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.

Zuranolone is an investigational positive allosteric modulator of synaptic and extrasynaptic GABAA receptors and a neuroactive steroid in clinical development as a once-daily, oral, 14-day treatment course for adults with major depressive disorder or postpartum depression (PPD). The randomized, double-blind, placebo-controlled SKYLARK Study (NCT04442503) demonstrated that zuranolone 50 mg significantly improved depressive symptoms (as assessed by 17-item Hamilton Rating Scale for Depression total score) at Day 15 (primary endpoint; p<0.001) and was generally well tolerated in adults with PPD.

In the SKYLARK Study, patients were randomized 1:1 to receive zuranolone 50 mg or placebo for 14 days. Safety and tolerability were assessed by the incidence and severity of treatment-emergent adverse events (TEAEs), rates of dose reduction and treatment discontinuation, as well as weight gain and sexual dysfunction.

The SKYLARK Study assessed safety data from 98 patients treated with zuranolone 50 mg and 98 patients treated with placebo. TEAEs were reported in 66.3% of zuranolone-treated patients and 53.1% of placebo-treated patients. In patients that experienced TEAEs, most reported mild (zuranolone, 50.8%; placebo, 75%) or moderate (zuranolone, 44.6%; placebo, 23.1%) events. The most common (≥5%) TEAEs were somnolence (26.5%), dizziness (13.3%), sedation (11.2%), headache (9.2%), diarrhea (6.1%), nausea (5.1%), urinary tract infection (5.1%), and COVID-19 (5.1%) with zuranolone, and headache (13.3%), dizziness (10.2%), nausea (6.1%), and somnolence (5.1%) with placebo. Dose reduction due to TEAEs was 16.3% in patients receiving zuranolone vs 1.0% in patients receiving placebo; the most common TEAEs (>1 patient) leading to zuranolone dose reduction were somnolence (7.1%), dizziness (6.1%), and sedation (3.1%). Treatment discontinuation due to TEAEs was 4.1% in patients receiving zuranolone vs 2.0% in patients receiving placebo; TEAEs leading to zuranolone discontinuation in >1 patient included somnolence (2.0%). Serious TEAEs were reported in 2.0% of zuranolone-treated and 0% of placebo-treated patients; these included upper abdominal pain (1.0%, [1/98]), peripheral edema (1.0%, [1/98]), perinatal depression (1.0%, [1/98]), and hypertension (1.0%, [1/98]). Per investigators, serious TEAEs were not related to zuranolone. No signals for weight gain or sexual dysfunction were identified.

In adults with PPD, zuranolone 50 mg was generally well tolerated. Most TEAEs were mild or moderate in severity. Dose reduction due to TEAEs mainly resulted from somnolence, dizziness, and sedation, while treatment discontinuation due to TEAEs was low. No signals for weight gain or sexual dysfunction were identified.

Sage Therapeutics, Inc., and Biogen Inc.

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Society of Thoracic Surgeons Congenital Heart Surgery Database is the largest congenital heart surgery database worldwide but does not provide information beyond primary episode of care. Linkage to hospital electronic health records would capture complications and comorbidities along with long-term outcomes for patients with CHD surgeries. The current study explores linkage success between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health record data in North Carolina and Georgia.

The Society of Thoracic Surgeons Congenital Heart Surgery Database was linked to hospital electronic health records from four North Carolina congenital heart surgery using indirect identifiers like date of birth, sex, admission, and discharge dates, from 2008 to 2013. Indirect linkage was performed at the admissions level and compared to two other linkages using a “direct identifier,” medical record number: (1) linkage between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health records from a subset of patients from one North Carolina institution and (2) linkage between Society of Thoracic Surgeons data from two Georgia facilities and Georgia’s CHD repository, which also uses direct identifiers for linkage.

Indirect identifiers successfully linked 79% (3692/4685) of Society of Thoracic Surgeons Congenital Heart Surgery Database admissions across four North Carolina hospitals. Direct linkage techniques successfully matched Society of Thoracic Surgeons Congenital Heart Surgery Database to 90.2% of electronic health records from the North Carolina subsample. Linkage between Society of Thoracic Surgeons and Georgia’s CHD repository was 99.5% (7,544/7,585).

