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 severely affects the outcome of people with psychotic disorders, yet there is a lack of treatments. To address this, in 2019 the National Health Service (NHS) Cannabis Clinic for Psychosis (CCP) was developed to support adults suffering from psychosis to reduce and/or stop their cannabis use.

Examine outcome data from the first 46 individuals to complete the CCP's intervention.

The sample (N = 46) consisted of adults (aged ≥ 18) with psychosis under the care of the South London and Maudsley NHS Foundation Trust, referred to the CCP between January 2020 and February 2023, who completed their intervention by September 2023. Clinical and functional measures were collected before (T0) and after (T1) the CCP intervention (one-to-one sessions and peer group attendance). Primary outcomes were changes in the Cannabis Use Disorders Identification Test-Revised (CUDIT-R) score and pattern of cannabis use. Secondary outcomes included T0–T1 changes in measures of delusions, paranoia, depression, anxiety and functioning.

A reduction in the mean CUDIT-R score was observed between T0 (mean difference = 17.10, 95% CI = 15.54–18.67) and T1, with 73.91% of participants achieving abstinence and 26.09% reducing the frequency and potency of their use. Significant improvements in all clinical and functional outcomes were observed, with 90.70% being in work or education at T1 compared with 8.70% at T0. The variance in CUDIT-R scores explained between 34 and 64% of the variance in our secondary measures.

The CCP intervention is a feasible strategy to support cannabis use cessation/reduction and improve clinical and functional outcomes of people with psychotic disorders.

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.

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.

Positive, negative and disorganised psychotic symptom dimensions are associated with clinical and developmental variables, but differing definitions complicate interpretation. Additionally, some variables have had little investigation.

To investigate associations of psychotic symptom dimensions with clinical and developmental variables, and familial aggregation of symptom dimensions, in multiple samples employing the same definitions.

We investigated associations between lifetime symptom dimensions and clinical and developmental variables in two twin and two general psychosis samples. Dimension symptom scores and most other variables were from the Operational Criteria Checklist. We used logistic regression in generalised linear mixed models for combined sample analysis (n = 875 probands). We also investigated correlations of dimensions within monozygotic (MZ) twin pairs concordant for psychosis (n = 96 pairs).

Higher symptom scores on all three dimensions were associated with poor premorbid social adjustment, never marrying/cohabiting and earlier age at onset, and with a chronic course, most strongly for the negative dimension. The positive dimension was also associated with Black and minority ethnicity and lifetime cannabis use; the negative dimension with male gender; and the disorganised dimension with gradual onset, lower premorbid IQ and substantial within twin-pair correlation. In secondary analysis, disorganised symptoms in MZ twin probands were associated with lower premorbid IQ in their co-twins.

These results confirm associations that dimensions share in common and strengthen the evidence for distinct associations of co-occurring positive symptoms with ethnic minority status, negative symptoms with male gender and disorganised symptoms with substantial familial influences, which may overlap with influences on premorbid IQ.

For 50 years, the Thomas Wickham-Jones (TWJ) Foundation has promoted the advancement of otology and audiology in the UK and Republic of Ireland through a series of overseas Fellowships and other grants.

The paper examines the history of the Foundation since its establishment in 1974, drawing upon the Foundation's archives and personal recollections. The analysis is located within a framework concerning the factors that shape the success or failure of a foundation including vision, strategy, information, leadership and finance.

The activities of the TWJ Foundation are charted over five decades, and the governance of the Foundation is detailed. Particular attention is given to the Major Fellowships offered, at first in North America, and to their subsequent development into the Foundation's current rotation.

The paper offers an assessment of the TWJ Foundation's impact on the training of otologists in the British Isles and concludes with a brief self-reflective analysis.

Data on associations between inflammation and depressive symptoms largely originate from high income population settings, despite the greatest disease burden in major depressive disorder being attributed to populations in lower-middle income countries (LMICs).

We assessed the prevalence of low-grade inflammation in adults with treatment-resistant depression (TRD) in Pakistan, an LMIC, and investigated associations between peripheral C-reactive protein (CRP) levels and depressive symptoms.

This is a secondary analysis of two randomised controlled trials investigating adjunctive immunomodulatory agents (minocycline and simvastatin) for Pakistani adults with TRD (n = 191). Logistic regression models were built to assess the relationship between pre-treatment CRP (≥ or <3 mg/L) and individual depressive symptoms measured using the Hamilton Depression Rating Scale. Descriptive statistics and regression were used to assess treatment response for inflammation-associated symptoms.

High plasma CRP (≥3 mg/L) was detected in 87% (n = 146) of participants. Early night insomnia (odds ratio 2.33, 95% CI 1.16–5.25), early morning waking (odds ratio 2.65, 95% CI 1.29–6.38) and psychic anxiety (odds ratio 3.79, 95% CI 1.39–21.7) were positively associated, while gastrointestinal (odds ratio 0.38, 95% CI 0.14–0.86) and general somatic symptoms (odds ratio 0.34, 95% CI 0.14–0.74) were negatively associated with inflammation. Minocycline, but not simvastatin, improved symptoms positively associated with inflammation.

The prevalence of inflammation in this LMIC sample with TRD was higher than that reported in high income countries. Insomnia and anxiety symptoms may represent possible targets for personalised treatment with immunomodulatory agents in people with elevated CRP. These findings require replication in independent clinical samples.

Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform.

Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts.

The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivity (0.85), specificity (0.96), precision (0.64), F1 score (0.73), and an area under the precision-recall curve of 0.84. Compared to non-suicidal posts, suicidal posts were more likely to contain explicit mentions of suicide, descriptions of risk factors (e.g. depression, PTSD) and help-seeking, and first-person singular pronouns.

Our results demonstrate the feasibility and potential promise of using social media posts to identify at-risk Servicemembers and Veterans. Future work will use this approach to deliver targeted interventions to social media users at risk for suicide.

Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are associated with various social determinants. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address known social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders.

To examine the evidence base for interventions that seek to improve mental health through targeting the social determinants of mental disorders.

We conducted a systematic review of reviews, using a five-domain conceptual framework which aligns with the UN SDGs (PROSPERO registration: CRD42022361534). PubMed, PsycInfo, and Scopus were searched from 01 January 2012 until 05 October 2022. Citation follow-up and expert consultation were used to identify additional studies. Systematic reviews including interventions seeking to change or improve a social determinant of mental disorders were eligible for inclusion. Study screening, selection, data extraction, and quality appraisal were conducted in accordance with PRISMA guidelines. The AMSTAR-2 was used to assess included reviews and results were narratively synthesised.

Over 20,000 records were screened, and 101 eligible reviews were included. Most reviews were of low, or critically low, quality. Reviews included interventions which targeted sociocultural (n = 31), economic (n = 24), environmental (n = 19), demographic (n = 15), and neighbourhood (n = 8) determinants of mental disorders. Interventions demonstrating the greatest promise for improved mental health from high and moderate quality reviews (n = 37) included: digital and brief advocacy interventions for female survivors of intimate partner violence; cash transfers for people in low-middle-income countries; improved work schedules, parenting programs, and job clubs in the work environment; psychosocial support programs for vulnerable individuals following environmental events; and social and emotional learning programs for school students. Few effective neighbourhood-level interventions were identified.

This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health. A range of issues across the literature were identified, including barriers to conducting randomised controlled trials and lack of follow-up limiting the ability to measure long-term mental health outcomes. Interdisciplinary and novel approaches to intervention design, implementation, and evaluation are required to improve the social circumstances and mental health experienced by individuals, communities, and populations.

None Declared

A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.