GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records.

Importance: Half of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients. Objective: To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. Design, Setting, and Participants: This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021. Main Outcomes and Measures: Suicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide. Results: A total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians' assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts. Conclusions and Relevance: This prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data.

Multi-environment gene interactions linked to the interplay between polysubstance dependence and suicidality.

Substance dependence diagnoses (SDs) are important risk factors for suicidality. We investigated the associations of multiple SDs with different suicidality outcomes, testing how genetic background moderates these associations. The Yale-Penn cohort (N = 15,557) was recruited to investigate the genetics of SDs. The Army STARRS (Study to Assess Risk and Resilience in Servicemembers) cohort (N = 11,236) was recruited to evaluate mental health risk and resilience among Army personnel. We applied multivariate logistic regression to investigate the associations of SDs with suicidality and, in the Yale-Penn cohort, we used the structured linear mixed model (StructLMM) to study multivariate gene-environment interactions. In Yale-Penn, lifetime polysubstance dependence was strongly associated with lifetime suicidality: having five SDs showed an association with suicidality, from odds ratio (OR) = 6.77 (95% confidence interval, CI = 5.74-7.99) for suicidal ideation (SI) to OR = 3.61 (95% CI = 2.7-4.86) for suicide attempt (SA). In Army STARRS, having multiple substance use disorders for alcohol and/or drugs was associated with increased suicidality ranging from OR = 2.88 (95% CI = 2.6-3.19) for SI to OR = 3.92 (95% CI = 3.19-4.81) for SA. In Yale-Penn, we identified multivariate gene-environment interactions (Bayes factors, BF > 0) of SI with respect to a gene cluster on chromosome 16 (LCAT, p = 1.82 × 10-7; TSNAXIP1, p = 2.13 × 10-7; CENPT, p = 2.32 × 10-7; PARD6A, p = 5.57 × 10-7) for opioid dependence (BF = 12.2), cocaine dependence (BF = 12.1), nicotine dependence (BF = 9.2), and polysubstance dependence (BF = 2.1). Comorbidity of multiple SDs is a significant associated with suicidality and heritability of suicidality is partially moderated by multivariate gene interactions.

Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR.

Epigenetic differences may help to distinguish between PTSD cases and trauma-exposed controls. Here, we describe the results of the largest DNA methylation meta-analysis of PTSD to date. Ten cohorts, military and civilian, contribute blood-derived DNA methylation data from 1,896 PTSD cases and trauma-exposed controls. Four CpG sites within the aryl-hydrocarbon receptor repressor (AHRR) associate with PTSD after adjustment for multiple comparisons, with lower DNA methylation in PTSD cases relative to controls. Although AHRR methylation is known to associate with smoking, the AHRR association with PTSD is most pronounced in non-smokers, suggesting the result was independent of smoking status. Evaluation of metabolomics data reveals that AHRR methylation associated with kynurenine levels, which are lower among subjects with PTSD. This study supports epigenetic differences in those with PTSD and suggests a role for decreased kynurenine as a contributor to immune dysregulation in PTSD.

Association between Mental Disorders and Subsequent Medical Conditions.

