In major depressive disorder (MDD), only ~35% achieve remission after first-line antidepressant therapy. Using UK Biobank data, we identify sociodemographic, clinical, and genetic predictors of antidepressant response through self-reported outcomes, aiming to inform personalized treatment strategies.

In UK Biobank Mental Health Questionnaire 2, participants with MDD reported whether specific antidepressants helped them. We tested whether retrospective lifetime response to four selective serotonin reuptake inhibitors (SSRIs) (N = 19,516) – citalopram (N = 8335), fluoxetine (N = 8476), paroxetine (N = 2297) and sertraline (N = 5883) – was associated with sociodemographic (e.g. age, gender) and clinical factors (e.g. episode duration). Genetic analyses evaluated the association between CYP2C19 variation and self-reported response, while polygenic score (PGS) analysis assessed whether genetic predisposition to psychiatric disorders and antidepressant response predicted self-reported SSRI outcomes.

71%–77% of participants reported positive responses to SSRIs. Non-response was significantly associated with alcohol and illicit drug use (OR = 1.59, p = 2.23 × 10−20), male gender (OR = 1.25, p = 8.29 × 10−08), and lower-income (OR = 1.35, p = 4.22 × 10−07). The worst episode lasting over 2 years (OR = 1.93, p = 3.87 × 10−16) and no mood improvement from positive events (OR = 1.35, p = 2.37 × 10−07) were also associated with non-response. CYP2C19 poor metabolizers had nominally higher non-response rates (OR = 1.31, p = 1.77 × 10−02). Higher PGS for depression (OR = 1.08, p = 3.37 × 10−05) predicted negative SSRI outcomes after multiple testing corrections.

Self-reported antidepressant response in the UK Biobank is influenced by sociodemographic, clinical, and genetic factors, mirroring clinical response measures. While positive outcomes are more frequent than remission reported in clinical trials, these self-reports replicate known treatment associations, suggesting they capture meaningful aspects of antidepressant effectiveness from the patient’s perspective.

A series of webinars covering widespread knowledge on paediatric cardiology and cardiac surgery topics was initiated by Association for European Paediatric and Congenital Cardiology, serving towards preparation for the Association for European Paediatric and Congenital Cardiology certification in paediatric and congenital cardiology. This study investigated the impact of webinars as educational tools for junior paediatric cardiologists in the post-COVID-19 pandemic era.

A cross-sectional survey design study using an online survey as a tool for the assessment of trainees. An open and closed-ended SurveyMonkey questionnaire was used to document the learners’ opinions on webinars. Results were reported using descriptive statistical analyses.

Twenty-seven Association for European Paediatric and Congenital Cardiology junior members participated in the online survey from twelve different countries. Most of the participants were trainees in paediatric cardiology (56%), and the remainder were junior consultants in paediatric cardiology. Approximately 70% found no difficulties in participating in the webinars. The webinars were appreciated by participants, who found the webinars interactive and highly educational with contents highly applicable to everyday clinical practice. Significant heterogeneity emerged in training programmes across Europe and worldwide in terms of programme duration, number of fellows, teaching approach, and assessments. Training opportunities such as courses, grants, and more webinars were suggested as tools to support continuous learning by the Association for European Paediatric and Congenital Cardiology.

The Association for European Paediatric and Congenital Cardiology webinar series has confirmed the crucial role of online-based learning resources in the new generation of junior paediatric cardiologists. Association for European Paediatric and Congenital Cardiology webinars and the examination in paediatric cardiology may help standardise training across Europe, promoting the highest standards in patient care.

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.

Clinical high-risk for psychosis (CHR-P) states exhibit diverse clinical presentations, prompting a shift towards broader outcome assessments beyond psychosis manifestation. To elucidate more uniform clinical profiles and their trajectories, we investigated CHR-P profiles in a community sample.

Participants (N = 829; baseline age: 16–40 years) comprised individuals from a Swiss community sample who were followed up over roughly 3 years. latent class analysis was applied to CHR-P symptom data at baseline and follow-up, and classes were examined for demographic and clinical differences, as well as stability over time.

Similar three-class solutions were yielded for both time points. Class 1 was mainly characterized by subtle, subjectively experienced disturbances in mental processes, including thinking, speech and perception (basic symptoms [BSs]). Class 2 was characterized by subthreshold positive psychotic symptoms (i.e., mild delusions or hallucinations) indicative of an ultra-high risk for psychosis. Class 3, the largest group (comprising over 90% of participants), exhibited the lowest probability of experiencing any psychosis-related symptoms (CHR-P symptoms). Classes 1 and 2 included more participants with functional impairment and psychiatric morbidity. Class 3 participants had a low probability of having functional deficits or mental disorders at both time points, suggesting that Class 3 was the healthiest group and that their mental health and functioning remained stable throughout the study period. While 91% of Baseline Class 3 participants remained in their class over time, most Baseline Classes 1 (74%) and Class 2 (88%) participants moved to Follow-up Class 3.

