Population-level preventive interventions are urgently needed and may be effective for psychosis due to social determinants. We tested three syndemic models along pathways from childhood adversity (CA) to psychotic spectrum disorder (PSD) and their implications for prevention.

Cross-sectional data from 7461 British men surveyed in 5 population subgroups. We tested interactions on both additive and multiplicative scales for a syndemic of violence/criminality (VC), sexual behavior (SH), and substance misuse (SM) according to the presence of CA and adult traumatic life events; mediation analysis of path models; and partial least squares path modeling, with PSD as outcome.

Multiplicative synergistic interactions were found between VC, SH, and SM among men, who experienced CA and traumatic adult life events. However, when disaggregated, only SM mediated the pathway from CA to PSD. Path modeling showed traumatic life events acted on PSD through the syndemic and had no direct effect on PSD. Higher syndemic scores and living in areas of deprivation characterized men with PSD and CA.

Our findings support a broad division of PSD into cases due to (i) biological/inherent causes, and (ii) social determinants, the latter including a syndemic pathway determined by CA. Preventive strategies should focus primarily on preventing adverse effects of CA on developmental pathways which result in PSD. Single component prevention strategies may prevent triggering effects of SM on PSD during adolescence/early adulthood among vulnerable individuals due to CA. Future research should determine applicability and transferability of interventions based on these findings to different populations, specifically those experiencing syndemics.

Data from an RCT of IAPT Norway (“Prompt Mental Health Care” [PMHC]) were linked to several administrative registers up to five years following the intervention. The aims were to (1) examine the effects of PMHC compared to treatment-as-usual (TAU) on work-related outcomes and health care use, (2) estimate the cost–benefit of PMHC, and (3) examine whether clinical outcomes at six-month follow-up explained the effects of PMHC on work−/cost–benefit-related outcomes.

RCTs with parallel assignment were conducted at two PMHC sites (N = 738) during 2016/2017. Eligible participants were considered for admission due to anxiety and/or depression. We used Bayesian estimation with 90% credibility intervals (CI) and posterior probabilities (PP) of effects in favor of PMHC. Primary outcome years were 2018–2022. The cost–benefit analysis estimated the overall economic gain expressed in terms of a benefit–cost ratio and the differences in overall public sector spending.

The PMHC group was more likely than the TAU group to be in regular work without receiving welfare benefits in 2019–2022 (1.27 ≤ OR ≤ 1.43). Some evidence was found that the PMHC group spent less on health care. The benefit–cost ratio in terms of economic gain relative to intervention costs was estimated at 5.26 (90%CI $ - $1.28, 11.8). The PP of PMHC being cost-beneficial for the economy as a whole was 85.9%. The estimated difference in public sector spending was small. PMHC effects on work participation and cost–benefit were largely explained by PMHC effects on mental health.

The results support the societal economic benefit of investing in IAPT-like services.

In major depressive disorder (MDD), only ~35% achieve remission after first-line antidepressant therapy. Using UK Biobank data, we identify sociodemographic, clinical, and genetic predictors of antidepressant response through self-reported outcomes, aiming to inform personalized treatment strategies.

In UK Biobank Mental Health Questionnaire 2, participants with MDD reported whether specific antidepressants helped them. We tested whether retrospective lifetime response to four selective serotonin reuptake inhibitors (SSRIs) (N = 19,516) – citalopram (N = 8335), fluoxetine (N = 8476), paroxetine (N = 2297) and sertraline (N = 5883) – was associated with sociodemographic (e.g. age, gender) and clinical factors (e.g. episode duration). Genetic analyses evaluated the association between CYP2C19 variation and self-reported response, while polygenic score (PGS) analysis assessed whether genetic predisposition to psychiatric disorders and antidepressant response predicted self-reported SSRI outcomes.

71%–77% of participants reported positive responses to SSRIs. Non-response was significantly associated with alcohol and illicit drug use (OR = 1.59, p = 2.23 × 10−20), male gender (OR = 1.25, p = 8.29 × 10−08), and lower-income (OR = 1.35, p = 4.22 × 10−07). The worst episode lasting over 2 years (OR = 1.93, p = 3.87 × 10−16) and no mood improvement from positive events (OR = 1.35, p = 2.37 × 10−07) were also associated with non-response. CYP2C19 poor metabolizers had nominally higher non-response rates (OR = 1.31, p = 1.77 × 10−02). Higher PGS for depression (OR = 1.08, p = 3.37 × 10−05) predicted negative SSRI outcomes after multiple testing corrections.

