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BackgroundCognitive inhibition deficits have previously been found in suicide attempters. This study examined the neural basis for these deficits in depressed patients with and without a history of suicidal behavior.MethodFunctional magnetic resonance imaging was used to measure brain activation during the Go/No-Go response inhibition task in 25 unmedicated and depressed middle-aged suicide attempters, 22 unmedicated depressed patient controls with no personal or family history of suicidal behavior, and 27 healthy controls. Whole-brain analyses were conducted with SPM12.ResultsSuicide attempters exhibited an elevated number of commission errors relative to both control groups. However, suicide attempters did not differ from patient controls in terms of brain activation for any contrast. Analyses showed a significant association between depression and brain activation in the left inferior frontal gyrus and medial thalamus during Go v. No-Go, and in the bilateral parietal cortex and left orbitofrontal cortex during No-Go v. baseline. These regions were correlated with psychological pain, suicidal ideation and global functioning. There was no association between brain activation and personal histories of suicidal act.ConclusionsOur study suggests that deficits in cognitive inhibition, in relation to the inferior frontal gyrus, thalamus, orbitofrontal cortex and parietal cortex, are related to the depressive state and not specifically to suicide vulnerability. We hypothesize that state-related deficits may add to trait-like cognitive impairments to facilitate suicidal acts. These different types of cognitive impairments may necessitate different therapeutic strategies for the prevention of suicide. [ABSTRACT FROM PUBLISHER]

ABSTRACT BACKGROUND: Little is known about differential suicide profiles across the life trajectory. This study introduces the life-course method in suicide research with the aim of refining the longitudinal and cumulative assessment of psychosocial factors by quantifying accumulation of burden over time in order to delineate distinctive pathways of completed suicide.MethodThe psychological autopsy method was used to obtain third-party information on consecutive suicides. Life-history calendar analysis served to arrive at an adversity score per 5-year segment that was then cluster-analysed and correlated to define victim profiles. RESULTS: Two distinct life trajectories emerged: (1) individuals who experienced childhood traumas, developmental adversity and little protection were more likely to present concurrent psychiatric and Axis II disorders; and (2) individuals who experienced less adversity but seemed more reactive to later major difficulties. CONCLUSIONS: The life calendar approach presented here in suicide research adds to the identification of life events, distal and recent, previously associated with suicide. It also quantifies the burden of adversity over the life course, defining two distinct profiles that could benefit from distinct targeted preventive intervention. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND: Suicidal behaviors in young individuals represent an important public health problem. Understanding their natural history and relationships would therefore be of clinical and research value. In this study, we examined the natural histories of several suicidal behaviors and investigated two conceptual models of suicidality (dimensional and categorical) in the context of adolescent and adult-onset suicide attempts.MethodParticipants were members of a prospectively studied, representative, population-based school cohort followed since age 6 (n=3017) through mid-adolescence (n=1715) to their early twenties (n=1684). Outcome measures included suicidal ideation, attempts and completions. RESULTS: Approximately one in 500 individuals died by suicide. About 33% had suicidal ideas and 9.3% made at least one suicide attempt. Over half (4.9%) of the self-reported attempters made their first attempt before age 18. With the exception of current suicidal ideas, non-fatal suicidal behaviors were more prevalent in females. In general, parental and cross-sectional self-reports underestimated suicidality rates. Aikaike (AIC) and Bayesian (BIC) information criteria suggested the ordinal model, and dimensional conceptualization of suicide attempts of different onset age, to be more optimal than its multinomial/categorical counterpart (ordinal: AIC 567.55, BIC 635.67; multinomial: AIC 616.59, BIC 723.83). Both models, nevertheless, identified five common factors of relevance to suicidal diathesis: gender, disruptive disorders, childhood anxiousness and abuse, and suicidal thoughts. CONCLUSIONS: Non-fatal suicidal behaviors in adolescents and young adults are more common than suggested by cross-sectional studies and parental reports. The dimensional model may be more useful in explaining the relationship of suicide attempts of different age of onset. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND: Identification of factors that distinguish between ideators who act on their suicidal thoughts from those who do not is an important clinical and research objective.MethodWe examined correlates of suicide attempts in suicidal ideators, members of a French-Canadian, school-based cohort. Suicidal thoughts were evaluated in adolescence and early adulthood in the total sample of suicidal ideators, who were then stratified into subgroups consisting of persistent ideators, male ideators and female ideators. RESULTS: In addition to persistent suicidal ideas [odds ratios (ORs) 2.1-2.8], Axis I psychopathology, female gender and childhood sexual abuse (CSA) were the most consistent correlates of suicide attempts. Externalizing disorders were significant contributors in persistent ideators [drug misuse: OR 2.8, 95% confidence interval (CI) 1.1-6.9] and in male ideators in particular (disruptive disorders: OR 5.9, 95% CI 2.2-16.0). In women, psychiatric co-morbidity also had a significant effect (OR 1.6, 95% CI 1.1-2.1). CSA was of relevance in both women (OR 1.2, 95% CI 1.1-1.4) and persistent ideators (OR 1.3, 95% CI 1.1-1.5). Personality traits showed gender-specific contribution with affective instability (OR 1.1, 95% CI 1.01-1.1) and anxiousness (OR 1.3, 95% CI 1.1-1.7) contributing in men and disruptive aggression (OR 1.1, 95% CI 1.03-1.3) in women. CONCLUSIONS: Correlates of suicide attempts in suicidal ideators vary as a function of the persistence of suicidal ideas and gender. This heterogeneity across subgroups of suicidal ideators may be attributed, at least in part, to differences between the sexes, early environmental adversity, maladaptive personality, and psychiatric symptoms. Further exploration and continued prospective follow-up is necessary to examine these possibilities. [ABSTRACT FROM AUTHOR]

