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.

Develop and implement a system in the Veterans Health Administration (VA) to alert local medical center personnel in real time when an acute- or long-term care patient/resident is admitted to their facility with a history of colonization or infection with a multidrug-resistant organism (MDRO) previously identified at any VA facility across the nation.

An algorithm was developed to extract clinical microbiology and local facility census data from the VA Corporate Data Warehouse initially targeting carbapenem-resistant Enterobacterales (CRE) and methicillin-resistant Staphylococcus aureus (MRSA). The algorithm was validated with chart review of CRE cases from 2010-2018, trialed and refined in 24 VA healthcare systems over two years, expanded to other MDROs and implemented nationwide on 4/2022 as “VA Bug Alert” (VABA). Use through 8/2023 was assessed.

VABA performed well for CRE with recall of 96.3%, precision of 99.8%, and F1 score of 98.0%. At the 24 trial sites, feedback was recorded for 1,011 admissions with a history of CRE (130), MRSA (814), or both (67). Among Infection Preventionists and MDRO Prevention Coordinators, 338 (33%) reported being previously unaware of the information, and of these, 271 (80%) reported they would not have otherwise known this information. By fourteen months after nationwide implementation, 113/130 (87%) VA healthcare systems had at least one VABA subscriber.

A national system for alerting facilities in real-time of patients admitted with an MDRO history was successfully developed and implemented in VA. Next steps include understanding facilitators and barriers to use and coordination with non-VA facilities nationwide.

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.

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.

23% of people experiencing a first episode of psychosis (FEP) develop treatment resistant schizophrenia (TRS). At present, there are no established methods to accurately identify who will develop TRS from baseline.

In this study we used patient data from three UK early intervention services (EIS) to investigate the predictive potential of routinely recorded sociodemographic, lifestyle and biological data at FEP baseline for the risk of TRS up to six years later.

We developed two risk prediction algorithms to predict the risk of TRS at 2-8 years from FEP onset using commonly recorded information at baseline. Using the forced-entry method, we created a model including age, sex, ethnicity, triglycerides, alkaline phosphatase levels and lymphocyte counts. We also produced a machine-learning-based model, including an additional four variables. The models were developed using data from two and externally validated in another UK psychosis EIS.

The development samples included 785 patients, and 1,110 were included in the validation sample. The models discriminated TRS well at internal validation (forced-entry: C 0.70, 95%CI 0.63-0.76; LASSO: C 0.69, 95%CI 0.63-0.77). At external validation, discrimination performance attenuated (forced-entry: C 0.63, 0.58-0.69; LASSO: C 0.64, 0.58-0.69) but recovered for the forced entry model after recalibration and revision of the lymphocyte predictor (C: 0.67, 0.62-0.73).

The use of commonly recorded clinical information including biomarkers taken at FEP onset could help to predict TRS. These measures should be considered in future studies modelling psychiatric outcomes.

No significant relationships.

Non-alcoholic fatty liver disease (NAFLD) is an increasing cause of chronic liver disease that accompanies obesity and the metabolic syndrome. Excess fructose consumption can initiate or exacerbate NAFLD in part due to a consequence of impaired hepatic fructose metabolism. Preclinical data emphasized that fructose-induced altered gut microbiome, increased gut permeability, and endotoxemia play an important role in NAFLD, but human studies are sparse. The present study aimed to determine if two weeks of excess fructose consumption significantly alters gut microbiota or permeability in humans.

We performed a pilot double-blind, cross-over, metabolic unit study in 10 subjects with obesity (body mass index [BMI] 30–40 mg/kg/m2). Each arm provided 75 grams of either fructose or glucose added to subjects’ individual diets for 14 days, substituted isocalorically for complex carbohydrates, with a 19-day wash-out period between arms. Total fructose intake provided in the fructose arm of the study totaled a mean of 20.1% of calories. Outcome measures included fecal microbiota distribution, fecal metabolites, intestinal permeability, markers of endotoxemia, and plasma metabolites.

Routine blood, uric acid, liver function, and lipid measurements were unaffected by the fructose intervention. The fecal microbiome (including Akkermansia muciniphilia), fecal metabolites, gut permeability, indices of endotoxemia, gut damage or inflammation, and plasma metabolites were essentially unchanged by either intervention.

