Chronic pain following traumatic stress exposure (TSE) is common. Increasing evidence suggests inflammatory and immune mechanisms are activated following TSE, play a role in the transition from acute to chronic pain, and may differ by sex. In this study, we tested the hypothesis that elevated levels of the inflammatory marker C-reactive protein (CRP) would be associated with acute and chronic pain in a sex-specific manner. We utilized blood-plasma samples and pain questionnaire data from men (n=116) and women (n=269) enrolled in AURORA, a multi-site emergency department (ED)-based longitudinal study of TSE survivors. CRP levels were measured by ELISA using plasma samples collected in the ED ('peritraumatic CRP') and six-months following TSE. Multivariate models were used to assess the relationship between CRP and pain. Men and women reported similar acute pain levels in the ED; however, pain resolved more rapidly in men over time. Peritraumatic CRP was not associated with acute pain severity in either men or women. However, six-month CRP levels were positively associated with six-month pain severity in both men (r=0.19, p=0.089, non-significant) and women (r=0.21, p=0.0015). In men only, higher peritraumatic CRP predicted lower chronic pain severity (β=-0.36, p=0.024) whereas no association was observed in women (β=0.04, p=0.628). Among men with elevated peritraumatic CRP, decreases in CRP over time were associated with decreases in pain over time (r=-0.38, p=0.0197). These findings suggest sex-specific relationships between CRP and chronic pain following TSE and highlight inflammation as a potential mechanism contributing to differential pain recovery trajectories in men and women. PERSPECTIVE: Longitudinal CRP levels following traumatic stress exposure showed sex-dependent associations with chronic pain outcomes. Unexpectedly, higher early CRP predicted lower chronic pain severity in men, suggesting inflammatory responses may differentially influence pain recovery trajectories in men and women.

Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts – model assumptions, identification, estimation, and diagnostics – while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

Childhood adversity is associated with susceptibility to posttraumatic stress disorder (PTSD) in adulthood. Both PTSD and adverse experiences in childhood are linked to disrupted white matter microstructure, yet the role of white matter as a potential neural mechanism connecting childhood adversity to PTSD remains unclear. The present study investigated the potential moderating role of previous childhood adversity on longitudinal changes in white matter microstructures and posttraumatic stress symptoms following a recent traumatic event in adulthood. As part of the AURORA Study, 114 recent trauma survivors completed diffusion weighted imaging at 2-weeks and 6-months after exposure. Participants reported on prior childhood adversity and PTSD symptoms at 2-weeks, 6-months, and 12-months post-trauma. We performed both region-of-interest (ROI) and whole-brain correlational tractography analyses to index associations between white matter microstructure changes and prior adversity. Whole-brain correlational tractography revealed that greater childhood adversity moderated the changes in quantitative anisotropy (QA) over time across threat and visual processing tracts including the cingulum bundle and inferior fronto-occipital fasciculus (IFOF). Further, QA changes within cingulum bundle, IFOF, and inferior longitudinal fasciculus were associated with changes in PTSD symptoms between 2-weeks and 6-months. Our findings suggest temporal variability in threat and visual white matter tracts may be a potential neural pathway through which childhood adversity confers risk to PTSD symptoms after adulthood trauma. Future studies should take the temporal properties of white matter into consideration to better understand the neurobiology of childhood adversity and PTSD.

