Exposure to adversities in early childhood is associated with psychotic experiences and disorders in adulthood. We aimed to examine whether early childhood adversities are associated with middle childhood psychotic experiences in a cohort of children at familial high risk of schizophrenia (FHR-SZ), bipolar disorder (FHR-BP) and population-based controls (controls).

Four hundred and forty-six children from The Danish High Risk and Resilience Study – VIA7 and VIA11 participated in this study (FHR-SZ = 170; FHR-BP = 103; controls = 173). Exposure to early childhood adversities and psychotic experiences were assessed using face-to-face interviews. Having childhood adversities assessed at baseline (age 7) was used as predictor. Psychotic experiences assessed at follow-up (age 11) were used as outcome.

Across the sample, exposure to early childhood interpersonal adversities was associated with an increased risk for any middle childhood psychotic experiences and subclinical delusions when adjusting for relevant confounders (OR 1.8, 95% CI 1.0–3.1, p = 0.05; OR 3.0, 95% CI 1.6–5.6, p < 0.001). There was no significant dose–response effect of exposure to multiple types of childhood adversities on any psychotic experiences. There were no interaction effects between early childhood adversities and FHR on middle childhood psychotic experiences. Exploratory analyses revealed that experiencing domestic violence in early childhood was associated with any middle childhood psychotic experiences (OR 2.8, 95% CI 1.5–5.1, p = 0.001).

Exposure to interpersonal adversities during early childhood is associated with an increased risk for middle childhood psychotic experiences including specifically subclinical delusions. Future studies should examine associations between exposure to childhood adversities and conversion to psychosis within this cohort.

While implicit distraction could ameliorate negative feelings in patients with major depressive disorders (MDD), it remains unclear whether patients could benefit from explicit, voluntary distraction. Meanwhile, though the dorsolateral prefrontal cortex (DLPFC) is established as a crucial brain region involved in attentional control, the causal relationship between the DLPFC and voluntary distraction is unexplored in patients.

Combing explicit distraction and transcranial magnetic stimulation (TMS), this study investigated whether TMS-activated DLPFC facilitates voluntary distraction in MDD patients. Eighty patients diagnosed with current MDD underwent either active (n = 40) or sham (n = 40) TMS sessions, followed by receiving negative social feedback from other patients, during which they were requied to use distraction strategy to down-regulate their painful feelings. Electroencephalogram was recorded during the task.

Both the subjective emotional rating and the amplitude of late positive potential showed that depressed patients successfully down-regulate their negative emotions via voluntary distraction, and the TMS-activated left DLPFC produced a larger benefit of emotion regulation compared to the sham TMS group. Results also revealed that while emotion regulation effect was negatively associated with depressive symptoms in the sham TMS group, this correlation was largely diminished when patients' left DLPFC was activated by TMS during the voluntary distraction.

These findings demonstrated that distraction is valuable for emotion regulation in MDD patients and they could be beneficial in voluntary distraction by activating their left DLPFC using neural modulation techniques. This study has valuable implications for clinical treatement of emotional dysregulation in MDD patients.

The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM).

Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD.

CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002).

This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.

Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established.

We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors.

We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811–0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity.

These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.

Mindfulness-based cognitive therapy (MBCT) seems a promising intervention for bipolar disorder (BD), but there is a lack of randomised controlled trials (RCT) investigating this. The purpose of this multicentre, evaluator blinded RCT was to investigate the added value of MBCT to treatment as usual (TAU) in BD up to 15 months follow-up (NCT03507647).

A total of 144 participants with BD type I and II were randomised to MBCT + TAU (n = 72) and TAU (n = 72). Primary outcome was current depressive symptoms. Secondary outcomes were current (hypo)manic and anxiety symptoms, recurrence rates, rumination, dampening of positive affect, functional impairment, mindfulness skills, self-compassion, and positive mental health. Potential moderators of treatment outcome were examined.

