Life events (LEs) are a risk factor for first onset and relapse of psychotic disorders. However, the impact of LEs on specific symptoms – namely reality distortion, disorganization, negative symptoms, depression, and mania – remains unclear. Moreover, the differential effects of negative v. positive LEs are poorly understood.

The present study utilizes an epidemiologic cohort of patients (N = 428) ascertained at first-admission for psychosis and followed for a decade thereafter. Symptoms were assessed at 6-, 24-, 48-, and 120-month follow-ups.

We examined symptom change within-person and found that negative events in the previous 6 months predicted an increase in reality distortion (β = 0.07), disorganized (β = 0.07), manic (β = 0.08), and depressive symptoms (β = 0.06), and a decrease in negative symptoms (β = −0.08). Conversely, positive LEs predicted fewer reality distortion (β = −0.04), disorganized (β = −0.04), and negative (β = −0.13) symptoms, and were unrelated to mood symptoms. A between-person approach to the same hypotheses confirmed that negative LEs predicted change in all symptoms, while positive LEs predicted change only in negative symptoms. In contrast, symptoms rarely predicted future LEs.

These findings confirm that LEs have an effect on symptoms, and thus contribute to the burden of psychotic disorders. That LEs increase positive symptoms and decrease negative symptoms suggest at least two different mechanisms underlying the relationship between LEs and symptoms. Our findings underscore the need for increased symptom monitoring following negative LEs, as symptoms may worsen during that time.

Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple learning models have been unable to provide a convincing account of why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment.

Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterised individuals with varying degrees of post-traumatic stress (N = 56). Model parameters describing individual differences in causal inference were related to multiple post-traumatic stress disorder (PTSD) and depression symptom dimensions via network analysis.

Individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, greater re-experiencing symptom severity was associated with a lower likelihood of inferring that multiple causes were active in the environment.

We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD. Specifically, a tendency to attribute a greater diversity of stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, impeding learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. In the future, better understanding of the role of causal inference in trauma-related psychopathology may help refine cognitive therapies for these disorders.

Studies of psychological interventions for the prevention of depression have found significant effects in the short-term, but the long-term efficacy has yet to be determined. This study evaluated the 8-year effect of a randomized controlled trial for indicated prevention of depression in female caregivers.

A total of 173 non-professional female caregivers with subclinical depressive symptoms not meeting criteria for a major depressive episode (MDE) were randomized to either a brief problem-solving intervention (n = 89) or usual-care control group (n = 84). Blinded evaluators conducted an assessment at the 8-year follow-up. The primary outcome was Depression Status, defined by diagnoses of MDE since the 1-year follow-up using the Structured Clinical Interview for the Disorders of the DSM-5. The secondary outcome was current Depressive Symptom Severity. Regression analyses were conducted to evaluate the effect of the intervention on the outcomes.

There were no significant differences in the Depression Status between the problem-solving (30.3%) and control groups (26.2%) (adjusted OR 1.25, 95% CI −0.58 to 2.69). Depressive Symptom Severity, however, was significantly lower in the problem-solving group compared to the control group at this follow-up, amounting to a small effect size of Cohen's d = 0.39 (adjusted B = −3.32, p = 0.018).

This is the first study to assess such a long-term follow-up of intervention of indicated prevention of depression. Results seem to indicate that the protective effect of the intervention became smaller over time during follow-up. Future research should replicate these results.

Depression even at the subclinical level is often accompanied by sleep disturbances, but little is known about the dynamics of the sleep stages in relation to depressive symptoms. We examined whether the amount, associations, and transition probabilities of various sleep stages were associated with depressive symptoms in a community sample of adolescents.

The participants (N = 172, 59% girls, mean age 16.9 years) underwent overnight polysomnography and provided data on depressive symptoms (Beck Depression Inventory II). The association between depression status and total duration of each stage type was analyzed using ANOVA and survival analyses. The associations between the number of different sleep stage types were analyzed using graphical Gaussian models, mixed graphical models, and relative importance networks. A Markov chain algorithm was used to estimate the transition probabilities between each state and these probabilities were further compared between depression status groups.

The associations between N1 and N3 were significantly stronger in both directions of the association (p-values for interactions 0.012 and 0.006) in those with more depressive symptoms. Similarly, a stronger association was observed from N1 to wake stage in those with more depressive symptoms (p-value for interaction 0.002). In those with more depressive symptoms, it was more likely to transition from N2 to N3 and from REM to N2 compared to others.

These findings indicate that changes in sleep architecture are not limited to clinical depression and that the transitional dynamics of sleep stages are an important marker of subclinical depression.

There are few theoretical proposals that attempt to account for the variation in affective processing across different affective states of bipolar disorder (BD). The Interacting Cognitive Subsystems (ICS) framework has been recently extended to account for manic states. Within the framework, positive mood state is hypothesized to tap into an implicational level of processing, which is proposed to be more extreme in states of mania.

Thirty individuals with BD and 30 individuals with no history of affective disorder were tested in euthymic mood state and then in induced positive mood state using the Question–Answer task to examine the mode of processing of schemas. The task was designed to test whether individuals would detect discrepancies within the prevailing schemas of the sentences.

Although the present study did not support the hypothesis that the groups differ in their ability to detect discrepancies within schemas, we did find that the BD group was significantly more likely than the control group to answer questions that were consistent with the prevailing schemas, both before and after mood induction.

These results may reflect a general cognitive bias, that individuals with BD have a tendency to operate at a more abstract level of representation. This may leave an individual prone to affective disturbance, although further research is required to replicate this finding.

