Major depressive disorder (MDD) is associated not only with disorders in multiple brain networks but also with frequency-specific brain activities. The abnormality of spatiotemporal networks in patients with MDD remains largely unclear.

We investigated the alterations of the global spatiotemporal network in MDD patients using a large-sample multicenter resting-state functional magnetic resonance imaging dataset. The spatiotemporal characteristics were measured by the variability of global signal (GS) and its correlation with local signals (GSCORR) at multiple frequency bands. The association between these indicators and clinical scores was further assessed.

The GS fluctuations were reduced in patients with MDD across the full frequency range (0–0.1852 Hz). The GSCORR was also reduced in the MDD group, especially in the relatively higher frequency range (0.0728–0.1852 Hz). Interestingly, these indicators showed positive correlations with depressive scores in the MDD group and relative negative correlations in the control group.

The GS and its spatiotemporal effects on local signals were weakened in patients with MDD, which may impair inter-regional synchronization and related functions. Patients with severe depression may use the compensatory mechanism to make up for the functional impairments.

Racial, ethnic, and socioeconomic disparities persist in posttraumatic stress disorder (PTSD), which are partly attributed to minoritized women being trauma-exposed, while also contending with harmful contextual stressors. However, few have used analytic strategies that capture the interplay of these experiences and their relation to PTSD. The current study used a person-centered statistical approach to examine heterogeneity in trauma and contextual stress exposure, and their associations with PTSD and underlying symptom dimensions, in a diverse sample of low-income postpartum women.

Using a community-based sample of Black, Hispanic/Latina, and White postpartum women recruited from five U.S. regions (n = 1577), a latent class analysis generated profiles of past-year exposure to traumatic events and contextual stress at one month postpartum. Regression analyses then examined associations between class membership and PTSD symptom severity at six months postpartum as a function of race/ethnicity.

A four-class solution best fit the data, yielding High Contextual Stress, Injury/Illness, Violence Exposure, and Low Trauma/Contextual Stress classes. Compared to the Low Trauma/Contextual Stress class, membership in any of the other classes was associated with greater symptom severity across nearly all PTSD symptom dimensions (all ps < 0.05). Additionally, constellations of exposures were differentially linked to total PTSD symptom severity, reexperiencing, and numbing PTSD symptoms across racial/ethnic groups (ps < 0.05).

A person-centered approach to trauma and contextual stress exposure can capture heterogeneity of experiences in diverse, low-income women. Moreover, racially/ethnically patterned links between traumatic or stressful exposures and PTSD symptom dimensions have implications for screening and intervention in the perinatal period.

Amygdala and dorsal anterior cingulate cortex responses to facial emotions have shown promise in predicting treatment response in medication-free major depressive disorder (MDD). Here, we examined their role in the pathophysiology of clinical outcomes in more chronic, difficult-to-treat forms of MDD.

Forty-five people with current MDD who had not responded to ⩾2 serotonergic antidepressants (n = 42, meeting pre-defined fMRI minimum quality thresholds) were enrolled and followed up over four months of standard primary care. Prior to medication review, subliminal facial emotion fMRI was used to extract blood-oxygen level-dependent effects for sad v. happy faces from two pre-registered a priori defined regions: bilateral amygdala and dorsal/pregenual anterior cingulate cortex. Clinical outcome was the percentage change on the self-reported Quick Inventory of Depressive Symptomatology (16-item).

We corroborated our pre-registered hypothesis (NCT04342299) that lower bilateral amygdala activation for sad v. happy faces predicted favorable clinical outcomes (rs[38] = 0.40, p = 0.01). In contrast, there was no effect for dorsal/pregenual anterior cingulate cortex activation (rs[38] = 0.18, p = 0.29), nor when using voxel-based whole-brain analyses (voxel-based Family-Wise Error-corrected p < 0.05). Predictive effects were mainly driven by the right amygdala whose response to happy faces was reduced in patients with higher anxiety levels.