BACKGROUND: Persons with mental disorders are at a higher risk than the general population for the subsequent development of certain medical conditions. METHODS: We used a population-based cohort from Danish national registries that included data on more than 5.9 million persons born in Denmark from 1900 through 2015 and followed them from 2000 through 2016, for a total of 83.9 million person-years. We assessed 10 broad types of mental disorders and 9 broad categories of medical conditions (which encompassed 31 specific conditions). We used Cox regression models to calculate overall hazard ratios and time-dependent hazard ratios for pairs of mental disorders and medical conditions, after adjustment for age, sex, calendar time, and previous mental disorders. Absolute risks were estimated with the use of competing-risks survival analyses. RESULTS: A total of 698,874 of 5,940,299 persons (11.8%) were identified as having a mental disorder. The median age of the total population was 32.1 years at entry into the cohort and 48.7 years at the time of the last follow-up. Persons with a mental disorder had a higher risk than those without such disorders with respect to 76 of 90 pairs of mental disorders and medical conditions. The median hazard ratio for an association between a mental disorder and a medical condition was 1.37. The lowest hazard ratio was 0.82 for organic mental disorders and the broad category of cancer (95% confidence interval [CI], 0.80 to 0.84), and the highest was 3.62 for eating disorders and urogenital conditions (95% CI, 3.11 to 4.22). Several specific pairs showed a reduced risk (e.g., schizophrenia and musculoskeletal conditions). Risks varied according to the time since the diagnosis of a mental disorder. The absolute risk of a medical condition within 15 years after a mental disorder was diagnosed varied from 0.6% for a urogenital condition among persons with a developmental disorder to 54.1% for a circulatory disorder among those with an organic mental disorder. CONCLUSIONS: Most mental disorders were associated with an increased risk of a subsequent medical condition; hazard ratios ranged from 0.82 to 3.62 and varied according to the time since the diagnosis of the mental disorder. (Funded by the Danish National Research Foundation and others; COMO-GMC ClinicalTrials.gov number, NCT03847753.).

Evaluating a screener to quantify PTSD risk using emergency care information: a proof of concept study.

BACKGROUND: Previous work has indicated that post-traumatic stress disorder (PTSD) symptoms, measured by the Clinician-Administered PTSD Scale (CAPS) within 60 days of trauma exposure, can reliably produce likelihood estimates of chronic PTSD among trauma survivors admitted to acute care centers. Administering the CAPS is burdensome, requires skilled professionals, and relies on symptoms that are not fully expressed upon acute care admission. Predicting chronic PTSD from peritraumatic responses, which are obtainable upon acute care admission, has yielded conflicting results, hence the rationale for a stepwise screening-and-prediction practice. This work explores the ability of peritraumatic responses to produce risk likelihood estimates of early CAPS-based PTSD symptoms indicative of chronic PTSD risk. It specifically evaluates the Peritraumatic Dissociative Experiences Questionnaire (PDEQ) as a risk-likelihood estimator. METHODS: We used individual participant data (IPD) from five acute care studies that used both the PDEQ and the CAPS (n = 647). Logistic regression calculated the probability of having CAPS scores ≥ 40 between 30 and 60 days after trauma exposure across the range of initial PDEQ scores, and evaluated the added contribution of age, sex, trauma type, and prior trauma exposure. Brier scores, area under the receiver-operating characteristic curve (AUC), and the mean slope of the calibration line evaluated the accuracy and precision of the predicted probabilities. RESULTS: Twenty percent of the sample had CAPS ≥ 40. PDEQ severity significantly predicted having CAPS ≥ 40 symptoms (p < 0.001). Incremental PDEQ scores produced a reliable estimator of CAPS ≥ 40 likelihood. An individual risk estimation tool incorporating PDEQ and other significant risk indicators is provided. CONCLUSION: Peritraumatic reactions, measured here by the PDEQ, can reliably quantify the likelihood of acute PTSD symptoms predictive of chronic PTSD and requiring clinical attention. Using them as a screener in a stepwise chronic PTSD prediction strategy may reduce the burden of later CAPS-based assessments. Other peritraumatic metrics may perform similarly and their use requires similar validation. TRIAL REGISTRATION: Jerusalem Trauma Outreach and Prevention Study (J-TOPS): NCT00146900.

An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci.

