Genetic Confounding of the Association Between Age at First Hormonal Contraception and Depression.

Background: Previous research has shown that females who use hormonal contraception are at increased risk of developing depression, and that the risk is highest among adolescents. While this finding could reflect age-specific effects of exogenous hormones on mental health, genetic liability for mental disorders could be confounding the association. Our goal was to test the plausibility of this hypothesis by determining whether polygenic liabilities for major depressive disorder (MDD), bipolar disorder (BD), schizophrenia (SCZ), and attention deficit hyperactivity disorder (ADHD) are associated with younger age at hormonal contraception initiation.

Predicting involuntary admission following inpatient psychiatric treatment using machine learning trained on electronic health record data.

Background: Involuntary admissions to psychiatric hospitals are on the rise. If patients at elevated risk of involuntary admission could be identified, prevention may be possible. Our aim was to develop and validate a prediction model for involuntary admission of patients receiving care within a psychiatric service system using machine learning trained on routine clinical data from electronic health records (EHRs).

Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review.

Objectives: Tools based on generative artificial intelligence (AI) such as ChatGPT have the potential to transform modern society, including the field of medicine. Due to the prominent role of language in psychiatry, e.g.

Assessing Solutions for Resilient Dairy Farming in Europe.

The objective of the EU project Resilience for Dairy (R4D) is to develop and strengthen a self-sustainable Thematic Network on resilient dairy farms in 15 European countries. This article focusses on those solutions (practices and techniques) that are assessed contributing to a resilient dairy farming sector. The opinions of experts, farmers, and stakeholders were collected and scored through surveys and in a series of local workshops.

Patient trust in the use of machine learning-based clinical decision support systems in psychiatric services: A randomized survey experiment.

Background: Clinical decision support systems (CDSS) based on machine-learning (ML) models are emerging within psychiatry. If patients do not trust this technology, its implementation may disrupt the patient-clinician relationship. Therefore, the aim was to examine whether receiving basic information about ML-based CDSS increased trust in them.

Associations between physical diseases and subsequent mental disorders: a longitudinal study in a population-based cohort.

People with physical diseases are reported to be at elevated risk of subsequent mental disorders. However, previous studies have considered only a few pairs of conditions, or have reported only relative risks. This study aimed to systematically explore the associations between physical diseases and subsequent mental disorders.

Clinical and sociodemographic characteristics associated with relapse following electroconvulsive therapy for bipolar disorder.

Objectives: Electroconvulsive therapy (ECT) is an effective treatment for bipolar disorder, but relapse following a successful ECT series is common. We aimed to identify clinical and sociodemographic characteristics associated with the risk of relapse following ECT in bipolar disorder.

Methods: Using data from nationwide Danish registers, we identified all patients receiving their first ECT series with an indication diagnosis of bipolar disorder between 2006 and 2018.

Housing mice near vs. below thermoneutrality affects drug-induced weight loss but does not improve prediction of efficacy in humans.

Evaluation of weight loss drugs is usually performed in diet-induced obese mice housed at ∼22°C. This is a cold stress that increases energy expenditure by ∼35% compared to thermoneutrality (∼30°C), which may overestimate drug-induced weight loss. We investigated five anti-obesity mechanisms that have been in clinical development, comparing weight loss in mice housed at 22°C vs.

Uncovering the BIN1-SH3 interactome underpinning centronuclear myopathy.

Truncation of the protein-protein interaction SH3 domain of the membrane remodeling Bridging Integrator 1 (BIN1, Amphiphysin 2) protein leads to centronuclear myopathy. Here, we assessed the impact of a set of naturally observed, previously uncharacterized BIN1 SH3 domain variants using conventional and cell-based assays monitoring the BIN1 interaction with dynamin 2 (DNM2) and identified potentially harmful ones that can be also tentatively connected to neuromuscular disorders. However, SH3 domains are typically promiscuous and it is expected that other, so far unknown partners of BIN1 exist besides DNM2, that also participate in the development of centronuclear myopathy.

