Much of suicide research focuses on suicide attempt (SA) survivors. Given that more than half of the suicide decedent population dies on their first attempt, this means a significant proportion of the population that dies by suicide is overlooked in research. Little is known about persons who die by suicide on their first attempt–and characterizing this understudied population may improve efforts to identify more individuals at risk for suicide.

Data were derived from the National Violent Death Reporting System, from 2005 to 2013. Suicide cases were included if they were 18–89 years old, with a known circumstance leading to their death based on law enforcement and/or medical examiner reports. Decedents with and without a history of SA were compared on demographic, clinical, and suicide characteristics, and circumstances that contributed to their suicide.

A total of 73 490 cases met criteria, and 57 920 (79%) died on their first SA. First attempt decedents were more likely to be male, married, African-American, and over 64. Demographic-adjusted models showed that first attempt decedents were more likely to use highly lethal methods, less likely to have a known mental health problem or to have disclosed their intent to others, and more likely to die in the context of physical health or criminal/legal problem.

First attempt suicide decedents are demographically different from decedents with a history of SA, are more likely to use lethal methods and are more likely to die in the context of specific stressful life circumstances.

Psychiatric disorders, including eating disorders (EDs), have clinical outcomes that range widely in severity and chronicity. The ability to predict such outcomes is extremely limited. Machine-learning (ML) approaches that model complexity may optimize the prediction of multifaceted psychiatric behaviors. However, the investigations of many psychiatric concerns have not capitalized on ML to improve prognosis. This study conducted the first comparison of an ML approach (elastic net regularized logistic regression) to traditional regression to longitudinally predict ED outcomes.

Females with heterogeneous ED diagnoses completed demographic and psychiatric assessments at baseline (n = 415) and Year 1 (n = 320) and 2 (n = 277) follow-ups. Elastic net and traditional logistic regression models comprising the same baseline variables were compared in ability to longitudinally predict ED diagnosis, binge eating, compensatory behavior, and underweight BMI at Years 1 and 2.

Elastic net models had higher accuracy for all outcomes at Years 1 and 2 [average Area Under the Receiving Operating Characteristics Curve (AUC) = 0.78] compared to logistic regression (average AUC = 0.67). Model performance did not deteriorate when the most important predictor was removed or an alternative ML algorithm (random forests) was applied. Baseline ED (e.g. diagnosis), psychiatric (e.g. hospitalization), and demographic (e.g. ethnicity) characteristics emerged as important predictors in exploratory predictor importance analyses.

ML algorithms can enhance the prediction of ED symptoms for 2 years and may identify important risk markers. The superior accuracy of ML for predicting complex outcomes suggests that these approaches may ultimately aid in advancing precision medicine for serious psychiatric disorders.

Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD.

GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls.

The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD.

Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Patients with obsessive–compulsive disorder (OCD) have to repeat their actions before feeling satisfied that the action reached its intended goal. Learning theory predicts that this may be due to a failure in the processing of external feedback.

We examined the performance of 29 OCD patients and 28 healthy volunteers on an associative learning task, in which initial learning is based solely on external feedback signals. Feedback valence was manipulated with monetary gains and losses.

As predicted, OCD patients were impaired during initial, external feedback-driven learning but not during later learning stages. The emotional salience of the feedback modulated learning during the initial stage in patients and controls alike. During later learning stages, however, patients approached near-normal performance with rewarding feedback but continued to produce deficient learning with punishing feedback.

OCD patients have a fundamental impairment in updating behavior based on the external outcome of their actions, possibly mediated by faulty error signals in response selection processes.

C-reactive protein (CRP) is a non-specific marker of inflammation that has been associated with depression and vascular disease, particularly in men. This study aimed to investigate the association between high CRP concentration and depression while taking physical health into account.

A cross-sectional study of a community-dwelling sample of 5438 men aged 70+. Participants with scores ⩾7 on the 15-item Geriatric Depression Scale (GDS-15) were considered to display clinically significant depressive symptoms. We measured the serum concentration of CRP with a high-sensitivity assay. The assessment of physical co-morbidity included three components: the Charlson weighted index, self-report of major health events on a standardized questionnaire, and the physical component of the 36-item Short-Form Health Survey (SF-36). Other measured factors included age, native language, education, a standardized socio-economic index, smoking, prior or current history of depression treatment, cognitive impairment (Mini-Mental State Examination score <24) and body mass index (BMI).

