Identifying adolescents at risk of internalizing problems is a key priority. However, studies have tended to consider such problems in simple ways using diagnoses, or item summaries. Network theory and methods instead allow for more complex interaction between symptoms. Two key hypotheses predict differences in global network properties for those at risk: altered structure and increased connectivity.

The current study evaluated these hypotheses for nine risk factors (e.g. income deprivation and low parent/carer support) individually and cumulatively in a large sample of 12–15 year-olds (N = 34 564). Recursive partitioning and bootstrapped networks were used to evaluate structural and connectivity differences.

The pattern of network interactions was shown to be significantly different via recursive partitioning for all comparisons across risk-present/absent groups and levels of cumulative risk, except for income deprivation. However, the magnitude of differences appeared small. Most individual risk factors also showed relatively small effects for connectivity. Exceptions were noted for gender and sexual minority risk groups, as well as low parent/carer support, where larger effects were evident. A strong linear trend was observed between increasing cumulative risk exposure and connectivity.

A robust approach to considering the effect of risk exposure on global network properties was demonstrated. Results are consistent with the ideas that pathological states are associated with higher connectivity, and that the number of risks, regardless of their nature, is important. Gender/sexual minority status and low parent/carer support had the biggest individual impacts on connectivity, suggesting these are particularly important for identification and prevention.

Psychosis is one of the most disabling psychiatric disorders. Pediatric traumatic brain injury (pTBI) has been cited as a developmental risk factor for psychosis, however this association has never been assessed meta-analytically.

A systematic review and meta-analysis of the association between pTBI and subsequent psychotic disorders/symptoms was performed. The study was pre-registered (CRD42022360772) adopting a random-effects model to estimate meta-analytic odds ratio (OR) and 95% confidence interval (CI) using the Paule–Mandel estimator. Subgroup (study location, study design, psychotic disorder v. subthreshold symptoms, assessment type, and adult v. adolescent onset) and meta-regression (quality of evidence) analyses were also performed. The robustness of findings was assessed through sensitivity analyses. The meta-analysis is available online as a computational notebook with an open dataset.

We identified 10 relevant studies and eight were included in the meta-analysis. Based on a pooled sample size of 479686, the pooled OR for the association between pTBI and psychosis outcomes was 1.80 (95% CI 1.11–2.95). There were no subgroup effects and no outliers. Both psychotic disorder and subthreshold symptoms were associated with pTBI. The overall association remained robust after removal of low-quality studies, however the OR reduced to 1.43 (95% CI 1.04–1.98). A leave-one-out sensitivity analysis showed the association was robust to removal of all but one study which changed the estimate to marginally non-significant.

We report cautious meta-analytic evidence for a positive association between pTBI and future psychosis. New evidence will be key in determining long-term reliability of this finding.

Individuals with schizophrenia spectrum and related psychotic disorders (SSD) experience significant impairments in social cognition that impede functioning. Social cognition is a multidimensional construct consisting of four domains: 1. theory of mind, 2. emotion processing, 3. attributional style and 4. social perception. Metacognitive training (MCT) is an intervention designed to target cognitive biases in psychosis containing two modules addressing social cognition.

A systematic review and meta-analysis was conducted to investigate the effects of MCT on social cognition and two of its domains: theory of mind and emotion processing. Ten electronic databases were scoured from 2007 to 1 February 2022 for MCT studies reporting social cognition outcomes for people with SSD (1050 identified, 282 assessed). Effect sizes were calculated using Cohen's d in R.

Nine studies were included in the meta-analysis (nMCT = 212, ncontrol = 194). MCT had a small but positive effect on global social cognition (d = 0.28 [95% CI 0.07–0.49]) and theory of mind (d = 0.27 [95% CI 0.01–0.52]). MCT showed no evidence of an effect on emotion processing (d = 0.03 [95% CI –0.26 to 0.32]).

