Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD.

Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age).

Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD.

Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.

Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.

Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.

Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Neuroprogressive models of the trajectory of cognitive dysfunction in patients with bipolar disorder (BD) have been proposed. However, few studies have explored the relationships among clinical characteristics of BD, cognitive dysfunction, and aging.

We conducted a cross-sectional analysis in euthymic participants with the MATRICS Cognitive Consensus Battery, the Trail Making Test B, the Stroop Test, and the Wechsler Test of Adult Reading. Age- and gender-equated control participants without a mental disorder [‘Healthy Controls’ – HC)] were assessed similarly. We compared cognitive performance both globally and in seven domains in four groups: younger BD (age ⩽49 years; n = 70), older BD (age ⩾50 years; n = 48), younger HC (n = 153), and older HC (n = 44). We also compared the BD and HC groups using age as a continuous measure. We controlled for relevant covariates and applied a Bonferroni correction.

Our results support both an early impairment (‘early hit’) model and an accelerated aging model: impairment in attention/vigilance, processing speed, and executive function/working memory were congruent with the accelerated aging hypothesis whereas impairment in verbal memory was congruent with an early impairment model. BD and HC participants exhibited similar age-related decline in reasoning/problem solving and visuospatial memory. There were no age- or diagnosis-related differences in social cognition.

Our findings support that different cognitive domains are affected differently by BD and aging. Longitudinal studies are needed to explore trajectories of cognitive performance in BD across the lifespan.

In Australia, aeromedical retrieval provides a vital link for rural communities with limited health services to definitive care in urban centers. Yet, there are few studies of aeromedical patient experiences and outcomes, or clear measures of the service quality provided to these patients.

This study explores whether a previously developed quality framework could usefully be applied to existing air ambulance patient journeys (ie, the sequences of care that span multiple settings; prehospital and hospital-based pre-flight, flight transport, after-flight hospital in-patient, and disposition). The study aimed to use linked data from aeromedical, emergency department (ED), and hospital sources, and from death registries, to document and analyze patient journeys.

A previously developed air ambulance quality framework was used to place patient, prehospital, and in-hospital service outcomes in relevant quality domains identified from the Institutes of Medicine (IOM) and Dr. Donabedian models. To understand the aeromedical patients’ journeys, data from all relevant data sources were linked by unique patient identifiers and the outcomes of the resulting analyses were applied to the air ambulance quality framework.

Overall, air ambulance referral pathways could be classified into three categories: Intraregional (those retrievals which stayed within the region), Out of Region, and Into Region. Patient journeys and service outcomes varied markedly between referral pathways. Prehospital and in-hospital service variables and patient outcomes showed that the framework could be used to explore air ambulance service quality.

The air ambulance quality framework can usefully be applied to air ambulance patient experiences and outcomes using linked data analysis. The framework can help guide prehospital and in-hospital performance reporting. With variations between regional referral pathways, this knowledge will aid with planning within the local service. The study successfully linked data from aeromedical, ED, in-hospital, and death sources and explored the aeromedical patients’ journeys.

Child maltreatment (CM) and migrant status are independently associated with psychosis. We examined prevalence of CM by migrant status and tested whether migrant status moderated the association between CM and first-episode psychosis (FEP). We further explored whether differences in CM exposure contributed to variations in the incidence rates of FEP by migrant status.

We included FEP patients aged 18–64 years in 14 European sites and recruited controls representative of the local populations. Migrant status was operationalized according to generation (first/further) and region of origin (Western/non-Western countries). The reference population was composed by individuals of host country's ethnicity. CM was assessed with Childhood Trauma Questionnaire. Prevalence ratios of CM were estimated using Poisson regression. We examined the moderation effect of migrant status on the odds of FEP by CM fitting adjusted logistic regressions with interaction terms. Finally, we calculated the population attributable fractions (PAFs) for CM by migrant status.