Participants with depression (n=340) were older than their controls without depression (age in years: 76·6±4·4 v. 75·4±4·1). Men with CRP concentration >3 mg/l had an increased odds ratio (OR) [1·59, 95% confidence interval (CI) 1·20–2·11] of being depressed compared to men with CRP ⩽3 mg/l. This association became non-significant once we adjusted the analysis for the measures of physical co-morbidity and other confounding factors (OR 1·22, 95% CI 0·86–1·73).

The physiological mechanisms that lead to the onset and maintenance of depressive symptoms in older men remain to be determined, but CRP concentration is unlikely to play a significant role in that process.

The aetiology of depression is multifactorial, with biological, cognitive and environmental factors across the life course influencing risk of a depressive episode. There is inconsistent evidence linking early life development and later depression. The aim of this study was to investigate relationships between low birthweight (LBW), infant neurodevelopment, and acute and chronic stress as components in pathways to depression in adulthood.

The sample included 4627 members of the National Survey of Health and Development (NSHD; the 1946 British birth cohort). Weight at birth, age of developmental milestones, economic deprivation in early childhood, acute stressors in childhood and adulthood, and socio-economic status (SES) in adulthood were assessed for their direct and indirect effects on adolescent (ages 13 and 15 years) and adult (ages 36, 43 and 53 years) measures of depressive symptoms in a structural equation modelling (SEM) framework. A structural equation model developed to incorporate all variables exhibited excellent model fit according to several indices.

The path of prediction from birthweight to age of developmental milestones to adolescent depression/anxiety to adult depression/anxiety was significant (p < 0.001). Notably, direct paths from birthweight (p = 0.25) and age of developmental milestones (p = 0.23) to adult depression were not significant. Childhood deprivation and stressors had important direct and indirect effects on depression. Stressors in adulthood were strongly associated with adult depression.

Depression in adulthood is influenced by an accumulation of stressors across the life course, including many that originate in the first years of life. Effects of early-life development on mental health appear by adolescence.

Perinatal factors seem to be implicated in the pathogenesis of anorexia nervosa (AN) and may be involved in the programming of stress response systems in humans. Our aim was to explore one of the possible pathways to explain the association between perinatal complications and a psychiatric disorder. In particular, we tested the hypothesis that neonatal immaturity may confer an enhanced vulnerability to AN after exposure to a severe stressful event, such as childhood abuse.

The sample was composed of subjects who took part in a prevalence study carried out on a representative sample of the general population and cases of AN referred to an out-patient specialist unit. All subjects (n=663) were born in the two obstetric wards of Padua Hospital between 1971 and 1979. We analysed data using both a case-control and a cohort design.

We found that functional signs of neonatal dysmaturity, but not a low birthweight or prematurity, had a significant additive interaction with childhood abuse in determining the risk for this illness. In normal subjects, but not in subjects with AN, neonatal dysmaturity was associated with being small, short or thin for gestational age at birth.

The synergistic effect of neonatal dysmaturity and childhood abuse in increasing the risk for AN provides evidence for the hypothesis that a prenatal programming of stress response systems can result in an impairment of the individual's resilience to severe stressful events.

Ethnicity is an important determinant of mental health outcomes including suicidality (i.e. suicidal ideation and suicide attempt). Understanding ethnic differences in the pathways to suicidality is important for suicide prevention efforts in ethnically diverse populations. These pathways can be conceptualized within a social stress framework.

The study examines ethnic differences in the pathways to suicidality in Canada within a social stress framework. Using data from the Canadian Community Health Survey Cycle 1.1 (CCHS 1.1) and path analysis, we examined the hypotheses that variations in (1) socio-economic status (SES), (2) sense of community belonging (SCB), (3) SES and SCB combined, and (4) SES, SCB and clinical factors combined can explain ethnic differences in suicidality.