BACKGROUND: Previous studies using candidate gene and genome-wide approaches have identified epigenetic changes in DNA methylation (DNAm) associated with posttraumatic stress disorder (PTSD). METHODS: In this study, we performed an EWAS of PTSD in a cohort of Veterans (n = 378 lifetime PTSD cases and 135 controls) from the Translational Research Center for TBI and Stress Disorders (TRACTS) cohort assessed using the Illumina EPIC Methylation BeadChip which assesses DNAm at more than 850,000 sites throughout the genome. Our model included covariates for ancestry, cell heterogeneity, sex, age, and a smoking score based on DNAm at 39 smoking-associated CpGs. We also examined in EPIC-based DNAm data generated from pre-frontal cortex (PFC) tissue from the National PTSD Brain Bank (n = 72). RESULTS: The analysis of blood samples yielded one genome-wide significant association with PTSD at cg19534438 in the gene G0S2 (p = 1.19 × 10-7, padj = 0.048). This association was replicated in an independent PGC-PTSD-EWAS consortium meta-analysis of military cohorts (p = 0.0024). We also observed association with the smoking-related locus cg05575921 in AHRR despite inclusion of a methylation-based smoking score covariate (p = 9.16 × 10-6), which replicates a previously observed PGC-PTSD-EWAS association (Smith et al. 2019), and yields evidence consistent with a smoking-independent effect. The top 100 EWAS loci were then examined in the PFC data. One of the blood-based PTSD loci, cg04130728 in CHST11, which was in the top 10 loci in blood, but which was not genome-wide significant, was significantly associated with PTSD in brain tissue (in blood p = 1.19 × 10-5, padj = 0.60, in brain, p = 0.00032 with the same direction of effect). Gene set enrichment analysis of the top 500 EWAS loci yielded several significant overlapping GO terms involved in pathogen response, including "Response to lipopolysaccharide" (p = 6.97 × 10-6, padj = 0.042). CONCLUSIONS: The cross replication observed in independent cohorts is evidence that DNA methylation in peripheral tissue can yield consistent and replicable PTSD associations, and our results also suggest that that some PTSD associations observed in peripheral tissue may mirror associations in the brain.

Accuracy of online survey assessment of mental disorders and suicidal thoughts and behaviors in Spanish university students. Results of the WHO World Mental Health- International College Student initiative.

OBJECTIVE: To assess the accuracy of WMH-ICS online screening scales for evaluating four common mental disorders (Major Depressive Episode[MDE], Mania/Hypomania[M/H], Panic Disorder[PD], Generalized Anxiety Disorder[GAD]) and suicidal thoughts and behaviors[STB] used in the UNIVERSAL project. METHODS: Clinical diagnostic reappraisal was carried out on a subsample of the UNIVERSAL project, a longitudinal online survey of first year Spanish students (18-24 years old), part of the WHO World Mental Health-International College Student (WMH-ICS) initiative. Lifetime and 12-month prevalence of MDE, M/H, PD, GAD and STB were assessed with the Composite International Diagnostic Interview-Screening Scales [CIDI-SC], the Self-Injurious Thoughts and Behaviors Interview [SITBI] and the Columbia-Suicide Severity Rating Scale [C-SSRS]. Trained clinical psychologists, blinded to responses in the initial survey, administered via telephone the Mini-International Neuropsychiatric Interview [MINI]. Measures of diagnostic accuracy and McNemar χ2 test were calculated. Sensitivity analyses were conducted to maximize diagnostic capacity. RESULTS: A total of 287 students were included in the clinical reappraisal study. For 12-month and lifetime mood disorders, sensitivity/specificity were 67%/88.6% and 65%/73.3%, respectively. For 12-month and lifetime anxiety disorders, these were 76.8%/86.5% and 59.6%/71.1%, and for 12-month and lifetime STB, 75.9%/94.8% and 87.2%/86.3%. For 12-month and lifetime mood disorders, anxiety disorders and STB, positive predictive values were in the range of 18.1-55.1% and negative predictive values 90.2-99.0%; likelihood ratios positive were in the range of 2.1-14.6 and likelihood ratios negative 0.1-0.6. All outcomes showed adequate areas under the curve [AUCs] (AUC>0.7), except M/H and PD (AUC = 0.6). Post hoc analyses to select optimal diagnostic thresholds led to improved concordance for all diagnoses (AUCs>0.8). CONCLUSION: The WMS-ICS survey showed reasonable concordance with the MINI telephone interviews performed by mental health professionals, when utilizing optimized cut-off scores. The current study provides initial evidence that the WMS-ICS survey might be useful for screening purposes.