Post-traumatic stress (PTS) symptoms are highly comorbid with substance use (i.e., alcohol, tobacco, and cannabis). Few studies have investigated potential individual-, household-, and neighborhood-level socioeconomic effect modifiers of this comorbidity in longitudinal analyses. We aim to examine interactions between this multi-level environment and PTS symptoms on future substance use behaviors. Data were drawn from the Advancing Understanding of RecOvery afteR traumA (AURORA) study, including 2943 individuals who presented to the emergency department (ED) within 72 h of a traumatic event. Frequency of tobacco, alcohol, cannabis use, and PTS symptoms were reported at 6 timepoints. Mixed effect Poisson models, clustered by state, were used to generate incidence rate ratios (IRRs) substance use, both cross-sectionally and prospectively. Moderation analysis of PTS and substance use, stratified by household income and area deprivation index (ADI), was conducted using mixed effect models and parallel process growth curves. Significant associations were observed between PTS with tobacco, alcohol, and cannabis use frequency cross-sectionally, and for tobacco and alcohol and PTS exposure prospectively. Lower income (P < 0.001) and higher deprivation (P < 0.001) were associated with tobacco use, while higher income (P < 0.001) and less deprivation (P = 0.01) were associated with increased alcohol use. We found modest modification by household income for alcohol and tobacco, and little evidence of modification by neighborhood ADI. Household income had greater evidence of effect modification for substance use, compared to neighborhood-level ADI. Our findings demonstrate that household indicators of socioeconomic status likely modify the relationship between PTS and substance use.

Over 100,000 women present for emergency care after sexual assault (SA) annually in the United States. To our knowledge, no large prospective studies have assessed SA survivor experiences with police. Women SA survivors enrolled at 13 sites (n = 706), and 630 survivors reported on their police interactions. Most women were interested in speaking with police, spoke with police, and reported positive experiences. Latinas and women with lower education and income were less likely to speak with police. Trauma and posttraumatic stress symptoms were associated with more negative experiences. Qualitative comments provide key points for police to consider when speaking with survivors.

This study examines the association between brain dynamic functional network connectivity (dFNC) and current/future posttraumatic stress (PTS) symptom severity, and the impact of sex on this relationship. By analyzing 275 participants' dFNC data obtained ~2 weeks after trauma exposure, we noted that brain dynamics of an inter-network brain state link negatively with current (r=-0.179, p corrected = 0.021) and future (r=-0.166, p corrected = 0.029) PTS symptom severity. Also, dynamics of an intra-network brain state correlated with future symptom intensity (r = 0.192, p corrected = 0.021). We additionally observed that the association between the network dynamics of the inter-network brain state with symptom severity is more pronounced in females (r=-0.244, p corrected = 0.014). Our findings highlight a potential link between brain network dynamics in the aftermath of trauma with current and future PTSD outcomes, with a stronger protective effect of inter-network brain states against symptom severity in females, underscoring the importance of sex differences.

BACKGROUND:Childhood adversity is associated with susceptibility to posttraumatic stress disorder (PTSD) in adulthood. PTSD and childhood adversity are linked to white matter microstructure, yet the role of white matter as a potential neural mechanism connecting childhood adversity to PTSD remains unclear. In the current study, we investigated the potential moderating role of previous childhood adversity on longitudinal changes in white matter microstructure and posttraumatic stress symptoms following a recent traumatic event in adulthood. METHODS:As part of the AURORA (Advancing Understanding of RecOvery afteR traumA) study, 114 recent trauma survivors completed diffusion-weighted imaging at 2 weeks and 6 months after exposure. Participants reported on prior childhood adversity and PTSD symptoms at 2 weeks, 6 months, and 12 months posttrauma. We performed region of interest (ROI) analysis using fractional anisotropy (FA) and whole-brain correlational tractography using quantitative anisotropy (QA) to index associations between white matter microstructure changes and prior adversity. RESULTS:ROI-based analyses did not identify significant associations between childhood adversity and changes in FA. Whole-brain correlational tractography revealed that greater childhood adversity moderated the QA changes within threat and visual processing tracts including the cingulum bundle and inferior fronto-occipital fasciculus (IFOF). QA changes within the cingulum bundle and IFOF were associated with changes in PTSD symptoms between 2 weeks and 6 months. CONCLUSIONS:Our findings suggest that temporal variability in threat and visual white matter tracts may be a potential neural pathway through which childhood adversity confers risk for PTSD symptoms after adulthood trauma. Future studies should take the temporal properties of white matter into consideration to better understand the neurobiology of childhood adversity and PTSD.