BACKGROUND: Adults in their twenties appear to be at high risk for suicidal behaviors (SBs) and there is substantial evidence suggesting that certain personality traits may increase individual vulnerability to suicide. METHOD: We investigated relationships of personality traits with two SBs in a cohort (n=1140) of 21- to 24-year-old adults, representative of the general population of Quebec. Subjects were assessed using a series of structured diagnostic and personality trait questionnaires. Multivariate logistic regression analyses were employed to identify personality trait correlates of suicide-attempt history and serious suicidal ideation in the context of other known risk factors, such as psychopathology and experiences of childhood sexual and physical abuse. RESULTS: Traits of conduct problems contributed to both suicide attempts [odds ratio (OR) 1.03, 95% confidence interval (CI) 1.01-1.06] and suicidal ideation (OR 1.04, 95% CI 1.02-1.07), while identity problems (OR 1.10, 95% CI 1.07-1.13) and gender-moderated impulsivity contributed exclusively to suicidal ideation. CONCLUSIONS: Personality traits may make independent contributions to current suicidal ideation and previous suicide attempts in certain subgroups of suicidal individuals. In order to further explore their utility as markers of suicide risk and targets of intervention further investigation in clinical samples and other cultural and age groups is necessary. [ABSTRACT FROM AUTHOR]

Background: Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers., Methods: In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively., Results: A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction., Conclusions: A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.

Background: Suicidal behavior is moderately heritable and a consequence of a combination of the diathesis traits for suicidal behavior and suicide-related major psychiatric disorders. Here, we sought to examine shared polygenic effects between various psychiatric disorders/traits and suicidal behavior and to compare the shared polygenic effects of various psychiatric disorders/traits on non-fatal suicide attempt and suicide death., Methods: We used our genotyped European ancestry sample of 260 non-fatal suicide attempters, 317 suicide decedents and 874 non-psychiatric controls to test whether polygenic risk scores (PRSs) obtained from large GWASs for 22 suicide-related psychiatric disorders/traits were associated with suicidal behavior. Results were compared between non-fatal suicide attempt and suicide death in a sensitivity analysis., Results: PRSs for major depressive disorder, bipolar disorder, schizophrenia, ADHD, alcohol dependence, sensitivity to environmental stress and adversity, educational attainment, cognitive performance, and IQ were associated with suicidal behavior (Bonferroni-corrected p < 2.5 × 10 -4 ). The polygenic effects of all 22 psychiatric disorders/traits had the same direction ( p for binomial tests = 4.8 × 10 -7 ) and were correlated (Spearman's ρ = 0.85) between non-fatal suicide attempters and suicide decedents., Conclusions: We found that polygenic effects for major psychiatric disorders and diathesis-related traits including stress responsiveness and intellect/cognitive function contributed to suicidal behavior. While we found comparable polygenic architecture between non-fatal suicide attempters and suicide decedents based on correlations with PRSs of suicide-related psychiatric disorders/traits, our analyses are limited by small sample size resulting in low statistical power to detect difference between non-fatal suicide attempt and suicide death.

Background: While childhood externalizing, internalizing and comorbid problems have been associated with suicidal risk, little is known about their specific associations with suicidal ideation and attempts. We examined associations between childhood externalizing, internalizing and comorbid problems and suicidal ideation (without attempts) and attempts by early adulthood, in males and females., Method: Participants were from the Quebec Longitudinal Study of Kindergarten Children, a population-based study of kindergarteners in Quebec from 1986 to 1988 and followed-up until 2005. We captured the co-development of teacher-rated externalizing and internalizing problems at age 6-12 using multitrajectories. Using the Diagnostic Interview Schedule administered at age 15 and 22, we identified individuals (1) who never experienced suicidal ideation/attempts, (2) experienced suicidal ideation but never attempted suicide and (3) attempted suicide., Results: The identified profiles were no/low problems (45%), externalizing (29%), internalizing (11%) and comorbid problems (13%). After adjusting for socioeconomic and familial characteristics, children with externalizing (OR 2.00, CI 1.39-2.88), internalizing (OR 2.34, CI 1.51-3.64) and comorbid (OR 3.29, CI 2.05-5.29) problems were at higher risk of attempting suicide ( v. non-suicidal) by age 22 than those with low/no problems. Females with comorbid problems were at higher risk of attempting suicide than females with one problem. Childhood problems were not associated with suicidal ideation. Externalizing (OR 2.01, CI 1.29-3.12) and comorbid problems (OR 2.28, CI 1.29-4.03) distinguished individuals who attempted suicide from those who thought about suicide without attempting., Conclusion: Childhood externalizing problems alone or combined with internalizing problems were associated with suicide attempts, but not ideation (without attempts), suggesting that these problems confer a specific risk for suicide attempts.