Self-reported antidepressant response in the UK Biobank is influenced by sociodemographic, clinical, and genetic factors, mirroring clinical response measures. While positive outcomes are more frequent than remission reported in clinical trials, these self-reports replicate known treatment associations, suggesting they capture meaningful aspects of antidepressant effectiveness from the patient’s perspective.

To improve early intervention and personalise treatment for individuals early on the psychosis continuum, a greater understanding of symptom dynamics is required. We address this by identifying and evaluating the movement between empirically derived attenuated psychotic symptomatic substates—clusters of symptoms that occur within individuals over time.

Data came from a 90-day daily diary study evaluating attenuated psychotic and affective symptoms. The sample included 96 individuals aged 18–35 on the psychosis continuum, divided into four subgroups of increasing severity based on their psychometric risk of psychosis, with the fourth meeting ultra-high risk (UHR) criteria. A multilevel hidden Markov modelling (HMM) approach was used to characterise and determine the probability of switching between symptomatic substates. Individual substate trajectories and time spent in each substate were subsequently assessed.

Four substates of increasing psychopathological severity were identified: (1) low-grade affective symptoms with negligible psychotic symptoms; (2) low levels of nonbizarre ideas with moderate affective symptoms; (3) low levels of nonbizarre ideas and unusual thought content, with moderate affective symptoms; and (4) moderate levels of nonbizarre ideas, unusual thought content, and affective symptoms. Perceptual disturbances predominantly occurred within the third and fourth substates. UHR individuals had a reduced probability of switching out of the two most severe substates.

Findings suggest that individuals reporting unusual thought content, rather than nonbizarre ideas in isolation, may exhibit symptom dynamics with greater psychopathological severity. Individuals at a higher risk of psychosis exhibited persistently severe symptom dynamics, indicating a potential reduction in psychological flexibility.

Sustained attention is integral to goal-directed tasks in everyday life. It is a demanding and effortful process prone to failure. Deficits are particularly prevalent in mood disorders. However, conventional methods of assessment, rooted in overall measures of performance, neglect the nuanced temporal dimensions inherent in sustained attention, necessitating alternative analytical approaches.

This study investigated sustained attention deficits and temporal patterns of attentional fluctuation in a large clinical cohort of patients with bipolar depression (BPd, n = 33), bipolar euthymia (BPe, n = 84), major depression (MDd, n = 38) and controls (HC, n = 138) using a continuous performance task (CPT). Longitudinal and spectral analyses were employed to examine trial-level reaction time (RT) data.

Longitudinal analysis revealed a significant worsening of performance over time (vigilance decrement) in BPd, whilst spectral analysis unveiled attentional fluctuations concentrated in the frequency range of 0.077 Hz (1/12.90 s)–0.049 Hz (1/20.24 s), with BPd and MDd demonstrating greater spectral power compared to BPe and controls.

Although speculative, the increased variability in this frequency range may have an association with the dysfunctional activity of the Default Mode Network, which has been shown to oscillate at a similar timescale. These findings underscore the importance of considering the temporal dimensions of sustained attention and show the potential of spectral analysis of RT in future clinical research.

It is unknown whether there is a general factor that accounts for the propensity for both physical and mental conditions in different age groups and how it is associated with lifestyle and well-being.

We analyzed health conditions data from the Millennium Cohort Study (MCS) (age = 17; N = 19,239), the National Child Development Study (NCDS) (age = 44; N = 9293), and the English Longitudinal Study of Ageing (ELSA) (age ≥ 50; N = 7585). The fit of three Confirmatory Factor models was used to select the optimal solution by Comparative Fit Index, Tucker-Lewis Index, and Root Mean Square Error of Approximation. The relationship among d factor, lifestyles, and well-being was further explored.

Supporting the existence of the d factor, the bi-factor model showed the best model fit in 17-year-olds (MCS:CFI = 0.97, TFI = 0.96, RMSEA = 0.01), 44-year-olds (NCDS:CFI = 0.96, TFI = 0.95, RMSEA = 0.02), and 50+ year-olds (ELSA:CFI = 0.97, TFI = 0.96, RMSEA = 0.02). The d factor scores significantly correlated with lifestyle and well-being, suggesting healthier lifestyles were associated with a reduced likelihood of physical and mental health comorbidities, which in turn improved well-being.

