospective longitudinal neuroimaging studies.
Some evidence indicates that high FA is a marker of resilience to the effects of stress71,72. A putative marker of resilience is the ability to attenuate stress-induced increases in corticotropinreleasing hormone and glucocorticoids through an elaborate negative feedback system, and to modulate the expression of brain-derived neurotrophic factor (BDNF)73,74. BDNF has myriad functions including supporting neuronal differentiation, maturation, and survival75,76. In particular, hippocampal BDNF is implicated in the development of neural circuits that promote stress adaptations73. These stress adaptation circuits involve white matter in the fornix and other fronto-limbic connections77.
Limitations
Our study has several limitations. One limitation of TBSS studies is the inability to fully attribute results to particular fiber bundles. Future studies may benefit by using tractography to more reliably identify the affected bundles, but this is difficult across so many varied sites. Second, not all participants classified as PTSD received clinician-administered interview (such as the CAPS) to confirm diagnoses. Third, we could not reliably measure chronicity across different cohorts. Other variables that we could not examine given the heterogeneity across sites include treatment effects, symptom clusters, trauma types, and lifetime as opposed to current PTSD diagnosis. Although we analyzed data from over 3,000 participants, we may have been underpowered to examine group-by-sex interactions, as 55% of our sample came from cohorts including only males or only females or samples that were >90% male. Diffusion metrics are not scanner invariant, and can vary even in scanners of the same model. For this reason, we were limited to a meta-analytic approach which may have lower power than mega-analysis. However, studies including both meta- and mega-analyses of brain volume in other ENIGMA groups have found minimal differences78,79.
Future studies should further investigate the tapetum using high spatial and angular resolution tractography to replicate our findings. Future and existing studies with more in-depth phenotyping than was possible here could examine how alterations in the tapetum vary with trauma type, chronicity, treatment, and whether they are associated with specific symptom clusters. The current study excluded pediatric cases, so additional research on white matter disruption in pediatric trauma and PTSD is warranted. Lastly, while we considered comorbidities as potential confounding variables, we did not examine their association with dMRI metrics. Future collaborations with the ENIGMA Brain Injury, MDD, and Addiction working groups will provide opportunities to separate general neuroimaging biomarkers of psychopathology and disorder-specific effects.
Conclusions
Here we presented results from the PGC-ENIGMA PTSD working group, reporting poorer white matter organization in the tapetum in individuals currently suffering from PTSD. We present the largest DTI study in PTSD to date and the first to use harmonized image processing across sites, increasing our power to detect subtle effects. While future studies need to confirm the involvement of the tapetum specifically, our results add to the existing literature implicating the hippocampus as a primary area of disruption in PTSD.
Conflicts of interest
Dr. Abdallah has served as a consultant, speaker and/or on advisory boards for FSV7, Lundbeck, Genentech and Janssen, and editor of Chronic Stress for Sage Publications, Inc.; he has filed a patent for using mTOR inhibitors to augment the effects of antidepressants (filed on August 20, 2018). Dr. Davidson is the founder and president of, and serves on the board of directors for, the non-profit organization Healthy Minds Innovations, Inc. Dr. Krystal is a consultant for AbbVie, Inc., Amgen, Astellas Pharma Global Development, Inc., AstraZeneca Pharmaceuticals, Biomedisyn Corporation, Bristol-Myers Squibb, Eli Lilly and Company, Euthymics Bioscience, Inc., Neurovance, Inc., FORUM Pharmaceuticals, Janssen Research & Development, Lundbeck Research USA, Novartis Pharma AG, Otsuka America Pharmaceutical, Inc., Sage Therapeutics, Inc., Sunovion Pharmaceuticals, Inc., and Takeda Industries; is on the Scientific Advisory Board for Lohocla Research Corporation, Mnemosyne Pharmaceuticals, Inc., Naurex, Inc., and Pfizer; is a stockholder in Biohaven Pharmaceuticals; holds stock options in Mnemosyne Pharmaceuticals, Inc.; holds patents for Dopamine and Noradrenergic Reuptake Inhibitors in Treatment of Schizophrenia, US Patent No. 5,447,948 (issued September 5, 1995), and Glutamate Modulating Agents in the Treatment of Mental Disorders, U.S. Patent No. 8,778,979 (issued July 15, 2014); and filed a patent for Intranasal Administration of Ketamine to Treat Depression. U.S. Application No. 14/197,767 (filed on March 5, 2014); US application or Patent Cooperation Treaty international application No. 14/306,382 (filed on June 17, 2014). Filed a patent for using mTOR inhibitors to augment the effects of antidepressants (filed on August 20, 2018). Dr. Jahanshad received partial research support from Biogen, Inc. (Boston, USA) for research unrelated to the content of this manuscript. Dr. Thompson received partial research support from Biogen, Inc. (Boston, USA) for research unrelated to the topic of this manuscript. All other authors report no conflicts of interest.
