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Abstract Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN’s utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results.

Abstract People who experience trauma and develop posttraumatic stress disorder (PTSD) are at increased risk for poor health. One mechanism that could explain this risk is accelerated biological aging, which is associated with the accumulation of chronic diseases, disability, and premature mortality. Using data from 2309 post-9/11 United States military veterans who participated in the VISN 6 MIRECC’s Post-Deployment Mental Health Study, we tested whether PTSD and trauma exposure were associated with accelerated rate of biological aging, assessed using a validated DNA methylation (DNAm) measure of epigenetic aging—DunedinPACE. Veterans with current PTSD were aging faster than those who did not have current PTSD, β = 0.18, 95% CI [0.11, 0.27], p

Abstract We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of $$\sim$$ ∼ 4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics.

Background: Shame and guilt are key emotions known to amplify trauma-related symptoms in veterans. Maintenance of symptoms is facilitated by avoidance behaviors, such as substance use. However, limited research has examined the associations between shame, guilt, and substance use in daily life. Methods: The current study sought to examine the cross-lagged association between shame, guilt, and substance use. Forty veterans completed 28 days of experience sampling reporting on their current emotional experiences and use of substances. Results: Results suggest a reciprocal relationship among shame and guilt and substance use, such that shame and guilt separately predicted subsequent substance use, and substance use predicted subsequent shame and guilt. Conclusions: These results highlight the dynamic relationship among shame, guilt, and substance use and suggest the potential value of conceptualizing these clinical targets as mutually reinforcing to inform integrative intervention strategies that can interrupt the in-the-moment cascade of negative consequences.

IntroductionDespite a recent global decrease in suicide rates, death by suicide has increased in the United States. It is therefore imperative to identify the risk factors associated with suicide attempts to combat this growing epidemic. In this study, we aim to identify potential risk factors of suicide attempt using geospatial features in an Artificial intelligence framework.MethodsWe use iterative Random Forest, an explainable artificial intelligence method, to predict suicide attempts using data from the Million Veteran Program. This cohort incorporated 405,540 patients with 391,409 controls and 14,131 attempts. Our predictive model incorporates multiple climatic features at ZIP-code-level geospatial resolution. We additionally consider demographic features from the American Community Survey as well as the number of firearms and alcohol vendors per 10,000 people to assess the contributions of proximal environment, access to means, and restraint decrease to suicide attempts. In total 1,784 features were included in the predictive model.ResultsOur results show that geographic areas with higher concentrations of married males living with spouses are predictive of lower rates of suicide attempts, whereas geographic areas where males are more likely to live alone and to rent housing are predictive of higher rates of suicide attempts. We also identified climatic features that were associated with suicide attempt risk by age group. Additionally, we observed that firearms and alcohol vendors were associated with increased risk for suicide attempts irrespective of the age group examined, but that their effects were small in comparison to the top features.DiscussionTaken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans.

ObjectivePosttraumatic stress disorder (PTSD) symptoms and pain interfere with daily functioning and quality of life for many combat Veterans. As individuals age, pain symptoms tend to increase whereas PTSD symptoms tend to decrease. PTSD symptoms exacerbate pain, but the nature of this relationship across the aging process is unclear. The purpose of this study was to determine how PTSD symptoms affect the association between age and pain intensity.MethodsParticipants in this cross-sectional study included 450 Veterans (80% male) who served after September 11, 2001. PTSD and pain intensity ratings were assessed by the PTSD Checklist for DSM-5 (PCL-5) and the Brief Pain Inventory (BPI), respectively. Hierarchical multiple linear regression evaluated main and interaction effects between age, PTSD symptoms, and pain intensity.ResultsAge (B = 0.04, p

IntroductionThe U.S. suicide mortality rate has steadily increased during the past two decades, particularly among military veterans; however, the epigenetic basis of suicidal thoughts and behaviors (STB) remains largely unknown.MethodsTo address this issue, we conducted an epigenome-wide association study of DNA methylation (DNAm) of peripheral blood samples obtained from 2,712 U.S. military veterans.ResultsThree DNAm probes were significantly associated with suicide attempts, surpassing the multiple testing threshold (FDR q-value

Abstract 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

PTSD has been associated with DNA methylation of specific loci in the genome, but studies have been limited by small sample sizes. Here, the authors perform a meta-analysis of DNA methylation data from 10 different cohorts and identify CpGs in AHRR that are associated with PTSD.