Contrary to the traditional dichotomy between mental and physical conditions, our study showed a general factor underlying the comorbidity across mental and physical diseases, related to lifestyle and well-being. Our results inform the conceptualization of mental and physical illness as well as future research assessing risk and pathways of disease transmission, intervention, and prevention. Our results also provide a strong rationale for a systematic screening for mental disorders in individuals with physical conditions and vice versa, and for integrated services addressing multimorbidity.

Schizophrenia is a chronic and complex mental disorder resulting from interactions between cumulative and synergistic genetic and environmental factors. Viral infection during the prenatal stage constitutes one of the most relevant risk factors for the development of schizophrenia later in adulthood.

A narrative review was conducted to explore the link between viral infections and schizophrenia, as well as the neuropsychiatric effects of antiviral drugs, particularly in the context of this specific mental condition. Literature searches were performed using the PubMed, Scopus, and Web of Science databases.

Several viral infections, such as herpesviruses, influenza virus, Borna disease virus, and coronaviruses, can directly or indirectly disrupt normal fetal brain development by modifying gene expression in the maternal immune system, thereby contributing to the pathophysiological symptoms of schizophrenia. In addition, neuropsychiatric effects caused by antiviral drugs are frequent and represent significant adverse outcomes for viral treatment.

Epidemiological evidence suggests a potential relationship between viruses and schizophrenia. Increases in inflammatory cytokine levels and changes in the expression of key genes observed in several viral infections may constitute potential links between these viral infections and schizophrenia. Furthermore, antivirals may affect the central nervous system, although for most drugs, their mechanisms of action are still unclear, and a strong relationship between antivirals and schizophrenia has not yet been established.

We utilize a novel contrastive genetic-epidemiological method, the Maternal Half-Sibling Families with Discordant Fathers (MHSFDF) design, to examine cross-generational genetic transmission of posttraumatic stress disorder (PTSD) and related internalizing major depression (MD), and externalizing disorders: alcohol use disorder (AUD) and drug use disorder (DUD).

Using Swedish national registries, we identified 72,467 maternal half-sibling pairs reared together whose biological fathers were discordant for the diagnoses of PTSD, MD, AUD, and DUD. Offspring selected had to have less than 1 year of contact with their affected fathers. We examined the differences in outcome for within- and cross-disorder risk of diagnosis in the half-siblings with an affected versus unaffected father.

Paternal PTSD increased the risk of PTSD (HR: 1.43, 95% CI: 1.05–1.96) and MD (HR: 1.55, CI: 1.28–1.88) in offspring. It did not, however, elevate the risk of externalizing disorders (AUD or DUD). Offspring of fathers with AUD, DUD, or MD had increased risk of PTSD, suggesting sharing of vertically transmitted genetic risk between these disorders. No sex effects were found for any studied diagnosis.

This study is the first to show cross-generation genetic transmission for PTSD using the MHSFDF design. The pattern of cross-disorder genetic risk broadly supported an internalizing versus externalizing disorder split.

Stressful life events (SLEs) increase the risk for subsequent major depression (MD) episodes. Most prior studies of SLEs utilized questionnaires or interview-based assessments. We sought to develop and evaluate an environmental risk score (ERS) for MD from multiple classes of SLEs obtained from national Swedish registries.

We assessed, in the entire adult population of Sweden (n = 7,105,712), the occurrence of 52 categories of SLEs derived from registry information for the 6 months prior to January 9, 2010 and the risk for MD registration over the subsequent 6 months. Weights for our ERS were obtained from a random half of our sample and ERS and its relationship to MD risk was evaluated in the second half.

The ERS was robustly related to risk for subsequent MD episodes. Women were more sensitive to the depressogenic effect of the ERS than men. Those with prior episodes of MD had larger absolute increases in MD risk from our ERS than those without previous episodes. Genetic risk for MD was associated with a greater sensitivity to the depressogenic effects of the ERS. A co-sibling control analysis suggested that most, but not all, of the association between ERS and subsequent risk for MD was causal.

Valid measures of SLEs that predispose to risk for MD can be assessed from high-quality registry data. While not all event categories (e.g. interpersonal or romantic difficulties) can be assessed, this method avoids problems with accurate dating and recall bias and can be performed in very large samples.