Language features may reflect underlying cognitive and emotional processes following a traumatic event that portend clinical outcomes. The authors sought to determine whether language features from usual smartphone use were markers associated with concurrent posttraumatic symptoms and worsening or improving posttraumatic symptoms over time following a traumatic exposure. This investigation was a secondary analysis of the Advancing Understanding of RecOvery afteR traumA study, a longitudinal study of traumatic outcomes among survivors recruited from 33 emergency departments across the United States. Adverse posttraumatic sequelae were assessed over the six months following the initial traumatic exposure. Language features were extracted from usual smartphone use in a specialized app. Bivariate linear mixed models were used to identify and validate language features that are markers associated with posttraumatic symptoms. Participants were 1744 trauma survivors, with a mean age of 39 [SD = 13] years old, and 56% were female. Fourteen language features were associated with severity level of posttraumatic symptoms at specific timepoints (cross-sectional markers) and five features were associated with change in severity level of posttraumatic symptoms (longitudinal markers). References to the body and health or illness were predictive of worsening pain, somatic, and thinking/concentration/fatigue symptom severity over time. An increase in references to others was associated with improvement in somatic symptom severity over time and increases in expressions of causation or cognitive processes were associated with improvement in pain symptom severity over time. Language features derived from usual smartphone use can convey important information about health, functioning, and recovery following a traumatic event. Clinicians might utilize such information to determine who may experience a high symptom burden or risk of worsening posttraumatic symptoms.

BACKGROUND:Posttraumatic stress disorder (PTSD) is a well-characterized psychiatric disorder that features changes in mood and arousal following traumatic events. Previous animal and human studies of social support during the peritraumatic window have demonstrated a buffering effect with regard to acute biological and psychological stress symptoms. Fewer studies have explored the magnitude of and mechanism through which early posttrauma social support can reduce longitudinal PTSD severity. METHODS:In this study, we investigated the beneficial impact of social support on longitudinal PTSD symptoms and probed brain regions sensitive to this buffering phenomenon, such as the amygdala and ventromedial prefrontal cortex. In the multisite AURORA study, 315 participants reported PTSD symptoms (PTSD Checklist for DSM-5) and perceived emotional support (Patient-Reported Outcomes Measurement Information System) at 2 weeks, 8 weeks, 3 months, and 6 months post emergency department visit. Additionally, neuroimaging data were collected at 2 weeks posttrauma. RESULTS:We hypothesized that early posttrauma social support would be linked with greater fractional anisotropic values in white matter tracts that have known connectivity between the amygdala and prefrontal cortex and would predict reduced neural reactivity to social threat cues in the amygdala. Interestingly, while we observed greater fractional anisotropy in the bilateral cingulum and bilateral uncinate fasciculus as a function of early posttrauma emotional support, we also identified greater threat reactivity in the precuneus/posterior cingulate, a component of the default mode network. CONCLUSIONS:Our findings suggest that the neurocircuitry underlying the response to social threat cues is facilitated through broader pathways that involve the posterior hub of the default mode network.

A barrier to research with sexual assault survivors is the concern that research participation might be a negative experience for participants. We report the experiences with research of adult women sexual assault survivors participating in a large-scale, multi-site, prospective observational study that enrolled participants at the time of presentation for emergency care. Participants (n = 706, M = 28 years of age; 57% white, 15% Black) self-reported their experience with research 1 week, 6 weeks, 6 months, and 1 year post-assault. The vast majority rated the research experience as positive (95-97%), reported no drawbacks (84-89%), and felt that participating was worth it (93-95%). Positive experiences with research remained stable across the year, were generally consistent across demographic and clinical groups, and were reflected in qualitative comments. Given the tremendous morbidity experienced by sexual assault survivors and lack of progress in developing improved treatments for this population, ethically-conducted research with sexual assault survivors receiving emergency care should be encouraged.