We confirmed the prediction that a lower amygdala response to negative v. positive facial expressions might be an adaptive neural signature, which predicts subsequent symptom improvement also in difficult-to-treat MDD. Anxiety reduced adaptive amygdala responses.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

We compared dissociative seizure specific cognitive behavior therapy (DS-CBT) plus standardized medical care (SMC) to SMC alone in a randomized controlled trial. DS-CBT resulted in better outcomes on several secondary trial outcome measures at the 12-month follow-up point. The purpose of this paper is to evaluate putative treatment mechanisms.

We carried out a secondary mediation analysis of the CODES trial. 368 participants were recruited from the National Health Service in secondary / tertiary care in England, Scotland, and Wales. Sixteen mediation hypotheses corresponding to combinations of important trial outcomes and putative mediators were assessed. Twelve-month trial outcomes considered were final-month seizure frequency, Work and Social Adjustment Scale (WSAS), and the SF-12v2, a quality-of-life measure providing physical (PCS) and mental component summary (MCS) scores. Mediators chosen for analysis at six months (broadly corresponding to completion of DS-CBT) included: (a) beliefs about emotions, (b) a measure of avoidance behavior, (c) anxiety and (d) depression.

All putative mediator variables except beliefs about emotions were found to be improved by DS-CBT. We found evidence for DS-CBT effect mediation for the outcome variables dissociative seizures (DS), WSAS and SF-12v2 MCS scores by improvements in target variables avoidance behavior, anxiety, and depression. The only variable to mediate the DS-CBT effect on the SF-12v2 PCS score was avoidance behavior.

Our findings largely confirmed the logic model underlying the development of CBT for patients with DS. Interventions could be additionally developed to specifically address beliefs about emotions to assess whether it improves outcomes.

Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life.

Data from the UK Biobank were available for 966 participants with BD, aged between 40 and 69 years. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; (1) health risk behaviors (physical activity, sedentary behavior, smoking, and sleep) and (2) physiological risk factors, stratified into (2a) anthropometric and clinical risk (handgrip strength, body composition, and blood pressure), and (2b) cardiometabolic disease risk biomarkers (CRP, lipid profile, and HbA1c). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models.

In the final combined model, lower mentally active and higher passive sedentary behavior, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition.

Health risk behaviors, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.

Suicidal thoughts and behaviors are elevated among active-duty service members (ADSM) and veterans compared to the general population. Hence, it is a priority to examine maintenance factors underlying suicidal ideation among ADSM and veterans to develop effective, targeted interventions. In particular, interpersonal risk factors, hopelessness, and overarousal have been robustly connected to suicidal ideation and intent.

To identify the suicidal ideation risk factors that are most relevant, we employed network analysis to examine between-subjects (cross-sectional), contemporaneous (within seconds), and temporal (across four hours) group-level networks of suicidal ideation and related risk factors in a sample of ADSM and veterans (participant n = 92, observations n = 10 650). Participants completed ecological momentary assessment (EMA) surveys four times a day for 30 days, where they answered questions related to suicidal ideation, interpersonal risk factors, hopelessness, and overarousal.

The between-subjects and contemporaneous networks identified agitation, not feeling close to others, and ineffectiveness as the most central symptoms. The temporal network revealed that feeling ineffective was most likely to influence other symptoms in the network over time.

Our findings suggest that ineffectiveness, low belongingness, and agitation are important drivers of moment-to-moment and longitudinal relations between risk factors for suicidal ideation in ADSM and veterans. Targeting these symptoms may disrupt suicidal ideation.

Determining whether the incidence of suicidal behavior during the COVID-19 pandemic changed for those with severe mental disorders is essential to ensure the provision of suicide preventive initiatives in the case of future health crises.