Background Worldwide, nearly 800,000 individuals die by suicide each year; however, longitudinal prediction of suicide attempts remains a major challenge within the field of psychiatry. The objective of the present research was to develop and evaluate an evidence-based suicide attempt risk checklist [i.e., the Durham Risk Score (DRS)] to aid clinicians in the identification of individuals at risk for attempting suicide in the future. Methods and findings Three prospective cohort studies, including a population-based study from the United States [i.e., the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) study] as well as 2 smaller US veteran cohorts [i.e., the Assessing and Reducing Post-Deployment Violence Risk (REHAB) and the Veterans After-Discharge Longitudinal Registry (VALOR) studies], were used to develop and validate the DRS. From a total sample size of 35,654 participants, 17,630 participants were selected to develop the checklist, whereas the remaining participants (N = 18,024) were used to validate it. The main outcome measure was future suicide attempts (i.e., actual suicide attempts that occurred after the baseline assessment during the 1- to 3-year follow-up period). Measure development began with a review of the extant literature to identify potential variables that had substantial empirical support as longitudinal predictors of suicide attempts and deaths. Next, receiver operating characteristic (ROC) curve analysis was utilized to identify variables from the literature review that uniquely contributed to the longitudinal prediction of suicide attempts in the development cohorts. We observed that the DRS was a robust prospective predictor of future suicide attempts in both the combined development (area under the curve [AUC] = 0.91) and validation (AUC = 0.92) cohorts. A concentration of risk analysis found that across all 35,654 participants, 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. The DRS also performed well among important subgroups, including women (AUC = 0.91), men (AUC = 0.93), Black (AUC = 0.92), White (AUC = 0.93), Hispanic (AUC = 0.89), veterans (AUC = 0.91), lower-income individuals (AUC = 0.90), younger adults (AUC = 0.88), and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) individuals (AUC = 0.88). The primary limitation of the present study was its its reliance on secondary data analyses to develop and validate the risk score. Conclusions In this study, we observed that the DRS was a strong predictor of future suicide attempts in both the combined development (AUC = 0.91) and validation (AUC = 0.92) cohorts. It also demonstrated good utility in many important subgroups, including women, men, Black, White, Hispanic, veterans, lower-income individuals, younger adults, and LGBTQ individuals. We further observed that 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. Taken together, these findings suggest that the DRS represents a significant advancement in suicide risk prediction over traditional clinical assessment approaches. While more work is needed to independently validate the DRS in prospective studies and to identify the optimal methods to assess the constructs used to calculate the score, our findings suggest that the DRS is a promising new tool that has the potential to significantly enhance clinicians’ ability to identify individuals at risk for attempting suicide in the future. Using data from three prospective cohorts in the US, Nathan Kimbrel and colleagues report on the development and validation of an evidence-based checklist to identify those at risk of future suicide attempts. Author summary Why was this study done? Nearly 800,000 individuals die by suicide each year worldwide; however, longitudinal prediction of suicide attempts remains a major challenge within the field of psychiatry. Current clinical risk instruments and assessments to detect risk for future suicide attempts lack sufficient diagnostic accuracy to guide treatment decisions. What did the researchers do and find? The goal of this study was to develop and evaluate a risk score (the Durham Risk Score or DRS) to aid clinicians in identifying individuals at risk for attempting suicide. Secondary analyses were conducted on 3 prospective cohort studies from the US (total sample size = 35,654 participants), including a large general population study and 2 smaller veteran cohorts. The risk score was a strong predictor of future suicide attempts in both the combined development (area under the curve [AUC] = 0.91) and validation (AUC = 0.92) cohorts. Moreover, 82% of prospective suicide attempts occurred among individuals in the top 15% of risk scores, whereas 27% occurred among individuals scoring in the top 1% of risk scores. The risk score also performed well among important subgroups, including women, men, Black, White, Hispanic, veterans, lower-income individuals, younger adults, and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) individuals. What do these findings mean? Our findings suggest that the DRS is a promising new tool that has the potential to enhance clinicians’ ability to identify individuals at risk for attempting suicide. The primary limitation of this work is its reliance on secondary data analyses to develop and validate the score. More work is needed to independently validate the DRS in prospective studies and to identify the optimal methods to assess each of the constructs used to calculate the score.

