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.

The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models.

A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5–18 years). Potential predictors included demographic, clinical, parental, and treatment variables with data obtained pre-treatment, post-treatment, and at least one follow-up.

All machine learning models performed similarly for remission outcomes, with AUC between 0.67 and 0.69. There was significant alignment between the factors that contributed to the models predicting two target outcomes: remission of all anxiety disorders and the primary anxiety disorder. Children who were older, had multiple anxiety disorders, comorbid depression, comorbid externalising disorders, received group treatment and therapy delivered by a more experienced therapist, and who had a parent with higher anxiety and depression symptoms, were more likely than other children to still meet criteria for anxiety disorders at the completion of therapy. In both models, the absence of a social anxiety disorder and being treated by a therapist with less experience contributed to the model predicting a higher likelihood of remission.

These findings underscore the utility of prediction models that may indicate which children are more likely to remit or are more at risk of non-remission following CBT for childhood anxiety.

Progress towards understanding the aetiology of major depression is compromised by its clinical heterogeneity. The variety of contexts underlying the development of a major depressive episode may contribute to such heterogeneity.

To compare risk factor profiles for three subgroups of major depression according to episode context.

Using self-report questionnaires and administrative records from the UK Biobank, we characterised three contextual subgroups of major depression: postpartum depression (3581 cases), depression following diagnosis of a chronic disease (409 cases) and a more typical (named heterogeneous) major depression phenotype excluding the two other contexts (34 699 cases). Controls with the same exposure were also defined. We tested each subgroup for association with the polygenic risk scores (PRS) for major depression and with other risk factors previously associated with major depression (bipolar disorder PRS, neuroticism, reported trauma in childhood and adulthood, socioeconomic status, family history of depression, education).

Major depression PRS was associated with all subgroups, but postpartum depression cases had higher PRS than heterogeneous major depression cases (OR = 1.06, 95% CI 1.02–1.10). Relative to heterogeneous depression, postpartum depression was more weakly associated with adulthood trauma and neuroticism. Depression following diagnosis of a chronic disease had weaker association with neuroticism and reported trauma in adulthood and childhood relative to heterogeneous depression.

The observed differences in risk factor profiles according to the context of a major depressive episode help provide insight into the heterogeneity of depression. Future studies dissecting such heterogeneity could help reveal more refined aetiological insights.

High rates of recidivism are reported after paediatric cholesteatoma surgery. Our practice has adapted to include non-echoplanar diffusion-weighted magnetic resonance imaging for the diagnosis of residual or recurrent cholesteatoma. This audit aimed to evaluate the performance of non-echoplanar diffusion-weighted magnetic resonance imaging in our paediatric population.

A retrospective review was conducted of non-echoplanar diffusion-weighted magnetic resonance imaging scans performed to detect residual disease or recurrence after surgery for cholesteatoma in children from 1 January 2012 to 30 November 2017 in our centre. Follow-up diffusion-weighted magnetic resonance imaging scans were reviewed to 16 August 2019.

Thirty-four diffusion-weighted magnetic resonance imaging scans were included. The sensitivity and specificity values of diffusion-weighted magnetic resonance imaging for detecting post-operative cholesteatoma were 81 per cent and 72 per cent, respectively. Positive predictive and negative predictive values were 72 per cent and 81 per cent, respectively.

Use of diffusion-weighted magnetic resonance imaging is recommended as a replacement for routine second-look surgical procedures in the paediatric population. However, we would caution that patients require close follow up after negative diffusion-weighted magnetic resonance imaging findings.

Researchers have begun to change their approach to training in the biomedical sciences through the development of communities of practice (CoPs). CoPs share knowledge across clinical and laboratory contexts to promote the progress of clinical and translational science. The Congressionally Directed Medical Research Programs’ (CDMRP) Ovarian Cancer Academy (OCA) was designed as a virtual CoP to promote interactions among early career investigators (ECIs) and their mentors with the goal of eliminating ovarian cancer.

A mixed-methods approach (surveys and interviews) was used to evaluate the effectiveness of the OCA for the eight ECIs and five mentors. Quantitative analysis included internal reliability of scales and descriptive statistics for each measure, as well as paired sample t-tests for Time 1 and Time 2. Qualitative data were analyzed for themes to discern which aspects of the program were useful and where more attention is needed.

Preliminary analyses reveal several trends, including the importance of training in grant writing to the ECI’s productivity, as well as the value of peer mentorship.

The results show that the OCA was an innovative and effective way to create a CoP with broad implications for the field of ovarian cancer research, as well as for the future of biomedical research training.

Retrospective self-reports of childhood trauma are associated with a greater risk of psychopathology in adulthood than prospective measures of trauma. Heritable reporter characteristics are anticipated to account for part of this association, whereby genetic predisposition to certain traits influences both the likelihood of self-reporting trauma and of developing psychopathology. However, previous research has not considered how gene–environment correlation influences these associations.

To investigate reporter characteristics associated with retrospective self-reports of childhood trauma and whether these associations are accounted for by gene–environment correlation.

