The association between heatwave and heat-related outcomes in people with mental health conditions with and without psychotropics was unclear.

We identified people with severe mental illness (SMI) and depression, respectively, using Japanese claim data of Ibaraki prefecture during 1/1/2014–31/12/2021. We conducted self-controlled case series to estimate the incidence rate ratio (IRR) of heat-related illness, myocardial infarction and delirium, respectively, during 5-day pre-heatwave, heatwave, and 5-day post-heatwave periods v. all other periods (baseline) within an individual, stratified by periods prescribed psychotropics and periods not prescribed psychotropics, respectively.

Among people with SMI, heatwave was associated with an increased rate of heat-related illness v. baseline, with no evidence of a difference in the IRRs between those prescribed v. not prescribed antipsychotics (IRR: 1.48 [95% CI 1.40–1.56]; 1.45 [95% CI 1.35–1.56] respectively, p interaction: 0.53). Among people with depression, heatwave was similarly associated with heat-related illness, with no evidence of a difference in the IRRs between those prescribed v. not prescribed antidepressants (IRR: 1.54 [95% CI 1.46–1.64]; 1.64 [95% CI 1.57–1.71] respectively, p interaction: 0.33). Smaller increased rates of heat-related illness were also observed in pre- and post-heatwave periods, v. baseline in both cohorts. There was weak evidence of an increased risk of MI and delirium associated with heatwave v. baseline.

We showed an increased risk of heat-related illness, myocardial infarction and delirium associated with heatwave in people with mental health conditions regardless of whether being prescribed psychotropics. Risks of heat-related illness, myocardial infarction and delirium associated with heatwave might not be factors to influence decisions about the routine use of psychotropics.

Markers of inflammation and cannabis exposure are associated with an increased risk of mental disorders. In the current study, we investigated associations between cannabis use and biomarkers of inflammation.

Utilizing a sample of 914 participants from the Avon Longitudinal Study of Parents and Children, we investigated whether interleukin-6 (IL-6), tumor necrosis factor α (TNFα), C-reactive protein (CRP), and soluble urokinase plasminogen activator receptor (suPAR) measured at age 24 were associated with past year daily cannabis use, less frequent cannabis use, and no past year cannabis use. We adjusted for a number of covariates including sociodemographic measures, body mass index, childhood trauma, and tobacco smoking. We found evidence of a strong association between daily or near daily cannabis use and suPAR.

We did not find any associations between less frequent cannabis use and suPAR. We did not find evidence of an association between IL-6, TNFα or CRP, and cannabis use.

Our finding that frequent cannabis use is strongly associated with suPAR, a biomarker of systemic chronic inflammation implicated in neurodevelopmental and neurodegenerative processes is novel. These findings may provide valuable insights into biological mechanisms by which cannabis affects the brain and impacts the risk of serious mental disorders.

Dialectical behavior therapy (DBT) is a specialized treatment that has a growing evidence base for binge-spectrum eating disorders. However, cost and workforce capacity limit wide-scale uptake of DBT since it involves over 20 in-person sessions with a trained professional (and six sessions for guided self-help format). Interventions translated for delivery through modern technology offer a solution to increase the accessibility of evidence-based treatments. We developed the first DBT-specific skills training smartphone application (Resilience: eDBT) for binge-spectrum eating disorders and evaluated its efficacy in a randomized clinical trial.

Participants reporting recurrent binge eating were randomized to Resilience (n = 287) or a waitlist (n = 289). Primary outcomes were objective binge eating episodes and global levels of eating disorder psychopathology. Secondary outcomes were behavioral and cognitive symptoms, psychological distress, and the hypothesized processes of change (mindfulness, emotion regulation, and distress tolerance).

Intention-to-treat analyses showed that the intervention group reported greater reductions in objective binge eating episodes (incidence rate ratio = 0.69) and eating disorder psychopathology (d = −0.68) than the waitlist at 6 weeks. Significant group differences favoring the intervention group were also observed on secondary outcomes, except for subjective binge eating, psychological distress, and distress tolerance. Primary symptoms showed further improvements from 6 to 12 weeks. However, dropout rate was high (48%) among the intervention group, and engagement decreased over the study period.

A novel, low-intensity DBT skills training app can effectively reduce symptoms of eating disorders. Scalable apps like these may increase the accessibility of evidence-based treatments.

Accumulating evidence suggests that rapid eye movement sleep (REM) supports the consolidation of extinction memory. REM is disrupted in posttraumatic stress disorder (PTSD), and REM abnormalities after traumatic events increase the risk of developing PTSD. Therefore, it was hypothesized that abnormal REM in trauma-exposed individuals may pave the way for PTSD by interfering with the processing of extinction memory. In addition, PTSD patients display reduced vagal activity. Vagal activity contributes to the strengthening of memories, including fear extinction memory, and recent studies show that the role of vagus in memory processing extends to memory consolidation during sleep. Therefore, it is plausible that reduced vagal activity during sleep in trauma-exposed individuals may be an additional mechanism that impairs extinction memory consolidation. However, to date, the contribution of sleep vagal activity to the consolidation of extinction memory or any emotional memory has not been investigated.