Posttraumatic stress disorder (PTSD) is a complex psychiatric disorder that can develop following exposure to traumatic events. The Psychiatric Genomics Consortium PTSD group (PGC-PTSD) has collected over 20,000 multi-ethnic PTSD cases and controls and has identified both genetic and epigenetic factors associated with PTSD risk. To further investigate biological correlates of PTSD risk, we examined three PGC-PTSD cohorts comprising 977 subjects to identify differentially expressed genes among PTSD cases and controls. Whole blood gene expression was quantified with the HumanHT-12 v4 Expression BeadChip for 726 OEF/OIF veterans from the Veterans Affairs (VA) Mental Illness Research Education and Clinical Center (MIRECC), 155 samples from the Injury and Traumatic Stress (INTRuST) Clinical Consortium, and 96 Australian Vietnam War veterans. Differential gene expression analysis was performed in each cohort separately followed by meta-analysis. In the largest cohort, we performed co-expression analysis to identify modules of genes that are associated with PTSD and MDD. We then conducted expression quantitative trait loci (eQTL) analysis and assessed the presence of eQTL interactions involving PTSD and major depressive disorder (MDD). Finally, we utilized PTSD and MDD GWAS summary statistics to identify regions that colocalize with eQTLs. Although not surpassing correction for multiple testing, the most differentially expressed genes in meta-analysis were interleukin-1 beta (IL1B), a pro-inflammatory cytokine previously associated with PTSD, and integrin-linked kinase (ILK), which is highly expressed in brain and can rescue dysregulated hippocampal neurogenesis and memory deficits. Pathway analysis revealed enrichment of toll-like receptor (TLR) and interleukin-1 receptor genes, which are integral to cellular innate immune response. Co-expression analysis identified four modules of genes associated with PTSD, two of which are also associated with MDD, demonstrating common biological pathways underlying the two conditions. Lastly, we identified four genes (UBA7, HLA-F, HSPA1B, and RERE) with high probability of a shared causal eQTL variant with PTSD and/or MDD GWAS variants, thereby providing a potential mechanism by which the GWAS variant contributes to disease risk. In summary, we provide additional evidence for genes and pathways previously reported and identified plausible novel candidates for PTSD. These data provide further insight into genetic factors and pathways involved in PTSD, as well as potential regions of pleiotropy between PTSD and MDD.

Growing research suggests that posttraumatic stress disorder (PTSD) may be a risk factor for poor cardiovascular health, and yet our understanding of who might be at greatest risk of adverse cardiovascular outcomes after trauma is limited. In this study, we conducted the first examination of the individual and synergistic contributions of PTSD symptoms and blood pressure genetics to continuous blood pressure levels. We harnessed the power of the Psychiatric Genomics Consortium-PTSD Physical Health Working Group and investigated these associations across 11 studies of 72,224 trauma-exposed individuals of European (n = 70,870) and African (n = 1,354) ancestry. Genetic contributions to blood pressure were modeled via polygenic scores (PGS) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) that were derived from a prior trans-ethnic blood pressure genome-wide association study (GWAS). Results of trans-ethnic meta-analyses revealed significant main effects of the PGS on blood pressure levels [SBP: β = 2.83, standard error (SE) = 0.06, p < 1E-20; DBP: β = 1.32, SE = 0.04, p < 1E-20]. Significant main effects of PTSD symptoms were also detected for SBP and DBP in trans-ethnic meta-analyses, though there was significant heterogeneity in these results. When including data from the largest contributing study – United Kingdom Biobank – PTSD symptoms were negatively associated with SBP levels (β = −1.46, SE = 0.44, p = 9.8E-4) and positively associated with DBP levels (β = 0.70, SE = 0.26, p = 8.1E-3). However, when excluding the United Kingdom Biobank cohort in trans-ethnic meta-analyses, there was a nominally significant positive association between PTSD symptoms and SBP levels (β = 2.81, SE = 1.13, p = 0.01); no significant association was observed for DBP (β = 0.43, SE = 0.78, p = 0.58). Blood pressure PGS did not significantly moderate the associations between PTSD symptoms and blood pressure levels in meta-analyses. Additional research is needed to better understand the extent to which PTSD is associated with high blood pressure and how genetic as well as contextual factors may play a role in influencing cardiovascular risk.

Post-traumatic stress disorder (PTSD) is a common mental health problem. Here, the authors report a GWAS from the Psychiatric Genomics Consortium in which they identify two risk loci in European ancestry and one locus in African ancestry individuals and find that PTSD is genetically correlated with several other psychiatric traits.