We present the R package MIIVefa, designed to implement the MIIV-EFA algorithm. This algorithm explores and identifies the underlying factor structure within a set of variables. The resulting model is not a typical exploratory factor analysis (EFA) model because some loadings are fixed to zero and it allows users to include hypothesized correlated errors such as might occur with longitudinal data. As such, it resembles a confirmatory factor analysis (CFA) model. But, unlike CFA, the MIIV-EFA algorithm determines the number of factors and the items that load on these factors directly from the data. We provide both simulation and empirical examples to illustrate the application of MIIVefa and discuss its benefits and limitations.

This study aims to develop and validate a brief bedside tool to screen women survivors presenting for emergency care following sexual assault for risk of persistent elevated posttraumatic stress symptoms (PTSS) six months after assault. Participants were 547 cisgender women sexual assault survivors who presented to one of 13 sexual assault nurse examiner (SANE) programs for medical care within 72 h of a sexual assault and completed surveys one week and six months after the assault. Data on 222 potential predictors from the SANE visit and the week one survey spanning seven broadly-defined risk factor domains were candidates for inclusion in the screening tool. Elevated PTSS six months after assault were defined as PCL-5 > 38. LASSO logistic regression was applied to 20 randomly selected bootstrapped samples to evaluate variable importance. Logistic regression models comprised of the top 10, 20, and 30 candidate predictors were tested in 10 cross-validation samples drawn from 80% of the sample. The resulting instrument was validated in the remaining 20% of the sample. AUC of the finalized eight-item prediction tool was 0.77 and the Brier Score was 0.19. A raw score of 41 on the screener corresponds to a 70% risk of elevated PTSS at 6 months. Similar performance was observed for elevated PTSS at one year. This brief, eight-item risk stratification tool consists of easy-to-collect information and, if validated, may be useful for clinical trial enrichment and/or patient screening.

BACKGROUND: Females are more likely to develop posttraumatic stress disorder (PTSD) than males. Impaired inhibition has been identified as a mechanism for PTSD development, but studies on potential sex differences in this neurobiological mechanism and how it relates to PTSD severity and progression are relatively rare. Here, we examined sex differences in neural activation during response inhibition and PTSD following recent trauma. METHODS: Participants ( n = 205, 138 female sex assigned at birth) were recruited from emergency departments within 72 hours of a traumatic event. PTSD symptoms were assessed 2 weeks and 6 months posttrauma. A Go/NoGo task was performed 2 weeks posttrauma in a 3T magnetic resonance imaging scanner to measure neural activity during response inhibition in the ventromedial prefrontal cortex, right inferior frontal gyrus, and bilateral hippocampus. General linear models were used to examine the interaction effect of sex on the relationship between our regions of interest and the whole brain, PTSD symptoms at 6 months, and symptom progression between 2 weeks and 6 months. RESULTS: Lower response inhibition-related ventromedial prefrontal cortex activation 2 weeks posttrauma predicted more PTSD symptoms at 6 months in females but not in males, while greater response inhibition-related right inferior frontal gyrus activation predicted lower PTSD symptom progression in males but not females. Whole-brain interaction effects were observed in the medial temporal gyrus and left precentral gyrus. CONCLUSIONS: There are sex differences in the relationship between inhibition-related brain activation and PTSD symptom severity and progression. These findings suggest that sex differences should be assessed in future PTSD studies and reveal potential targets for sex-specific interventions.

We used data from the Advancing Understanding of Recovery after Trauma (AURORA) study to investigate prospective links between five factor model and impulsive personality traits and PTSD symptoms at baseline (N = 2943), three-months post-trauma (N = 2400), and one-year post-trauma (N = 1591) in individuals recruited from emergency departments within 72 h of trauma exposure. Neuroticism and Negative Urgency bore the largest relations (rs > 0.30) to nearly all individual PTSD symptoms and symptom total at all time points. Neuroticism was an incremental predictor of every PTSD symptom at each time point. Low Agreeableness and low Conscientiousness were incremental predictors of several PTSD symptoms. These findings highlight personality assessment as an efficient, effective screening tool for PTSD risk.