Using population-based registers, quarterly cohorts from the first quarter of 2018 (2018Q1) to 2021Q4 were formed including all Swedish-residents >10 years old. Interrupted time series and generalized estimating equations analyses were used to evaluate changes in Incidence Rates (IR) of specialised healthcare use for suicide attempt and death by suicide per 10 000 person-years for individuals with or without specific severe mental disorders (SMDs) during, compared to before the pandemic.

The IR (95% Confidence interval, CI) of suicide in individuals with SMDs decreased from 16.0 (15.0–17.1) in 2018Q1 to 11.6 (10.8–12.5) in 2020Q1 (i.e. the quarter before the start of the pandemic), after which it dropped further to 6.7 (6.3–7.2) in 2021Q2. In contrast, IRs of suicide attempt in SMDs showed more stable trends, as did the trends regarding suicide and suicide attempt for individuals without SMD. These discrepancies were most evident for individuals with substance use disorder and ASD/ADHD. Changes in IRs of suicide v. suicide attempt for one quarter during the pandemic for substance misuse were 11.2% v. 3.6% respectively. These changes for ASD/ADHD were 10.7% v. 3.6%.

The study shows pronounced decreases in suicide rates in individuals with SMDs during the pandemic. Further studies aiming to understand mechanisms behind these trends are warranted to consult future suicide prevention strategies.

Major depressive disorder (MDD) is one of the most prevalent and disabling illnesses worldwide. Treatment of MDD typically relies on trial-and-error to find an effective approach. Identifying early response-related biomarkers that predict response to antidepressants would help clinicians to decide, as early as possible, whether a particular treatment might be suitable for a given patient.

Data were from the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial. A whole-brain, voxel-wise, mixed-effects model was applied to identify early-treatment cerebral blood flow (CBF) changes as biomarkers of treatment response. We examined changes in CBF measured with arterial spin labeling 1-week after initiating double-masked sertraline/placebo. We tested whether these early 1-week scans could be used to predict response observed after 8-weeks of treatment.

Response to 8-week placebo treatment was associated with increased cerebral perfusion in temporal cortex and reduced cerebral perfusion in postcentral region captured at 1-week of treatment. Additionally, CBF response in these brain regions was significantly correlated with improvement in Hamilton Depression Rating Scale score in the placebo group. No significant associations were found for selective serotonin reuptake inhibitor treatment.

We conclude that early CBF responses to placebo administration in multiple brain regions represent candidate neural biomarkers of longer-term antidepressant effects.

Although numerous neuroimaging studies have depicted neural alterations in individuals with obsessive–compulsive disorder (OCD), a psychiatric disorder characterized by intrusive cognitions and repetitive behaviors, the molecular mechanisms connecting brain structural changes and gene expression remain poorly understood.

This study combined the Allen Human Brain Atlas dataset with neuroimaging data from the Meta-Analysis (ENIGMA) consortium and independent cohorts. Later, partial least squares regression and enrichment analysis were performed to probe the correlation between transcription and cortical thickness variation among adults with OCD.

The cortical map of case-control differences in cortical thickness was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms preferentially expressed across different cell types and cortical layers. These genes were specifically expressed in brain tissue, spanning all cortical developmental stages. Protein–protein interaction analysis revealed that these genes coded a network of proteins encompassing various highly interactive hubs.

The study findings bridge the gap between neural structure and transcriptome data in OCD, fostering an integrative understanding of the potential biological mechanisms.

Observational studies consistently report associations between tobacco use, cannabis use and mental illness. However, the extent to which this association reflects an increased risk of new-onset mental illness is unclear and may be biased by unmeasured confounding.

A systematic review and meta-analysis (CRD42021243903). Electronic databases were searched until November 2022. Longitudinal studies in general population samples assessing tobacco and/or cannabis use and reporting the association (e.g. risk ratio [RR]) with incident anxiety, mood, or psychotic disorders were included. Estimates were combined using random-effects meta-analyses. Bias was explored using a modified Newcastle–Ottawa Scale, confounder matrix, E-values, and Doi plots.