MCT has a small but significant effect on social cognition for people with SSD. Our results add to other recent meta-analyses showing significant effects of MCT on clinically relevant outcomes such as positive symptoms, cognitive biases and cognitive insight. We recommend that future studies on MCT report outcomes on all four domains of social cognition.

PROSPERO (in the process of registration) available at https://www.crd.york.ac.uk/prospero/#recordDetails

This paper investigates whether age of onset of depression, duration of the last episode, number of episodes, and residual symptoms of depression and anxiety are associated with depression relapse in primary care patients who have been on long–term maintenance antidepressant treatment and no longer meet ICD10 criteria for depression.

An observational cohort using data from ANTLER (N = 478), a double-blind placebo-controlled trial. The primary outcome was time to relapse using the retrospective CIS-R. Participants were followed for 12 months.

Primary outcome was available for 468 participants. Time to relapse in those with more than five previous episodes of depression was shorter, hazard ratio (HR) 1.84 (95% confidence interval [CI] 1.23–2.75) compared to people with two episodes; HR 1.57 (95% CI 1.01–2.43) after adjustment. The residual symptoms of depression at baseline were also associated with increased relapse: HR 1.05 (95% CI 1.01–1.09) and HR 1.06 (95% CI 1.01–1.12) in the adjusted model. There was evidence of reduced rate of relapse in older age of onset group: HR 0.86 (95% CI 0.78–0.95); HR attenuated after adjustment HR 0.91 (95% CI 0.81–1.02). There was no evidence of an association between duration of the current episode and residual anxiety symptoms with relapse.

The number of previous episodes and residual symptoms of depression were associated with increased likelihood of relapse. These factors could inform joint decision making when patients are considering tapering off maintenance antidepressant treatment or considering other treatments to prevent relapse.

Individuals with schizophrenia exposed to second-generation antipsychotics (SGA) have an increased risk for diabetes, with aripiprazole purportedly a safer drug. Less is known about the drugs' mortality risk or whether serious mental illness (SMI) diagnosis or race/ethnicity modify these effects.

Authors created a retrospective cohort of non-elderly adults with SMI initiating monotherapy with an SGA (olanzapine, quetiapine, risperidone, and ziprasidone, aripiprazole) or haloperidol during 2008–2013. Three-year diabetes incidence or all-cause death risk differences were estimated between each drug and aripiprazole, the comparator, as well as effects within SMI diagnosis and race/ethnicity. Sensitivity analyses evaluated potential confounding by indication.

38 762 adults, 65% White and 55% with schizophrenia, initiated monotherapy, with haloperidol least (6%) and quetiapine most (26·5%) frequent. Three-year mortality was 5% and diabetes incidence 9.3%. Compared with aripiprazole, haloperidol and olanzapine reduced diabetes risk by 1.9 (95% CI 1.2–2.6) percentage points, or a 18.6 percentage point reduction relative to aripiprazole users' unadjusted risk (10.2%), with risperidone having a smaller advantage. Relative to aripiprazole users' unadjusted risk (3.4%), all antipsychotics increased mortality risk by 1.1–2.2 percentage points, representing 32.4–64.7 percentage point increases. Findings within diagnosis and race/ethnicity were generally consistent with overall findings. Only quetiapine's higher mortality risk held in sensitivity analyses.

Haloperidol's, olanzapine's, and risperidone's lower diabetes risks relative to aripiprazole were not robust in sensitivity analyses but quetiapine's higher mortality risk proved robust. Findings expand the evidence on antipsychotics' risks, suggesting a need for caution in the use of quetiapine among individuals with SMI.

Stress and depression have a reciprocal relationship, but the neural underpinnings of this reciprocity are unclear. We investigated neuroimaging phenotypes that facilitate the reciprocity between stress and depressive symptoms.

In total, 22 195 participants (52.0% females) from the population-based UK Biobank study completed two visits (initial visit: 2006–2010, age = 55.0 ± 7.5 [40–70] years; second visit: 2014–2019; age = 62.7 ± 7.5 [44–80] years). Structural equation modeling was used to examine the longitudinal relationship between self-report stressful life events (SLEs) and depressive symptoms. Cross-sectional data were used to examine the overlap between neuroimaging correlates of SLEs and depressive symptoms on the second visit among 138 multimodal imaging phenotypes.

