Jennifer A. Sumner

Posttraumatic stress disorder (PTSD) is associated with elevated cardiovascular disease (CVD) risk, but the extent of shared inherited liability is unclear. Large genome‐wide association studies (GWAS) allow for multivariate evaluation of common genetic architecture. We analyzed European‐ancestry GWAS summary statistics for PTSD ( N _eff ≈ 1.22 million), CVD outcomes (CVD _outcomes ; coronary artery disease, stroke, hypertension; N _eff = 126,000–574,000), and CVD risk factors (CVD _risk ; high‐density lipoprotein, triglycerides, fasting glucose, waist circumference; N = 211,000–526,000). Using genomic structural equation modeling, we modeled latent genetic structure across PTSD and CVD phenotypes and conducted multivariate GWAS of latent factors with gene and gene‐set annotation. A three‐factor model distinguishing PTSD, CVD _risk , and CVD _outcomes best fit the data, χ ² = 256.9, CFI = .990, SRMR = .040. PTSD showed a moderate genetic correlation with CVD _risk , rg = .340, p < .001, and a significant but negligible genetic correlation with CVD _outcomes , rg = 0.030, p < .001, suggesting minimal shared genetic liability at the latent‐factor level. Multivariate GWAS identified seven loci for PTSD, 96 for CVD _risk , and 51 for CVD _outcomes . Gene‐based tests implicated 85, 910, and 390 genes, respectively, with 18 overlapping between PTSD and CVD _risk . Enrichment highlighted RNA metabolism for PTSD and lipid/vascular pathways for CVD traits. Additional locus‐level overlaps emerged, including a genomic hub in the major histocompatibility complex region on Chromosome 6 for both phenotypes. PTSD shares moderate polygenic overlap with CVD, particularly CVD _risk , but many loci are trait‐specific, implicating lipid metabolism, vascular tone, immune/inflammatory pathways, and RNA regulation as potential links.

Background: There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, most research has specifically examined post‐traumatic stress disorder—despite evidence that a range of psychiatric disorders may follow trauma. We applied machine learning to identify key post‐traumatic psychiatric predictors of incident major adverse cardiac and cerebrovascular events (MACCE) in a population‐based cohort. Methods: We conducted a case–control study of adults aged ≥18 years, nested within a trauma‐exposed cohort of all Denmark residents from 1995 to 2018. Cases ( n =43 994) experienced MACCE (non‐fatal myocardial infarction, non‐fatal stroke, coronary revascularization, cardiovascular death) between 1995 and 2019. Controls ( n =175 872) were matched 4:1 on MACCE date, sex, year of trauma, and age at trauma. Machine learning model predictors included a range of psychiatric disorders diagnosed ≤3 years following trauma. Sex‐stratified machine learning models were trained using extreme gradient boosting (men: n =91 111; women: n =84 781) and tested in hold‐out datasets (men: n =22 777; women: n =21 197). We identified the 15 most important psychiatric disorder predictors of MACCE using Shapley Additive Explanations values. Results: For men and women, the most important psychiatric predictor of MACCE was alcohol use disorders. Other important psychiatric predictors included depressive disorders, post‐traumatic stress disorder/stress‐related disorders, brain‐related/physiological conditions, and non‐substance‐induced delirium. Some sex‐specific findings also emerged (eg, depressive episodes more important for women than men). Overall, odds ratios in training and testing sets indicated that odds of MACCE were greater among those with (versus without) psychiatric disorders. Conclusions: Results emphasize the importance of considering a range of psychiatric disorders when assessing cardiovascular risk following trauma.