MBCT + TAU was not more efficacious than TAU in reducing current depressive symptoms at post-treatment (95% CI [−7.0 to 1.8], p = 0.303, d = 0.24) or follow-up (95% CI [−2.2 to 6.3], p = 0.037, d = 0.13). At post-treatment, MBCT + TAU was more effective than TAU in improving mindfulness skills. At follow-up, TAU was more effective than MBCT + TAU in reducing trait anxiety and improving mindfulness skills and positive mental health. Exploratory analysis revealed that participants with higher depressive symptoms and functional impairment at baseline benefitted more from MBCT + TAU than TAU.

In these participants with highly recurrent BD, MBCT may be a treatment option in addition to TAU for those who suffer from moderate to severe levels of depression and functional impairment.

ClinicalTrials.gov, NCT03507647. Registered the 25 April 2018, https://www.clinicaltrials.gov/ct2/show/NCT01126827.

Resting cerebral blood flow (rCBF) in striatum and thalamus is increased in medicated patients with psychosis, but whether this is caused by treatment or illness pathology is unclear. Specifically, effects of partial dopamine agonism, sex, and clinical correlates on rCBF are sparsely investigated. We therefore assessed rCBF in antipsychotic-naïve psychosis patients before and after aripiprazole monotherapy and related findings to sex and symptom improvement.

We assessed rCBF with the pseudo-Continuous Arterial Spin Labeling (PCASL) sequence in 49 first-episode patients (22.6 ± 5.2 years, 58% females) and 50 healthy controls (HCs) (22.3 ± 4.4 years, 63% females) at baseline and in 29 patients and 49 HCs after six weeks. RCBF in striatum and thalamus was estimated with a region-of-interest (ROI) approach. Psychopathology was assessed with the positive and negative syndrome scale.

Baseline rCBF in striatum and thalamus was not altered in the combined patient group compared with HCs, but female patients had lower striatal rCBF compared with male patients (p = 0.009). Treatment with a partial dopamine agonist increased rCBF significantly in striatum (p = 0.006) in the whole patient group, but not significantly in thalamus. Baseline rCBF in nucleus accumbens was negatively associated with improvement in positive symptoms (p = 0.046), but baseline perfusion in whole striatum and thalamus was not related to treatment outcome.

The findings suggest that striatal perfusion is increased by partial dopamine agonism and decreased in female patients prior to first treatment. This underlines the importance of treatment effects and sex differences when investigating the neurobiology of psychosis.

Characteristic changes in the asymmetric nature of the human brain are associated with neurodevelopmental differences related to autism. In people with autism, these differences are thought to affect brain structure and function, although the structural and functional bases of these defects are yet to be fully characterized.

We applied a comprehensive meta-analysis to resting-state functional and structural magnetic resonance imaging datasets from 370 people with autism and 498 non-autistic controls using seven datasets of the Autism Brain Imaging Data Exchange Project. We studied the meta-effect sizes based on standardized mean differences and standard deviations (s.d.) for lateralization of gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo). We examined the functional correlates of atypical laterality through an indirect annotation approach followed by a direct correlation analysis with symptom scores.

In people with autism, 85, 51, and 51% of brain regions showed a significant diagnostic effect for lateralization in GMV, fALFF, and ReHo, respectively. Among these regions, 35.7% showed overlapping differences in lateralization in GMV, fALFF, and ReHo, particularly in regions with functional annotations for language, motor, and perceptual functions. These differences were associated with clinical measures of reciprocal social interaction, communication, and repetitive behaviors. A meta-analysis based on s.d. showed that people with autism had lower variability in structural lateralization but higher variability in functional lateralization.

These findings highlight that atypical hemispheric lateralization is a consistent feature in autism across different sites and may be used as a neurobiological marker for autism.

Mood instability and risk-taking are hallmarks of borderline personality disorder (BPD). Schema modes are combinations of self-reflective evaluations, negative emotional states, and destructive coping strategies common in BPD. When activated, they can push patients with BPD into emotional turmoil and a dissociative state of mind. Our knowledge of the underlying neurocognitive mechanisms driving these changes is incomplete. We hypothesized that in patients with BPD, affective instability is more influenced by reward expectation, outcomes, and reward prediction errors (RPEs) during risky decision-making than in healthy controls. Additionally, we expected that these alterations would be related to schema modes.