Developing an optimal short-form of the PTSD Checklist for DSM-5 (PCL-5).

BACKGROUND: Although several short-forms of the posttraumatic stress disorder (PTSD) Checklist (PCL) exist, all were developed using heuristic methods. This report presents the results of analyses designed to create an optimal short-form PCL for DSM-5 (PCL-5) using both machine learning and conventional scale development methods. METHODS: The short-form scales were developed using independent datasets collected by the Army Study to Assess Risk and Resilience among Service members. We began by using a training dataset (n = 8,917) to fit short-form scales with between 1 and 8 items using different statistical methods (exploratory factor analysis, stepwise logistic regression, and a new machine learning method to find an optimal integer-scored short-form scale) to predict dichotomous PTSD diagnoses determined using the full PCL-5. A smaller subset of best short-form scales was then evaluated in an independent validation sample (n = 11,728) to select one optimal short-form scale based on multiple operating characteristics (area under curve [AUC], calibration, sensitivity, specificity, net benefit). RESULTS: Inspection of AUCs in the training sample and replication in the validation sample led to a focus on 4-item integer-scored short-form scales selected with stepwise regression. Brier scores in the validation sample showed that a number of these scales had comparable calibration (0.015-0.032) and AUC (0.984-0.994), but that one had consistently highest net benefit across a plausible range of decision thresholds. CONCLUSIONS: The recommended 4-item integer-scored short-form PCL-5 generates diagnoses that closely parallel those of the full PCL-5, making it well-suited for screening.

Twelve-month utilization rates and adequacy of treatment for mental health and substance use disorders in Argentina

Objective: To estimate the 12-month prevalence of mental health services utilization (overall and by type of service sector), the adequacy of treatment provided, and sociodemographic correlates in the Argentinean Study of Mental Health Epidemiology (ASMHE). Methods: The ASMHE is a multistage probability household sample representative of adults in urban areas of Argentina. The World Health Organization World Mental Health Composite International Diagnostic Interview (WMH-CIDI) was used to evaluate psychiatric diagnosis and service utilization. Results: Among those with a disorder, 27.6% received any treatment in the prior 12 months. Of these, 78.3% received minimally adequate treatment using a broad definition and only 43.6% using a stringent definition. For individuals with a disorder, more services were provided by mental health professionals (17.7%) than by general medical professionals (11.5%) or non-healthcare sectors (2.6%). Younger individuals with low education and income were less likely to receive treatment; those never married and those with an anxiety or mood disorder were more likely to receive treatment. Among those in treatment, treatment was least adequate among younger individuals with low education and low income. Conclusions: Policies to increase access to services for mental health disorders in Argentina are needed, as is training for primary care practitioners in the early detection and treatment of psychiatric disorders.

Association of Cohort and Individual Substance Use With Risk of Transitioning to Drug Use, Drug Use Disorder, and Remission From Disorder: Findings From the World Mental Health Surveys.

