Second-generation antipsychotics (SGAs) cause metabolic side effects. However, patients’ metabolic profiles were influenced by time-invariant and time-varying confounders. Real-world evidence on the long-term, dynamic effects of SGAs (e.g. different treatment sequences) are limited. We employed advanced causal inference methods to evaluate the metabolic impact of SGAs in a naturalistic cohort.

We followed 696 Chinese patients with schizophrenia-spectrum disorders receiving SGAs. Longitudinal targeted maximum likelihood estimation (LTMLE) was used to estimate the average treatment effects (ATEs) of continuous SGA treatment versus ‘no treatment’ on metabolic outcomes, including total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), fasting glucose (FG), and body mass index (BMI), over 6–18 months at 3-month intervals. LTMLE accounted for time-invariant and time-varying confounders. Post-SGA discontinuation side effects were also assessed.

The ATEs of continuous SGA treatment on BMI and TG showed an inverted U-shaped pattern, peaking at 12 months and declining afterwards. Similar patterns were observed for TC and LDL, albeit the ATEs peaked at 15 months. For FG and HDL, the ATEs peaked at ~6 months. The adverse impact of SGAs on BMI persisted even after medication discontinuation, yet other metabolic parameters did not show such lingering side effects. Clozapine and olanzapine exhibited greater metabolic side effects compared to other SGAs.

Our real-world study suggests that metabolic side effects may stabilize with prolonged continuous treatment. Clozapine and olanzapine confer higher cardiometabolic risks than other SGAs. The side effects of SGAs on BMI may persist after drug discontinuation. These insights may guide antipsychotic choice and improve management of metabolic side effects.

The etiology of depression remains poorly understood. Changes in blood lipid levels were reported to be associated with depression and suicide, however study findings were mixed.

We performed a two-sample Mendelian randomisation (MR) analysis to investigate the causal relationship between blood lipids and depression phenotypes, based on large-scale GWAS summary statistics (N = 188 577/480 359 for lipid/depression traits respectively). Five depression-related phenotypes were included, namely major depression (MD; from PGC), depressive symptoms (DS; from SSGAC), longest duration and number of episodes of low mood, and history of deliberate self-harm (DSH)/suicide (from UK Biobank). MR was conducted with inverse-variance weighted (MR-IVW), Egger and Generalised Summary-data-based MR (GSMR) methods.

There was consistent evidence that triglyceride (TG) is causally associated with DS (MR-IVW β for one-s.d. increase in TG = 0.0346, 95% CI 0.0114–0.0578), supported by MR-IVW and GSMR and multiple r2 clumping thresholds. We also observed relatively consistent associations of TG with DSH/suicide (MR-Egger OR = 2.514, CI 1.579–4.003). There was moderate evidence for positive associations of TG with MD and the number of episodes of low mood. For HDL-c, we observed moderate evidence for causal associations with DS and MD. LDL-c and TC did not show robust causal relationships with depression phenotypes, except for weak evidence that LDL-c is inversely related to DSH/suicide. We did not detect significant associations when depression phenotypes were treated as exposures.

This study provides evidence to a causal relationship between TG, and to a lesser extent, altered cholesterol levels with depression phenotypes. Further studies on its mechanistic basis and the effects of lipid-lowering therapies are warranted.

Depression and anxiety disorders (AD) are the first and sixth leading causes of disability worldwide. Despite their high prevalence and significant disability resulted, there are limited advances in new drug development. Recently, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic basis underlying psychiatric disorders.

Here we employed gene-set analyses of GWAS summary statistics for drug repositioning. We explored five related GWAS datasets, including two on major depressive disorder (MDD2018 and MDD-CONVERGE, with the latter focusing on severe melancholic depression), one on AD, and two on depressive symptoms and neuroticism in the population. We extracted gene-sets associated with each drug from DSigDB and examined their association with each GWAS phenotype. We also performed repositioning analyses on meta-analyzed GWAS data, integrating evidence from all related phenotypes.

Importantly, we showed that the repositioning hits are generally enriched for known psychiatric medications or those considered in clinical trials. Enrichment was seen for antidepressants and anxiolytics but also for antipsychotics. We also revealed new candidates or drug classes for repositioning, some of which were supported by experimental or clinical studies. For example, the top repositioning hit using meta-analyzed p values was fendiline, which was shown to produce antidepressant-like effects in mouse models by inhibition of acid sphingomyelinase.

Taken together, our findings suggest that human genomic data such as GWAS are useful in guiding drug discoveries for depression and AD.

Cardiovascular diseases represent a major health issue in patients with schizophrenia (SCZ) and bipolar disorder (BD), but the exact nature of cardiometabolic (CM) abnormalities involved and the underlying mechanisms remain unclear. Psychiatric medications are known risk factors, but it is unclear whether there is a connection between the disorders (SCZ/BD) themselves and CM abnormalities.

Using polygenic risk scores and linkage disequilibrium score regression, we investigated the shared genetic bases of SCZ and BD with 28 CM traits. We performed Mendelian randomization (MR) to elucidate causal relationships between the two groups of disorders. The analysis was based on large-scale meta-analyses of genome-wide association studies. We also identified the potential shared genetic variants and inferred the pathways involved.

We found tentative polygenic associations of SCZ with glucose metabolism abnormalities, adverse adipokine profiles, increased waist-to-hip ratio and visceral adiposity (false discovery rate or FDR<0.05). However, there was an inverse association with body mass index. For BD, we observed several polygenic associations with favorable CM profiles at FDR<0.05. MR analysis showed that SCZ may be causally linked to raised triglyceride and that lower fasting glucose may be linked to BD. We also identified numerous single nucleotide polymorphisms and pathways shared between SCZ/BD with CM traits, some of which are related to inflammation or the immune system.

Our findings suggest that SCZ patients may be genetically predisposed to several CM abnormalities independent of medication side effects. On the other hand, CM abnormalities in BD may be more likely to be secondary. However, the findings require further validation.

Evidence indicates that the positive effects of 2-year early intervention services for psychosis are not maintained after service withdrawal. Optimal duration of early intervention in sustaining initial improved outcomes remains to be determined.

To examine the sustainability of the positive effects of an extended, 3-year, early intervention programme for patients with first-episode psychosis (FEP) after transition to standard care.

A total of 160 patients, who had received a 2-year early intervention programme for FEP, were enrolled to a 12-month randomised-controlled trial (ClinicalTrials.gov: NCT01202357) comparing a 1-year extension of the early intervention (3-year specialised treatment) with step-down care (2-year specialised treatment). Participants were followed up and reassessed 2 and 3 years after inclusion to the trial.

There were no significant differences between the treatment groups in outcomes on functioning, symptom severity and service use during the post-trial follow-up period.

The therapeutic benefits achieved by the extended, 3-year early intervention were not sustainable after termination of the specialised service.