In 3963 unrelated individuals from the Twins Early Development Study, we tested whether polygenic scores for 21 psychiatric, cognitive, anthropometric and personality traits were associated with retrospectively self-reported childhood emotional and physical abuse. To assess the presence of gene–environment correlation, we investigated whether these associations remained after controlling for composite scores of environmental adversity across development.

Retrospectively self-reported childhood trauma was associated with polygenic scores for autism spectrum disorder (ASD), body mass index (BMI), post-traumatic stress disorder (PTSD) and risky behaviours. When composite scores of environmental adversity were controlled for, only associations with the polygenic scores for ASD and PTSD remained significant.

Genetic predisposition to ASD and PTSD may increase liability to experiencing or interpreting events as traumatic. Associations between genetic predisposition for risky behaviour and BMI with self-reported childhood trauma may reflect gene–environment correlation. Studies of the association between retrospectively self-reported childhood trauma and later-life outcomes should consider that genetically influenced reporter characteristics may confound associations, both directly and through gene–environment correlation.

Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart.

To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability.

We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores.

Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’ and ‘extensively affected’ individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment.

Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.

Anxiety and depressive disorders can be chronic and disabling. Although there are effective treatments, only a fraction of those impaired receive treatment. Predictors of treatment-seeking and treatment receipt could be informative for initiatives aiming to tackle the burden of untreated anxiety and depression.

To investigate sociodemographic characteristics associated with treatment-seeking and treatment receipt.

Two binary retrospective reports of lifetime treatment-seeking (n = 44 810) and treatment receipt (n = 37 346) were regressed on sociodemographic factors (age, gender, UK ethnic minority background, educational attainment, household income, neighbourhood deprivation and social isolation) and alternative coping strategies (self-medication with alcohol/drugs and self-help) in UK Biobank participants with lifetime generalised anxiety or major depressive disorder. Analyses were also stratified by gender.

Treatment access was more likely in those who reported use of self-help strategies, with university-level education and those from less economically advantaged circumstances (household income <£30 000 and greater neighbourhood deprivation). Treatment access was less likely in those who were male, from a UK ethnic minority background and with high household incomes (>£100 000). Men who self-medicated and/or had a vocational qualification were also less likely to seek treatment.

This work on retrospective reports of treatment-seeking and treatment receipt at any time of life replicates known associations with treatment-seeking and treatment receipt during time of treatment need. More work is required to understand whether improving rates of treatment-seeking improves prognostic outcomes for individuals with anxiety or depression.

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD.

Genetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals.

Genetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01–1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001)

Our findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.

People with bipolar disorder (BPD) are more likely to die prematurely, which is partly attributed to comorbid cardiometabolic traits. Previous studies report cardiometabolic abnormalities in BPD, but their shared aetiology remains poorly understood. This study examined the phenotypic associations and shared genetic aetiology between BPD and various cardiometabolic traits.

In a subset of the UK Biobank sample (N = 61 508) we investigated phenotypic associations between BPD (ncases = 4186) and cardiometabolic traits, represented by biomarkers, anthropometric traits and cardiometabolic diseases. To determine shared genetic aetiology in European ancestry, polygenic risk scores (PRS) and genetic correlations were calculated between BPD and cardiometabolic traits.

Several traits were significantly associated with increased risk for BPD, namely low total cholesterol, low high-density lipoprotein cholesterol, high triglycerides, high glycated haemoglobin, low systolic blood pressure, high body mass index, high waist-to-hip ratio; and stroke, coronary artery disease and type 2 diabetes diagnosis. BPD was associated with higher polygenic risk for triglycerides, waist-to-hip ratio, coronary artery disease and type 2 diabetes. Shared genetic aetiology persisted for coronary artery disease, when correcting PRS associations for cardiometabolic base phenotypes. Associations were not replicated using genetic correlations.

This large study identified increased phenotypic cardiometabolic abnormalities in BPD participants. It is found that the comorbidity of coronary artery disease may be based on shared genetic aetiology. These results motivate hypothesis-driven research to consider individual cardiometabolic traits rather than a composite metabolic syndrome when attempting to disentangle driving mechanisms of cardiometabolic abnormalities in BPD.

To assess the relationship between food insecurity, sleep quality, and days with mental and physical health issues among college students.

An online survey was administered. Food insecurity was assessed using the ten-item Adult Food Security Survey Module. Sleep was measured using the nineteen-item Pittsburgh Sleep Quality Index (PSQI). Mental health and physical health were measured using three items from the Healthy Days Core Module. Multivariate logistic regression was conducted to assess the relationship between food insecurity, sleep quality, and days with poor mental and physical health.

Twenty-two higher education institutions.

College students (n 17 686) enrolled at one of twenty-two participating universities.