Importance: Limited empirical research has examined the extent to which cohort-level prevalence of substance use is associated with the onset of drug use and transitioning into greater involvement with drug use. Objective: To use cross-national data to examine time-space variation in cohort-level drug use to assess its associations with onset and transitions across stages of drug use, abuse, dependence, and remission. Design, Setting, and Participants: The World Health Organization World Mental Health Surveys carried out cross-sectional general population surveys in 25 countries using a consistent research protocol and assessment instrument. Adults from representative household samples were interviewed face-to-face in the community in relation to drug use disorders. The surveys were conducted between 2001 and 2015. Data analysis was performed from July 2017 to July 2018. Main Outcomes and Measures: Data on timing of onset of lifetime drug use, DSM-IV drug use disorders, and remission from these disorders was assessed using the Composite International Diagnostic Interview. Associations of cohort-level alcohol prevalence and drug use prevalence were examined as factors associated with these transitions. Results: Among the 90 027 respondents (48.1% [SE, 0.2%] men; mean [SE] age, 42.1 [0.1] years), 1 in 4 (24.8% [SE, 0.2%]) reported either illicit drug use or extramedical use of prescription drugs at some point in their lifetime, but with substantial time-space variation in this prevalence. Among users, 9.1% (SE, 0.2%) met lifetime criteria for abuse, and 5.0% (SE, 0.2%) met criteria for dependence. Individuals who used 2 or more drugs had an increased risk of both abuse (odds ratio, 5.17 [95% CI, 4.66-5.73]; P < .001) and dependence (odds ratio, 5.99 [95% CI, 5.02-7.16]; P < .001) and reduced probability of remission from abuse (odds ratio, 0.86 [95% CI, 0.76-0.98]; P = .02). Birth cohort prevalence of drug use was also significantly associated with both initiation and illicit drug use transitions; for example, after controlling for individuals' experience of substance use and demographics, for each additional 10% of an individual's cohort using alcohol, a person's odds of initiating drug use increased by 28% (odds ratio, 1.28 [95% CI, 1.26-1.31]). Each 10% increase in a cohort's use of drug increased individual risk by 12% (1.12 [95% CI, 1.11-1.14]). Conclusions and Relevance: Birth cohort substance use is associated with drug use involvement beyond the outcomes of individual histories of alcohol and other drug use. This has important implications for understanding pathways into and out of problematic drug use.

Nicotine Dependence and Pre-Enlistment Suicidal Behavior Among U.S. Army Soldiers.

INTRODUCTION: Identification of modifiable risk factors for suicidal behaviors is a priority for the U.S. Army. This study investigated associations of nicotine dependence with suicidal behaviors among incoming soldiers. METHODS: Lifetime DSM-IV nicotine dependence, mental disorders, suicidal behaviors, and their ages of onset were retrospectively assessed in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) New Soldier Study. Discrete-time survival analysis of person-year data from 30,436 soldiers was performed to evaluate associations of nicotine dependence with subsequent suicidal ideation, plans, and attempts. Among respondents with lifetime ideation (n=4,060), models tested associations of nicotine dependence with progression from ideation to first onset of plan, from plan to first attempt, and, among ideators without plans, from ideation to first unplanned attempt. A hierarchy of models incorporated increasing controls for other risk factors. Data were collected in 2011-2012 and analyzed in 2017-2018. RESULTS: In models controlling for sociodemographic characteristics, nicotine dependence was associated with onset of all suicidal behaviors (AORs, 2.07-4.08, p<0.001) and with each type of progression of suicidal behavior (AORs, 1.48-2.44, p<0.005). After adjusting for childhood adversities and mental disorders, nicotine dependence remained associated with onset of ideation (AOR=1.27, 95% CI=1.10, 1.46, p=0.001) and attempt (AOR=1.83, 95% CI=1.41, 2.37, p<0.001); and with progression from ideation to unplanned attempt (AOR=2.03, 95% CI=1.17, 1.74, p<0.001). CONCLUSIONS: Nicotine dependence exhibited associations with onset of suicidal ideation and suicide attempt-and with progression from ideation to unplanned attempt-that were independent of other measured risk factors. Awareness of associations of nicotine dependence with suicidal behaviors may inform risk assessment, facilitate targeting of prevention efforts, and provide further impetus for reducing nicotine dependence.

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

Prediction of major depressive disorder onset in college students.