We seek to clarify how changes in the prevalence of drug use disorder (DUD) in Sweden in the 1950–1990 birth cohort impact the aggregation and co-aggregation in siblings of DUD and alcohol use disorder (AUD).

We examined risk for DUD and AUD in siblings of 102,624 DUD cases and matched control probands and 123,837 AUD case and matched control probands identified using Swedish registries. Flexible parametric survival models assessed the difference in disorder risk in siblings of case versus control probands.

Over birthyears 1950–1990, rates of DUD increased substantially in the Swedish population. In siblings of DUD cases versus controls, the risk for DUD increased dramatically starting in birthyear 1965 while their risk for AUD fell moderately. A similar, but less pronounced pattern, was seen in the siblings of AUD versus control probands. These differences were much larger in male than in female siblings.

The factors that drove upward population rates of DUD in Sweden (e.g. increased availability, reduced stigma) produced much stronger effects in high-risk subjects (siblings of DUD and AUD probands) than in normal risk groups (siblings of controls), thereby increasing familial aggregation of DUD. However, parallel declines in AUD rates in high-risk versus normal-risk siblings were observed, likely due to ‘competitive effects’ reducing coaggregation of DUD and AUD. Results of genetic studies of substance use disorders can be substantially impacted by changes in availability and stigma of psychoactive substance use and indirectly by ‘competition’ as predicted by behavioral economic models, between abusable substances.

Numerous studies have explored the relationship between brain aging and major depressive disorder (MDD) and attempted to explain the phenomenon of faster brain aging in patients with MDD from multiple perspectives. However, a major challenge in this field is elucidating the ontological basis of these changes. Here, we aimed to explore the relationship between brain structural changes in MDD-related brain aging and neurotransmitter expression levels and transcriptomics.

Imaging data from 670 Japanese participants (MDD: health controls = 233:437) and the support vector regression model were utilized to predict and compare brain age between MDD patients and healthy controls. A map of differences in cortical thickness was generated, furthermore, spatial correlation analysis with neurotransmitters and correlation analysis with gene expression were performed.

The degree of brain aging was found to be significantly higher in patients with MDD. Moreover, significant cortical thinning was observed in the left ventral area, and premotor eye field in patients with MDD. A significant correlation was observed between MDD-related cortical thinning and neurotransmitter receptors/transporters, including dopaminergic, serotonergic, and glutamatergic systems. Enriched Gene Ontology terms, including protein binding, plasma membrane, and protein processing, contribute to MDD-related cortical thinning.

The findings of this study provide further evidence that patients with MDD experience more severe brain aging, deepening our understanding of the underlying neural mechanisms and genetic basis of the brain changes involved. Additionally, these findings hold promise for the development of interventions aimed at preventing further deterioration in MDD-related brain aging, thus offering potential therapeutic avenues.

Suicidal thoughts and behaviors (STBs) are a major concern in people with psychotic disorders. There is a need to examine their prevalence over long-term follow-up after first-episode psychosis (FEP) and determine their early predictors.

Of 510 participants with FEP evaluated on 26 risk factors for later outcomes, 260 were reassessed after 21 years of follow-up for lifetime ratings of most severe suicidal ideation, number of suicide attempts, and lethality of the most severe attempt. Risk factors and STB outcomes were modeled using hierarchical linear regression analysis.

Over the 21-year follow-up period, 62.7% of participants experienced suicidal thoughts, 40.8% attempted suicide, and 18 died of suicide (3.5% case fatality and 20.6% proportionate mortality). Suicidal ideation was independently predicted by parental socioeconomic status, familial load of major depression, neurodevelopmental delay, poor adolescence social networks, and suicidal thoughts/behavior at FEP. The number of suicide attempts was independently predicted by years of follow-up, familial load of major depression, obstetric complications, childhood adversity, and suicidal thoughts/behavior at FEP. Lethality was independently predicted by familial load of major depression, obstetric complications, neurodevelopmental delay, and poor adolescence social networks. The proportion of variance in suicidal ideation, attempts, and lethality explained by the independent predictors was 29.3%, 21.2%, and 18.1%, respectively.

STBs are highly prevalent in psychotic disorders and leads to substantial morbidity and mortality. They were predicted by a number of early risk factors, whose clinical recognition should contribute to improved prediction and prevention in people with psychotic disorders.

