Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).

We conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.

There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.

These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.

Young people with 22q11.2 deletion syndrome (22q11.2DS) are at high risk for neurodevelopmental disorders. Sleep problems may play a role in this risk but their prevalence, nature and links to psychopathology and cognitive function remain undescribed in this population.

Sleep problems, psychopathology, developmental coordination and cognitive function were assessed in 140 young people with 22q11.2DS (mean age = 10.1, s.d. = 2.46) and 65 unaffected sibling controls (mean age = 10.8, s.d.SD = 2.26). Primary carers completed questionnaires screening for the children's developmental coordination and autism spectrum disorder.

Sleep problems were identified in 60% of young people with 22q11.2DS compared to 23% of sibling controls (OR 5.00, p < 0.001). Two patterns best-described sleep problems in 22q11.2DS: restless sleep and insomnia. Restless sleep was linked to increased ADHD symptoms (OR 1.16, p < 0.001) and impaired executive function (OR 0.975, p = 0.013). Both patterns were associated with elevated symptoms of anxiety disorder (restless sleep: OR 1.10, p = 0.006 and insomnia: OR 1.07, p = 0.045) and developmental coordination disorder (OR 0.968, p = 0.0023, and OR 0.955, p = 0.009). The insomnia pattern was also linked to elevated conduct disorder symptoms (OR 1.53, p = 0.020).

Clinicians and carers should be aware that sleep problems are common in 22q11.2DS and index psychiatric risk, cognitive deficits and motor coordination problems. Future studies should explore the physiology of sleep and the links with the neurodevelopment in these young people.

To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.

To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.

Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.

Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.

Mental disorders may emerge as the result of interactions between observable symptoms. Such interactions can be analyzed using network analysis. Several recent studies have used network analysis to examine eating disorders, indicating a core role of overvaluation of weight and shape. However, no studies to date have applied network models to binge-eating disorder (BED), the most prevalent eating disorder.

We constructed a cross-sectional graphical LASSO network in a sample of 788 individuals with BED. Symptoms were assessed using the Eating Disorders Examination Interview. We identified core symptoms of BED using expected influence centrality.

Overvaluation of shape emerged as the symptom with the highest centrality. Dissatisfaction with weight and overvaluation of weight also emerged as highly central symptoms. On the other hand, behavioral symptoms such as binge eating, eating in secret, and dietary restraint/restriction were less central. The network was stable, allowing for reliable interpretations (centrality stability coefficient = 0.74).

Overvaluation of shape and weight emerged as core symptoms of BED. This trend is consistent with past network analyses of eating disorders more broadly, as well as literature that suggests a primary role of shape and weight concerns in BED. Although DSM-5 diagnostic criteria for BED does not currently include a cognitive criterion related to body image or shape/weight overvaluation, our results provide support for including shape/weight overvaluation as a diagnostic specifier.

To identify developmental sub-groups of depressive symptoms during the second decade of life, a critical period of brain development, using data from a prospective birth cohort. To test whether childhood intelligence and inflammatory markers are associated with subsequent persistent depressive symptoms.

IQ, a proxy for neurodevelopment, was measured at age 8 years. Interleukin 6 (IL-6) and C-reactive protein, typical inflammatory markers, were measured at age 9 years. Depressive symptoms were measured six times between 10 and 19 years using the short mood and feelings questionnaire (SMFQ), which were coded as binary variable and then used in latent class analysis to identify developmental sub-groups of depressive symptoms.

Longitudinal SMFQ data from 9156 participants yielded three distinct population sub-groups of depressive symptoms: no symptoms (81.2%); adolescent-onset symptoms (13.2%); persistent symptoms (5.6%). Lower IQ and higher IL-6 levels in childhood were independently associated with subsequent persistent depressive symptoms in a linear, dose–response fashion, but not with adolescent-onset symptoms. Compared with the group with no symptoms the adjusted odds ratio for persistent depressive symptoms per s.d. increase in IQ was 0.80 (95% CI, 0.68–0.95); that for IL-6 was 1.20 (95% CI, 1.03–1.39). Evidence for an association with IL-6 remained after controlling for initial severity of depressive symptoms at 10 years. There was no evidence that IL-6 moderated or mediated the IQ-persistent depressive symptom relationship.

The results indicate potentially important roles for two distinct biological processes, neurodevelopment and inflammation, in the aetiology of persistent depressive symptoms in young people.

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

The P300 amplitude and latency were not associated (regression coef. −0.06, 95% CI −0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10–0.28, p < 0.001). There was no evidence of associations between lateral ventricular volume and the other measures (all p > 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

Differences between verbal and non-verbal cognitive development from childhood to adulthood may differentiate between those with and without psychotic symptoms and affective symptoms in later life. However, there has been no study exploring this in a population-based cohort.

The sample was drawn from the MRC National Survey of Health and Development, and consisted of 2384 study members with self-reported psychotic experiences and affective symptoms at the age of 53 years, and with complete cognitive data at the ages of 8 and 15 years. The association between verbal and non-verbal cognition at age 8 years and relative developmental lag from age 8 to 15 years, and both adult outcomes were tested with the covariates adjusted, and mutually adjusted for verbal and non-verbal cognition.

Those with psychotic experiences [thought interference (n = 433), strange experience (n = 296), hallucination (n = 88)] had lower cognition at both the ages of 8 and 15 years in both verbal and non-verbal domains. After mutual adjustment, lower verbal cognition at age 8 years and greater verbal developmental lag were associated with higher likelihood of psychotic experiences within individuals, whereas there was no association between non-verbal cognition and any psychotic experience. In contrast, those with case-level affective symptoms (n = 453) had lower non-verbal cognition at age 15 years, and greater developmental lag in the non-verbal domain. After adjustment, lower non-verbal cognition at age 8 years and greater non-verbal developmental lag were associated with higher risk of case-level affective symptoms within individuals.

These results suggest that cognitive profiles in childhood and adolescence differentiate psychiatric disease spectra.