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.

Recent stressful life events (SLE) are a risk factor for psychosis, but limited research has explored how SLEs affect individuals at clinical high risk (CHR) for psychosis. The current study investigated the longitudinal effects of SLEs on functioning and symptom severity in CHR individuals, where we hypothesized CHR would report more SLEs than healthy controls (HC), and SLEs would be associated with poorer outcomes.

The study used longitudinal data from the EU-GEI High Risk study. Data from 331 CHR participants were analyzed to examine the effects of SLEs on changes in functioning, positive and negative symptoms over a 2-year follow-up. We compared the prevalence of SLEs between CHR and HCs, and between CHR who did (CHR-T) and did not (CHR-NT) transition to psychosis.

CHR reported 1.44 more SLEs than HC (p < 0.001), but there was no difference in SLEs between CHR-T and CHR-NT at baseline. Recent SLEs were associated with poorer functioning and more severe positive and negative symptoms in CHR individuals (all p < 0.01) but did not reveal a significant interaction with time.

CHR individuals who had experienced recent SLEs exhibited poorer functioning and more severe symptoms. However, as the interaction between SLEs and time was not significant, this suggests SLEs did not contribute to a worsening of symptoms and functioning over the study period. SLEs could be a key risk factor to becoming CHR for psychosis, however further work is required to inform when early intervention strategies mitigating against the effects of stress are most effective.

Adverse childhood experiences (ACE) can affect educational attainments, but little is known about their impact on educational achievements in people at clinical high risk of psychosis (CHR).

In total, 344 CHR individuals and 67 healthy controls (HC) were recruited as part of the European Community’s Seventh Framework Programme-funded multicenter study the European Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI). The brief version of the Child Trauma Questionnaire was used to measure ACE, while educational attainments were assessed using a semi-structured interview.

At baseline, compared with HC, the CHR group spent less time in education and had higher rates of ACE, lower rates of employment, and lower estimated intelligence quotient (IQ). Across both groups, the total number of ACE was associated with fewer days in education and lower level of education. Emotional abuse was associated with fewer days in education in HC. Emotional neglect was associated with a lower level of education in CHR, while sexual abuse was associated with a lower level of education in HC. In the CHR group, the total number of ACE, physical abuse, and neglect was significantly associated with unemployment, while emotional neglect was associated with employment.

ACE are strongly associated with developmental outcomes such as educational achievement. Early intervention for psychosis programs should aim at integrating specific interventions to support young CHR people in their educational and vocational recovery. More generally, public health and social interventions focused on the prevention of ACE (or reduce their impact if ACE occur) are recommended.

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.

Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.

We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.

Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).

Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.

Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

The high prevalence of smoking in individuals who are at ultra-high risk (UHR) for psychosis is well known and moderate cognitive deficits have also been found in UHR. However, the association between smoking and cognition in UHR is unknown and longitudinal studies are lacking.

A cohort study with 330 UHR individuals and 66 controls was conducted, as part of the European network of national schizophrenia networks studying gene–environment interactions (EU-GEI). At baseline and after 6, 12, and 24 months, smoking behavior was assessed with the Composite International Diagnostic Interview and cognitive functioning with a comprehensive test battery. Linear mixed-effects analyses were used to examine the multicross-sectional and prospective associations between (change in) smoking behavior and cognitive functioning, accounting for confounding variables.

At baseline, 53% of UHR and 27% of controls smoked tobacco. Smoking UHR and controls did not significantly differ from nonsmoking counterparts on the tested cognitive domains (speed of processing, attention/vigilance, working memory, verbal learning, or reasoning/problem solving) across different assessment times. Neither smoking cessation nor initiation was associated with a significant change in cognitive functioning in UHR.

No associations were found between smoking and cognitive impairment in UHR nor in controls. However, the fact that one in every two UHR individuals report daily use of tobacco is alarming. Our data suggest that UHR have fewer cognitive impairments and higher smoking cessation rates compared to patients with first-episode psychosis found in literature. Implications to promote smoking cessation in the UHR stage need further investigation.

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.

Psychosis is associated with a reasoning bias, which manifests as a tendency to ‘jump to conclusions’. We examined this bias in people at clinical high-risk for psychosis (CHR) and investigated its relationship with their clinical outcomes.

In total, 303 CHR subjects and 57 healthy controls (HC) were included. Both groups were assessed at baseline, and after 1 and 2 years. A ‘beads’ task was used to assess reasoning bias. Symptoms and level of functioning were assessed using the Comprehensive Assessment of At-Risk Mental States scale (CAARMS) and the Global Assessment of Functioning (GAF), respectively. During follow up, 58 (16.1%) of the CHR group developed psychosis (CHR-T), and 245 did not (CHR-NT). Logistic regressions, multilevel mixed models, and Cox regression were used to analyse the relationship between reasoning bias and transition to psychosis and level of functioning, at each time point.