Novel ultrasound neuromodulation techniques allow therapeutic brain stimulation with unmet precision and non-invasive targeting of deep brain areas. Transcranial pulse stimulation (TPS), a multifrequency sonication technique, is approved for the clinical treatment of Alzheimer’s disease (AD). Here, we present the largest real-world retrospective analysis of ultrasound neuromodulation therapy in dementia (AD, vascular, mixed) and mild cognitive impairment (MCI).

The consecutive sample involved 58 patients already receiving state-of-the-art treatment in an open-label, uncontrolled, retrospective study. TPS therapy typically comprises 10 sessions (range 8–12) with individualized MRI-based target areas defined according to brain pathology and individual pathophysiology. We compared the CERAD-Plus neuropsychological test battery results before and after treatment, with the CERAD Corrected Total Score ( CTS) as the primary outcome. Furthermore, we analyzed side effects reported by patients during the treatment period.

CERAD Corrected Total Score (CTS) significantly improved (p = .017, d = .32) after treatment (Baseline: M = 56.56, SD = 18.56; Post-treatment: M = 58.65, SD = 19.44). The group of top-responders (top quartile) improved even by 9.8 points. Fewer than one-third of all patients reported any sensation during treatment. Fatigue and transient headaches were the most common, with no severe adverse events.

The findings implicate TPS as a novel and safe add-on therapy for patients with dementia or MCI with the potential to further improve current state-of-the-art treatment results. Despite the individual benefits, further randomized, sham-controlled, longitudinal clinical trials are needed to differentiate the effects of verum and placebo.

Although cognitive remediation (CR) improves cognition and functioning, the key features that promote or inhibit its effectiveness, especially between cognitive domains, remain unknown. Discovering these key features will help to develop CR for more impact.

To identify interrelations between cognition, symptoms, and functioning, using a novel network analysis approach and how CR affects these recovery outcomes.

A secondary analysis of randomized controlled trial data (N = 165) of CR in early psychosis. Regularized partial correlation networks were estimated, including symptoms, cognition, and functioning, for pre-, post-treatment, and change over time. Pre- and post-CR networks were compared on global strength, structure, edge invariance, and centrality invariance.

Cognition, negative, and positive symptoms were separable constructs, with symptoms showing independent relationships with cognition. Negative symptoms were central to the CR networks and most strongly associated with change in functioning. Verbal and visual learning improvement showed independent relationships to improved social functioning and negative symptoms. Only visual learning improvement was positively associated with personal goal achievement. Pre- and post-CR networks did not differ in structure (M = 0.20, p = 0.45) but differed in global strength, reflecting greater overall connectivity in the post-CR network (S = 0.91, p = 0.03).

Negative symptoms influenced network changes following therapy, and their reduction was linked to improvement in verbal and visual learning following CR. Independent relationships between visual and verbal learning and functioning suggest that they may be key intervention targets to enhance social and occupational functioning.

Mentalizing—our ability to make inferences about the mental states of others—is impaired across psychiatric disorders and robustly associated with functional outcomes. Mentalizing deficits have been prominently linked to aberrant activity in cortical regions considered to be part of the “social brain network” (e.g., dorsomedial prefrontal cortex, temporoparietal junction), yet emerging evidence also suggests the importance of cerebellar dysfunction. In the present study—using a transdiagnostic, clinical psychiatric sample spanning the psychosis-autism-social anxiety spectrums—we examined the role of the cerebellum in mentalizing and its unique contributions to broader social functioning.

Sixty-two participants (38 with significant social dysfunction secondary to psychiatric illness and 24 nonclinical controls without social dysfunction) completed a mentalizing task during functional magnetic resonance imaging. General linear model analysis, latent variable modeling, and regression analyses were used to examine the contribution of cerebellum activation to the prediction of group status and social functioning.

Mentalizing activated a broad set of social cognitive brain regions, including cerebral mentalizing network (MN) nodes and posterior cerebellum. Higher posterior cerebellum activation significantly predicted clinical status (i.e., individuals with psychiatric disorders versus nonclinical controls). Finally, cerebellar activation accounted for significant variance in social functioning independent of all other cerebral MN brain regions identified in a whole-brain analysis.

Findings add to an accumulating body of evidence establishing the unique role of the posterior cerebellum in mentalizing deficits and social dysfunction across psychiatric illnesses. Collectively, our results suggest that the posterior cerebellum should be considered – alongside established cerebral regions – as part of the mentalizing network.