Trauma-exposed individuals (n = 113) underwent a 2-day fear conditioning and extinction protocol. Conditioning and extinction learning phases were followed by extinction recall 24 h later. The association of extinction recall with REM characteristics and REM vagal activity (indexed as heart rate variability) during the intervening consolidation night was examined.

Consistent with our hypotheses, REM disruption was associated with poorer physiological and explicit extinction memory. Furthermore, higher vagal activity during REM was associated with better explicit extinction memory, and physiological extinction memory in males.

These findings support the notion that abnormal REM, including reduced REM vagal activity, may contribute to PTSD by impairing the consolidation of extinction memory.

The lifetime prevalence of suicide is around 5% in patients with schizophrenia. Non-adherence to antipsychotic medication is an important risk factor, but prospective studies investigating joint effects of antipsychotic drugs, antidepressants, and benzodiazepines on suicidality are scarce. We aimed to investigate how use and non-use of psychotropic medications are associated with suicidality in schizophrenia.

An open cohort study followed all patients consecutively admitted to a psychiatric acute unit during a 10-year period with a diagnosis of schizophrenia (n = 696). Cox multiple regression analyses were conducted with use of antipsychotics, antidepressants, and benzodiazepines as time-dependent variables. Adjustments were made for age, gender, depressive mood, agitated behavior, and use of alcohol and illicit substances.

A total of 32 (4.6%) suicide events were registered during follow-up. Of these, 9 (28%) were completed suicides and 23 (72%) were attempted suicides. A total of 59 (8.5%) patients were readmitted with suicidal plans during the follow-up. Compared to non-use, use of antipsychotics was associated with 70% lower risk of attempted or completed suicide (adjusted hazard ratio [AHR] = 0.30, p < 0.01, CI 0.14–0.65) and 69% reduced risk of readmission with suicidal plans (AHR = 0.31, p < 0.01, CI 0.18–0.55). Use of prescribed benzodiazepines was associated with 126% increased risk of readmission with suicidal plans (AHR = 2.26, p = 0.01, CI 1.24–4.13).

Adherence to antipsychotic medication is strongly associated with reduced suicidal risk in schizophrenia. The use of prescribed benzodiazepines was identified as a significant risk factor for being readmitted with suicidal plans.

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Among those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used.

In a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model.

Strongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use.

Network analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.

Past studies indicate daily increases in estrogen across the menstrual cycle protect against binge-eating (BE) phenotypes (e.g. emotional eating), whereas increases in progesterone enhance risk. Two previous studies from our laboratory suggest these associations could be due to differential genomic effects of estrogen and progesterone. However, these prior studies were unable to directly model effects of daily changes in hormones on etiologic risk, instead relying on menstrual cycle phase or mean hormone levels. The current study used newly modified twin models to examine, for the first time, the effects of daily changes in estradiol and progesterone on genetic/environmental influences on emotional eating in our archival twin sample assessed across 45 consecutive days.

Participants included 468 female twins from the Michigan State University Twin Registry. Daily emotional eating was assessed with the Dutch Eating Behavior Questionnaire, and daily saliva samples were assayed for ovarian hormone levels. Modified genotype × environment interaction models examined daily changes in genetic/environmental effects across hormone levels.

Findings revealed differential effects of daily changes in hormones on etiologic risk, with increasing genetic influences across progesterone levels, and increasing shared environmental influences at the highest estradiol levels. Results were consistent across primary analyses examining all study days and sensitivity analyses within menstrual cycle phases.

Findings are significant in being the first to identify changes in etiologic risk for BE symptoms across daily hormone levels and highlighting novel mechanisms (e.g. hormone threshold effects, regulation of conserved genes) that may contribute to the etiology of BE.

Cognitive impairment constitutes a prevailing issue in the schizophrenia spectrum, severely impacting patients' functional outcomes. A global cognitive score, sensitive to the stages of the spectrum, would benefit the exploration of potential factors involved in the cognitive decline.

First, we performed principal component analysis on cognitive scores from 768 individuals across the schizophrenia spectrum, including first-degree relatives of patients, individuals at ultra-high risk, who had a first-episode psychosis, and chronic schizophrenia patients, alongside 124 healthy controls. The analysis provided 10 g-factors as global cognitive scores, validated through correlations with intelligence quotient and assessed for their sensitivity to the stages on the spectrum using analyses of variance. Second, using the g-factors, we explored potential mechanisms underlying cognitive impairment in the schizophrenia spectrum using correlations with sociodemographic, clinical, and developmental data, and linear regressions with genotypic data, pooled through meta-analyses.