Importance Research on resilience after trauma has often focused on individual-level factors (eg, ability to cope with adversity) and overlooked influential neighborhood-level factors that may help mitigate the development of posttraumatic stress disorder (PTSD). Objective To investigate whether an interaction between residential greenspace and self-reported individual resources was associated with a resilient PTSD trajectory (ie, low/no symptoms) and to test if the association between greenspace and PTSD trajectory was mediated by neural reactivity to reward. Design, Setting, and Participants As part of a longitudinal cohort study, trauma survivors were recruited from emergency departments across the US. Two weeks after trauma, a subset of participants underwent functional magnetic resonance imaging during a monetary reward task. Study data were analyzed from January to November 2023. Exposures Residential greenspace within a 100-m buffer of each participant's home address was derived from satellite imagery and quantified using the Normalized Difference Vegetation Index and perceived individual resources measured by the Connor-Davidson Resilience Scale (CD-RISC). Main Outcome and Measures PTSD symptom severity measured at 2 weeks, 8 weeks, 3 months, and 6 months after trauma. Neural responses to monetary reward in reward-related regions (ie, amygdala, nucleus accumbens, orbitofrontal cortex) was a secondary outcome. Covariates included both geocoded (eg, area deprivation index) and self-reported characteristics (eg, childhood maltreatment, income). Results In 2597 trauma survivors (mean [SD] age, 36.5 [13.4] years; 1637 female [63%]; 1304 non-Hispanic Black [50.2%], 289 Hispanic [11.1%], 901 non-Hispanic White [34.7%], 93 non-Hispanic other race [3.6%], and 10 missing/unreported [0.4%]), 6 PTSD trajectories (resilient, nonremitting high, nonremitting moderate, slow recovery, rapid recovery, delayed) were identified through latent-class mixed-effect modeling. Multinominal logistic regressions revealed that for individuals with higher CD-RISC scores, greenspace was associated with a greater likelihood of assignment in a resilient trajectory compared with nonremitting high (Wald z test = -3.92; P < .001), nonremitting moderate (Wald z test = -2.24; P = .03), or slow recovery (Wald z test = -2.27; P = .02) classes. Greenspace was also associated with greater neural reactivity to reward in the amygdala (n = 288; t(277) = 2.83; adjusted P value = 0.02); however, reward reactivity did not differ by PTSD trajectory. Conclusions and Relevance In this cohort study, greenspace and self-reported individual resources were significantly associated with PTSD trajectories. These findings suggest that factors at multiple ecological levels may contribute to the likelihood of resiliency to PTSD after trauma.

BackgroundPost-traumatic stress disorder (PTSD) and substance use (tobacco, alcohol, and cannabis) are highly comorbid. Many factors affect this relationship, including sociodemographic and psychosocial characteristics, other prior traumas, and physical health. However, few prior studies have investigated this prospectively, examining new substance use and the extent to which a wide range of factors may modify the relationship to PTSD.MethodsThe Advancing Understanding of RecOvery afteR traumA (AURORA) study is a prospective cohort of adults presenting at emergency departments (N = 2,943). Participants self-reported PTSD symptoms and the frequency and quantity of tobacco, alcohol, and cannabis use at six total timepoints. We assessed the associations of PTSD and future substance use, lagged by one timepoint, using the Poisson generalized estimating equations. We also stratified by incident and prevalent substance use and generated causal forests to identify the most important effect modifiers of this relationship out of 128 potential variables.ResultsAt baseline, 37.3% (N = 1,099) of participants reported likely PTSD. PTSD was associated with tobacco frequency (incidence rate ratio (IRR): 1.003, 95% CI: 1.00, 1.01, p = 0.02) and quantity (IRR: 1.01, 95% CI: 1.001, 1.01, p = 0.01), and alcohol frequency (IRR: 1.002, 95% CI: 1.00, 1.004, p = 0.03) and quantity (IRR: 1.003, 95% CI: 1.001, 1.01, p = 0.001), but not with cannabis use. There were slight differences in incident compared to prevalent tobacco frequency and quantity of use; prevalent tobacco frequency and quantity were associated with PTSD symptoms, while incident tobacco frequency and quantity were not. Using causal forests, lifetime worst use of cigarettes, overall self-rated physical health, and prior childhood trauma were major moderators of the relationship between PTSD symptoms and the three substances investigated.ConclusionPTSD symptoms were highly associated with tobacco and alcohol use, while the association with prospective cannabis use is not clear. Findings suggest that understanding the different risk stratification that occurs can aid in tailoring interventions to populations at greatest risk to best mitigate the comorbidity between PTSD symptoms and future substance use outcomes. We demonstrate that this is particularly salient for tobacco use and, to some extent, alcohol use, while cannabis is less likely to be impacted by PTSD symptoms across the strata.