Longitudinal data were consistent with significant bidirectional causal relationship between SLEs and depressive symptoms. In cross-sectional analyses, SLEs were significantly associated with lower bilateral nucleus accumbal volume and lower fractional anisotropy of the forceps major. Depressive symptoms were significantly associated with extensive white matter hyperintensities, thinner cortex, lower subcortical volume, and white matter microstructural deficits, mainly in corticostriatal-limbic structures. Lower bilateral nucleus accumbal volume were the only imaging phenotypes with overlapping effects of depressive symptoms and SLEs (B = −0.032 to −0.023, p = 0.006–0.034). Depressive symptoms and SLEs significantly partially mediated the effects of each other on left and right nucleus accumbens volume (proportion of effects mediated = 12.7–14.3%, p < 0.001−p = 0.008). For the left nucleus accumbens, post-hoc seed-based analysis showed lower resting-state functional connectivity with the left orbitofrontal cortex (cluster size = 83 voxels, p = 5.4 × 10−5) in participants with high v. no SLEs.

The nucleus accumbens may play a key role in the reciprocity between stress and depressive symptoms.

Two established staging models outline the longitudinal progression in bipolar disorder (BD) based on episode recurrence or inter-episodic functioning. However, underlying neurobiological mechanisms and corresponding biomarkers remain unexplored. This study aimed to investigate if global and (sub)cortical brain structures, along with brain-predicted age difference (brain-PAD) reflect illness progression as conceptualized in these staging models, potentially identifying brain-PAD as a biomarker for BD staging.

In total, 199 subjects with bipolar-I-disorder and 226 control subjects from the Dutch Bipolar Cohort with a high-quality T1-weighted magnetic resonance imaging scan were analyzed. Global and (sub)cortical brain measures and brain-PAD (the difference between biological and chronological age) were estimated. Associations between individual brain measures and the stages of both staging models were explored.

A higher brain-PAD (higher biological age than chronological age) correlated with an increased likelihood of being in a higher stage of the inter-episodic functioning model, but not in the model based on number of mood episodes. However, after correcting for the confounding factors lithium-use and comorbid anxiety, the association lost significance. Global and (sub)cortical brain measures showed no significant association with the stages.

These results suggest that brain-PAD may be associated with illness progression as defined by impaired inter-episodic functioning. Nevertheless, the significance of this association changed after considering lithium-use and comorbid anxiety disorders. Further research is required to disentangle the intricate relationship between brain-PAD, illness stages, and lithium intake or anxiety disorders. This study provides a foundation for potentially using brain-PAD as a biomarker for illness progression.

Suicidal behaviors are prevalent among college students; however, students remain reluctant to seek support. We developed a predictive algorithm to identify students at risk of suicidal behavior and used telehealth to reduce subsequent risk.

Data come from several waves of a prospective cohort study (2016–2022) of college students (n = 5454). All first-year students were invited to participate as volunteers. (Response rates range: 16.00–19.93%). A stepped-care approach was implemented: (i) all students received a comprehensive list of services; (ii) those reporting past 12-month suicidal ideation were directed to a safety planning application; (iii) those identified as high risk of suicidal behavior by the algorithm or reporting 12-month suicide attempt were contacted via telephone within 24-h of survey completion. Intervention focused on support/safety-planning, and referral to services for this high-risk group.

5454 students ranging in age from 17–36 (s.d. = 5.346) participated; 65% female. The algorithm identified 77% of students reporting subsequent suicidal behavior in the top 15% of predicted probabilities (Sensitivity = 26.26 [95% CI 17.93–36.07]; Specificity = 97.46 [95% CI 96.21–98.38], PPV = 53.06 [95% CI 40.16–65.56]; AUC range: 0.895 [95% CIs 0.872–0.917] to 0.966 [95% CIs 0.939–0.994]). High-risk students in the Intervention Cohort showed a 41.7% reduction in probability of suicidal behavior at 12-month follow-up compared to high-risk students in the Control Cohort.