Acknowledgements
K99NS096116 to Dr. Emily Dennis; CIHR, CIMVHR; Dana Foundation (to Dr. Nitschke); the University of Wisconsin Institute for Clinical and Translational Research (to Dr. Emma Seppala); a National Science Foundation Graduate Research Fellowship (to Dr. Daniel Grupe); R01MH043454 and T32MH018931 (to Dr. Richard Davidson); and a core grant to the Waisman Center from the National Institute of Child Health and Human Development (P30HD003352); Defense and Veterans Brain Injury Centers, the U.S. Army Medical Research and Materiel Command (USAMRMC; W81XWH-13-2-0025) and the Chronic Effects of Neurotrauma Consortium (CENC; PT108802-SC104835); Department of Defense award number W81XWH-12-2-0012; ENIGMA was also supported in part by NIH U54EB020403 from the Big Data to Knowledge (BD2K) program, R56AG058854, R01MH116147, R01MH111671, and P41EB015922 to Dr. Paul Thompson and Dr. Neda Jahanshad; Department of Veterans Affairs via support for the National Center for PTSD, NIAAA via its support for (P50) Center for the Translational Neuroscience of Alcohol, and NCATS via its support of (CTSA) Yale Center for Clinical Investigation; DoD W81XWH-10-1-0925; Center for Brain and Behavior Research Pilot Grant; South Dakota Governor’s Research Center Grant; F32MH109274; Funding from the Bill & Melinda Gates Foundation; Funding from the SAMRC Unit on Risk & Resilience in Mental Disorders; German Research Foundation grant to J. K. Daniels (numbers DA 1222/4-1 and WA 1539/8-2); German Research Society (Deutsche Forschungsgemeinschaft, DFG; SFB/TRR 58: C06, C07); I01-CX000715 & I01-CX001542; K01MH118428; K23MH090366; K2CX001772, Clinical Science Research and Development Service, VA Office of Research and Development; MH098212; MH071537; M01RR00039; UL1TR000454; HD071982; HD085850; MH101380; NARSAD 27040; NARSAD Young Investigator, K01MH109836, Young Investigator Grant, Korean Scientists and Engineers Association; NHMRC Program Grant # 1073041; R01AG050595, R01AG022381; R01AG058822; R01EB015611; R01MH105355; R01MH105355, R01DA035484; R01MH111671, R01MH117601, R01AG059874, MJFF 14848; R01MH111671; VISN6 MIRECC; R21MH112956, Anonymous Women’s Health Fund, Kasparian Fund, Trauma Scholars Fund, Barlow Family Fund; South African Medical Research Council for the “Shared Roots” Flagship Project, Grant no. MRC-RFA-IFSP-01-2013/SHARED ROOTS” through funding received from the South African National Treasury under its Economic Competitiveness and Support Package. The work by Dr. Leigh van Heuvel reported herein was made possible through funding by the South African Medical Research Council through its Division of Research Capacity Development under the SAMRC Clinician Researcher (M.D PHD) Scholarship Programme from funding received from the South African National Treasury; South African Research Chairs Initiative in Posttraumatic Stress Disorder through the Department of Science and Technology and the National Research Foundation.; the National Natural Science Foundation of China (No. 31271099, 31471004), the Key Research Program of the Chinese Academy of Sciences (No. ZDRW-XH-2019-4); The study was supported by ZonMw, the Netherlands organization for Health Research and Development (40-00812-98-10041), and by a grant from the Academic Medical Center Research Council (110614) both awarded to Dr. Miranda Olff; Translational Research Center for TBI and Stress Disorders (TRACTS), a VA Rehabilitation Research and Development (RR&D) Traumatic Brain Injury Center of Excellence (B9254-C) at VA Boston Healthcare System; VA CSR&D 1IK2CX001680; VISN17 Center of Excellence Pilot funding; VA CSR&D 822-MR-18176 and Senior Career Scientist Award; VA National Center for PTSD; VA RR&D 1IK2RX000709; VA RR&D 1K1RX002325; 1K2RX002922; VA RR&D I01RX000622; CDMRP W81XWH-08–2–0038; W81XWH08-2-0159 to Dr. Murray Stein from the US Department of Defense. The views reflected here are strictly those of the authors and do not constitute endorsement by any of the funding sources listed here.