In contrast to rodent preclinical findings, excess fructose did not cause changes in the gut microbiome, metabolome, and permeability as well as endotoxemia in humans with obesity fed fructose for 14 days in amounts known to enhance NAFLD.

Nonsuicidal self-injury (NSSI) is prevalent among adolescents and research is needed to clarify the mechanisms which contribute to the behavior. Here, the authors relate behavioral neurocognitive measures of impulsivity and compulsivity to repetitive and sporadic NSSI in a community sample of adolescents.

Computerized laboratory tasks (Affective Go/No-Go, Cambridge Gambling Task, and Probabilistic Reversal Task) were used to evaluate cognitive performance. Participants were adolescents aged 15 to 17 with (n = 50) and without (n = 190) NSSI history, sampled from the ROOTS project which recruited adolescents from secondary schools in Cambridgeshire, UK. NSSI was categorized as sporadic (1-3 instances per year) or repetitive (4 or more instances per year). Analyses were carried out in a series of linear and negative binomial regressions, controlling for age, gender, intelligence, and recent depressive symptoms.

Adolescents with lifetime NSSI, and repetitive NSSI specifically, made significantly more perseverative errors on the Probabilistic Reversal Task and exhibited significantly lower quality of decision making on the Cambridge Gambling Task compared to no-NSSI controls. Those with sporadic NSSI did not significantly differ from no-NSSI controls on task performance. NSSI was not associated with behavioral measures of impulsivity.

Repetitive NSSI is associated with increased behavioral compulsivity and disadvantageous decision making, but not with behavioral impulsivity. Future research should continue to investigate how neurocognitive phenotypes contribute to the onset and maintenance of NSSI, and determine whether compulsivity and addictive features of NSSI are potential targets for treatment.

Perceived discrimination is associated with worse mental health. Few studies have assessed whether perceived discrimination (i) is associated with the risk of psychotic disorders and (ii) contributes to an increased risk among minority ethnic groups relative to the ethnic majority.

We used data from the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions Work Package 2, a population-based case−control study of incident psychotic disorders in 17 catchment sites across six countries. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between perceived discrimination and psychosis using mixed-effects logistic regression models. We used stratified and mediation analyses to explore differences for minority ethnic groups.

Reporting any perceived experience of major discrimination (e.g. unfair treatment by police, not getting hired) was higher in cases than controls (41.8% v. 34.2%). Pervasive experiences of discrimination (≥3 types) were also higher in cases than controls (11.3% v. 5.5%). In fully adjusted models, the odds of psychosis were 1.20 (95% CI 0.91–1.59) for any discrimination and 1.79 (95% CI 1.19–1.59) for pervasive discrimination compared with no discrimination. In stratified analyses, the magnitude of association for pervasive experiences of discrimination appeared stronger for minority ethnic groups (OR = 1.73, 95% CI 1.12–2.68) than the ethnic majority (OR = 1.42, 95% CI 0.65–3.10). In exploratory mediation analysis, pervasive discrimination minimally explained excess risk among minority ethnic groups (5.1%).

Pervasive experiences of discrimination are associated with slightly increased odds of psychotic disorders and may minimally help explain excess risk for minority ethnic groups.

The authors have not supplied their declaration of competing interest.

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

The P300 amplitude and latency were not associated (regression coef. −0.06, 95% CI −0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10–0.28, p < 0.001). There was no evidence of associations between lateral ventricular volume and the other measures (all p > 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

We examined longitudinally the course and predictors of treatment resistance in a large cohort of first-episode psychosis (FEP) patients from initiation of antipsychotic treatment. We hypothesized that antipsychotic treatment resistance is: (a) present at illness onset; and (b) differentially associated with clinical and demographic factors.

The study sample comprised 323 FEP patients who were studied at first contact and at 10-year follow-up. We collated clinical information on severity of symptoms, antipsychotic medication and treatment adherence during the follow-up period to determine the presence, course and predictors of treatment resistance.

From the 23% of the patients, who were treatment resistant, 84% were treatment resistant from illness onset. Multivariable regression analysis revealed that diagnosis of schizophrenia, negative symptoms, younger age at onset, and longer duration of untreated psychosis predicted treatment resistance from illness onset.

The striking majority of treatment-resistant patients do not respond to first-line antipsychotic treatment even at time of FEP. Clinicians must be alert to this subgroup of patients and consider clozapine treatment as early as possible during the first presentation of psychosis.