To assess the comorbidity rates of alcohol use disorders (AUDs) in bipolar disorder (BD) and to explore possible sources of heterogeneity.

Studies were identified through database searches. Meta-analytic techniques were employed to aggregate data on lifetime comorbidity and to explore possible sources of heterogeneity. Funnel plots were used to detect publication bias.

In clinical studies, AUDs affected more than one in three subjects with BD. Significant heterogeneity was found, which was largely explained by the geographical location of study populations and gender ratio of participants. AUDs affected more than one in five women and two in five men.

AUDs are highly prevalent in BD. Our study revealed a substantial heterogeneity across studies. Further research including control groups is needed. Patients with BD should be assessed for current and previous AUDs.

There has been increasing interest in the association between childhood trauma and psychosis. Proposals for potential mechanisms involved include affective dysregulation and appraisals of threat, yet few large-scale clinical studies exist in affective psychosis.

We hypothesise that within bipolar disorder (BD), childhood events will show a significant association with psychosis, and in particular with symptoms driven by dysregulation of mood or with a persecutory content.

2019 participants were recruited as part of our programme of research into the genetic and non-genetic determinants of BD (www.bdrn.org). Data on lifetime ever presence of psychosis and specific psychotic symptoms were determined by detailed structured interview with case note review. Childhood events were recorded after self-report questionnaire and case note information.

There was no relationship between childhood events, or childhood abuse, and psychosis per se. Childhood events were not associated with increased risk of persecutory or other delusions. Significant associations were found between childhood abuse and auditory hallucinations, strongest between sexual abuse and mood congruent or abusive voices. These relationships remain significant after controlling for lifetime ever cannabis misuse.

Within affective disorder, the relationship between childhood events and psychosis appears to be relatively symptom-specific. It is possible that the pathways leading to psychotic symptoms differ, with delusions and non-hallucinatory symptoms being influenced less by childhood or early environmental experience.

1. Upthegrove R, Chard C, Jones, L, Gordon –Smith K, Forty L, Jones I and Craddock N. Adverse Childhood Events and Psychosis in Bipolar Affective Disorder. BJPsych In press BJP/2014/152611

The perinatal period is a high-risk period for the development of illness episodes in women with bipolar disorder. Relapse rates vary between 9 and 75% depending on the study. The overall risk of a severe episode is approximately 20%. The impact on women, the relationships with their babies and their families can be devastating. In the UK costs to society are £8.1 billion per year-cohort of births. The advice currently given to women is based of general risk rates. Women's needs of information for decision-making in the perinatal period are not being met.

To review the risk prediction approaches used for women with bipolar disorder in the perinatal period.

To understand the existing risk prediction models and approaches used for prognosis of the risk of recurrence of bipolar disorder for women in the perinatal period.

Systematic literature search of public medical electronic databases and grey literature on risk prediction for bipolar episodes in the perinatal period.

We will present the existing models and approaches used for risk prediction of illness episodes in the perinatal period.

Awareness of existing risk prediction models for recurrence of bipolar disorder in the perinatal period will allow better informed risk-benefit analysis of treatment and management options.

This person-centred approach will help women and clinicians in their decision-making at this crucial high-risk period.

The authors have not supplied their declaration of competing interest.

For women with bipolar disorder, childbirth is a high-risk period with 40–50% experiencing a recurrence and 20% developing a severe episode of postpartum psychosis. Bipolar episodes in the perinatal period affect women and their families.

Managing bipolar disorder in pregnancy and postpartum is a challenge. There is lack of literature to inform that and an urgent need for more data.

To develop and validate a risk prediction model for individual prognosis of the risk of recurrence of bipolar disorder for women in the perinatal period.

To provide evidence-based information to help women and the clinicians that look after them make decisions about their care, taking into account the most recent scientific knowledge and their individual characteristics.

The development of the model will be done in retrospective data from a large clinical cohort from the Bipolar Disorder Research Network (BDRN.org). The validation will be done in a prospectively recruited sample.

Participants will be 2181 parous women with a lifetime diagnosis of bipolar disorder from BDRN and 300 prospectively recruited pregnant women with a history of postpartum psychosis or bipolar disorder.

Predictors will be chosen based on clinical experience and literature, from data collected via semi-structured interview (in pregnancy and 3 months postpartum, medical and psychiatric notes) e.g. medication, smoking, parity, obstetric complications and sleep.

N/A.

We will present the full prediction model (regression coefficients and model intercept) and report performance measures (with CIs).

We will discuss its potential clinical use and implications for future research.

The authors have not supplied their declaration of competing interest.

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.

The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.

PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10−6). SLEs and CT were also associated with MDD status (p = 2.19 × 10−4 and p = 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.

CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.

Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).

For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.

Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.

AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Although usually thought of as external environmental stressors, a significant heritable component has been reported for measures of stressful life events (SLEs) in twin studies.

We examined the variance in SLEs captured by common genetic variants from a genome-wide association study (GWAS) of 2578 individuals. Genome-wide complex trait analysis (GCTA) was used to estimate the phenotypic variance tagged by single nucleotide polymorphisms (SNPs). We also performed a GWAS on the number of SLEs, and looked at correlations between siblings.

A significant proportion of variance in SLEs was captured by SNPs (30%, p = 0.04). When events were divided into those considered to be dependent or independent, an equal amount of variance was explained for both. This ‘heritability’ was in part confounded by personality measures of neuroticism and psychoticism. A GWAS for the total number of SLEs revealed one SNP that reached genome-wide significance (p = 4 × 10−8), although this association was not replicated in separate samples. Using available sibling data for 744 individuals, we also found a significant positive correlation of R2 = 0.08 in SLEs (p = 0.03).

These results provide independent validation from molecular data for the heritability of reporting environmental measures, and show that this heritability is in part due to both common variants and the confounding effect of personality.

Recent data provide strong support for a substantial common polygenic contribution (i.e. many alleles each of small effect) to genetic susceptibility for schizophrenia and overlapping susceptibility for bipolar disorder.

To test hypotheses about the relationship between schizophrenia and psychotic types of bipolar disorder.

Using a polygenic score analysis to test whether schizophrenia polygenic risk alleles, en masse, significantly discriminate between individuals with bipolar disorder with and without psychotic features. The primary sample included 1829 participants with bipolar disorder and the replication sample comprised 506 people with bipolar disorder.

The subset of participants with Research Diagnostic Criteria schizoaffective bipolar disorder (n = 277) were significantly discriminated from the remaining participants with bipolar disorder (n = 1552) in both the primary (P = 0.00059) and the replication data-sets (P = 0.0070). In contrast, those with psychotic bipolar disorder as a whole were not significantly different from those with non-psychotic bipolar disorder in either data-set.

Genetic susceptibility influences at least two major domains of psychopathological variation in the schizophrenia–bipolar disorder clinical spectrum: one that relates to expression of a ‘bipolar disorder-like’ phenotype and one that is associated with expression of ‘schizophrenia-like’ psychotic symptoms.

Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological–genetic research.

To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case–control bipolar disorder sample.

We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant at P<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type.

The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42 × 10–7). Biological systems implicated included gamma amniobutyric acid (GABA)A receptors. Genes having at least one associated polymorphism at P<10–4 included B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and CDH12.

Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes.