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.

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.

In the UK, acute mental healthcare is provided by in-patient wards and crisis resolution teams. Readmission to acute care following discharge is common. Acute day units (ADUs) are also provided in some areas.

To assess predictors of readmission to acute mental healthcare following discharge in England, including availability of ADUs.

We enrolled a national cohort of adults discharged from acute mental healthcare in the English National Health Service (NHS) between 2013 and 2015, determined the risk of readmission to either in-patient or crisis teams, and used multivariable, multilevel logistic models to evaluate predictors of readmission.

Of a total of 231 998 eligible individuals discharged from acute mental healthcare, 49 547 (21.4%) were readmitted within 6 months, with a median time to readmission of 34 days (interquartile range 10–88 days). Most variation in readmission (98%) was attributable to individual patient-level rather than provider (trust)-level effects (2.0%). Risk of readmission was not associated with local availability of ADUs (adjusted odds ratio 0.96, 95% CI 0.80–1.15). Statistically significant elevated risks were identified for participants who were female, older, single, from Black or mixed ethnic groups, or from more deprived areas. Clinical predictors included shorter index admission, psychosis and being an in-patient at baseline.

Relapse and readmission to acute mental healthcare are common following discharge and occur early. Readmission was not influenced significantly by trust-level variables including availability of ADUs. More support for relapse prevention and symptom management may be required following discharge from acute mental healthcare.

Nightmares are a hallmark symptom of posttraumatic stress disorder (PTSD). This strong association may reflect a shared pathophysiology in the form of altered autonomic activity and increased reactivity. Using an acoustic startle paradigm, we investigated the interrelationships of psychophysiological measures during wakefulness and PTSD diagnosis, posttraumatic nightmares, and nontraumatic nightmares.

A community sample of 122 trauma survivors were presented with a series of brief loud tones, while heart rate (HRR), skin conductance (SCR), and orbicularis oculi electromyogram (EMGR) responses were measured. Prior to the tone presentations, resting heart rate variability (HRV) was assessed. Nightmares were measured using nightmare logs. Three dichotomous groupings of participants were compared: (1) current PTSD diagnosis (n = 59), no PTSD diagnosis (n = 63), (2) those with (n = 26) or without (n = 96) frequent posttraumatic nightmares, and (3) those with (n = 22) or without (n = 100) frequent nontraumatic nightmares.

PTSD diagnosis was associated with posttraumatic but not with nontraumatic nightmares. Both PTSD and posttraumatic nightmares were associated with a larger mean HRR to loud tones, whereas nontraumatic nightmare frequency was associated with a larger SCR. EMGR and resting HRV were not associated with PTSD diagnosis or nightmares.

Our findings suggest a shared pathophysiology between PTSD and posttraumatic nightmares in the form of increased HR reactivity to startling tones, which might reflect reduced parasympathetic tone. This shared pathophysiology could explain why PTSD is more strongly related to posttraumatic than nontraumatic nightmares, which could have important clinical implications.

For people in mental health crisis, acute day units (ADUs) provide daily structured sessions and peer support in non-residential settings, often as an addition or alternative to crisis resolution teams (CRTs). There is little recent evidence about outcomes for those using ADUs, particularly compared with those receiving CRT care alone.

We aimed to investigate readmission rates, satisfaction and well-being outcomes for people using ADUs and CRTs.

We conducted a cohort study comparing readmission to acute mental healthcare during a 6-month period for ADU and CRT participants. Secondary outcomes included satisfaction (Client Satisfaction Questionnaire), well-being (Short Warwick–Edinburgh Mental Well-being Scale) and depression (Center for Epidemiologic Studies Depression Scale).

We recruited 744 participants (ADU: n = 431, 58%; CRT: n = 312, 42%) across four National Health Service trusts/health regions. There was no statistically significant overall difference in readmissions: 21% of ADU participants and 23% of CRT participants were readmitted over 6 months (adjusted hazard ratio 0.78, 95% CI 0.54–1.14). However, readmission results varied substantially by setting. At follow-up, ADU participants had significantly higher Client Satisfaction Questionnaire scores (2.5, 95% CI 1.4–3.5, P < 0.001) and well-being scores (1.3, 95% CI 0.4–2.1, P = 0.004), and lower depression scores (−1.7, 95% CI −2.7 to −0.8, P < 0.001), than CRT participants.

Patients who accessed ADUs demonstrated better outcomes for satisfaction, well-being and depression, and no significant differences in risk of readmission, compared with those who only used CRTs. Given the positive outcomes for patients, and the fact that ADUs are inconsistently provided in the National Health Service, their value and place in the acute care pathway needs further consideration and research.

Predictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of ‘at-risk’ cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.

Multi-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12–30) presenting to mental health services.

Of 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.

Identifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.

Obesity and excess bodyweight are highly prevalent in individuals with bipolar disorders (BD) and are associated with adverse consequences. Multiple factors may explain increased bodyweight in BD including side effects of psychotropic medications, and reduced physical activity. Research in the general population demonstrates that sleep disturbances may also contribute to metabolic burden. We present a cross-sectional study of the associations between body mass index (BMI) and sleep parameters in patients with BD as compared with healthy controls (HC).