Predictive risk algorithms embedded into universal screening, coupled with telehealth intervention, offer significant potential as a suicide prevention approach for students.

Response inhibition − or the ability to withhold a suboptimal response − relies on the efficacy of fronto-striatal networks, and is impaired in neuropsychiatric disorders including addiction. Cortical paired associative stimulation (cPAS) is a form of transcranial magnetic stimulation (TMS) which can strengthen neuronal connections via spike-timing-dependent plasticity mechanisms. Here, we used cPAS targeting the fronto-striatal inhibitory network to modulate performance on a response inhibition measure in chronic alcohol use.

Fifty-five participants (20 patients with a formal alcohol use disorder (AUD) diagnosis (26–74 years, 6[30%] females) and 20 matched healthy controls (HCs) (27–73 years, 6[30%] females) within a larger sample of 35 HCs (23–84 years, 11[31.4%] females) underwent two randomized sessions of cPAS 1-week apart: right inferior frontal cortex stimulation preceding right presupplementary motor area stimulation by either 4 ms (excitation condition) or 100 ms (control condition), and were subsequently administered the Stop Signal Task (SST) in both sessions.

HCs showed decreased stop signal reaction time in the excitation condition (t(19) = −3.01, p = 0.007, [CIs]:−35.6 to −6.42); this facilitatory effect was not observed for AUD (F(1,31) = 9.57, p = 0.004, CIs: −68.64 to −14.11). Individually, rates of SST improvement were substantially higher for healthy (72%) relative to AUD (13.6%) groups (OR: 2.33, p = 0.006, CIs:−3.34 to −0.55).

In line with previous findings, cPAS improved response inhibition in healthy adults by strengthening the fronto-striatal network through putative long-term potentiation-like plasticity mechanisms. Furthermore, we identified a possible marker of impaired cortical excitability, and, thus, diminished capacity for cPAS-induced neuroplasticity in AUD with direct implications to a disorder-relevant cognitive process.

Learning from rewarded and punished choices is perturbed in depressed patients, suggesting that abnormal reinforcement learning may be a cognitive mechanism of the illness. However, previous studies have disagreed about whether this behavior is produced by alterations in the rate of learning or sensitivity to experienced outcomes. This previous work has generally assessed learning in response to binary outcomes of one valence, rather than to both rewarding and punishing continuous outcomes.

A novel drifting reward and punishment magnitude reinforcement-learning task was administered to patients with current (n = 40) and remitted depression (n = 39), and healthy volunteers (n = 40) to capture potential differences in learning behavior. Standard questionnaires were administered to measure self-reported depressive symptom severity, trait and state anxiety and level of anhedonic symptoms.

Our findings demonstrate that patients with current depression adjust their learning behaviors to a lesser degree in response to trial-by-trial variations in reward and loss magnitudes than the other groups. Computational modeling revealed that this behavioral signature of current depressive state is better accounted for by reduced reward and punishment sensitivity (all p < 0.031), rather than a change in learning rate (p = 0.708). However, between-group differences were not related to self-reported symptom severity or comorbid anxiety disorders in the current depression group.

These findings suggest that current depression is associated with reduced outcome sensitivity rather than altered learning rate. Previous findings reported in this domain mainly from binary learning tasks seem to generalize to learning from continuous outcomes.

Individuals with serious mental illness have a markedly shorter life expectancy. A major contributor to premature death is cardiovascular disease (CVD). We investigated associations of (genetic liability for) depressive disorder, bipolar disorder and schizophrenia with a range of CVD traits and examined to what degree these were driven by important confounders.

We included participants of the Dutch Lifelines cohort (N = 147 337) with information on self-reported lifetime diagnosis of depressive disorder, bipolar disorder, or schizophrenia and CVD traits. Employing linear mixed-effects models, we examined associations between mental illness diagnoses and CVD, correcting for psychotropic medication, demographic and lifestyle factors. In a subsample (N = 73 965), we repeated these analyses using polygenic scores (PGSs) for the three mental illnesses.

