Recent guidance from UK health authorities strongly cautions against the use of valproic acid (VPA) in persons under 55 because of reevaluated risk of teratogenicity.

To summarize the extant literature documenting VPA-associated anatomical, behavioral, and cognitive teratogenicity.

Pubmed, Medline, Cochrane Library, PsychInfo, Embase, Scopus, Web of Science, and Google Scholar were searched in accordance with PRISMA guidelines. Collected data covered study design, participant characteristics, anatomical, behavioral, or cognitive effects, and folic acid outcomes.

122 studies were identified meeting inclusion comprised of studies evaluating anatomical (n = 67), behavioral (n = 28), and cognitive (n = 47) teratogenicity. Twenty studies were identified reporting on the risk mitigation effects of folic acid supplementation. Prenatal VPA exposure is associated with anatomical teratogenicity including major congenital malformations (odds ratio [OR] 2.47–9.30; p < 0.005). Behavioral teratogenicity including autism (OR 1.70–4.38), impaired motor development (OR 7.0), and ADHD (OR 1.39) are also significantly associated with VPA exposure. VPA was associated with intellectual disability and low IQ (hazard ratio [HR] 2.4–4.48, verbal intelligence: Spearman’s ρ = −0.436, respectively). Teratogenic effects were dose-dependent across all domains and were significant when compared with controls and other antiepileptic drugs (eg, carbamazepine, lamotrigine, and levetiracetam). Folic acid supplementation does not significantly reduce the hazard associated with VPA.

VPA is significantly associated with anatomical, behavioral, and cognitive teratogenicity. Folic acid supplementation does not abrogate the risk of teratogenicity associated with VPA exposure. Available evidence supports recommendations to reduce VPA exposure in women of reproductive age.

There is a lack of large-scale studies exploring labor market marginalization (LMM) among individuals diagnosed with bipolar disorder (BD). We aimed to investigate the association of BD with subsequent LMM in Sweden, and the effect of sex on LMM in BD.

Individuals aged 19–60 years living in Sweden with a first-time BD diagnosis between 2007 and 2016 (n = 25 231) were followed from the date of diagnosis for a maximum of 14 years. Risk of disability pension (DP), long-term sickness absence (SA) (>90 days), and long-term unemployment (>180 days) was compared to a matched comparison group from the general population, matched 1:5 on sex and birth year (n = 126 155), and unaffected full siblings (n = 24 098), using sex-stratified Cox regression analysis, yielding hazard ratios (HRs) with 95% confidence intervals (CIs).

After adjusting for socioeconomic factors, baseline labor market status, and comorbid disorders, individuals with BD had a significantly higher risk of DP compared to the general population (HR = 16.67, 95% CI 15.33–18.13) and their unaffected siblings (HR = 5.54, 95% CI 4.96–6.18). Individuals with BD were also more likely to experience long-term SA compared to the general population (HR = 3.19, 95% CI 3.09–3.30) and their unaffected siblings (HR = 2.83, 95% CI 2.70–2.97). Moreover, individuals diagnosed with BD had an elevated risk of long-term unemployment relative to both comparison groups (HR range: 1.75–1.78). Men with BD had a higher relative risk of SA and unemployment than women. No difference was found in DP.

Individuals with BD face elevated risks of LMM compared to both the general population and unaffected siblings.

Observational studies consistently report associations between tobacco use, cannabis use and mental illness. However, the extent to which this association reflects an increased risk of new-onset mental illness is unclear and may be biased by unmeasured confounding.

A systematic review and meta-analysis (CRD42021243903). Electronic databases were searched until November 2022. Longitudinal studies in general population samples assessing tobacco and/or cannabis use and reporting the association (e.g. risk ratio [RR]) with incident anxiety, mood, or psychotic disorders were included. Estimates were combined using random-effects meta-analyses. Bias was explored using a modified Newcastle–Ottawa Scale, confounder matrix, E-values, and Doi plots.