Thirty-two patients with BPD and thirty-one healthy controls were recruited. We used an established behavioral paradigm to measure mood fluctuations during risky decision-making. The impact of expectations and RPEs on momentary mood was quantified by a computational model, and its parameters were estimated with hierarchical Bayesian analysis. Model parameters were compared using High-Density Intervals.

We found that model parameters capturing the influence of RPE and Certain Rewards on mood were significantly higher in patients with BPD than in controls. These model parameters correlated significantly with schema modes, but not with depression severity.

BPD is coupled with altered associations between mood fluctuation and reward processing under uncertainty. Our findings seem to be BPD-specific, as they stand in contrast with the correlates of depressive symptoms. Future studies should establish the clinical utility of these alterations, such as predicting or assessing therapeutic response in BPD.

Converging evidence suggests that a subgroup of bipolar disorder (BD) with an early age at onset (AAO) may develop from aberrant neurodevelopment. However, the definition of early AAO remains unprecise. We thus tested which age cut-off for early AAO best corresponds to distinguishable neurodevelopmental pathways.

We analyzed data from the FondaMental Advanced Center of Expertise-Bipolar Disorder cohort, a naturalistic sample of 4421 patients. First, a supervised learning framework was applied in binary classification experiments using neurodevelopmental history to predict early AAO, defined either with Gaussian mixture models (GMM) clustering or with each of the different cut-offs in the range 14 to 25 years. Second, an unsupervised learning approach was used to find clusters based on neurodevelopmental factors and to examine the overlap between such data-driven groups and definitions of early AAO used for supervised learning.

A young cut-off, i.e. 14 up to 16 years, induced higher separability [mean nested cross-validation test AUROC = 0.7327 (± 0.0169) for ⩽16 years]. Predictive performance deteriorated increasing the cut-off or setting early AAO with GMM. Similarly, defining early AAO below 17 years was associated with a higher degree of overlap with data-driven clusters (Normalized Mutual Information = 0.41 for ⩽17 years) relatively to other definitions.

Early AAO best captures distinctive neurodevelopmental patterns when defined as ⩽17 years. GMM-based definition of early AAO falls short of mapping to highly distinguishable neurodevelopmental pathways. These results should be used to improve patients' stratification in future studies of BD pathophysiology and biomarkers.

Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment.

US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data.

Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06–1.43) and 1.18 (1.02–1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01–1.25) and 1.16 (1.04–1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03–1.31)]. No other associations were statistically significant.

Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Anorexia nervosa (AN) is a psychiatric disorder associated with marked morbidity. Whilst AN genetic studies could identify novel treatment targets, integration of functional genomics data, including transcriptomics and proteomics, would assist to disentangle correlated signals and reveal causally associated genes.

We used models of genetically imputed expression and splicing from 14 tissues, leveraging mRNA, protein, and mRNA alternative splicing weights to identify genes, proteins, and transcripts, respectively, associated with AN risk. This was accomplished through transcriptome, proteome, and spliceosome-wide association studies, followed by conditional analysis and finemapping to prioritise candidate causal genes.

We uncovered 134 genes for which genetically predicted mRNA expression was associated with AN after multiple-testing correction, as well as four proteins and 16 alternatively spliced transcripts. Conditional analysis of these significantly associated genes on other proximal association signals resulted in 97 genes independently associated with AN. Moreover, probabilistic finemapping further refined these associations and prioritised putative causal genes. The gene WDR6, for which increased genetically predicted mRNA expression was correlated with AN, was strongly supported by both conditional analyses and finemapping. Pathway analysis of genes revealed by finemapping identified the pathway regulation of immune system process (overlapping genes = MST1, TREX1, PRKAR2A, PROS1) as statistically overrepresented.

We leveraged multiomic datasets to genetically prioritise novel risk genes for AN. Multiple-lines of evidence support that WDR6 is associated with AN, whilst other prioritised genes were enriched within immune related pathways, further supporting the role of the immune system in AN.

Neuropsychiatric disorders are common in 22q11.2 Deletion Syndrome (22q11DS) with about 25% of affected individuals developing schizophrenia spectrum disorders by young adulthood. Longitudinal evaluation of psychosis spectrum features and neurocognition can establish developmental trajectories and impact on functional outcome.