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.

While repetitive transcranial magnetic stimulation (rTMS) is widely used to treat psychiatric disorders, innovations are needed to improve its efficacy. An important limitation is that while psychiatric disorders are associated with fronto-limbic dysregulation, rTMS does not have sufficient depth penetration to modulate affected subcortical structures. Recent advances in task-related functional connectivity provide a means to better link superficial and deeper cortical sources with the possibility of increasing fronto-limbic modulation to induce stronger therapeutic effects. The objective of this pilot study was to test whether task-related, connectivity-based rTMS could modulate amygdala activation through its connectivity with the medial prefrontal cortex (mPFC). fMRI was collected to identify a node in the mPFC showing the strongest connectivity with the amygdala, as defined by psychophysiological interaction analysis. To promote Hebbian-like plasticity, and potentially stronger modulation, 5 Hz rTMS was applied while participants viewed frightening video-clips that engaged the fronto-limbic network. Significant increases in both the mPFC and amygdala were found for active rTMS compared to sham, offering promising preliminary evidence that functional connectivity-based targeting may provide a useful approach to treat network dysregulation. Further research is needed to better understand connectivity influences on rTMS effects to leverage this information to improve therapeutic applications.

Objective: Moral injury may result from perpetration-based and betrayal-based acts that violate deeply held norms; however, researchers and clinicians have little guidance about the moral injury syndrome's specific developmental pathways following morally injurious events. The present study's objective was to examine the direct and indirect pathways proposed in a frequently cited model of moral injury (1) in relation to two types of military-related traumas [experiencing military sexual trauma (MST) and combat exposure].Methods: Secondary analyses were conducted within a sample of post-9/11 veterans at a Southwestern Veterans Health Care System (N = 310) across two time-points. Structural equation modeling tested the direct and indirect pathways from MST and combat to a PTSD-depression factor via betrayal, perpetration, guilt, and shame.Results: Betrayal accounted for the association between MST and PTSD-depression (β = 0.10, p < 0.01, 95% CI = 0.01 − 0.11) and perpetration accounted for the association between combat and PTSD-depression (β = 0.07, p < 0.05, 95% CI = 0.02 − 0.14). The indirect path from combat to shame to PTSD-depression was significant (β = 0.16, p < 0.01, 95% CI = 0.07 − 0.28) but the path through guilt was not. The specific indirect paths through perpetration or betrayal to shame or guilt were non-significant.Conclusions: Betrayal and perpetration are associated with PTSD-depression following MST and combat. Results suggest multiple pathways of moral injury development following different military traumas and morally injurious events. Implications for moral injury conceptualization and treatment are discussed.

Recent work inspired by graph theory has begun to conceptualize mental disorders as networks of interacting symptoms. Posttraumatic stress disorder (PTSD) symptom networks have been investigated in clinical samples meeting full diagnostic criteria, including military veterans, natural disaster survivors, civilian survivors of war, and child sexual abuse survivors. Despite reliable associations across reported networks, more work is needed to compare central symptoms across trauma types. Additionally, individuals without a diagnosis who still experience symptoms, also referred to as subthreshold cases, have not been explored with network analysis in veterans. A sample of 1,050 Iraq/Afghanistan-era U.S. military veterans (851 males, mean age = 36.3, SD = 9.53) meeting current full-criteria PTSD (n = 912) and subthreshold PTSD (n = 138) were assessed with the Structured Clinical Interview for DSM-IV Disorders (SCID). Combat Exposure Scale (CES) scores were used to group the sample meeting full-criteria into high (n = 639) and low (n = 273) combat exposure subgroups. Networks were estimated using regularized partial correlation models in the R-package qgraph, and robustness tests were performed with bootnet. Frequently co-occurring symptom pairs (strong network connections) emerged between two avoidance symptoms, hypervigilance and startle response, loss of interest and detachment, as well as, detachment and restricted affect. These associations replicate findings reported across PTSD trauma types. A symptom network analysis of PTSD in a veteran population found significantly greater overall connectivity in the full-criteria PTSD group as compared to the subthreshold PTSD group. Additionally, novel findings indicate that the association between intrusive thoughts and irritability is a feature of the symptom network of veterans with high levels of combat exposure. Mean node predictability is high for PTSD symptom networks, averaging 51.5% shared variance. With the tools described here and by others, researchers can help refine diagnostic criteria for PTSD, develop more accurate measures for assessing PTSD, and eventually inform therapies that target symptoms with strong network connections to interrupt interconnected symptom complexes and promote functional recovery.