Seventy-five studies were included. Tobacco use was associated with mood disorders (K = 43; RR: 1.39, 95% confidence interval [CI] 1.30–1.47), but not anxiety disorders (K = 7; RR: 1.21, 95% CI 0.87–1.68) and evidence for psychotic disorders was influenced by treatment of outliers (K = 4, RR: 3.45, 95% CI 2.63–4.53; K = 5, RR: 2.06, 95% CI 0.98–4.29). Cannabis use was associated with psychotic disorders (K = 4; RR: 3.19, 95% CI 2.07–4.90), but not mood (K = 7; RR: 1.31, 95% CI 0.92–1.86) or anxiety disorders (K = 7; RR: 1.10, 95% CI 0.99–1.22). Confounder matrices and E-values suggested potential overestimation of effects. Only 27% of studies were rated as high quality.

Both substances were associated with psychotic disorders and tobacco use was associated with mood disorders. There was no clear evidence of an association between cannabis use and mood or anxiety disorders. Limited high-quality studies underscore the need for future research using robust causal inference approaches (e.g. evidence triangulation).

Fatigue is a central feature of myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS), but many ME/CFS patients also report comorbid pain symptoms. It remains unclear whether these symptoms are related to similar or dissociable brain networks. This study used resting-state fMRI to disentangle networks associated with fatigue and pain symptoms in ME/CFS patients, and to link changes in those networks to clinical improvements following cognitive behavioral therapy (CBT).

Relationships between pain and fatigue symptoms and cortico-cortical connectivity were assessed within ME/CFS patients at baseline (N = 72) and after CBT (N = 33) and waiting list (WL, N = 18) and compared to healthy controls (HC, N = 29). The analyses focused on four networks previously associated with pain and/or fatigue, i.e. the fronto-parietal network (FPN), premotor network (PMN), somatomotor network (SMN), and default mode network (DMN).

At baseline, variation in pain and fatigue symptoms related to partially dissociable brain networks. Fatigue was associated with higher SMN-PMN connectivity and lower SMN-DMN connectivity. Pain was associated with lower PMN-DMN connectivity. CBT improved SMN-DMN connectivity, compared to WL. Larger clinical improvements were associated with larger increases in frontal SMN-DMN connectivity. No CBT effects were observed for PMN-DMN or SMN-PMN connectivity.

These results provide insight into the dissociable neural mechanisms underlying fatigue and pain symptoms in ME/CFS and how they are affected by CBT in successfully treated patients. Further investigation of how and in whom behavioral and biomedical treatments affect these networks is warranted to improve and individualize existing or new treatments for ME/CFS.

Shared genetic risk between schizophrenia (SCZ) and bipolar disorder (BD) is well-established, yet the extent to which they share environmental risk factors remains unclear. We compare the associations between environmental exposures during childhood/prior to disorder onset with the risk of developing SCZ and BD.

We conducted a Swedish register-based nested case–control study using 4184 SCZ cases and 18 681 BD cases diagnosed 1988–2013. Cases were matched to five controls by birth year, birth region, and sex. Conditional logistic regression was used to estimate incidence rate ratios (IRR) for SCZ and BD for each exposure (severe childhood infections, adverse childhood experiences (ACEs), substance use disorders (SUDs), urban birth/longest residence).

All SUD types were associated with very high risk (IRR 4.9–25.5), and all forms of ACEs with higher risk (IRR 1.5–4.3) for both disorders. In the mutually adjusted models, ACEs demonstrated slightly higher risk for BD (SCZ IRR 1.30, 1.19-1.42; BD IRR 1.49, 1.44–1.55), while for SUD, risk was higher for SCZ (SCZ IRR 9.43, 8.15–10.92; BD IRR 5.50, 5.15–5.88). Infections were associated with increased risk of BD (IRR 1.21, 1.17–1.26) but not SCZ. Urban birth and urban longest residence were associated with higher risk of SCZ (IRR 1.19, 1.03–1.37), while only the combination of urban birth and rural longest residence showed higher risk for BD (IRR 1.24, 1.13–1.35).