157 youth with 22q11DS were assessed longitudinally for psychopathology focusing on psychosis spectrum symptoms, neurocognitive performance and global functioning. We contrasted the pattern of positive and negative psychosis spectrum symptoms and neurocognitive performance differentiating those with more prominent Psychosis Spectrum symptoms (PS+) to those without prominent psychosis symptoms (PS−).

We identified differences in the trajectories of psychosis symptoms and neurocognitive performance between the groups. The PS+ group showed age associated increase in symptom severity, especially negative symptoms and general nonspecific symptoms. Correspondingly, their level of functioning was worse and deteriorated more steeply than the PS− group. Neurocognitive performance was generally comparable in PS+ and PS− groups and demonstrated a similar age-related trajectory. However, worsening executive functioning distinguished the PS+ group from PS− counterparts. Notably, of the three executive function measures examined, only working memory showed a significant difference between the groups in rate of change. Finally, structural equation modeling showed that neurocognitive decline drove the clinical change.

Youth with 22q11DS and more prominent psychosis features show worsening of symptoms and functional decline driven by neurocognitive decline, most related to executive functions and specifically working memory. The results underscore the importance of working memory in the developmental progression of psychosis.

The extent to which digital media use by adolescents contributes to poor mental health, or vice-versa, remains unclear. The purpose of the present study is to clarify the strength and direction of associations between adolescent internet use and the development of depression symptoms using a longitudinal modeling approach. We also examine whether associations differ for boys and girls.

Data are drawn from (N = 1547) participants followed for the Quebec longitudinal Study of Child Development (QLSCD 1998–2020). Youth self-reported internet use in terms of the average hours of use per week at the ages of 13, 15, and 17. Youth also self-reported depression symptoms at the same ages.

After testing sex-invariance, random intercepts cross-lagged panel models stratified by sex, revealed that internet use by girls was associated with significant within-person (time-varying) change in depression symptoms. Girl's internet use at age 13 was associated with increased depression symptoms at age 15 (ß = 0.12) and internet use at age 15 increased depression at age 17 (ß = 0.10). For boys, internet use was not associated with significant time varying change in depression symptoms.

The present findings support the hypothesis that internet use by adolescents can represent a significant risk factor for the development of depressive symptoms, particularly in girls.

Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.

Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.

Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.

These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics.

Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report.

After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed.

There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.

Prevalence of smoking in schizophrenia (SCZ) is larger than in general population. Genetic studies provided some evidence of a causal effect of smoking on SCZ. We aim to characterize the genetic susceptibility to SCZ affected by genetic susceptibility to smoking.

Multi-trait-based conditional and joint analysis was applied to the largest European SCZ genome-wide association studies (GWAS) to remove genetic effects on SCZ driven by smoking, estimated by generalized summary data-based Mendelian randomization. Enrichment analysis was performed to compare original v. conditional GWAS. Change in genetic correlation between SCZ and relevant traits after conditioning was assessed. Colocalization analysis was performed to identify specific loci confirming general findings.

Conditional analysis identified 19 new risk loci for SCZ and 42 lost loci whose association with SCZ may be partially driven by smoking. These results were strengthened by colocalization analysis. Enrichment analysis indicated a higher association of differentially expressed genes at prenatal brain stages after conditioning. Genetic correlation of SCZ with substance use and dependence, attention deficit-hyperactivity disorder, and several externalizing traits significantly changed after conditioning. Colocalization of association signal between SCZ and these traits was identified for some of the lost loci, such as CHRNA2, CUL3, and PCDH7.

Our approach led to identification of potential new SCZ loci, loci partially associated to SCZ through smoking, and a shared genetic susceptibility between SCZ and smoking behavior related to externalizing phenotypes. Application of this approach to other psychiatric disorders and substances may lead to a better understanding of the role of substances on mental health.

Mental health and functional difficulties are highly comorbid across neurological disorders, but supportive care options are limited. This randomised controlled trial assessed the efficacy of a novel transdiagnostic internet-delivered psychological intervention for adults with neurological disorders.