Although racial/ethnic differences have been found in the use of mental health services for depression in the general population, research among Veterans has produced mixed results. This study examined racial/ethnic differences in the use of mental health services among 148 Operation Enduring/Iraqi Freedom (OEF/OIF) Veterans with high levels of depression and posttraumatic stress disorder (PTSD) symptoms and evaluated whether religious coping affected service use. No differences between African American, Hispanic, and Non-Hispanic white Veterans were found in use of secular mental health services or religious counseling. Women Veterans were more likely than men to seek secular treatment. After controlling for PTSD symptoms, depression symptom level was a significant predictor of psychotherapy attendance but not medication treatment. African American Veterans reported higher levels of religious coping than whites. Religious coping was associated with participation in religious counseling, but not secular mental health services.

Suicidal ideation (SI) often precedes and predicts suicide attempt and death, is the most common suicidal phenotype and is over-represented in veterans. The genetic architecture of SI in the absence of suicide attempt (SA) is unknown, yet believed to have distinct and overlapping risk with other suicidal behaviors. We performed the first GWAS of SI without SA in the Million Veteran Program (MVP), identifying 99,814 SI cases from electronic health records without a history of SA or suicide death (SD) and 512,567 controls without SI, SA or SD. GWAS was performed separately in the four largest ancestry groups, controlling for sex, age and genetic substructure. Ancestry-specific results were combined via meta-analysis to identify pan-ancestry loci. Four genome-wide significant (GWS) loci were identified in the pan-ancestry meta-analysis with loci on chromosomes 6 and 9 associated with suicide attempt in an independent sample. Pan-ancestry gene-based analysis identified GWS associations with DRD2, DCC, FBXL19, BCL7C, CTF1, ANNK1, and EXD3. Gene-set analysis implicated synaptic and startle response pathways (q's

BackgroundWorldwide, nearly 800,000 individuals die by suicide each year; however, longitudinal prediction of suicide attempts remains a major challenge within the field of psychiatry. The objective of the present research was to develop and evaluate an evidence-based suicide attempt risk checklist [i.e., the Durham Risk Score (DRS)] to aid clinicians in the identification of individuals at risk for attempting suicide in the future.Methods and findingsThree prospective cohort studies, including a population-based study from the United States [i.e., the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) study] as well as 2 smaller US veteran cohorts [i.e., the Assessing and Reducing Post-Deployment Violence Risk (REHAB) and the Veterans After-Discharge Longitudinal Registry (VALOR) studies], were used to develop and validate the DRS. From a total sample size of 35,654 participants, 17,630 participants were selected to develop the checklist, whereas the remaining participants (N = 18,024) were used to validate it. The main outcome measure was future suicide attempts (i.e., actual suicide attempts that occurred after the baseline assessment during the 1- to 3-year follow-up period). Measure development began with a review of the extant literature to identify potential variables that had substantial empirical support as longitudinal predictors of suicide attempts and deaths. Next, receiver operating characteristic (ROC) curve analysis was utilized to identify variables from the literature review that uniquely contributed to the longitudinal prediction of suicide attempts in the development cohorts. We observed that the DRS was a robust prospective predictor of future suicide attempts in both the combined development (area under the curve [AUC] = 0.91) and validation (AUC = 0.92) cohorts. A concentration of risk analysis found that across all 35,654 participants, 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. The DRS also performed well among important subgroups, including women (AUC = 0.91), men (AUC = 0.93), Black (AUC = 0.92), White (AUC = 0.93), Hispanic (AUC = 0.89), veterans (AUC = 0.91), lower-income individuals (AUC = 0.90), younger adults (AUC = 0.88), and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) individuals (AUC = 0.88). The primary limitation of the present study was its its reliance on secondary data analyses to develop and validate the risk score.ConclusionsIn this study, we observed that the DRS was a strong predictor of future suicide attempts in both the combined development (AUC = 0.91) and validation (AUC = 0.92) cohorts. It also demonstrated good utility in many important subgroups, including women, men, Black, White, Hispanic, veterans, lower-income individuals, younger adults, and LGBTQ individuals. We further observed that 82% of prospective suicide attempts occurred among individuals in the top 15% of DRS scores, whereas 27% occurred in the top 1%. Taken together, these findings suggest that the DRS represents a significant advancement in suicide risk prediction over traditional clinical assessment approaches. While more work is needed to independently validate the DRS in prospective studies and to identify the optimal methods to assess the constructs used to calculate the score, our findings suggest that the DRS is a promising new tool that has the potential to significantly enhance clinicians' ability to identify individuals at risk for attempting suicide in the future.