The g-factors were highly correlated with intelligence quotient and with each other, confirming their validity. They presented significant differences between subgroups along the schizophrenia spectrum. They were positively correlated with educational attainment and the polygenic risk score (PRS) for cognitive performance, and negatively correlated with general psychopathology of schizophrenia, neurodevelopmental load, and the PRS for schizophrenia.

The g-factors appeared as valid estimators of global cognition, enabling discerning cognitive states within the schizophrenia spectrum. Educational attainment and genetics related to cognitive performance may have a positive influence on cognitive functioning, while general psychopathology of schizophrenia, neurodevelopmental load, and genetic liability to schizophrenia may have an adverse impact.

Drug use Disorder (DUD), the risk for which is substantially influenced by both genetic and social factors, is geographically concentrated in high-risk regions. An important step toward understanding this pattern is to examine geographical distributions of the genetic liability to DUD and a key demographic risk factor – social deprivation.

We calculated the mean family genetic risk score (FGRS) for DUD ((FGRSDUD) and social deprivation for each of the 5983 areas Demographic Statistical Areas (DeSO) for all of Sweden and used geospatial techniques to analyze and map these factors.

Using 2018 data, substantial spatial heterogeneity was seen in the distribution of the genetic risk for DUD in Sweden as a whole and in its three major urban centers which was confirmed by hot-spot analyses. Across DeSOs, FGRSDUD and s.d. levels were substantially but imperfectly correlated (r = + 0.63), with more scattering at higher FGRSDUD and s.d. scores. Joint mapping across DeSOs for FGRSDUD and s.d. revealed a diversity of patterns across Sweden. The stability of the distributions of FGRSDUD and s.d. in DeSOs within Sweden over the years 2012–2018 was quite high.

The geographical distribution of the genetic risk to DUD is quite variable in Sweden. DeSO levels of s.d. and FRGSDUD were substantially correlated but also disassociated in a number of regions. The observed patterns were largely consistent with known trends in the human geography of Sweden. This effort lays the groundwork for further studies of the sources of geographic variation in rates of DUD.

Robust clinical indices of etiologic heterogeneity for psychiatric disorders are rare. We investigate whether age at onset (AAO) reflects genetic heterogeneity, utilizing Genetic Risk Ratios (GRR) derived from Family Genetic Risk Scores (FGRS).

We examined, in individuals born in Sweden 1940–2003, whether AAO for five primary disorders -- drug use disorder (DUD), alcohol use disorder (AUD), major depression (MD), bipolar disorder (BD), and schizophrenia (SZ)-- was associated with varying levels of GRRs with a range of informative secondary disorders and traits.

Our disorders displayed a varying pattern of change of GRRs with increasing AAO. At one end was SZ, where all GRRs rose with increasing AAO meaning that SZ became increasing genetically heterogeneous with later AAO. The most balanced disorder was AUD where, with increasing AAO, GRRs rose for AD, BD, and MD and declined for DUD, CB, and ADHD. That is, at young AAO, AUD had high levels of genetic risk for other externalizing disorders while at older AAO, high genetic risk for internalizing disorders were more prominent. MD was at the continuum's other end where all GRRs, except for AD, decreased with higher AAO, meaning that MD became increasingly genetically homogeneous with later AAO.

Genetic heterogeneity was robustly associated with AAO across our five primary disorders with substantial inter-disorder differences in the observed patterns. In particular, young AAO was associated with maximal genetic homogeneity for SZ and DUD while older AAO had greater genetic homogeneity for MD with AUD falling in between.

Motor activity fluctuations in healthy adults exhibit fractal patterns characterized by consistent temporal correlations across wide-ranging time scales. However, these patterns are disrupted by aging and psychiatric conditions. This study aims to investigate how fractal patterns vary across the sleep–wake cycle, differ based on individuals' recency of depression diagnosis, and change before and after a depressive episode.

Using actigraphy from two cohorts (n = 378), we examined fractal motor activity patterns both between individuals without depression and with varying recencies of depression and within individuals before and after depressive symptom recurrence. To evaluate fractal patterns, we quantified temporal correlations in motor activity fluctuations across different time scales using a scaling exponent, α. Linear mixed models were utilized to assess the influence of the sleep–wake cycle, (recency of) depression, and their interaction on α.

Fractal activity patterns in all individuals varied across the sleep–wake cycle, showing stronger temporal correlations during wakefulness (larger α = 1.035 ± 0.003) and more random activity fluctuations during sleep (smaller α = 0.784 ± 0.004, p < 0.001). This sleep–wake difference was reduced in recently depressed individuals (1–6 months), leading to larger α during sleep (0.836 ± 0.017), compared to currently depressed (0.781 ± 0.018, p = 0.006), remitted (0.776 ± 0.014, p < 0.001), and never-depressed individuals (0.773 ± 0.016, p < 0.001). Moreover, remitted individuals who experienced depressive symptom recurrence during antidepressant tapering exhibited a larger α during sleep after the symptom onset as compared to before (after: α = 0.703 ± 0.022; before: α = 0.680 ± 0.022; p < 0.001).