Using three independent methods, prior studies in Swedish sibling pairs indicate that environmental factors contribute substantially to familial aggregation for drug abuse (DA). Could we replicate these results in cousin pairs?

Using multiple Swedish public databases (1964–2011), we defined DA using medical, legal or pharmacy registry records and examined concordance in full cousin pairs as a function of age differences, younger–older relationships and geographical proximity while growing up.

Replicating prior results in siblings, cousin pairs were significantly more similar in their history of DA if they were (i) closer versus more distant in age and (ii) grew up in high versus low geographical proximity to one another. Furthermore, controlling for background factors, having an older cousin with DA conveys a greater risk for DA than having a younger drug-abusing cousin. The greater transmission of DA from older to younger versus younger to older cousin was more prominent in pairs who grew up close to one another. In age difference and geographical proximity analyses, effects were consistently strongest in male–male cousin pairs. In analyses of older → younger versus younger → older transmission, effects were stronger in male–male and male–female than in female–female or female–male relative pairs.

In accord with prior results in siblings, environmental factors contribute substantially to the familial aggregation of DA in cousins and these effects are, in general, stronger in males than in females.

Preliminary evidence shows that discordance in stress experience, expression, and physiology (EEP) in adolescents is linked to depression, suicidal ideation (SI), non-suicidal self-injury (NSSI), and brain functioning. This study employs person-centered analysis to probe the relationship between stress responses, psychopathology, and neural patterns in female adolescents who are oversampled for engagement in NSSI.

Adolescent females (N = 109, ages 12–17) underwent a social stress test from which self-report measures of stress experience, observer ratings of stress expression, and physiological metrics of stress (via salivary cortisol) were obtained. Multi-trajectory modeling was employed to identify concordant and discordant stress EEP groups. Depressive symptoms, SI and attempt, NSSI engagement, frontal and limbic activation to emotional stimuli, and resting state fronto-limbic connectivity were examined in the EEP groups derived from the multi-trajectory models.

Four groups were identified, three of which demonstrated relatively concordant EEP and one which demonstrated discordant EEP (High Experience-High Expression-Low Physiology). Further, replicating past research, the High Experience-High Expression-Low Physiology discordant group exhibited higher depressive symptoms, SI, suicide attempt, and NSSI episodes (only for sensitivity analyses based on past year) relative to other EEP groups. No significant group differences in brain functioning emerged.

Results indicate that within-person, multi-level patterns in stress responding capture risk for dysfunction including depression and self-injurious thoughts and behaviors. Further interrogating of system-level stress functioning may better inform assessment and intervention efforts.

Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results.

Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes.

The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased.

SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.

This study assessed the extent to which women's preconception binge drinking, tobacco use and cannabis use, reported prospectively in adolescence and young adulthood, predicted use of these substances during pregnancy and at 1 year postpartum.

Data were pooled from two intergenerational cohort studies: the Australian Temperament Project Generation 3 Study (395 mothers, 691 pregnancies) and the Victorian Intergenerational Health Cohort Study (398 mothers, 609 pregnancies). Alcohol, tobacco and cannabis use were assessed in adolescence (13–18 years), young adulthood (19–29 years) and at ages 29–35 years for those transitioning to parenthood. Exposures were weekly or more frequent preconception binge drinking (5 + drinks in one session), tobacco use and cannabis use. Outcomes were any alcohol, tobacco and cannabis use prior to awareness of the pregnancy, after awareness of pregnancy (up to and including the third trimester pregnancy) and at 1 year postpartum.

Frequent preconception binge drinking, tobacco use and cannabis use across both adolescence and young adulthood were strong predictors of continued use post-conception, before and after awareness of the pregnancy and at 1 year postpartum. Substance use limited to young adulthood also predicted continued use post-conception.

Persistent alcohol, tobacco use and cannabis use that starts in adolescence has a strong continuity into parenthood. Reducing substance use in the perinatal period requires action well before pregnancy, commencing in adolescence and continuing into the years before conception and throughout the perinatal period.

The transition to adolescence implicates heightened vulnerability alongside increased opportunities for resilience. Contexts of early life stress (ELS) exacerbate risk; still, little research addressed biobehavioral mediators of risk and resilience across the adolescent transition following ELS. Utilizing a unique cohort, we tested biosocial moderators of chronicity in adolescents’ internalizing disorders v. resilience.

Families exposed to chronic war-related trauma, v. controls, were followed. We utilized data from three time-points framing the adolescent transition: late childhood (N = 177, Mage = 9.3 years ± 1.41), early adolescence (N = 111, Mage = 11 0.66 years ± 1.23), and late adolescence (N = 138, Mage = 15.65 years ± 1.31). In late childhood and late adolescence children's internalizing disorders were diagnosed. At early adolescence maternal and child's hair cortisol concentrations (HCC), maternal sensitivity, and mothers’ post-traumatic symptoms evaluated.

War-exposed children exhibited more internalizing disorders of chronic trajectory and mothers were less sensitive and more symptomatic. Three pathways elucidated the continuity of psychopathology: (a) maternal sensitivity moderated the risk of chronic psychopathology, (b) maternal post-traumatic symptoms mediated continuity of risk, (c) trauma exposure moderated the association between child internalizing disorders at late childhood and maternal HCC, which linked with child HCC. Child HCC linked with maternal post-traumatic symptoms, which were associated with child disorders in late adolescence.

Results demonstrate the complex interplay of maternal and child's biosocial factors as mediators and moderators of risk chronicity across the adolescent transition following trauma. Findings are first to utilize maternal and child's HCC as biomarkers of chronic stress v. resilience during adolescence, a period of neural reorganization and personal growth that shapes the individual's lifetime adaptation.