The introduction of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) was accompanied by the elimination of the Global Assessment of Functioning (GAF) scale, which was previously used to assess functioning. Although the World Health Organization Disability Assessment Schedule, Version 2.0 (WHODAS 2.0) was offered as a measure for further study, widespread adoption of the WHODAS 2.0 has yet to occur. The lack of a standardized instrument for assessing posttraumatic stress disorder (PTSD)-related disability has important implications for disability compensation. Accordingly, this study was designed to determine and codify the utility of the WHODAS 2.0 for assessing PTSD-related disability. Veterans from several VA medical centers (N = 1109) were included. We examined PTSD using several definitions and modalities and considered results by gender and age. Across definitions and modalities, veterans with PTSD reported significantly greater WHODAS 2.0 total (large effects; all ts > 6.00; all ps < .01; all Cohen's ds > 1.03) and subscale (medium-to-large effects; all ts > 2.29; all ps < .05; all Cohen's ds > .39) scores than those without PTSD. WHODAS 2.0 scores did not vary by gender; however, younger veterans reported less disability than older veterans (small effects; all Fs > 4.30; all ps < .05; all η2s < .05). We identified 32 as the optimally efficient cutoff score for discriminating veterans with and without PTSD-related disability, although this varied somewhat by age and gender. Findings support the utility of the WHODAS 2.0 in assessing PTSD-related disability.

Returning veterans of the wars in Iraq and Afghanistan experience high rates of post-traumatic stress disorder (PTSD) and suicidal behavior. Suicidal ideation is among the strongest risk factors for completed suicide. Some research suggests an association between PTSD and suicidal ideation, and that health-promoting behaviors-behaviors that sustain or increase well-being-play a role in this association. The current study examined whether health-promoting behaviors moderate the association between PTSD severity and suicidal ideation.Veterans of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF; N = 108) completed measures of PTSD symptoms, trauma exposure, suicidal ideation, and health-promoting behaviors.Moderated regression was used to test the hypothesis. Results indicated that health promoting behaviors, β = -.06, p = .001, and PTSD symptoms, β = .36, p < .001, were significantly related to suicidal ideation. Consistent with our main hypothesis, the health promoting behaviors x PTSD interaction term was significantly associated with suicidal ideation, β = -.09, p = .001. The overall model accounted for 13% of the variance in suicidal ideation. Among individuals with high PTSD symptom severity, those who engaged in more health promoting behaviors reported less suicidal ideation than those who engaged in fewer health promoting behaviors.Health-promoting behaviors could be important for reducing suicidal ideation among veterans with high levels of PTSD symptoms. It is recommended that future research examine health promotion interventions as a means of reducing suicidal ideation.

To examine the association between the 5-HTTLPR polymorphism of the serotonin transporter (SLC6A4) gene, combat exposure, and posttraumatic stress disorder (PTSD) diagnosis and among two samples of combat-exposed veterans.The first sample included 550 non-Hispanic Black (NHB) combat-exposed veterans. The second sample included 555 non-Hispanic White (NHW) combat-exposed veterans. Participants were genotyped for the 5-HTTLPR/rs25531 variants of the SLC6A4 gene. A structured clinical interview was used to diagnose PTSD. Combat and civilian trauma exposure were assessed with validated self-report instruments. Logistic regression was used to test for main effects of 5-HTTLPR on PTSD diagnosis as well as gene x environment (GxE) interactions after adjusting for sex, ancestry proportion scores, civilian trauma exposure, and combat exposure.Within the NHB sample, a significant additive effect was observed for 5-HTTLPR (OR = 1.502, p = .0025), such that the odds of having a current diagnosis of PTSD increased by 1.502 for each additional S' allele. No evidence for an association between 5-HTTLPR and PTSD was observed in the NHW sample. In addition, no evidence for combat x 5-HTTLPR effects were observed in either sample.The present study suggests that there may be an association between 5-HTTLPR genotype and PTSD diagnosis among NHB veterans; however, no evidence for the hypothesized 5-HTTLPR x combat interaction was found.