Despite some temporal fluctuations, CHR-P symptoms within community samples cluster into distinct subgroups, reflecting varying levels of symptom severity and risk profiles. This clustering highlights the largely distinct nature of BSs and attenuated positive symptoms within the community. The association of Classes 1 and 2 with Axis-I disorders and functional deficits emphasizes the clinical significance of CHR-P symptoms. These findings highlight the need for personalized preventive measures targeting specific risk profiles in community-based populations.

Anhedonia characterizes major depressive episodes in bipolar depression and is associated with more severe illness/poor prognosis. These post hoc analyses assess effect of cariprazine 1.5 and 3 mg/d on anhedonia symptoms in patients with bipolar I depression.

Data were pooled from 3 randomized, double-blind, placebo-controlled bipolar I depression trials in cariprazine. Cariprazine 1.5 and 3 mg/d versus placebo were evaluated in patient subgroups stratified by median baseline MADRS anhedonia score (higher anhedonia=score ≥19; lower anhedonia=score <19). Outcomes included mean change from baseline to week 6 in MADRS total and anhedonia factor score (sum of apparent sadness, reported sadness, concentration, lassitude, and inability to feel items). The proportion of patients with week 6 anhedonia factor response (≥50% improvement from baseline) was also determined. Changes from baseline were analyzed using a mixed-effect model for repeated measures.

There were 760 patients in the higher anhedonia subgroup (placebo=249, cariprazine: 1.5 mg/d=261; 3 mg/d=250) and 623 patients in the lower anhedonia subgroup (placebo=211, cariprazine: 1.5 mg/d=200; 3 mg/d=212). Mean baseline MADRS total score was higher in the higher anhedonia subgroup (total=33.6) than in the lower anhedonia subgroup (total=27.6). Change from baseline to week 6 in MADRS total score was greater for both cariprazine doses versus placebo in the higher anhedonia subgroup (least squares mean difference [LSMD] and 95% confidence interval [CI]: 1.5 mg/d=-3.01 [-4.84, -1.19], P=.0012; 3 mg/d: -3.26 [-5.12, -1.40], P=.0006); in the lower anhedonia subgroup, cariprazine 1.5 mg/d was statistically significant versus placebo (-2.61 [-4.28, -0.93], P=.0024). In the higher anhedonia subgroup at week 6, change from baseline in anhedonia factor score was significant versus placebo for both cariprazine doses (1.5 mg/d=-1.97 [-3.13, -0.81], P=.0009; 3 mg/d=-2.07 [-3.26, -0.89], P=.0006); in the lower subgroup, the difference was significant versus placebo for cariprazine 1.5 mg/d (-1.70 [-2.77, -0.62], P=.0021). After adjusting for changes in other depressive symptoms, LSMDs versus placebo in the anhedonia factor score remained significant for cariprazine 1.5 mg/d (-1.21 [-2.05, -0.36], P=.0052) and 3 mg/d (-1.00 [-1.86, -0.14], P=.0233) in the higher anhedonia subgroup, and for 1.5 mg/d (-1.06 [-1.92, -0.19], P=.0164) in the lower subgroup. In the higher anhedonia subgroup, rates of anhedonia factor response were greater versus placebo (31.7%) for cariprazine 1.5 mg/d (44.8%, P=.0028) and 3 mg/d (45.6%, P=.0019); in the lower subgroup, response rates were 39.3% for placebo, 48.0% for 1.5 mg/d, and 46.7% for 3 mg/d. Adverse events in ≥5% cariprazine and twice placebo were nausea, akathisia, restlessness, and EPS.

Those with bipolar depression and anhedonia cariprazine demonstrated a potent antidepressant and antianhedonic effect in higher/lower anhedonia subgroups.

AbbVie

This data was previously presented at the European College of Neuropsychopharmacology (ECNP) Congress; Barcelona, Spain; October 7 – 10, 2023.

The study objective was to develop and validate a clinical decision support system (CDSS) to guide clinicians through the diagnostic evaluation of hospitalized individuals with suspected pulmonary tuberculosis (TB) in low-prevalence settings.

The “TBorNotTB” CDSS was developed using a modified Delphi method. The CDSS assigns points based on epidemiologic risk factors, TB history, symptoms, chest imaging, and sputum/bronchoscopy results. Below a set point threshold, airborne isolation precautions are automatically discontinued; otherwise, additional evaluation, including infection control review, is recommended. The model was validated through retrospective application of the CDSS to all individuals hospitalized in the Mass General Brigham system from July 2016 to December 2022 with culture-confirmed pulmonary TB (cases) and equal numbers of age and date of testing-matched controls with three negative respiratory mycobacterial cultures.

104 individuals with TB (cases) and 104 controls were identified. Prior residence in a highly endemic country, positive interferon release assay, weight loss, absence of symptom resolution with treatment for alternative diagnoses, and findings concerning for TB on chest imaging were significant predictors of TB (all P < 0.05). CDSS contents and scoring were refined based on the case–control analysis. The final CDSS demonstrated 100% sensitivity and 27% specificity for TB with an AUC of 0.87.

The TBorNotTB CDSS demonstrated modest specificity and high sensitivity to detect TB even when AFB smears were negative. This CDSS, embedded into the electronic medical record system, could help reduce risks of nosocomial TB transmission, patient-time in airborne isolation, and person-time spent reviewing individuals with suspected TB.

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.