Linkage methodology was successfully demonstrated between surgical data and hospital-based electronic health records in North Carolina and Georgia, uniting granular procedural details with clinical, developmental, and economic data. Indirect identifiers linked most patients, consistent with similar linkages in adult populations. Future directions include applying these linkage techniques with other data sources and exploring long-term outcomes in linked populations.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Major depressive disorder (MDD) is a prevalent and disabling condition. Approximately 30-50% of patients do not respond to first-line medication or psychotherapy. Therefore, several studies have investigated the predictive potential of pretreatment severity rating or neuroimaging features to guide clinical approaches that can speed optimal treatment selection.

To evaluate the performance of 1) severity ratings (scores of Hamilton Depression/Anxiety Scale, illness duration, and sleep quality, etc.) and demographic characteristic and 2) brain magnetic resonance imaging (MRI) features in predicting treatment outcomes for MDD. Second, to assess performance variations among varied modalities and interventions in MRI studies.

We searched studies in PubMed, Embase, Web of Science, and Science Direct databases before March 22, 2023. We extracted a confusion matrix for prediction in each study. Separate meta-analyses were performed for clinical and MRI studies. The logarithm of diagnostic odds ratio [log(DOR)], sensitivity, and specificity were conducted using Reitsma’s random effect model. The area under curve (AUC) of summary receiver operating characteristic (SROC) curve was calculated.

Subgroup analyses were conducted in MRI studies based on modalities: resting-state functional MRI (rsfMRI), task-based fMRI (tbfMRI), and structural MRI (sMRI), and interventions: antidepressant (including selective serotonin reuptake inhibitors [SSRI]) and electroconvulsive therapy (ECT). Meta-regression was conducted 1) between clinical and MRI studies and 2) among modality or intervention subgroups in MRI studies.

We included ten studies used clinical features covering 6494 patients, yielded a log(DOR) of 1.42, AUC of 0.71, sensitivity of 0.61, and specificity of 0.74. In terms of MRI, 44 studies with 2623 patients were included, revealing an overall log(DOR) of 2.53. The AUC, sensitivity, and specificity were 0.89, 0.78, and 0.75.

Studies using MRI features had a higher sensitivity (0.89 vs. 0.61) in predicting treatment outcomes than clinical features (P < 0.001). RsfMRI had higher specificity (0.79 vs. 0.69) than tbfMRI subgroup (P = 0.01). No significant differences were found between sMRI and other modalities, nor between antidepressants (SSRIs and others) and ECT. Antidepressant studies primarily identified predictive imaging features in limbic and default mode networks, while ECT mainly focused on limbic network.

Our findings suggest a robust promise for pretreatment brain MRI features in predicting treatment outcomes in MDD, offering higher accuracy than clinical studies. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. For MRI studies, overlapping but distinct network level measures predicted outcomes for antidepressants and ECT.

None Declared

Obsessive-compulsive disorder (OCD) is a common psychiatric disorder. It is considered that dysregulation of cytokine levels is related to the pathophysiological mechanism of OCD. However, the results of previous studies on cytokine levels in OCD are inconsistent.

To perform a meta-analysis assessing cytokine levels in peripheral blood of OCD patients.

We searched in PubMed, Web of Science, and Embase from inception to March 31, 2023 for eligible studies. We conducted multivariate meta-analysis in combined proinflammatory cytokines (interleukin-6 [IL-6], IL-1β, IL-2, tumor necrosis factor-α [TNF-α], and interferon-γ [IFN-γ]) and combined anti-inflammatory cytokines (IL-10 and IL-4) respectively, and calculated the same meta-analysis in each cytokine. We also performed sensitivity analysis and publication bias tests, as well as subgroup analysis (i.e. different age groups, varied cytokine measurement methods, medication treated or naïve, and presence of psychiatric comorbidities) and meta-regression analysis (variables including patients’ sex ratio, age, age at symptom onset, illness duration, scores of Y-BOCS, family history of psychiatric disorders, and BMI).

17 original studies (13, 13, 10, 5, 4, 3, 2 studies for IL-6, TNF-α, IL-1β, IL-10, IL-2, IL-4, and IFN-γ, respectively), 573 patients (mean age, 25.2; 50.3% female) and 498 healthy controls (HC; mean age, 25.3; 51.4% female) were included. The results showed that the levels of combined pro- or anti-inflammatory cytokines and each signle cytokine were not significantly different between OCD patients and HC (all P>0.05), with significant heterogeneities in all analyses (I2 from 79.1% to 91.7%). We did not find between-group differences in cytokine levels in all subgroup analyses. Meta-regression analysis suggested that age at onset (P=0.0003) and family history (P=0.0062) might be the source of heterogeneity in TNF-α level. Sensitivity analysis confirmed that all results were stable, except for IL-4 where different cytokine measurement methods may be the contributing factor. Egger test did not find publication bias.