Twenty-six French outpatients with remitted BD and 29 HC with a similar BMI completed a 21-day study of sleep parameters using objective (actigraphy) and subjective (PSQI: Pittsburgh Sleep Quality Index) assessments.

In BD cases, but not in HC, higher BMI was significantly correlated with lower sleep efficiency (P = 0.009) and with several other sleep parameters: shorter total sleep time (P = 0.01), longer sleep onset latency (P = 0.05), higher fragmentation index (P = 0.008), higher inter-day variability (P = 0.05) and higher PSQI total score (P = 0.004).

The findings suggest a link between a high BMI and several sleep disturbances in BD, including lower sleep efficiency. Physiological mechanisms in BD cases may include an exaggeration of phenomena observed in non-clinical populations. However, larger scale studies are required to clarify the links between metabolic and sleep-wake cycle disturbances in BD.

Role functioning is key to optimal health and inoculates against life-long inequality. Depression is a leading cause of functional disability. In most cases, improved symptomatology corresponds with improved functioning; however, functioning does not always return to “normal”, despite symptom remission. Furthermore, the relationship between symptom remission and the likelihood of being Not in Employment, Education or Training (NEET) is unknown.

To examine the temporal associations between depression course, functioning, and NEET status in young adults with mental health problems.

A prospective and multisite clinical cohort study of young people aged 15–25 years seeking help from a primary mental health service (n = 448). Participants completed a clinical interview (incl. QIDS-C16) and self-report battery (incl. WHODAS 2.0, employment, education) at baseline which was repeated at 12-month follow-up whilst continuing treatment as usual.

Remitted depression was significantly associated with improved functioning; however, 12 month functioning was still lower than the normative ranges for age-matched peers. Remittance of depression did not change the likelihood of being NEET. Only 10% of those who were NEET had received vocational support during the study.

Remittance of depression was associated with improved functioning but it did not reduce the likelihood of being NEET. This may be explained by economic influences or alternatively, a time lag may exist where improvements in functioning do not immediately correspond with reduced NEET rates. Lastly, there may be a scarring effect of depression such that change in NEET status requires an additional intervention to depression treatment.

The authors have not supplied their declaration of competing interest.

Intermittent explosive disorder (IED) is characterised by impulsive anger attacks that vary greatly across individuals in severity and consequence. Understanding IED subtypes has been limited by lack of large, general population datasets including assessment of IED. Using the 17-country World Mental Health surveys dataset, this study examined whether behavioural subtypes of IED are associated with differing patterns of comorbidity, suicidality and functional impairment.

IED was assessed using the Composite International Diagnostic Interview in the World Mental Health surveys (n = 45 266). Five behavioural subtypes were created based on type of anger attack. Logistic regression assessed association of these subtypes with lifetime comorbidity, lifetime suicidality and 12-month functional impairment.

The lifetime prevalence of IED in all countries was 0.8% (s.e.: 0.0). The two subtypes involving anger attacks that harmed people (‘hurt people only’ and ‘destroy property and hurt people’), collectively comprising 73% of those with IED, were characterised by high rates of externalising comorbid disorders. The remaining three subtypes involving anger attacks that destroyed property only, destroyed property and threatened people, and threatened people only, were characterised by higher rates of internalising than externalising comorbid disorders. Suicidal behaviour did not vary across the five behavioural subtypes but was higher among those with (v. those without) comorbid disorders, and among those who perpetrated more violent assaults.

The most common IED behavioural subtypes in these general population samples are associated with high rates of externalising disorders. This contrasts with the findings from clinical studies of IED, which observe a preponderance of internalising disorder comorbidity. This disparity in findings across population and clinical studies, together with the marked heterogeneity that characterises the diagnostic entity of IED, suggests that it is a disorder that requires much greater research.

Epidemiological studies indicate that individuals with one type of mental disorder have an increased risk of subsequently developing other types of mental disorders. This study aimed to undertake a comprehensive analysis of pair-wise lifetime comorbidity across a range of common mental disorders based on a diverse range of population-based surveys.

The WHO World Mental Health (WMH) surveys assessed 145 990 adult respondents from 27 countries. Based on retrospectively-reported age-of-onset for 24 DSM-IV mental disorders, associations were examined between all 548 logically possible temporally-ordered disorder pairs. Overall and time-dependent hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. Absolute risks were estimated using the product-limit method. Estimates were generated separately for men and women.

Each prior lifetime mental disorder was associated with an increased risk of subsequent first onset of each other disorder. The median HR was 12.1 (mean = 14.4; range 5.2–110.8, interquartile range = 6.0–19.4). The HRs were most prominent between closely-related mental disorder types and in the first 1–2 years after the onset of the prior disorder. Although HRs declined with time since prior disorder, significantly elevated risk of subsequent comorbidity persisted for at least 15 years. Appreciable absolute risks of secondary disorders were found over time for many pairs.

Survey data from a range of sites confirms that comorbidity between mental disorders is common. Understanding the risks of temporally secondary disorders may help design practical programs for primary prevention of secondary disorders.