Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Cannabis use and familial vulnerability to psychosis have been associated with social cognition deficits. This study examined the potential relationship between cannabis use and cognitive biases underlying social cognition and functioning in patients with first episode psychosis (FEP), their siblings, and controls.

We analyzed a sample of 543 participants with FEP, 203 siblings, and 1168 controls from the EU-GEI study using a correlational design. We used logistic regression analyses to examine the influence of clinical group, lifetime cannabis use frequency, and potency of cannabis use on cognitive biases, accounting for demographic and cognitive variables.

FEP patients showed increased odds of facial recognition processing (FRP) deficits (OR = 1.642, CI 1.123–2.402) relative to controls but not of speech illusions (SI) or jumping to conclusions (JTC) bias, with no statistically significant differences relative to siblings. Daily and occasional lifetime cannabis use were associated with decreased odds of SI (OR = 0.605, CI 0.368–0.997 and OR = 0.646, CI 0.457–0.913 respectively) and JTC bias (OR = 0.625, CI 0.422–0.925 and OR = 0.602, CI 0.460–0.787 respectively) compared with lifetime abstinence, but not with FRP deficits, in the whole sample. Within the cannabis user group, low-potency cannabis use was associated with increased odds of SI (OR = 1.829, CI 1.297–2.578, FRP deficits (OR = 1.393, CI 1.031–1.882, and JTC (OR = 1.661, CI 1.271–2.171) relative to high-potency cannabis use, with comparable effects in the three clinical groups.

Our findings suggest increased odds of cognitive biases in FEP patients who have never used cannabis and in low-potency users. Future studies should elucidate this association and its potential implications.

Racial and ethnic variations in antibiotic utilization are well-reported in outpatient settings but little is known about inpatient settings. Our objective was to describe national inpatient antibiotic utilization among children by race and ethnicity.

This study included hospital visit data from the Pediatric Health Information System between 01/01/2022 and 12/31/2022 for patients <20 years. Primary outcomes were the percentage of hospitalization encounters that received an antibiotic and antibiotic days of therapy (DOT) per 1000 patient days. Mixed-effect regression models were used to determine the association of race-ethnicity with outcomes, adjusting for covariates.

There were 846,530 hospitalizations. 45.2% of children were Non-Hispanic (NH) White, 27.1% were Hispanic, 19.2% were NH Black, 4.5% were NH Other, 3.5% were NH Asian, 0.3% were NH Native Hawaiian/Other Pacific Islander (NHPI) and 0.2% were NH American Indian. Adjusting for covariates, NH Black children had lower odds of receiving antibiotics compared to NH White children (aOR 0.96, 95%CI 0.94–0.97), while NH NHPI had higher odds of receiving antibiotics (aOR 1.16, 95%CI 1.05–1.29). Children who were Hispanic, NH Asian, NH American Indian, and children who were NH Other received antibiotic DOT compared to NH White children, while NH NHPI children received more antibiotic DOT.

Antibiotic utilization in children’s hospitals differs by race and ethnicity. Hospitals should assess policies and practices that may contribute to disparities in treatment; antibiotic stewardship programs may play an important role in promoting inpatient pharmacoequity. Additional research is needed to examine individual diagnoses, clinical outcomes, and drivers of variation.

The psychometric rigor of unsupervised, smartphone-based assessments and factors that impact remote protocol engagement is critical to evaluate prior to the use of such methods in clinical contexts. We evaluated the validity of a high-frequency, smartphone-based cognitive assessment protocol, including examining convergence and divergence with standard cognitive tests, and investigating factors that may impact adherence and performance (i.e., time of day and anticipated receipt of feedback vs. no feedback).

Cognitively unimpaired participants (N = 120, Mage = 68.8, 68.3% female, 87% White, Meducation = 16.5 years) completed 8 consecutive days of the Mobile Monitoring of Cognitive Change (M2C2), a mobile app-based testing platform, with brief morning, afternoon, and evening sessions. Tasks included measures of working memory, processing speed, and episodic memory. Traditional neuropsychological assessments included measures from the Preclinical Alzheimer’s Cognitive Composite battery.

Findings showed overall high compliance (89.3%) across M2C2 sessions. Average compliance by time of day ranged from 90.2% for morning sessions, to 77.9% for afternoon sessions, and 84.4% for evening sessions. There was evidence of faster reaction time and among participants who expected to receive performance feedback. We observed excellent convergent and divergent validity in our comparison of M2C2 tasks and traditional neuropsychological assessments.

This study supports the validity and reliability of self-administered, high-frequency cognitive assessment via smartphones in older adults. Insights into factors affecting adherence, performance, and protocol implementation are discussed.

It remains unknown whether severe mental disorders contribute to fatally harmful effects of physical illness.

To investigate the risk of all-cause death and loss of life-years following the onset of a wide range of physical health conditions in people with severe mental disorders compared with matched counterparts who had only these physical health conditions, and to assess whether these associations can be fully explained by this patient group having more clinically recorded physical illness.