Our study showed no difference in cytokine levels between OCD patients and HC, but age at onset and family history may affect TNF-α level. Confounding factors such as age at onset, family history, and cytokine measurement methods should be controlled in future studies to further explore the immune mechanism of OCD.

None Declared

There’s large heterogeneity present in major depressive disorder (MDD) and controversial evidence on alterations of brain functional connectivity (FC), making it hard to elucidate the neurobiological basis of MDD. Subtyping is one promising solution to characterize this heterogeneity.

To identify neurophysiological subtypes of MDD based on FC derived from resting-state functional magnetic resonance imaging using large multisite data and investigate the differences in genetic mechanisms and neurotransmitter basis of FC alterations, and the differences of FC-related cognition between each subtype.

Consensus clustering of FC patterns was applied to a population of 829 MDD patients from REST-Meta-MDD database after data cleaning and image quality control. Gene transcriptomic data derived from Allen Human Brain Atlas and neurotransmitter receptor/transporter density data acquired by using neuromap toolbox were used to characterize the molecular mechanism underlying each FC-based subtype by identifying the gene set and neurotransmitters/transporters showing high spatial similarity with the profiles of FC alterations between each subtype and 770 healthy controls. The FC-related cognition in each subtype was also selected by lasso regression.

Two stable neurophysiological MDD subtypes were found and labeled as hypoconnectivity (n=527) and hyperconnectivity (n=299) characterized by the FC differences in each subtype relative to controls, respectively. The two subtypes did not differ in age, sex, and scores of Hamilton Depression/Anxiety Scale.

The genes related to FC alterations were enriched in ion transmembrane transport, synaptic transmission/organization, axon development, and regulation of neurotransmitter level for both subtypes, but specifically enriched in glial cell differentiation for hypoconnectivity subtype, while enriched in regulation of presynaptic membrane and regulation of neuron differentiation for hyperconnectivity subtype.

FC alterations were associated with the density of 5-HT2a receptor in both subtypes. For hyperconnectivity subtype, FC alterations were also correlated with the density of norepinephrine transporter, glutamate receptor, GABA receptor, 5-HT1b receptor, and cannabinoid receptor.

Both subtypes showed correlations between FC and categorization, motor inhibition, and localization. The FC in hypoconnectivity subtype correlated with response inhibition, selective attention, face recognition, sleep, empathy, expertise, uncertainty, and anticipation, while that was related to inference, speech perception, and reward anticipation in hyperconnectivity subtype.

Our findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypo or hyper-connectivity. The two subtypes had both shared and distinct genetic mechanisms, neurotransmitter receptor/transporter profiles, and cognition types.

None Declared

To examine the effectiveness of Self-Help Plus (SH+) as an intervention for alleviating stress levels and mental health problems among healthcare workers.

This was a prospective, two-arm, unblinded, parallel-designed randomised controlled trial. Participants were recruited at all levels of medical facilities within all municipal districts of Guangzhou. Eligible participants were adult healthcare workers experiencing psychological stress (10-item Perceived Stress Scale scores of ≥15) but without serious mental health problems or active suicidal ideation. A self-help psychological intervention developed by the World Health Organization in alleviating psychological stress and preventing the development of mental health problems. The primary outcome was psychological stress, assessed at the 3-month follow-up. Secondary outcomes were depression symptoms, anxiety symptoms, insomnia, positive affect (PA) and self-kindness assessed at the 3-month follow-up.

Between November 2021 and April 2022, 270 participants were enrolled and randomly assigned to either SH+ (n = 135) or the control group (n = 135). The SH+ group had significantly lower stress at the 3-month follow-up (b = −1.23, 95% CI = −2.36, −0.10, p = 0.033) compared to the control group. The interaction effect indicated that the intervention effect in reducing stress differed over time (b = −0.89, 95% CI = −1.50, −0.27, p = 0.005). Analysis of the secondary outcomes suggested that SH+ led to statistically significant improvements in most of the secondary outcomes, including depression, insomnia, PA and self-kindness.

This is the first known randomised controlled trial ever conducted to improve stress and mental health problems among healthcare workers experiencing psychological stress in a low-resource setting. SH+ was found to be an effective strategy for alleviating psychological stress and reducing symptoms of common mental problems. SH+ has the potential to be scaled-up as a public health strategy to reduce the burden of mental health problems in healthcare workers exposed to high levels of stress.

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.