Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Hypersalivation is a major side-effect of clozapine in patients with treatment-resistant schizophrenia.

We investigated the efficacy of topical anticholinergic formulation sofpironium bromide gel for improving hypersalivation in patients with treatment-resistant schizophrenia receiving clozapine.

A double-blind, controlled crossover study was conducted with sofpironium bromide gel and a placebo gel to treat clozapine-induced hypersalivation in 16 patients with treatment-resistant schizophrenia. Patients were randomly divided between groups A and B (each n = 8). Group A was treated with sofpironium bromide gel for 6 weeks, followed by a 2-week washout period and 6 weeks of placebo gel, after which they were observed for another 2 weeks. In contrast, group B was treated with placebo gel for 6 weeks, followed by a 2-week washout period, 6 weeks of sofpironium bromide gel and a 2-week observation period. One-minute saliva volume, objective salivation ratings (Drooling Severity and Frequency Scale and Nocturnal Hypersalivation Rating Scale) and subjective salivation ratings (Visual Analogue Scale) were assessed every 2 weeks.

All patients completed the trials. Three patients reported mild, spontaneously resolved skin itching. Compared with baseline values, the 1-min saliva volumes of both groups were significantly decreased by approximately 30% at the second week of sofpironium bromide gel treatment (P < 0.001), and significantly decreased by >40% at the fourth and sixth weeks of treatment (P < 0.001). The effects were maintained for over 2 weeks even after the treatment was discontinued.

We suggest that sofpironium bromide gel is effective in treating clozapine-induced hypersalivation in patients with treatment-resistant schizophrenia.

Individuals with schizophrenia (SCZ) and bipolar disorder (BD) display cognitive impairments, but the impairments in those with SCZ are more prominent, supported by genetic overlap between SCZ and cognitive impairments. However, it remains unclear whether cognitive performances differ between individuals at high and low genetic risks for SCZ or BD.

Using the latest Psychiatric Genomics Consortium (PGC) data, we calculated PGC3 SCZ-, PGC3 BD-, and SCZ v. BD polygenic risk scores (PRSs) in 173 SCZ patients, 70 unaffected first-degree relatives (FRs) and 196 healthy controls (HCs). Based on combinations of three PRS deciles, individuals in the genetic SCZ, genetic BD and low genetic risk groups were extracted. Cognitive performance was assessed by the Brief Assessment of Cognition in Schizophrenia.

SCZ-, BD-, SCZ v. BD-PRSs were associated with case–control status (R2 = 0.020–0.061), and SCZ-PRS was associated with relative–control status (R2 = 0.023). Furthermore, individuals in the highest decile for SCZ PRSs had elevated BD-PRSs [odds ratio (OR) = 6.33] and SCZ v. BD-PRSs (OR = 1.86) compared with those in the lowest decile. Of the three genetic risk groups, the low genetic risk group contained more HCs, whereas the genetic BD and SCZ groups contained more SCZ patients (p < 0.05). SCZ patients had widespread cognitive impairments, and FRs had cognitive impairments that were between those of SCZ patients and HCs (p < 0.05). Cognitive differences between HCs in the low genetic risk group and SCZ patients in the genetic BD or genetic SCZ groups were more prominent (Cohen's d > −0.20) than those between HCs and SCZ patients in the no genetic risk group. Furthermore, SCZ patients in the genetic SCZ group displayed lower scores in verbal fluency and attention than those in the genetic BD group (d > −0.20).

Our findings suggest that cognitive impairments in SCZ are partially mediated through genetic loadings for SCZ but not BD.

Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes.

The present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner.

Seven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ.

Four clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters.

Intellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.

Clinical practice guidelines for schizophrenia and major depressive disorder have been published. However, these have not had sufficient penetration in clinical settings. We developed the Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE) project as a dissemination and education programme for psychiatrists.

The aim of this study is to assess the effectiveness of the EGUIDE project on the subjective clinical behaviour of psychiatrists in accordance with clinical practice guidelines before and 1 and 2 years after participation in the programmes.

A total of 607 psychiatrists participated in this study during October 2016 and March 2019. They attended both 1-day educational programmes based on the clinical practice guidelines for schizophrenia and major depressive disorder, and answered web questionnaires about their clinical behaviours before and 1 and 2 years after attending the programmes. We evaluated the changes in clinical behaviours in accordance with the clinical practice guidelines between before and 2 years after the programme.

All of the scores for clinical behaviours in accordance with clinical practice guidelines were significantly improved after 1 and 2 years compared with before attending the programmes. There were no significant changes in any of the scores between 1 and 2 years after attending.

All clinical behaviours in accordance with clinical practice guidelines improved after attending the EGUIDE programme, and were maintained for at least 2 years. The EGUIDE project could contribute to improved guideline-based clinical behaviour among psychiatrists.

Intelligence is inversely associated with schizophrenia (SCZ) and bipolar disorder (BD); it remains unclear whether low intelligence is a cause or consequence. We investigated causal associations of intelligence with SCZ or BD risk and a shared risk between SCZ and BD and SCZ-specific risk.