Seventy-five studies were included. Tobacco use was associated with mood disorders (K = 43; RR: 1.39, 95% confidence interval [CI] 1.30–1.47), but not anxiety disorders (K = 7; RR: 1.21, 95% CI 0.87–1.68) and evidence for psychotic disorders was influenced by treatment of outliers (K = 4, RR: 3.45, 95% CI 2.63–4.53; K = 5, RR: 2.06, 95% CI 0.98–4.29). Cannabis use was associated with psychotic disorders (K = 4; RR: 3.19, 95% CI 2.07–4.90), but not mood (K = 7; RR: 1.31, 95% CI 0.92–1.86) or anxiety disorders (K = 7; RR: 1.10, 95% CI 0.99–1.22). Confounder matrices and E-values suggested potential overestimation of effects. Only 27% of studies were rated as high quality.

Both substances were associated with psychotic disorders and tobacco use was associated with mood disorders. There was no clear evidence of an association between cannabis use and mood or anxiety disorders. Limited high-quality studies underscore the need for future research using robust causal inference approaches (e.g. evidence triangulation).

Mood and anxiety disorders are heterogeneous conditions with variable course. Knowledge on latent classes and transitions between these classes over time based on longitudinal disorder status information provides insight into clustering of meaningful groups with different disease prognosis.

Data of all four waves of the Netherlands Mental Health Survey and Incidence Study-2 were used, a representative population-based study of adults (mean duration between two successive waves = 3 years; N at T0 = 6646; T1 = 5303; T2 = 4618; T3 = 4007; this results in a total number of data points: 20 574). Presence of eight mood and anxiety DSM-IV disorders was assessed with the Composite International Diagnostic Interview. Latent class analysis and latent Markov modelling were used.

The best fitting model identified four classes: a healthy class (prevalence: 94.1%), depressed-worried class (3.6%; moderate-to-high proportions of mood disorders and generalized anxiety disorder (GAD)), fear class (1.8%; moderate-to-high proportions of panic and phobia disorders) and high comorbidity class (0.6%). In longitudinal analyses over a three-year period, the minority of those in the depressed-worried and high comorbidity class persisted in their class over time (36.5% and 38.4%, respectively), whereas the majority in the fear class did (67.3%). Suggestive of recovery is switching to the healthy class, this was 39.7% in the depressed-worried class, 12.5% in the fear class and 7.0% in the high comorbidity class.

People with panic or phobia disorders have a considerably more persistent and chronic disease course than those with depressive disorders including GAD. Consequently, they could especially benefit from longer-term monitoring and disease management.

To examine if the COVID-19 pandemic was associated with a differential effect longitudinally in relation to its psychological and functional impact on patients with bipolar disorder and Emotionally Unstable Personality Disorder (EUPD).

Semi-structured interviews were conducted with 29 individuals attending the Galway-Roscommon Mental Health Services with an ICD-10 diagnosis of either bipolar disorder (n = 18) or EUPD (n = 11). The impact of the COVID-19 pandemic was assessed in relation to anxiety and mood symptoms, social and occupational functioning, and quality of life utilising psychometric instruments and Likert scale data, with qualitative data assessing participants’ subjective experiences.

Individuals with EUPD exhibited significant anxiety and depressive symptoms and increased hopelessness compared to individuals with bipolar disorder. Repeated measures data demonstrated no significant change in symptomatology for either the EUPD or bipolar disorder group over time, but demonstrated an improvement in social (t = 4.40, p < 0.001) and occupational functioning (t = 3.65, p = 0.03), and in quality of life (t = 4.03, p < 0.001) for both participant groups. Themes attained from qualitative data included the positive impact of the discontinuation of COVID-19 mandated restrictions (n = 19), and difficulties experienced secondary to reductions in the provision of mental health services during the COVID-19 pandemic (n = 17).

Individuals with EUPD demonstrated increased symptomatology over a two-year period compared to those with bipolar disorder. The importance of face-to-face mental health supports for this cohort are indicated, particularly if future pandemics impact the delivery of mental health services.

Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine.

We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort.

Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable.

Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.