Oral contraceptive pills (OCP) have received increased critical attention recently owing to their perceived link with mental health, especially among adolescent girls. The empirical literature, however, includes mixed findings on whether OCP use is associated with poorer mental health.

To examine the association between the use of OCP and internalising problems in adolescent girls.

This study was embedded in the iBerry study, a population-based cohort of adolescents oversampled for behavioural and emotional problems from the greater Rotterdam area, The Netherlands. In 372 girls, internalising problems were measured using the Youth Self Report, and use of OCP was determined by parental interview and self-report questionnaire across two subsequent waves (mean ages 14.9 and 17.9 years, respectively). Multiple regression analyses were performed to determine the association. Analyses were adjusted for various sociodemographic factors and adjusted for previous internalising problems assessed at a mean age of 14.9 years.

In total, 204 girls (54.8%) used OCP. OCP use was associated with fewer internalising problems in adolescent girls compared with non-use (adjusted β = −2.22, 95% CI [−4.24, −0.20]; P = 0.031).

In this research, we found that adolescent girls using OCP reported fewer internalising problems compared with non-users. This association was most prominent for girls with pre-existing internalising problems. Although healthy user bias may have a role, our observations suggest a potential therapeutic benefit for those with greater baseline challenges.

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.

Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP) is involved in the stress response and may play a key role in mood disorders, but no information is available on PACAP for the human brain in relation to mood disorders.

PACAP-peptide levels were determined in a major stress-response site, the hypothalamic paraventricular nucleus (PVN), of people with major depressive disorder (MDD), bipolar disorder (BD) and of a unique cohort of Alzheimer's disease (AD) patients with and without depression, all with matched controls. The expression of PACAP-(Adcyap1mRNA) and PACAP-receptors was determined in the MDD and BD patients by qPCR in presumed target sites of PACAP in stress-related disorders, the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC).

PACAP cell bodies and/or fibres were localised throughout the hypothalamus with differences between immunocytochemistry and in situ hybridisation. In the controls, PACAP-immunoreactivity-(ir) in the PVN was higher in women than in men. PVN-PACAP-ir was higher in male BD compared to the matched male controls. In all AD patients, the PVN-PACAP-ir was lower compared to the controls, but higher in AD depressed patients compared to those without depression. There was a significant positive correlation between the Cornell depression score and PVN-PACAP-ir in all AD patients combined. In the ACC and DLPFC, alterations in mRNA expression of PACAP and its receptors were associated with mood disorders in a differential way depending on the type of mood disorder, suicide, and psychotic features.

The results support the possibility that PACAP plays a role in mood disorder pathophysiology.

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.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, with its impact on our way of life, is affecting our experiences and mental health. Notably, individuals with mental disorders have been reported to have a higher risk of contracting SARS-CoV-2. Personality traits could represent an important determinant of preventative health behaviour and, therefore, the risk of contracting the virus.

We examined overlapping genetic underpinnings between major psychiatric disorders, personality traits and susceptibility to SARS-CoV-2 infection.

Linkage disequilibrium score regression was used to explore the genetic correlations of coronavirus disease 2019 (COVID-19) susceptibility with psychiatric disorders and personality traits based on data from the largest available respective genome-wide association studies (GWAS). In two cohorts (the PsyCourse (n = 1346) and the HeiDE (n = 3266) study), polygenic risk scores were used to analyse if a genetic association between, psychiatric disorders, personality traits and COVID-19 susceptibility exists in individual-level data.

We observed no significant genetic correlations of COVID-19 susceptibility with psychiatric disorders. For personality traits, there was a significant genetic correlation for COVID-19 susceptibility with extraversion (P = 1.47 × 10−5; genetic correlation 0.284). Yet, this was not reflected in individual-level data from the PsyCourse and HeiDE studies.