These findings suggest a link between fractal motor activity patterns during sleep and depressive symptom recurrence in remitted individuals and those with recent depression.

Severe fatigue and cognitive complaints are frequently reported after SARS-CoV-2 infection and may be accompanied by depressive symptoms and/or limitations in physical functioning. The long-term sequelae of COVID-19 may be influenced by biomedical, psychological, and social factors, the interplay of which is largely understudied over time. We aimed to investigate how the interplay of these factors contribute to the persistence of symptoms after COVID-19.

RECoVERED, a prospective cohort study in Amsterdam, the Netherlands, enrolled participants aged⩾16 years after SARS-CoV-2 diagnosis. We used a structural network analysis to assess relationships between biomedical (initial COVID-19 severity, inflammation markers), psychological (illness perceptions, coping, resilience), and social factors (loneliness, negative life events) and persistent symptoms 24 months after initial disease (severe fatigue, difficulty concentrating, depressive symptoms and limitations in physical functioning). Causal discovery, an explorative data-driven approach testing all possible associations and retaining the most likely model, was performed.

Data from 235/303 participants (77.6%) who completed the month 24 study visit were analysed. The structural model revealed associations between the putative factors and outcomes. The outcomes clustered together with severe fatigue as its central point. Loneliness, fear avoidance in response to symptoms, and illness perceptions were directly linked to the outcomes. Biological (inflammatory markers) and clinical (severity of initial illness) variables were connected to the outcomes only via psychological or social variables.

Our findings support a model where biomedical, psychological, and social factors contribute to the development of long-term sequelae of SARS-CoV-2 infection.

Cognitive impairment, a major determinant of poor functioning in schizophrenia, had limited responses to existing antipsychotic drugs. The limited efficacy could be due to regional differences in the dysregulation of the dopamine system. This study investigated striatal and peripheral dopaminergic makers in schizophrenia and their relationship with cognitive impairment.

Thirty-three patients with schizophrenia and 36 age- and sex-matched healthy controls (HC) participated. We evaluated their cognitive performance, examined the availability of striatal dopamine transporter (DAT) using single-photon emission computed tomography with 99mTc-TRODAT, and measured plasma levels of dopaminergic precursors (phenylalanine and tyrosine) and three branched-chain amino acids (BCAA) that compete with precursors for brain uptake via ultra-performance liquid chromatography.

Schizophrenia patients exhibited lower cognitive performance, decreased striatal DAT availability, and reduced levels of phenylalanine, tyrosine, leucine, and isoleucine, and the ratio of phenylalanine plus tyrosine to BCAA. Within the patient group, lower DAT availability in the left caudate nucleus (CN) or putamen was positively associated with attention deficits. Meanwhile, lower tyrosine levels and the ratio of phenylalanine plus tyrosine to BCAA were positively related to executive dysfunction. Among all participants, DAT availability in the right CN or putamen was positively related to memory function, and plasma phenylalanine level was positively associated with executive function.

This study supports the role of dopamine system abnormalities in cognitive impairment in schizophrenia. The distinct associations between different dopaminergic alterations and specific cognitive domain impairments suggest the potential need for multifaceted treatment approaches to target these impairments.

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).

Adolescents with a history of conduct problems (CP) are at heightened risk of increased service utilization as they develop. While the mechanisms underlying this association are unclear, early CP have also been linked with peer victimization and internalizing problems. The goals of the current study were: (1) to examine peer victimization and internalizing problems as potential serial mediators explaining increased medical and psychiatric service use in adolescents with a history of childhood CP, and; (2) to explore whether the proposed mediation models vary by sex.

Participants (N = 744; 53% boys, Mage = 8.39 years) from an ongoing longitudinal study that began in 2008 in Québec, Canada were recruited and assessed for CP, service use, and other behaviours via self-, parent- and teacher-reported questionnaires. Serial mediation analyses were conducted to examine the effects of peer victimization and internalizing problems on the association between childhood CP and adolescent medical and psychiatric service use, controlling for sex and household income.

Adolescents with childhood CP reported higher medical and psychiatric service use than non-CP peers. Peer victimization and internalizing problems significantly mediated this association in both general medical and psychiatric service use models. The models did not vary by sex.

Findings support higher levels of service use in adolescents with a history of CP, mediated by peer victimization and internalizing problems. Specifically, results highlight the importance of examining peer and socioemotional factors that may explain the increased service usage observed among youth with CP, to support better health outcomes.