Using Czech national in-patient register data, we identified individuals with 28 physical health conditions recorded between 1999 and 2017, separately for each condition. In these people, we identified individuals who had severe mental disorders recorded before the physical health condition and exactly matched them with up to five counterparts who had no recorded prior severe mental disorders. We estimated the risk of all-cause death and lost life-years following each of the physical health conditions in people with pre-existing severe mental disorders compared with matched counterparts without severe mental disorders.

People with severe mental disorders had an elevated risk of all-cause death following the onset of 7 out of 9 broadly defined and 14 out of 19 specific physical health conditions. People with severe mental disorders lost additional life-years following the onset of 8 out 9 broadly defined and 13 out of 19 specific physical health conditions. The vast majority of results remained robust after considering the potentially confounding role of somatic multimorbidity and other clinical and sociodemographic factors.

A wide range of physical illnesses are more likely to result in all-cause death in people with pre-existing severe mental disorders. This premature mortality cannot be fully explained by having more clinically recorded physical illness, suggesting that physical disorders are more likely to be fatally harmful in this patient group.

Knowledge of sex differences in risk factors for posttraumatic stress disorder (PTSD) can contribute to the development of refined preventive interventions. Therefore, the aim of this study was to examine if women and men differ in their vulnerability to risk factors for PTSD.

As part of the longitudinal AURORA study, 2924 patients seeking emergency department (ED) treatment in the acute aftermath of trauma provided self-report assessments of pre- peri- and post-traumatic risk factors, as well as 3-month PTSD severity. We systematically examined sex-dependent effects of 16 risk factors that have previously been hypothesized to show different associations with PTSD severity in women and men.

Women reported higher PTSD severity at 3-months post-trauma. Z-score comparisons indicated that for five of the 16 examined risk factors the association with 3-month PTSD severity was stronger in men than in women. In multivariable models, interaction effects with sex were observed for pre-traumatic anxiety symptoms, and acute dissociative symptoms; both showed stronger associations with PTSD in men than in women. Subgroup analyses suggested trauma type-conditional effects.

Our findings indicate mechanisms to which men might be particularly vulnerable, demonstrating that known PTSD risk factors might behave differently in women and men. Analyses did not identify any risk factors to which women were more vulnerable than men, pointing toward further mechanisms to explain women's higher PTSD risk. Our study illustrates the need for a more systematic examination of sex differences in contributors to PTSD severity after trauma, which may inform refined preventive interventions.

We examined whether cannabis use contributes to the increased risk of psychotic disorder for non-western minorities in Europe.

We used data from the EU-GEI study (collected at sites in Spain, Italy, France, the United Kingdom, and the Netherlands) on 825 first-episode patients and 1026 controls. We estimated the odds ratio (OR) of psychotic disorder for several groups of migrants compared with the local reference population, without and with adjustment for measures of cannabis use.

The OR of psychotic disorder for non-western minorities, adjusted for age, sex, and recruitment area, was 1.80 (95% CI 1.39–2.33). Further adjustment of this OR for frequency of cannabis use had a minimal effect: OR = 1.81 (95% CI 1.38–2.37). The same applied to adjustment for frequency of use of high-potency cannabis. Likewise, adjustments of ORs for most sub-groups of non-western countries had a minimal effect. There were two exceptions. For the Black Caribbean group in London, after adjustment for frequency of use of high-potency cannabis the OR decreased from 2.45 (95% CI 1.25–4.79) to 1.61 (95% CI 0.74–3.51). Similarly, the OR for Surinamese and Dutch Antillean individuals in Amsterdam decreased after adjustment for daily use: from 2.57 (95% CI 1.07–6.15) to 1.67 (95% CI 0.62–4.53).

The contribution of cannabis use to the excess risk of psychotic disorder for non-western minorities was small. However, some evidence of an effect was found for people of Black Caribbean heritage in London and for those of Surinamese and Dutch Antillean heritage in Amsterdam.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

There has been increased interest in repurposing anti-inflammatories for the treatment of bipolar depression. Evidence from high-income countries suggests that these agents may work best for specific depressive symptoms in a subset of patients with biochemical evidence of inflammation but data from lower-middle income countries (LMICs) is scarce. This secondary analysis explored the relationship between pretreatment inflammatory markers and specific depressive symptoms, clinical measures, and demographic variables in participants with bipolar depression in Pakistan.

The current study is a cross-sectional secondary analysis of a randomized controlled trial of two anti-inflammatory medications (minocycline and celecoxib) for bipolar depression (n = 266). A series of logistic and linear regression models were completed to assess the relationship between C-reactive protein (CRP) (CRP > or < 3 mg/L and log10CRP) and clinical and demographic features of interest and symptoms of depression. Baseline clinical trial data was used to extract clinical and demographic features and symptoms of depression were assessed using the 24-item Hamilton Depression Rating Scale.

The prevalence of low-grade inflammation (CRP > 3 mg/L) in the sample was 70.9%. After adjusting for baseline body mass index, socioeconomic status, age, gender, symptoms related to anhedonia, fatigue, and motor retardation were most associated with low-grade inflammation.

Bipolar disorder (BD) patients from LMICs may experience higher rates of peripheral inflammation than have been reported in Western populations with BD. Future trials of repurposed anti-inflammatory agents that enrich for participants with these symptom profiles may inform the development of personalized treatment for bipolar depression in LMICs.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

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.

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.