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.

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

Given the many statistical analysis options used for randomized controlled trials (RCTs) of behavioral interventions and the lack of clear guidance for analysis selection, the present study aimed to characterize the predominate statistical analyses utilized in RCTs in palliative care and behavioral research and to highlight the relative strengths and weaknesses of each of these methods as guidance for future researchers and reform.

All RCTs published between 2015 and 2021 were systematically extracted from 4 behavioral medicine journals and analyzed based on prespecified inclusion criteria. Two independent raters classified each of the manuscripts into 1 of 5 RCT analysis strategies.

There was wide variation in the methods used. The 2 most prevalent analyses for RCTs were longitudinal modeling and analysis of covariance. Application of method varied significantly by sample size.

Each statistical analysis presents its own unique strengths and weaknesses. The information resulting from this research may prove helpful for researchers in palliative care and behavioral medicine in navigating the variety of statistical methods available. Future discussion around best practices in RCT analyses is warranted to compare the relative impact of interventions in a more standardized way.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

The investigators conducted a psychosocial needs assessment of mesothelioma patients through self-report measures of quality of life (QOL), coping, depression, and social support.

Patients with malignant pleural mesothelioma (MPM) (N = 67) completed a battery of assessments at a single timepoint after being approached during routine medical oncology clinic appointments or by letter.

Participants were predominately male (70.0%; n = 47) and ranged in age from 35 to 83 years old (M = 65.61, SD = 9.71). Most participants were white (88.0%; n = 59), and 10.0% (n = 7) were identified as Hispanic. The majority were married or living with a partner (93.0%; n = 62) and had some college or more education (64.0%; n = 43). Fourteen percent of participants (n = 11) endorsed significantly elevated depression symptoms. No significant demographic or clinical differences in depressed compared to nondepressed participants were observed, with a trend toward those identifying as Hispanic and those who were divorced as being more likely to be depressed. For the total sample, the most frequently endorsed coping strategies were active coping, emotional support, and acceptance.

The present study did not identify any clear correlates of depression or QOL among patients with MPM. This research contributes to the small literature on psychosocial functioning in patients with MPM and provides putative directions for future larger studies and the development of interventions to provide appropriate support to diverse patients with MPM.

Post-traumatic growth (PTG) is a positive psychological consequence of trauma. The aims of this study were to investigate whether combat injury was associated with deployment-related PTG in a cohort of UK military personnel who were deployed to Afghanistan, and whether post-traumatic stress disorder (PTSD), depression and pain mediate this relationship.

521 physically injured (n = 138 amputation; n = 383 non-amputation injury) and 514 frequency-matched uninjured personnel completed questionnaires including the deployment-related Post-Traumatic Growth Inventory (DPTGI). DPTGI scores were categorised into tertiles of: no/low (score 0–20), moderate (score 21–34) or a large (35–63) degree of deployment-related PTG. Analysis was completed using generalised structural equation modelling.

A large degree of PTG was reported by 28.0% (n = 140) of the uninjured group, 36.9% (n = 196) of the overall injured group, 45.4% (n = 62) of amputee and 34.1% (n = 134) of the non-amputee injured subgroups. Combat injury had a direct effect on reporting a large degree of PTG [Relative risk ratio (RRR) 1.59 (95% confidence interval (CI) 1.17–2.17)] compared to sustaining no injury. Amputation injuries also had a significant direct effect [RRR 2.18 (95% CI 1.24–3.75)], but non-amputation injuries did not [RRR 1.35 (95% CI 0.92–1.93)]. PTSD, depression and pain partially mediate this relationship, though mediation differed depending on the injury subtype. PTSD had a curvilinear relationship with PTG, whilst depression had a negative association and pain had a positive association.

Combat injury, in particular injury resulting in traumatic amputation, is associated with reporting a large degree of PTG.

The COVID-19 pandemic has affected all our lives, not only through the infection itself but also through the measures taken to control the spread of the virus (e.g. lockdown).

Here, we investigated how the COVID-19 pandemic and unprecedented lockdown affected the mental health of young adults in England and Wales.

We compared the mental health symptoms of up to 4773 twins in their mid-20s in 2018 prior to the COVID-19 pandemic (T1) and during four-wave longitudinal data collection during the pandemic in April, July and October 2020, and in March 2021 (T2–T5) using phenotypic and genetic longitudinal designs.

The average changes in mental health were small to medium and mainly occurred from T1 to T2 (average Cohen d = 0.14). Despite the expectation of catastrophic effects of the pandemic on mental health, we did not observe trends in worsening mental health during the pandemic (T3–T5). Young people with pre-existing mental health problems were disproportionately affected at the beginning of the pandemic, but their increased problems largely subsided as the pandemic persisted. Twin analyses indicated that the aetiology of individual differences in mental health symptoms did not change during the lockdown (average heritability 33%); the average genetic correlation between T1 and T2–T5 was 0.95, indicating that genetic effects before the pandemic were substantially correlated with genetic effects up to a year later.

We conclude that on average the mental health of young adults in England and Wales has been remarkably resilient to the effects of the pandemic and associated lockdown.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations.

The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner.

We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating.

The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of ‘neural efficiency’ (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Although mental wellbeing has been linked with positive health outcomes, including longevity and improved emotional and cognitive functioning, studies examining the underlying neural mechanisms of both subjective and psychological wellbeing have been sparse. We assessed whether both forms of wellbeing are associated with neural activity engaged during positive and negative emotion processing and the extent to which this association is driven by genetics or environment.

We assessed mental wellbeing in 230 healthy adult monozygotic and dizygotic twins using a previously validated questionnaire (COMPAS-W) and undertook functional magnetic resonance imaging during a facial emotion viewing task. We used linear mixed models to analyse the association between COMPAS-W scores and emotion-elicited neural activation. Univariate twin modelling was used to evaluate heritability of each brain region. Multivariate twin modelling was used to compare twin pairs to assess the contributions of genetic and environmental factors to this association.

Higher levels of wellbeing were associated with greater neural activity in the dorsolateral prefrontal cortex, localised in the right inferior frontal gyrus (IFG), in response to positive emotional expressions of happiness. Univariate twin modelling showed activity in the IFG to have 20% heritability. Multivariate twin modelling suggested that the association between wellbeing and positive emotion-elicited neural activity was driven by common variance from unique environment (r = 0.208) rather than shared genetics.

Higher mental wellbeing may have a basis in greater engagement of prefrontal neural regions in response to positive emotion, and this association may be modifiable by unique life experiences.