Background: We aimed to identify groups of children presenting distinct perinatal adversity profiles and test the association between profiles and later risk of suicide attempt., Methods: Data were from the Québec Longitudinal Study of Child Development (QLSCD, N = 1623), and the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 5734). Exposures to 32 perinatal adversities (e.g. fetal, obstetric, psychosocial, and parental psychopathology) were modeled using latent class analysis, and associations with a self-reported suicide attempt by age 20 were investigated with logistic regression. We investigated to what extent childhood emotional and behavioral problems, victimization, and cognition explained the associations., Results: In both cohorts, we identified five profiles: No perinatal risk, Poor fetal growth, Socioeconomic adversity, Delivery complications, Parental mental health problems (ALSPAC only). Compared to children with No perinatal risk, children in the Poor fetal growth (pooled estimate QLSCD-ALSPAC, OR 1.89, 95% CI 1.04-3.44), Socioeconomic adversity (pooled-OR 1.42, 95% CI 1.08-1.85), and Parental mental health problems (OR 1.74, 95% CI 1.27-2.40), but not Delivery complications, profiles were more likely to attempt suicide. The proportion of this effect mediated by the putative mediators was larger for the Socioeconomic adversity profile compared to the others., Conclusions: Perinatal adversities associated with suicide attempt cluster in distinct profiles. Suicide prevention may begin early in life and requires a multidisciplinary approach targeting a constellation of factors from different domains (psychiatric, obstetric, socioeconomic), rather than a single factor, to effectively reduce suicide vulnerability. The way these factors cluster together also determined the pathways leading to a suicide attempt, which can guide decision-making on personalized suicide prevention strategies.

Background: Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes., Methods: Of 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment., Results: Eight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56-0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72-0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy., Conclusions: The negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.

Background: Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment., Methods: In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy., Results: At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar., Conclusion: Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.

Background: Suicide is a leading cause of mortality in youth, yet the course of suicide attempts is poorly documented. We explored the vulnerable transition from adolescence to emerging adulthood to identify group trajectories and risk factors., Methods: The National Longitudinal Survey of Children and Youth is a prospective representative cohort of Canadian children. We followed participants aged 7-11 years in 1994-95 to age 23 (2008-09). We modelled self-reported past-year suicide attempts (ages 12 to 23 years) using growth mixture models. We analysed risk factors from self- and parent-report questionnaires at pre-adolescence (ages 10-11) and early adolescence (ages 12-13) using multinomial logistic regressions. Analyses were adjusted for sample non-response and attrition., Results: In 2233 participants answering questions on teen and adult suicide attempts, we identified three trajectories: never attempted (96.0%), adolescence-limited (2.0%) and persisting into adulthood (2.0%). Adolescent girls aged 12-13 with depression/anxiety symptoms, and with mothers experiencing depression had higher risks of adolescence-limited than never-attempted [relative risk RR 9.27 (95% confidence interval: 1.73-49.82); 2.03 (1.02-3.32), for each standard deviation increase; 1.07 (1.00-1.15); respectively]. Preteen ADHD symptoms increased the risk of attempts persisting into adulthood as compared to never-attempted [RR 2.05 (1.29-3.28) for each standard deviation increase]. Suicide death of schoolmate/acquaintance increased risks of an adulthood trajectory as compared to never-attempted and adolescence-limited [RR 8.41 (3.04-23.27) and 6.63 (1.29-34.06), respectively]., Conclusion: In half the participants attempting suicide, attempts continued into adulthood. We stress the need for preventive strategies in early adolescence and differential clinical/educational interventions as identified for each trajectory.

Background: Poor cognitive abilities and low intellectual quotient (IQ) are associated with an increased risk of suicide attempts and suicide mortality. However, knowledge of how this association develops across the life-course is limited. Our study aims to establish whether individuals who died by suicide by mid-adulthood are distinguishable by their child-to-adolescence cognitive trajectories., Methods: Participants were from the 1958 British Birth Cohort and were assessed for academic performance at ages 7, 11, and 16 and intelligence at 11 years. Suicides occurring by September 2012 were identified from linked national death certificates. We compared mean mathematics and reading abilities and rate of change across 7-16 years for individuals who died by suicide v. those still alive, with and without adjustment for potential early-life confounding factors. Analyses were based on 14 505 participants., Results: Fifty-five participants (48 males) had died by suicide by age 54 years. While males who died by suicide did not differ from participants still alive in reading scores at age 7 [effect size (g) = -0.04, p = 0.759], their reading scores had a less steep improvement up to age 16 compared to other participants. Adjustments for early-life confounding factors explained these differences. A similar pattern was observed for mathematics scores. There was no difference between individuals who died by suicide v. participants still alive on intelligence at 11 years., Conclusions: While no differences in tests of academic performance and IQ were observed, individuals who died by suicide had a less steep improvement in reading abilities over time compared to same-age peers.