We identified no significant correlation between genetic risk factors for severe psychiatric disorders and genetic risk for COVID-19 susceptibility. Among the personality traits, extraversion showed evidence for a positive genetic association with COVID-19 susceptibility, in one but not in another setting. Overall, these findings highlight a complex contribution of genetic and non-genetic components in the interaction between COVID-19 susceptibility and personality traits or mental disorders.

MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.

We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.

The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.

Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

Schizotypy is a putative risk phenotype for psychosis liability, but the overlap of its genetic architecture with schizophrenia is poorly understood.

We tested the hypothesis that dimensions of schizotypy (assessed with the SPQ-B) are associated with a polygenic risk score (PRS) for schizophrenia in a sample of 623 psychiatrically healthy, non-clinical subjects from the FOR2107 multi-centre study and a second sample of 1133 blood donors.

We did not find correlations of schizophrenia PRS with either overall SPQ or specific dimension scores, nor with adjusted schizotypy scores derived from the SPQ (addressing inter-scale variance). Also, PRS for affective disorders (bipolar disorder and major depression) were not significantly associated with schizotypy.

This important negative finding demonstrates that despite the hypothesised continuum of schizotypy and schizophrenia, schizotypy might share less genetic risk with schizophrenia than previously assumed (and possibly less compared to psychotic-like experiences).

Adding another antipsychotic to a treatment regimen was previously used in evaluating the medication's efficacy. Supplementation of depot antipsychotics with oral antipsychotics is particularly meaningful because depot formulations are typically chosen for patients struggling with adherence to oral antipsychotics. This post-hoc analysis assessed supplementation of olanzapine long-acting injection (olanzapine-LAI) with oral olanzapine.

We used 12 months of data from an open-label, single-arm extension study of patients with schizophrenia or schizoaffective disorder (N = 931) treated with olanzapine-LAI. The prevalence, duration, time to first supplementation, and best predictors of oral supplementation were assessed.

Oral supplementation occurred in 21% of patients for a median of 31 days with mean modal dose of 10.8 mg/day. Mean time to first supplementation was shorter for patients who were at least moderately ill at baseline compared to less ill patients (47 vs. 97 days, p < 0.001). Best predictors of oral supplementation included a more severe illness profile at baseline, lower olanzapine-LAI dose prior to oral supplementation, supervised living arrangements, and being African-American.

Supplementation of olanzapine-LAI appears to be infrequent, of relatively short duration, and reserved for more severely ill patients who may require a targeted rescue medication due to signs of impending relapse.

Pathological gambling is a behavioural addiction with negative economic, social, and psychological consequences. Identification of contributing genes and pathways may improve understanding of aetiology and facilitate therapy and prevention. Here, we report the first genome-wide association study of pathological gambling. Our aims were to identify pathways involved in pathological gambling, and examine whether there is a genetic overlap between pathological gambling and alcohol dependence.

Four hundred and forty-five individuals with a diagnosis of pathological gambling according to the Diagnostic and Statistical Manual of Mental Disorders were recruited in Germany, and 986 controls were drawn from a German general population sample. A genome-wide association study of pathological gambling comprising single marker, gene-based, and pathway analyses, was performed. Polygenic risk scores were generated using data from a German genome-wide association study of alcohol dependence.

No genome-wide significant association with pathological gambling was found for single markers or genes. Pathways for Huntington's disease (P-value = 6.63 × 10−3); 5′-adenosine monophosphate-activated protein kinase signalling (P-value = 9.57 × 10−3); and apoptosis (P-value = 1.75 × 10−2) were significant. Polygenic risk score analysis of the alcohol dependence dataset yielded a one-sided nominal significant P-value in subjects with pathological gambling, irrespective of comorbid alcohol dependence status.

The present results accord with previous quantitative formal genetic studies which showed genetic overlap between non-substance- and substance-related addictions. Furthermore, pathway analysis suggests shared pathology between Huntington's disease and pathological gambling. This finding is consistent with previous imaging studies.