There were both shared and unique environmental risk factors: SUDs and ACEs were risk factors for both disorders, while infections were more strongly associated with BD and urbanicity with SCZ.

Very late-onset psychosis (VLOP) is associated with higher rates of dementia but the proportion who develop dementia with Lewy bodies (DLB) is unknown. We aimed to identify individuals with VLOP who develop dementia and DLB and characterize the risk factors for progression.

Anonymized data were retrieved from electronic records for individuals with VLOP. Patients developing dementia after psychosis were identified, in addition to those with >2 core features of DLB at the time of dementia or DLB identified by a natural language processing application (NLP-DLB). Demographic factors, Health of the National Outcome Scale (HoNOS) and symptoms at index psychosis were explored as predictors of progression to dementia.

In 1425 patients with VLOP over 4.29 years (mean) follow up, 197 (13.8%) received a subsequent diagnosis of dementia. Of these, 24.4% (n = 48) had >2 core features of DLB and 6% (n = 12) had NLP-DLB. In cox proportional hazard models, older age and cognitive impairment at the time of psychosis were associated with increased risk of incident dementia. Visual hallucinations and 2+ core features of DLB at index psychosis were associated with increased risk of dementia with 2+ symptoms of DLB but not all-cause dementia. Two or more core features of DLB at index psychosis were associated with 81% specificity and 67% sensitivity for incident NLP-DLB.

In patients with VLOP who develop dementia, core features of DLB are common. Visual hallucinations or two core features of DLB in VLOP should prompt clinicians to consider DLB and support further investigation.

Although the importance of the dynamic intra-individual relationship between mother-to-infant bonding and postpartum depressive symptoms has been widely recognized, the complex interplay between them is not well understood. Furthermore, the potential role of prenatal depressive symptoms and infant temperament in this relationship remains unclear. This study aims to examine the bidirectional influence of mother-to-infant bonding on postpartum depressive symptoms within individuals and to elucidate whether prenatal depressive symptoms and infant temperament would influence deviations from stable individual states.

Longitudinal data were collected from 433 women in early pregnancy. Of these, 360 participants completed the main questionnaires measuring impaired mother-to-infant bonding and postpartum depressive symptoms at least once during the postpartum period. Data were collected at early and late pregnancy and several postpartum time points: shortly after birth and at one, four, ten, and 18 months postpartum. We also assessed prenatal depressive symptoms and infant temperament. A random-intercept cross-lagged panel model was used.

Within-individual variability in mother-to-infant bonding, especially anger and rejection, significantly predicted subsequent postpartum depressive symptoms. However, the inverse relationship was not significant. Additionally, prenatal depressive symptoms and difficult infant temperament were associated with greater within-individual variability in impaired mother-to-infant bonding and postpartum depressive symptoms.

The present study demonstrated that the within-individual relationship between mother-to-infant bonding and postpartum depressive symptoms is likely non-bidirectional. The significance of the findings is underscored by the potential for interventions aimed at improving mother-to-infant bonding to alleviate postpartum depressive symptoms, suggesting avenues for future research and practice.

Evidence suggests that cannabis may be a causal factor for development of schizophrenia. We aimed to investigate whether use of antipsychotic medication, benzodiazepines, and psychiatric service use differs among patients with schizophrenia depending on whether psychosis was precipitated by a diagnosis of cannabis use disorder (CUD).

We utilized the nationwide Danish registries to identify all individuals with an incident diagnosis of schizophrenia from 1995 to 2016. We also collected information on whether first CUD diagnosis preceded schizophrenia and thus defined a group of potentially cannabis-related schizophrenia. We compared the cannabis-related schizophrenia group both with all non-cannabis-related patients with schizophrenia and with non-cannabis-related patients with schizophrenia that were propensity-score matched to cases using a range of potentially confounding variables.