There was no association between reasoning bias at baseline and the subsequent onset of psychosis. However, when assessed after the transition to psychosis, CHR-T participants showed a greater tendency to jump to conclusions than CHR-NT and HC participants (55, 17, 17%; χ2 = 8.13, p = 0.012). There was a significant association between jumping to conclusions (JTC) at baseline and a reduced level of functioning at 2-year follow-up in the CHR group after adjusting for transition, gender, ethnicity, age, and IQ.

In CHR participants, JTC at baseline was associated with adverse functioning at the follow-up. Interventions designed to improve JTC could be beneficial in the CHR population.

Sex differences in cognitive functioning have long been recognized in schizophrenia patients and healthy controls (HC). However, few studies have focused on patients with an at-risk mental state (ARMS) for psychosis. Thus, the aim of the present study was to investigate sex differences in neurocognitive performance in ARMS patients compared with HC.

The data analyzed in this study were collected within the multicenter European Gene–Environment Interactions study (11 centers). A total of 343 ARMS patients (158 women) and 67 HC subjects (33 women) were included. All participants completed a comprehensive neurocognitive battery. Linear mixed effects models were used to explore whether sex differences in cognitive functioning were present in the total group (main effect of sex) and whether sex differences were different for HC and ARMS (interaction between sex and group).

Women performed better in social cognition, speed of processing, and verbal learning than men regardless of whether they were ARMS or HC. However, only differences in speed of processing and verbal learning remained significant after correction for multiple testing. Additionally, ARMS patients displayed alterations in attention, current IQ, speed of processing, verbal learning, and working memory compared with HC.

Findings indicate that sex differences in cognitive functioning in ARMS are similar to those seen between healthy men and women. Thus, it appears that sex differences in cognitive performance may not be specific for ARMS, a finding resembling that in patients with schizophrenic psychoses.

Gender differences in symptomatology in chronic schizophrenia and first episode psychosis patients have often been reported. However, little is known about gender differences in those at risk of psychotic disorders. This study investigated gender differences in symptomatology, drug use, comorbidity (i.e. substance use, affective and anxiety disorders) and global functioning in patients with an at-risk mental state (ARMS) for psychosis.

The sample consisted of 336 ARMS patients (159 women) from the prodromal work package of the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI; 11 centers). Clinical symptoms, drug use, comorbidity and functioning were assessed at first presentation to an early detection center using structured interviews.

In unadjusted analyses, men were found to have significantly higher rates of negative symptoms and current cannabis use while women showed higher rates of general psychopathology and more often displayed comorbid affective and anxiety disorders. No gender differences were found for global functioning. The results generally did not change when corrected for possible cofounders (e.g. cannabis use). However, most differences did not withstand correction for multiple testing.

Findings indicate that gender differences in symptomatology and comorbidity in ARMS are similar to those seen in overt psychosis and in healthy controls. However, observed differences are small and would only be reliably detected in studies with high statistical power. Moreover, such small effects would likely not be clinically meaningful.

To determine whether probiotic prophylaxes reduce the odds of Clostridium difficile infection (CDI) in adults and children.

Individual participant data (IPD) meta-analysis of randomized controlled trials (RCTs), adjusting for risk factors.

We searched 6 databases and 11 grey literature sources from inception to April 2016. We identified 32 RCTs (n=8,713); among them, 18 RCTs provided IPD (n=6,851 participants) comparing probiotic prophylaxis to placebo or no treatment (standard care). One reviewer prepared the IPD, and 2 reviewers extracted data, rated study quality, and graded evidence quality.

Probiotics reduced CDI odds in the unadjusted model (n=6,645; odds ratio [OR] 0.37; 95% confidence interval [CI], 0.25–0.55) and the adjusted model (n=5,074; OR, 0.35; 95% CI, 0.23–0.55). Using 2 or more antibiotics increased the odds of CDI (OR, 2.20; 95% CI, 1.11–4.37), whereas age, sex, hospitalization status, and high-risk antibiotic exposure did not. Adjusted subgroup analyses suggested that, compared to no probiotics, multispecies probiotics were more beneficial than single-species probiotics, as was using probiotics in clinical settings where the CDI risk is ≥5%. Of 18 studies, 14 reported adverse events. In 11 of these 14 studies, the adverse events were retained in the adjusted model. Odds for serious adverse events were similar for both groups in the unadjusted analyses (n=4,990; OR, 1.06; 95% CI, 0.89–1.26) and adjusted analyses (n=4,718; OR, 1.06; 95% CI, 0.89–1.28). Missing outcome data for CDI ranged from 0% to 25.8%. Our analyses were robust to a sensitivity analysis for missingness.

Moderate quality (ie, certainty) evidence suggests that probiotic prophylaxis may be a useful and safe CDI prevention strategy, particularly among participants taking 2 or more antibiotics and in hospital settings where the risk of CDI is ≥5%.

PROSPERO 2015 identifier: CRD42015015701

Infect Control Hosp Epidemiol 2018;771–781