BACKGROUND: Major depressive disorder (MDD) in college students is associated with substantial burden. AIMS: To assess 1-year incidence of MDD among incoming freshmen and predictors of MDD-incidence in a representative sample of students. METHOD: Prospective cohort study of first-year college students (baseline: n = 2,519, 1-year follow-up: n = 958) RESULTS: The incidence of MDD within the first year of college was 6.9% (SE = 0.8). The most important individual-level predictors of onset were prior suicide plans and/or attempts (OR = 9.5). The strongest population-level baseline predictors were history of childhood-adolescent trauma, stressful experience in the past 12 months, parental psychopathology, and other 12-month mental disorder. Multivariate cross-validated prediction (cross-validated AUC = 0.73) suggest that 36.1% of incident MDD cases in a replication sample would occur among the 10% of students at highest predicted risk (24.5% predicted incidence in this highest-risk subgroup). CONCLUSIONS: Screening at college entrance is a promising strategy to identify students at risk of MDD onset, which may improve the development and deployment of targeted preventive interventions.

Traumatic stress and accelerated DNA methylation age: A meta-analysis.

BACKGROUND: Recent studies examining the association between posttraumatic stress disorder (PTSD) and accelerated aging, as defined by DNA methylation-based estimates of cellular age that exceed chronological age, have yielded mixed results. METHODS: We conducted a meta-analysis of trauma exposure and PTSD diagnosis and symptom severity in association with accelerated DNA methylation age using data from 9 cohorts contributing to the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (combined N = 2186). Associations between demographic and cellular variables and accelerated DNA methylation age were also examined, as was the moderating influence of demographic variables. RESULTS: Meta-analysis of regression coefficients from contributing cohorts revealed that childhood trauma exposure (when measured with the Childhood Trauma Questionnaire) and lifetime PTSD severity evidenced significant, albeit small, meta-analytic associations with accelerated DNA methylation age (ps = 0.028 and 0.016, respectively). Sex, CD4T cell proportions, and natural killer cell proportions were also significantly associated with accelerated DNA methylation age (all ps < 0.02). PTSD diagnosis and lifetime trauma exposure were not associated with advanced DNA methylation age. There was no evidence of moderation of the trauma or PTSD variables by demographic factors. CONCLUSIONS: Results suggest that traumatic stress is associated with advanced epigenetic age and raise the possibility that cells integral to immune system maintenance and responsivity play a role in this. This study highlights the need for additional research into the biological mechanisms linking traumatic stress to accelerated DNA methylation age and the importance of furthering our understanding of the neurobiological and health consequences of PTSD.

The associations between psychotic experiences and substance use and substance use disorders: findings from the World Health Organization World Mental Health surveys.

BACKGROUND AND AIMS: Prior research has found bidirectional associations between psychotic experiences (PEs) and selected substance use disorders. We aimed to extend this research by examining the bidirectional association between PEs and various types of substance use (SU) and substance use disorders (SUDs), and the influence of antecedent mental disorders on these associations. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: We used data from the World Health Organization World Mental Health surveys. A total of 30 902 adult respondents across 18 countries were assessed for (a) six types of life-time PEs, (b) a range of types of SU and DSM-IV SUDs and (c) mental disorders using the Composite International Diagnostic Interview. Discrete-time survival analyses based on retrospective age-at-onset reports examined the bidirectional associations between PEs and SU/SUDs controlling for antecedent mental disorders. FINDINGS: After adjusting for demographics, comorbid SU/SUDs and antecedent mental disorders, those with prior alcohol use disorders [odds ratio (OR) = 1.6, 95% confidence interval (CI) = 1.2-2.0], extra-medical prescription drug use (OR = 1.5, 95% CI = 1.1-1.9), alcohol use (OR = 1.4, 95% CI = 1.1-1.7) and tobacco use (OR = 1.3, 95% CI = 1.0-1.8) had increased odds of subsequent first onset of PEs. In contrast, those with temporally prior PEs had increased odds of subsequent onset of tobacco use (OR = 1.5, 95% CI = 1.2-1.9), alcohol use (OR = 1.3, 95% CI = 1.1-1.6) or cannabis use (OR = 1.3, 95% CI = 1.0-1.5) as well as of all substance use disorders (ORs ranged between 1.4 and 1.5). There was a dose response relationship between both count and frequency of PEs and increased subsequent odds of selected SU/SUDs. CONCLUSIONS: Associations between psychotic experiences (PEs) and substance use/substance use disorders (SU/SUDs) are often bidirectional, but not all types of SU/SUDs are associated with PEs. These findings suggest that it is important to be aware of the presence of PEs within those with SUDs or at risk of SUDs, given the plausibility that they may each impact upon the other.