Early life adversity (ELA), characterized by threat (experiences involving threat of harm), and not deprivation (absence of expected environmental inputs), has been associated with accelerated biological aging in youth. Although understanding of underlying processes is limited, heightened fear responding is a candidate. In 168 youth, we tested whether threat- and deprivation-related ELA were associated with fear responses across multiple levels of analysis and whether fear responses explained links of threat with accelerated biological aging (advanced pubertal stage and epigenetic age). Youth and caregivers reported on youths’ lifetime ELA experiences to compute threat and deprivation composites. Youth reported their pubertal maturation and provided saliva samples for epigenetic age estimation. Fear responses (indexed by skin conductance response [SCR], self-reported fear, and amygdala activation) were collected during a fear conditioning and extinction task (SCR, self-reported fear) and emotional stimulus viewing task (amygdala activation). Multilevel models revealed that greater threat was associated with impaired discrimination between danger and safety cues during conditioning based on self-report and during early extinction based on SCR. Greater deprivation related to enhanced danger-safety discrimination during late conditioning based on SCR. Additionally, only threat was associated with greater left amygdala activation to negative (vs. neutral) stimuli. No evidence of indirect effects was found linking threat with accelerated biological aging. Results suggest that threat-related ELA may correspond to heightened neural sensitivity to danger and reduced danger-safety discrimination, whereas deprivation-related ELA may enhance learning of danger vs. safety cues. Findings indicate potential differential associations between threat- and deprivation-related ELA and fear-related processes.

Posttraumatic stress disorder (PTSD) is a mental health condition with widespread effects on mental and physical health and mortality. In this paper, we present the current state of research on the epidemiology of PTSD, including its prevalence, risk factors, and impact. The U.S. lifetime prevalence of PTSD is estimated to be 6.1%–8.3%, and the global prevalence is estimated at 3.9%. PTSD prevalence has been consistently found to be higher among certain subgroups, including women and military veterans. Risk factors for PTSD include pretrauma variables, preexisting mental health conditions, sociodemographic characteristics, and features of the traumatic event itself. Consequences of PTSD include effects on psychiatric comorbidity, physical health conditions, and all‐cause and cause‐specific mortality. Points of consideration and challenges affecting the study of PTSD epidemiology are noted, including debates on specifying a trauma criterion for diagnosis, the validity of complex PTSD as a diagnosis, and the dearth of recent population‐based longitudinal data to understand this disorder. Suggestions for future research and clinical implications are discussed.

Multigroup cohort studies are used to compare exposed and unexposed groups on important outcomes. Recruitment for these studies can be done simultaneously or sequentially. When recruitment is simultaneous, there are many advanced statistical techniques, including propensity score matching, that can be used to select balanced groups to account for confounders of the effect of the exposure on the outcome. This paper presents a novel method for using propensity score matching for sequential recruitment using a five-step modular approach: (1) estimate propensity scores, (2) create propensity clusters, (3) match participants, (4) create holdout groups, and (5) enroll. These steps are repeated each recruitment period. We explain each step, providing R code to assist researchers in implementation, then demonstrate the performance of the method in a multigroup cohort study examining the effects of posttraumatic stress disorder on cardiovascular risk markers among trauma-exposed individuals. The method performed well and improved balance compared to using no selection technique, and it also performed similarly to propensity score matching with simultaneous recruitment. This method provides a novel approach to sequential recruitment in multigroup cohort studies. Future research should explore how more sophisticated methods for selecting covariates, generating propensity scores, and selecting matches could improve this method further.

Transdiagnostic treatments are needed to address the diverse manifestations and effects of trauma-related psychopathology. Acceptance and commitment therapy (ACT) is a promising intervention, although little is known about its application among trauma-exposed civilians. A single-arm pilot study evaluated outcomes of a virtual, group-based ACT intervention for trauma delivered through a training clinic. Five female clients (mean age=42.6 years) with a history of criterion A trauma completed an 11-week skills group and repeated measures assessing posttraumatic and related psychopathology symptoms (e.g., depression, anxiety, posttraumatic stress disorder [PTSD]), emotion regulation, quality of life, posttraumatic growth, and experiential avoidance. Paired-samples t tests were used to assess pre- to postintervention effects. All clients completed the intervention, suggesting high acceptability. Analyses of pre- to postintervention effects demonstrated significant reductions in depression (d=1.16, p=0.03) and anxiety (d=0.95, p=0.05) symptoms but not in PTSD symptoms; effect sizes for significant changes were large. Significant and large increases in effective use of emotion regulation strategies (d=1.02, p=0.04) and posttraumatic growth (d=1.18, p=0.03) were also observed. Experiential avoidance, a hypothesized treatment mechanism in ACT, decreased from pre- to postintervention (d=1.22, p=0.03). Findings provide initial evidence for acceptability and beneficial clinical outcomes of a virtual, group-based ACT intervention to address the transdiagnostic consequences of traumatic stress.