We examined 849 FEP cases and 1142 controls. CM prevalence was higher among migrants, their descendants and migrants of non-Western heritage. Migrant status, classified by generation (likelihood test ratio:χ2 = 11.3, p = 0.004) or by region of origin (likelihood test ratio:χ2 = 11.4, p = 0.003), attenuated the association between CM and FEP. PAFs for CM were higher among all migrant groups compared with the reference populations.

The higher exposure to CM, despite a smaller effect on the odds of FEP, accounted for a greater proportion of incident FEP cases among migrants. Policies aimed at reducing CM should consider the increased vulnerability of specific subpopulations.

Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample.

Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of ‘Genetic’ models (solely fitted with PRS-SZ), ‘Environmental’ models (solely fitted with each environmental stressor), ‘Independent’ models (with PRS-SZ and each environmental factor), and ‘Interaction’ models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models.

There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension.

This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample.

The comorbidity between cardiometabolic and psychotic disorders develops early. This is a crucial window of opportunity to reduce excess morbidity and mortality. Recently, a cardiometabolic risk prediction algorithm for young people with psychosis, the psychosis metabolic risk calculator (PsyMetRiC) was developed and externally validated in the UK. However, its international transportability is unknown.

We performed the first international validation study of PsyMetRiC in Lausanne, Switzerland, and examined whether additional variables (clinical and/or genetic) may improve the predictive performance of the algorithm

We included people aged 16-35y with psychosis from the PsyMetab cohort, who did not have MetS at baseline, and who had 1-6y follow-up data. The PsyMetRiC partial (age, sex, ethnicity, body mass index, smoking status, and prescription of a metabolically-active antipsychotic) and full (also including high-density lipoprotein and triglycerides) algorithms were applied. Predictive performance was assessed using measures of discrimination (C-statistic) and calibration (calibration plots). Recalibration steps included refitting the intercept and/or slope if necessary. Additional variables (e.g. speed of weight gain, polygenic risk scores) were added to the model and predictive performance was reassessed.

We included 545 participants. The discrimination performance of both PsyMetRiC algorithms was good (C>0.75), and calibration plots showed good agreement between observed and predicted risk. Additional analyses to be conducted.

PsyMetRiC is likely to be generalizable for use in Switzerland, suggesting that PsyMetRiC may also be suitable for use in other European populations. While additional international validations are required, these findings are an encouraging step toward an international cardiometabolic risk prediction algorithm for young people with psychosis.

No significant relationships.

Lurasidone is a second-generation antipsychotic shown to have a lower risk of weight gain and a lower incidence of metabolic adverse events compared with some medications in the same class.

To describe treatment patterns, clinical outcomes and adverse drug reactions (ADRs) over 12 months following lurasidone initiation in patients with schizophrenia.

This was a multi-centre observational study involving data collection from patients’ medical records, conducted in seven mental health centres in the United Kingdom (UK) and Switzerland. The study included patients aged ≥18 years who initiated lurasidone after 1 January 2016 for the treatment of schizophrenia. Data were collected from medical records both retrospectively and prospectively using a standardised data collection form. Data collected included patient characteristics, treatment history, lurasidone regimens, clinical outcomes and ADRs.

Forty-eight patients participated in the study. The median (interquartile range [IQR]) age at lurasidone initiation was 33.5 (25.5-50.3) years and 31 (65%) patients were male. The median (range) lurasidone starting dose was 37 mg daily (9.3–148 mg). Thirty-eight (79%) patients continued lurasidone for the entire 12-month follow-up period. Among the 14 (29%) patients with documented relapse, the median (IQR) time to relapse was 3.4 (1.5–7.9) months. Five ADRs were recorded in patient notes judged as related to lurasidone: agitation, nausea, akathisia, somnolence and vomiting (one patient each).

In this real-world study of patients with schizophrenia in the UK and Switzerland, 79% of patients continued lurasidone for at least 12 months, and ADRs were reported rarely in patient notes.

This study was sponsored by CNX Therapeutics Ltd (formerly Sunovion Pharmaceuticals Europe Ltd). AJ is an employee of CNX Therapeutics. MA is an employee of OPEN HEALTH who was contracted by CNX Therapeutics for data analysis and medical writing.