There was strong evidence that depressive disorder diagnosis is associated with increased arrhythmia and atherosclerosis risk and lower heart rate variability, even after confounder adjustment. Positive associations were also found for the depression PGSs with arrhythmia and atherosclerosis. Bipolar disorder was associated with a higher risk of nearly all CVD traits, though most diminished after adjustment. The bipolar disorder PGSs did not show any associations. While the schizophrenia PGSs was associated with increased arrhythmia risk and lower heart rate variability, schizophrenia diagnosis was not. All mental illness diagnoses were associated with lower blood pressure and a lower risk of hypertension.

Our study shows widespread associations of (genetic liability to) mental illness (primarily depressive disorder) with CVD, even after confounder adjustment. Future research should focus on clarifying potential causal pathways between mental illness and CVD.

Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome.

In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t0), after ECT (t1) and 2 years later (t2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed.

Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t0 to t1 and decreases from t1 to t2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t0 to t1 correlate with immediate and delayed symptom increase, while volume decreases from t1 to t2 correlate with long-term depressive outcome (all p ⩽ 0.049).

Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes.

Cross-sectional studies report high levels of depressive symptoms during the COVID-19 pandemic, especially in youth and females. However, longitudinal research comparing depressive symptoms before and during the pandemic is lacking. Little is known about how the pandemic affected individuals with familial history of mental illness. The present study examines the impact of the pandemic on youth depressive symptoms, including offspring of parents with major mood and psychotic disorders.

Between March 2018 and February 2020, we measured depressive symptoms in 412 youth aged 5–25 years. We measured depressive symptoms again in 371 (90%) of these youth between April 2020 and May 2022. Two thirds (249) participants had a biological parent with a major mood or psychotic disorder. We tested the effect of the pandemic by comparing depression symptoms before and after March 2020. We examined age, sex, and family history as potential moderators.

We found an overall small increase in youth depressive symptoms (b = 0.07, 95% CI −0.01 to 0.15, p = 0.062). This was driven by an increase in female youth without familial history of mental illness (b = 0.35, 95% CI 0.14 to 0.56, p = 0.001). There was no change in depressive symptoms among offspring of parents with mental illness or males.

Our results provide reassurance about the wellbeing of children of parents with mental illness during a period of restricted access to resources outside the family. Rather than increasing symptoms in established risk groups, the pandemic led to a redistribution of depression burden towards segments of the youth population that were previously considered to be low-risk.

The DSM-5 features hundreds of diagnoses comprising a multitude of symptoms, and there is considerable repetition in the symptoms among diagnoses. This repetition undermines what we can learn from studying individual diagnostic constructs because it can obscure both disorder- and symptom-specific signals. However, these lost opportunities are currently veiled because symptom repetition in the DSM-5 has not been quantified.

This descriptive study mapped the repetition among the 1419 symptoms described in 202 diagnoses of adult psychopathology in section II of the DSM-5. Over a million possible symptom comparisons needed to be conducted, for which we used both qualitative content coding and natural language processing.

In total, we identified 628 distinct symptoms: 397 symptoms (63.2%) were unique to a single diagnosis, whereas 231 symptoms (36.8%) repeated across multiple diagnoses a total of 1022 times (median 3 times per symptom; range 2–22). Some chapters had more repetition than others: For example, every symptom of every diagnosis in the bipolar and related disorders chapter was repeated in other chapters, but there was no repetition for any symptoms of any diagnoses in the elimination disorders, gender dysphoria or paraphilic disorders. The most frequently repeated symptoms included insomnia, difficulty concentrating, and irritability – listed in 22, 17 and 16 diagnoses, respectively. Notably, the top 15 most frequently repeating diagnostic criteria were dominated by symptoms of major depressive disorder.

Overall, our findings lay the foundation for a better understanding of the extent and potential consequences of symptom overlap.