Alcohol Misuse and Co-Occurring Mental Disorders Among New Soldiers in the U.S. Army.

BACKGROUND: Problem drinking that predates enlistment into military service may contribute to the overall burden of alcohol misuse in the Armed Forces; however, evidence bearing on this issue is limited. This study examines prevalence and correlates of alcohol misuse among new U.S. Army soldiers. METHODS: Cross-sectional survey data were collected from soldiers reporting for basic combat training. The survey retrospectively assessed lifetime alcohol consumption and substance abuse/dependence, enabling estimation of the prevalence of lifetime binge drinking and heavy drinking in a sample of 30,583 soldiers and of probable alcohol use disorder (AUD) among 26,754 soldiers with no/minimal lifetime use of other drugs. Co-occurrence of mental disorders and other adverse outcomes with binge drinking, heavy drinking, and AUD was examined. Discrete-time survival analysis, with person-year the unit of analysis and a logistic link function, was used to estimate associations of AUD with subsequent onset of mental disorders and vice versa. RESULTS: Weighted prevalence of lifetime binge drinking was 27.2% (SE = 0.4) among males and 18.9% (SE = 0.7) among females; respective estimates for heavy drinking were 13.9% (SE = 0.3) and 9.4% (SE = 0.4). Among soldiers with no/minimal drug use, 9.5% (SE = 0.2) of males and 7.2% (SE = 0.5) of females had lifetime AUD. Relative to no alcohol misuse, binge drinking, heavy drinking, and AUD were associated with increased odds of all mental disorders and other adverse outcomes under consideration (adjusted odds ratios [AORs] = 1.5 to 4.6; ps < 0.001). Prior mental disorders and suicidal ideation were associated with onset of AUD (AORs = 2.3 to 2.8; ps < 0.001), and prior AUD was associated with onset of mental disorders and suicidal ideation (AORs = 2.0 to 3.2, ps < 0.005). CONCLUSIONS: Strong bidirectional associations between alcohol misuse and mental disorders were observed in a cohort of soldiers beginning Army service. Conjoint recognition of alcohol misuse and mental disorders upon enlistment may provide opportunities for risk mitigation early in a soldier's career.

Risk Factors, Methods, and Timing of Suicide Attempts Among US Army Soldiers.