Compared with food-secure students, those classified as food insecure (43·4 %) had higher PSQI scores indicating poorer sleep quality (P < 0·0001) and reported more days with poor mental (P < 0·0001) and physical (P < 0·0001) health as well as days when mental and physical health prevented them from completing daily activities (P < 0·0001). Food-insecure students had higher adjusted odds of having poor sleep quality (adjusted OR (AOR): 1·13; 95 % CI 1·12, 1·14), days with poor physical health (AOR: 1·01; 95 % CI 1·01, 1·02), days with poor mental health (AOR: 1·03; 95 % CI 1·02, 1·03) and days when poor mental or physical health prevented them from completing daily activities (AOR: 1·03; 95 % CI 1·02, 1·04).

College students report high food insecurity which is associated with poor mental and physical health, and sleep quality. Multi-level policy changes and campus wellness programmes are needed to prevent food insecurity and improve student health-related outcomes.

The UK Biobank contains data with varying degrees of reliability and completeness for assessing depression. A third of participants completed a Mental Health Questionnaire (MHQ) containing the gold-standard Composite International Diagnostic Interview (CIDI) criteria for assessing mental health disorders.

To investigate whether multiple observations of depression from sources other than the MHQ can enhance the validity of major depressive disorder (MDD).

In participants who did not complete the MHQ, we calculated the number of other depression measures endorsed, for example from hospital episode statistics and interview data. We compared cases defined this way with CIDI-defined cases for several estimates: the variance explained by polygenic risk scores (PRS), area under the curve attributable to PRS, single nucleotide polymorphisms (SNPs)-based heritability and genetic correlations with summary statistics from the Psychiatric Genomics Consortium MDD genome-wide association study.

The strength of the genetic contribution increased with the number of measures endorsed. For example, SNP-based heritability increased from 7% in participants who endorsed only one measure of depression, to 21% in those who endorsed four or five measures of depression. The strength of the genetic contribution to cases defined by at least two measures approximated that for CIDI-defined cases. Most genetic correlations between UK Biobank and the Psychiatric Genomics Consortium MDD study exceeded 0.7, but there was variability between pairwise comparisons.

Multiple measures of depression can serve as a reliable approximation for case status where the CIDI measure is not available, indicating sample size can be optimised using the entire suite of UK Biobank data.

To examine children’s sugar-sweetened beverage (SSB) and water intakes in relation to implemented intervention activities across the social ecological model (SEM) during a multilevel community trial.

Children’s Healthy Living was a multilevel, multicomponent community trial that reduced young child obesity (2013–2015). Baseline and 24-month cross-sectional data were analysed from nine intervention arm communities. Implemented intervention activities targeting reduced SSB and increased water consumption were coded by SEM level (child, caregiver, organisation, community and policy). Child SSB and water intakes were assessed by caregiver-completed 2-day dietary records. Multilevel linear regression models examined associations of changes in beverage intakes with activity frequencies at each SEM level.

US-Affiliated Pacific region.

Children aged 2–8 years (baseline: n 1343; 24 months: n 1158).

On average (± sd), communities implemented 74 ± 39 SSB and 72 ± 40 water activities. More than 90 % of activities targeted both beverages together. Community-level activities (e.g. social marketing campaign) were most common (61 % of total activities), and child-level activities (e.g. sugar counting game) were least common (4 %). SSB activities across SEM levels were not associated with SSB intake changes. Additional community-level water activities were associated with increased water intake (0·62 ml/d/activity; 95 % CI: 0·09, 1·15) and water-for-SSB substitution (operationalised as SSB minus water: –0·88 ml/d/activity; 95 % CI: –1·72, –0·03). Activities implemented at the organization level (e.g. strengthening preschool wellness guidelines) and policy level (e.g. SSB tax advocacy) also suggested greater water-for-SSB substitution (P < 0·10).

Community-level intervention activities were associated with increased water intake, alone and relative to SSB intake, among young children in the Pacific region.

Major depression (MD) is often characterised as a categorical disorder; however, observational studies comparing sub-threshold and clinical depression suggest MD is continuous. Many of these studies do not explore the full continuum and are yet to consider genetics as a risk factor. This study sought to understand if polygenic risk for MD could provide insight into the continuous nature of depression.

Factor analysis on symptom-level data from the UK Biobank (N = 148 957) was used to derive continuous depression phenotypes which were tested for association with polygenic risk scores (PRS) for a categorical definition of MD (N = 119 692).

Confirmatory factor analysis showed a five-factor hierarchical model, incorporating 15 of the original 18 items taken from the PHQ-9, GAD-7 and subjective well-being questionnaires, produced good fit to the observed covariance matrix (CFI = 0.992, TLI = 0.99, RMSEA = 0.038, SRMR = 0.031). MD PRS associated with each factor score (standardised β range: 0.057–0.064) and the association remained when the sample was stratified into case- and control-only subsets. The case-only subset had an increased association compared to controls for all factors, shown via a significant interaction between lifetime MD diagnosis and MD PRS (p value range: 2.23 × 10−3–3.94 × 10−7).

An association between MD PRS and a continuous phenotype of depressive symptoms in case- and control-only subsets provides support against a purely categorical phenotype; indicating further insights into MD can be obtained when this within-group variation is considered. The stronger association within cases suggests this variation may be of particular importance.