221 participants with a confirmed diagnosis of epilepsy, multiple sclerosis, Parkinson's disease, or an acquired brain injury were allocated to either an immediate treatment group (n = 115) or treatment-as-usual waitlist control (n = 106). The intervention, the Wellbeing Neuro Course, was delivered online via the eCentreClinic website. The Course includes six lessons, based on cognitive behavioural therapy, delivered over 10 weeks with support from a psychologist via email and telephone. Primary outcomes were symptoms of depression (PHQ-9), anxiety (GAD-7) and disability (WHODAS 2.0).

215 participants commenced the trial (treatment n = 111; control n = 104) and were included in intention-to-treat analysis. At post-treatment, we observed significant between-group differences in depression (PHQ-9; difference = 3.07 [95% CI 2.04–4.11], g = 0.62), anxiety (GAD-7; difference = 1.87 [0.92–2.81], g = 0.41) and disability (WHODAS 2.0 difference = 3.08 [1.09–5.06], g = 0.31), that favoured treatment (all ps < 0.001). Treatment-related effects were maintained at 3-month follow-up. Findings were achieved with minimal clinician time (average of 95.7 min [s.d. = 59.3] per participant), highlighting the public health potential of this approach to care. No adverse treatment events were reported.

Internet-delivered psychological interventions could be a suitable model of accessible supportive care for patients with neurological disorders.

Many studies aggregate prescription opioid misuse (POM) and heroin use into a single phenotype, but emerging evidence suggests that their genetic and environmental influences may be partially distinct.

In total, 7164 individual twins (84.12% complete pairs; 59.81% female; mean age = 30.58 years) from the Australian Twin Registry reported their lifetime misuse of prescription opioids, stimulants, and sedatives, and lifetime use of heroin, cannabis, cocaine/crack, illicit stimulants, hallucinogens, inhalants, solvents, and dissociatives via telephone interview. Independent pathway models (IPMs) and common pathway models (CPMs) partitioned the variance of drug use phenotypes into general and drug-specific genetic (a), common environmental (c), and unique environmental factors (e).

An IPM with one general a and one general e factor and a one-factor CPM provided comparable fit to the data. General factors accounted for 55% (a = 14%, e = 41%) and 79% (a = 64%, e = 15%) of the respective variation in POM and heroin use in the IPM, and 25% (a = 12%, c = 8%, e = 5%) and 80% (a = 38%, c = 27%, e = 15%) of the respective variation in POM and heroin use in the CPM. Across both models, POM emerged with substantial drug-specific genetic influence (26–39% of total phenotypic variance; 69–74% of genetic variance); heroin use did not (0% of total phenotypic variance; 0% of genetic variance in both models). Prescription sedative misuse also demonstrated significant drug-specific genetic variance.

Genetic variation in POM, but not heroin use, is predominantly drug-specific. Misuse of prescription medications that reduce experiences of subjective distress may be partially influenced by sources of genetic variation separate from illicit drug use.

Consistent evidence supports the involvement of genetic and environmental factors, and their interactions, in the etiology of psychosis. First-episode psychosis (FEP) comprises a group of disorders that show great clinical and long-term outcome heterogeneity, and the extent to which genetic, familial and environmental factors account for predicting the long-term outcome in FEP patients remains scarcely known.

The SEGPEPs is an inception cohort study of 243 first-admission patients with FEP who were followed-up for a mean of 20.9 years. FEP patients were thoroughly evaluated by standardized instruments, with 164 patients providing DNA. Aggregate scores estimated in large populations for polygenic risk score (PRS-Sz), exposome risk score (ERS-Sz) and familial load score for schizophrenia (FLS-Sz) were ascertained. Long-term functioning was assessed by means of the Social and Occupational Functioning Assessment Scale (SOFAS). The relative excess risk due to interaction (RERI) was used as a standard method to estimate the effect of interaction of risk factors.

Our results showed that a high FLS-Sz gave greater explanatory capacity for long-term outcome, followed by the ERS-Sz and then the PRS-Sz. The PRS-Sz did not discriminate significantly between recovered and non-recovered FEP patients in the long term. No significant interaction between the PRS-Sz, ERS-Sz or FLS-Sz regarding the long-term functioning of FEP patients was found.

Our results support an additive model of familial antecedents of schizophrenia, environmental risk factors and polygenic risk factors as contributors to a poor long-term functional outcome for FEP patients.