IMPORTANCE: Suicide attempts in the US Army have risen in the past decade. Understanding the association between suicide attempts and deployment, as well as method and timing of suicide attempts, can assist in developing interventions. OBJECTIVE: To examine suicide attempt risk factors, methods, and timing among soldiers currently deployed, previously deployed, and never deployed at the time this study was conducted. DESIGN, SETTING, AND PARTICIPANTS: This longitudinal, retrospective cohort study of Regular Army-enlisted soldiers on active duty from 2004 through 2009 used individual-level person-month records to examine risk factors (sociodemographic, service related, and mental health), method, and time of suicide attempt by deployment status (never, currently, and previously deployed). Administrative data for the month before each of 9650 incident suicide attempts and an equal-probability sample of 153 528 control person-months for other soldiers were analyzed using a discrete-time survival framework. MAIN OUTCOMES AND MEASURES: Suicide attempts and career, mental health, and demographic predictors were obtained from administrative and medical records. RESULTS: Of the 9650 enlisted soldiers who attempted suicide, 86.3% were male, 68.4% were younger than 30 years, 59.8% were non-Hispanic white, 76.5% were high school educated, and 54.7% were currently married. The 40.4% of enlisted soldiers who had never been deployed (n = 12 421 294 person-months) accounted for 61.1% of enlisted soldiers who attempted suicide (n = 5894 cases). Risk among those never deployed was highest in the second month of service (103 per 100 000 person-months). Risk among soldiers on their first deployment was highest in the sixth month of deployment (25 per 100 000 person-months). For those previously deployed, risk was highest at 5 months after return (40 per 100 000 person-months). Currently and previously deployed soldiers were more likely to attempt suicide with a firearm than those never deployed (currently deployed: OR, 4.0; 95% CI, 2.9-5.6; previously deployed: OR, 2.7; 95% CI, 1.8-3.9). Across deployment status, suicide attempts were more likely among soldiers who were women (currently deployed: OR, 3.4; 95% CI, 3.0-4.0; previously deployed: OR, 1.5; 95% CI, 1.4-1.7; and never deployed: OR, 2.4; 95% CI, 2.3-2.6), in their first 2 years of service (currently deployed: OR, 1.9; 95% CI, 1.5-2.3; previously deployed: OR, 2.2; 95% CI, 1.9-2.7; and never deployed: OR, 3.1; 95% CI, 2.7-3.6), and had a recently received a mental health diagnosis in the previous month (currently deployed: OR, 29.8; 95% CI, 25.0-35.5; previously deployed: OR, 22.2; 95% CI, 20.1-24.4; and never deployed: OR, 15.0; 95% CI, 14.2-16.0). Among soldiers with 1 previous deployment, odds of a suicide attempt were higher for those who screened positive for depression or posttraumatic stress disorder after return from deployment and particularly at follow-up screening, about 4 to 6 months after deployment (depression: OR, 1.4; 95% CI, 1.1-1.9; posttraumatic stress disorder: OR, 2.4; 95% CI, 2.1-2.8). CONCLUSIONS AND RELEVANCE: Identifying the timing and risk factors for suicide attempt in soldiers requires consideration of environmental context, individual characteristics, and mental health. These factors can inform prevention efforts.

Associations between DSM-IV mental disorders and subsequent COPD diagnosis.

OBJECTIVES: COPD and mental disorder comorbidity is commonly reported, although findings are limited by substantive weaknesses. Moreover, few studies investigate mental disorder as a risk for COPD onset. This research aims to investigate associations between current (12-month) DSM-IV mental disorders and COPD, associations between temporally prior mental disorders and subsequent COPD diagnosis, and cumulative effect of multiple mental disorders. METHODS: Data were collected using population surveys of 19 countries (n=52,095). COPD diagnosis was assessed by self-report of physician's diagnosis. The World Mental Health-Composite International Diagnostic Interview (WMH-CIDI) was used to retrospectively assess lifetime prevalence and age at onset of 16 DSM-IV disorders. Adjusting for age, gender, smoking, education, and country, survival analysis estimated associations between first onset of mental disorder and subsequent COPD diagnosis. RESULTS: COPD and several mental disorders were concurrently associated across the 12-month period (ORs 1.5-3.8). When examining associations between temporally prior disorders and COPD, all but two mental disorders were associated with COPD diagnosis (ORs 1.7-3.5). After comorbidity adjustment, depression, generalized anxiety disorder, and alcohol abuse were significantly associated with COPD (ORs 1.6-1.8). There was a substantive cumulative risk of COPD diagnosis following multiple mental disorders experienced over the lifetime. CONCLUSIONS: Mental disorder prevalence is higher in those with COPD than those without COPD. Over time, mental disorders are associated with subsequent diagnosis of COPD; further, the risk is cumulative for multiple diagnoses. Attention should be given to the role of mental disorders in the pathogenesis of COPD using prospective study designs.

Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis.

BACKGROUND: Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis. METHODS: Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models. RESULTS: Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age<50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754). CONCLUSIONS: Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.