To estimate putative causal associations, we performed multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) using generalized summary-data-based MR (GSMR). Summary-level datasets from five GWASs (intelligence, SCZ vs. control [CON], BD vs. CON, SCZ + BD vs. CON, and SCZ vs. BD; sample sizes of up to 269,867) were utilized.

A strong bidirectional association between risks for SCZ and BD was observed (odds ratio; ORSCZ → BD = 1.47, p = 2.89 × 10−41, ORBD → SCZ = 1.44, p = 1.85 × 10−52). Low intelligence was bidirectionally associated with a high risk for SCZ, with a stronger effect of intelligence on SCZ risk (ORlower intelligence → SCZ = 1.62, p = 3.23 × 10−14) than the reverse (ORSCZ → lower intelligence = 1.06, p = 3.70 × 10−23). Furthermore, low intelligence affected a shared risk between SCZ and BD (OR lower intelligence → SCZ + BD = 1.23, p = 3.41 × 10−5) and SCZ-specific risk (ORlower intelligence → SCZvsBD = 1.64, p = 9.72 × 10−10); the shared risk (ORSCZ + BD → lower intelligence = 1.04, p = 3.09 × 10−14) but not SCZ-specific risk (ORSCZvsBD → lower intelligence = 1.00, p = 0.88) weakly affected low intelligence. Conversely, there was no significant causal association between intelligence and BD risk (p > 0.05).

These findings support observational studies showing that patients with SCZ display impairment in premorbid intelligence and intelligence decline. Moreover, a shared factor between SCZ and BD might contribute to impairment in premorbid intelligence and intelligence decline but SCZ-specific factors might be affected by impairment in premorbid intelligence. We suggest that patients with these genetic factors should be categorized as having a cognitive disorder SCZ or BD subtype.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with impaired intelligence that predicts poor functional outcomes. However, little is known regarding the extent and severity of intelligence decline, that is, decreased present intelligence quotient (IQ) relative to premorbid levels, across psychiatric disorders and which clinical characteristics affect the decline.

Premorbid IQ, present IQ, and intelligence decline were compared across patients with MDD (n = 45), BD (n = 30), and SCZ (n = 139), and healthy controls (HCs; n = 135). Furthermore, we investigated which factors contribute to the intelligence decline in each diagnostic group.

Significant differences were observed in premorbid IQ, present IQ, and intelligence decline across the diagnostic groups. Patients with each psychiatric disorder displayed lower premorbid and present IQ and more intelligence decline than HCs. Patients with SCZ displayed lower premorbid and present IQ and more intelligence decline than patients with MDD and BD, while there were no significant differences between patients with MDD and BD. When patients with BD were divided based on bipolar I disorder (BD-I) and bipolar II disorder (BD-II), degrees of intelligence decline were similar between MDD and BD-II and between BD-I and SCZ. Lower educational attainment was correlated with a greater degree of intelligence decline in patients with SCZ and BD but not MDD.

These findings confirm that although all psychiatric disorders display intelligence decline, the severity of intelligence decline differs across psychiatric disorders (SCZ, BD-I > BD-II, MDD > HCs). Higher educational attainment as cognitive reserve contributes to protection against intelligence decline in BD and SCZ.

Psychiatric disorders and related intermediate phenotypes are highly heritable and have a complex, overlapping polygenic architecture. A large-scale genome-wide association study (GWAS) of anxiety disorders identified genetic variants that are significant on a genome-wide. The current study investigated the genetic etiological overlaps between anxiety disorders and frequently cooccurring psychiatric disorders and intermediate phenotypes.

Using case–control and factor score models, we investigated the genetic correlations of anxiety disorders with eight psychiatric disorders and intermediate phenotypes [the volumes of seven subcortical brain regions, childhood cognition, general cognitive ability and personality traits (subjective well-being, loneliness, neuroticism and extraversion)] from large-scale GWASs (n = 7556–298 420) by linkage disequilibrium score regression.

Among psychiatric disorders, the risk of anxiety disorders was positively genetically correlated with the risks of major depressive disorder (MDD) (rg ± standard error = 0.83 ± 0.16, p = 1.97 × 10−7), schizophrenia (SCZ) (0.28 ± 0.09, p = 1.10 × 10−3) and attention-deficit/hyperactivity disorder (ADHD) (0.34 ± 0.13, p = 8.40 × 10−3). Among intermediate phenotypes, significant genetic correlations existed between the risk of anxiety disorders and neuroticism (0.81 ± 0.17, p = 1.30 × 10−6), subjective well-being (−0.73 ± 0.18, p = 4.89 × 10−5), general cognitive ability (−0.23 ± 0.08, p = 4.70 × 10−3) and putamen volume (−0.50 ± 0.18, p = 5.00 × 10−3). No other significant genetic correlations between anxiety disorders and psychiatric or intermediate phenotypes were observed (p > 0.05). The case–control model yielded stronger genetic effect sizes than the factor score model.

Our findings suggest that common genetic variants underlying the risk of anxiety disorders contribute to elevated risks of MDD, SCZ, ADHD and neuroticism and reduced quality of life, putamen volume and cognitive performance. We suggest that the comorbidity of anxiety disorders is partly explained by common genetic variants.