Spearman (Am J Psychol 15(1):201–293, 1904. https://doi.org/10.2307/1412107 ) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.

Model-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, non-iterative estimator for latent variable models. Associated with this estimator are equation specific tests of model misspecification. One issue with equation specific tests is that they lack specificity, in that they indicate that some instruments are problematic without revealing which specific ones. Instruments that are poor predictors of their target variables (weak instruments) is a second potential problem. We propose a novel extension to detect instrument specific tests of misspecification and weak instruments. We term this the Model-Implied Instrumental Variable Two-Stage Bayesian Model Averaging (MIIV-2SBMA) estimator. We evaluate the performance of MIIV-2SBMA against MIIV-2SLS in a simulation study and show that it has comparable performance in terms of parameter estimation. Additionally, our instrument specific overidentification tests developed within the MIIV-2SBMA framework show increased power to detect specific problematic and weak instruments. Finally, we demonstrate MIIV-2SBMA using an empirical example.

Although resilience is a dynamic process of recovery after trauma, in most studies it is conceptualized as the absence of specific psychopathology following trauma. Here, using the emergency department AURORA study (n = 1,835 with 63% women), we took a longitudinal, dynamic and transdiagnostic approach to define a static resilience (r) factor, which could explain greater than 50% of variance in mental well-being 6 months following trauma and a dynamic resilience factor, which represented recovery from initial symptoms. We then assessed its neurobiological profile across threat, inhibition and reward processes using functional magnetic resonance imaging collected 2 weeks post-trauma (n = 260). Our whole-brain and study-wide Bonferroni-corrected results suggest that resilience is promoted by activation of regions involved in higher-level cognitive functioning, reward valuation and salience detection in response to reward, whereas resilience is hampered by posterior default mode network activation to threat and reward. These findings serve to generate new hypotheses for brain mechanisms that could promote dynamic and multifaceted components of resilience following trauma.

The neurocardiac circuit is integral to physiological regulation of threat and trauma-related responses. However, few direct investigations of brain-behavior associations with replicable physiological markers of PTSD have been conducted. The current study probed the neurocardiac circuit by examining associations among its core regions in the brain (e.g., insula, hypothalamus) and the periphery (heart rate [HR], high frequency heart rate variability [HF-HRV], and blood pressure [BP]). We sought to characterize these associations and to determine whether there were differences by PTSD status. Participants were N = 315 (64.1 % female) trauma-exposed adults enrolled from emergency departments as part of the prospective AURORA study. Participants completed a deep phenotyping session (e.g., fear conditioning, magnetic resonance imaging) two weeks after emergency department admission. Voxelwise analyses revealed several significant interactions between PTSD severity 8-weeks posttrauma and psychophysiological recordings on hypothalamic connectivity to the prefrontal cortex (PFC), insula, superior temporal sulcus, and temporoparietaloccipital junction. Among those with PTSD, diastolic BP was directly correlated with right insula-hypothalamic connectivity, whereas the reverse was found for those without PTSD. PTSD status moderated the association between systolic BP, HR, and HF-HRV and hypothalamic connectivity in the same direction. While preliminary, our findings may suggest that individuals with higher PTSD severity exhibit compensatory neural mechanisms to down-regulate autonomic imbalance. Additional study is warranted to determine how underlying mechanisms (e.g., inflammation) may disrupt the neurocardiac circuit and increase cardiometabolic disease risk in PTSD.