Francophone whites and Aboriginals were more likely to report suicidality compared to Anglophone whites whereas visible minorities and Foreign-born whites were least likely. Disadvantages in income, income and education, income and its combined effect with depression and alcohol dependence/abuse led to high rates even among the low-risk visible minority group. Indirect pathways for Asians differed from that of Blacks and South Asians, specifically through SCB. With the exception of SCB, Aboriginals were most disadvantaged, which exacerbated their risk for suicidality. However, their strong SCB buffered the risk for suicidality across pathways. Disadvantages in education, income and SCB were associated with the high risk for suicidality in Francophone whites.

Francophone whites and Aboriginals had higher odds of suicidality compared to Anglophone whites; however, some pathways differed, indicating the need for targeted program planning and prevention efforts.

Normative and pathological personality traits have rarely been integrated into a joint large-scale structural analysis with psychiatric disorders, although a recent study suggested they entail a common individual differences continuum.

We explored the joint factor structure of 11 psychiatric disorders, five personality-disorder trait domains (DSM-5 Section III), and five normative personality trait domains (the ‘Big Five’) in a population-based sample of 2796 Norwegian twins, aged 19‒46.

Three factors could be interpreted: (i) a general risk factor for all psychopathology, (ii) a risk factor specific to internalizing disorders and traits, and (iii) a risk factor specific to externalizing disorders and traits. Heritability estimates for the three risk factor scores were 48% (95% CI 41‒54%), 35% (CI 28‒42%), and 37% (CI 31‒44%), respectively. All 11 disorders had uniform loadings on the general factor (congruence coefficient of 0.991 with uniformity). Ignoring sign and excluding the openness trait, this uniformity of factor loadings held for all the personality trait domains and all disorders (congruence 0.983).

Based on our findings, future research should investigate joint etiologic and transdiagnostic models for normative and pathological personality and other psychopathology.

Monoamine oxidase A (MAOA) is an important enzyme that metabolizes monoamines such as serotonin, norepinephrine and dopamine in the brain. In prefrontal cortex, low MAOA binding is associated with aggression and high binding is associated with major depressive disorder (MDD) and also risk for recurrence of depressive episodes. In rodent models, low MAOA levels are associated with increased aggression and fear conditioning, and decreased social and exploratory investigative behaviors. Our objective was to measure MAOA binding in prefrontal cortex and concurrently evaluate a broad range of validated personality traits. We hypothesized that prefrontal MAOA binding would correlate negatively with angry-hostility, a trait related to aggression/anger, and positively with traits intuitively related to adaptive investigative behavior.

Participants were aged 19–49 years, healthy and non-smoking. MAOA binding was measured with [11C]harmine positron emission tomography (PET) in prefrontal brain regions and personality traits were measured with the NEO Personality Inventory Revised (NEO PI-R).

Prefrontal MAOA binding correlated negatively with angry-hostility (r=−0.515, p=0.001) and positively with deliberation (r=0.514, p=0.001). In a two-factor regression model, these facets explained 38% of variance in prefrontal MAOA binding. A similar relationship was found in prefrontal cortex subregions.

We propose a new continuum describing the relationship between personality and MAOA: deliberate/thoughtful contrasting aggressive/impulsive. Additionally, the association between high MAOA binding and greater deliberation may explain why some people have moderately high levels of MAOA, although very high levels occur during MDD. In health, higher MAOA binding is associated with an adaptive personality facet.

Identification of emotional facial expression and emotional prosody (i.e. speech melody) is often impaired in schizophrenia. For facial emotion identification, a recent study suggested that the relative deficit in schizophrenia is enhanced when the presented emotion is easier to recognize. It is unclear whether this effect is specific to face processing or part of a more general emotion recognition deficit.

We used clarity-graded emotional prosodic stimuli without semantic content, and tested 25 in-patients with paranoid schizophrenia, 25 healthy control participants and 25 depressive in-patients on emotional prosody identification. Facial expression identification was used as a control task.

Patients with paranoid schizophrenia performed worse than both control groups in identifying emotional prosody, with no specific deficit in any individual emotion category. This deficit was present in high-clarity but not in low-clarity stimuli. Performance in facial control tasks was also impaired, with identification of emotional facial expression being a better predictor of emotional prosody identification than illness-related factors. Of those, negative symptoms emerged as the best predictor for emotional prosody identification.

This study suggests a general deficit in identifying high-clarity emotional cues. This finding is in line with the hypothesis that schizophrenia is characterized by high noise in internal representations and by increased fluctuations in cerebral networks.