We included 35 714 people with incident schizophrenia, including 4116 (11.5%) that were cannabis-related. In the unmatched-comparison analyses, there were no clear differences over time in use of antipsychotics and benzodiazepines related to whether the diagnosis of schizophrenia was cannabis-related. After propensity-score matching, use of antipsychotics and benzodiazepines was significantly lower among cannabis-related cases of schizophrenia. In the unmatched comparison, the cannabis-related group had significantly more days admitted than the non-cannabis-related group. This was markedly attenuated after propensity-score matching.

Our findings indicate the importance of considering cannabis-related cases of schizophrenia as a potentially distinct disorder in terms of prognosis. It is unclear, however, if these differences are due to different biological types of schizophrenia being compared or if they rather indicate behavioral differences such as reduced adherence and treatment-seeking.

Recent stressful life events (SLE) are a risk factor for psychosis, but limited research has explored how SLEs affect individuals at clinical high risk (CHR) for psychosis. The current study investigated the longitudinal effects of SLEs on functioning and symptom severity in CHR individuals, where we hypothesized CHR would report more SLEs than healthy controls (HC), and SLEs would be associated with poorer outcomes.

The study used longitudinal data from the EU-GEI High Risk study. Data from 331 CHR participants were analyzed to examine the effects of SLEs on changes in functioning, positive and negative symptoms over a 2-year follow-up. We compared the prevalence of SLEs between CHR and HCs, and between CHR who did (CHR-T) and did not (CHR-NT) transition to psychosis.

CHR reported 1.44 more SLEs than HC (p < 0.001), but there was no difference in SLEs between CHR-T and CHR-NT at baseline. Recent SLEs were associated with poorer functioning and more severe positive and negative symptoms in CHR individuals (all p < 0.01) but did not reveal a significant interaction with time.

CHR individuals who had experienced recent SLEs exhibited poorer functioning and more severe symptoms. However, as the interaction between SLEs and time was not significant, this suggests SLEs did not contribute to a worsening of symptoms and functioning over the study period. SLEs could be a key risk factor to becoming CHR for psychosis, however further work is required to inform when early intervention strategies mitigating against the effects of stress are most effective.

Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups.

Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992–2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors.

Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01–1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06–1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates.

We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.

Early exposure to neighborhood social fragmentation has been shown to be associated with schizophrenia. The impact of social fragmentation and friendships on distressing psychotic-like experiences (PLE) remains unknown. We investigate the relationships between neighborhood social fragmentation, number of friends, and distressing PLE among early adolescents.

Data were collected from the Adolescent Brain Cognitive Development Study. Generalized linear mixed models tested associations between social fragmentation and distressing PLE, as well as the moderating role of the number of total and close friends.

Participants included 11 133 adolescents aged 9 to 10, with 52.3% being males. Greater neighborhood social fragmentation was associated with higher levels of distressing PLE (adjusted β = 0.05; 95% CI: 0.01–0.09). The number of close but not total friends significantly interacted with social fragmentation to predict distressing PLE (adjusted β = −0.02; 95% CI: −0.04 to <−0.01). Among those with fewer close friends, the association between neighborhood social fragmentation and distressing PLE was significant (adjusted β = 0.07; 95% CI: 0.03–0.11). However, among those with more close friends, the association was non-significant (adjusted β = 0.03; 95% CI: −0.01 to 0.07).

Greater neighborhood social fragmentation is associated with higher levels of distressing PLE, particularly among those with fewer close friends. Further research is needed to disentangle aspects of the interaction between neighborhood characteristics and the quality of social interactions that may contribute to psychosis, which would have implications for developing effective interventions at the individual and community levels.

Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = −0.07, p = 0.02) and PFI (ß = −0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = −0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = −1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.