A Nationwide Target Trial Emulation Assessing the Risk of Antidepressant-Induced Mania Among Patients With Bipolar Depression.

Objective: Antidepressants are commonly used to treat bipolar depression but may increase the risk of mania. The evidence from randomized controlled trials, however, is limited by short treatment durations, providing little evidence for the long-term risk of antidepressant-induced mania. The authors performed a target trial emulation to compare the risk of mania among individuals with bipolar depression treated or not treated with antidepressants over a 1-year period.

Interaction between mental disorders and social disconnectedness on mortality: a population-based cohort study.

Background: Despite the recognised importance of mental disorders and social disconnectedness for mortality, few studies have examined their co-occurrence.

Aims: To examine the interaction between mental disorders and three distinct aspects of social disconnectedness on mortality, while taking into account sex, age and characteristics of the mental disorder.

Method: This cohort study included participants from the Danish National Health Survey in 2013 and 2017 who were followed until 2021.

Development and validation of a machine learning model for prediction of type 2 diabetes in patients with mental illness.

Background: Type 2 diabetes (T2D) is approximately twice as common among individuals with mental illness compared with the background population, but may be prevented by early intervention on lifestyle, diet, or pharmacologically. Such prevention relies on identification of those at elevated risk (prediction). The aim of this study was to develop and validate a machine learning model for prediction of T2D among patients with mental illness.

Clinical validation of the self-reported 6-item Hamilton Depression Rating Scale (HAM-D6-SR) among inpatients.

Background: Brief and valid patient-rated symptom scales represent a valuable addition to clinician-rated scales for assessing depression. Studies on the psychometric properties of the self-rated 6-item Hamilton Depression Rating Scale (HAM-D6-SR) have shown promising results for outpatients with depression. The aim of the present study was to evaluate the psychometric properties of the HAM-D6-SR among inpatients using the clinician-rated 17-item Hamilton Rating Scale for Depression (HAMD17) as the gold standard.

Is Attention-Deficit/Hyperactivity Disorder (ADHD) a Dimension or a Category? What Does the Relationship Between ADHD Traits and Psychosocial Quality of Life Tell Us?

Objective: The question of whether attention-deficit/hyperactivity disorder (ADHD) is a discrete category or a continuous dimension remains clinically relevant. We report the first examination of this question from the viewpoint of the relationship between ADHD traits and psychosocial quality of life (QoL), and whether the level of QoL declines markedly around a certain high ADHD trait range suggestive of a categorical boundary.

Methods: Parents/caregivers of 1,967 schoolchildren aged 6 to 11 from the general population completed the Pediatric Quality of Life Inventory and the ADHD-Rating Scale IV.

Structural validity of the 5-item World Health Organization Well-being Index (WHO-5) in patients with schizophrenia spectrum disorders.

Background: When monitoring the severity and impact of schizophrenia spectrum disorders, a measure of subjective well-being should ideally accompany measures of symptom severity and medication side effects. The self-reported 5-item World Health Organization Well-being Index (WHO-5) is a brief, generic, and widely used measure of subjective well-being. However, the structural validity of the WHO-5, namely, whether the individual item scores can be combined to produce a meaningful total score, has not been examined among patients with schizophrenia spectrum disorders.

Clinical and Legal Differences in the Use of Involuntary Electroconvulsive Therapy for Life-Threatening Illness Across European Countries.

Objectives: Electroconvulsive therapy (ECT) can be life-saving in situations where patients are at risk of dying from severe manifestations of psychiatric illness. In some of these cases, patients are unwilling/unable to consent to ECT, and involuntary ECT is required. Such use of involuntary ECT varies substantially across European countries for unclear reasons.

PDZome-wide and structural characterization of the PDZ-binding motif of VANGL2.

VANGL2 is a core component of the non-canonical Wnt/Planar Cell Polarity signaling pathway that uses its highly conserved carboxy-terminal type 1 PDZ-binding motif (PBM) to bind a variety of PDZ proteins. In this study, we characterize and quantitatively assess the largest VANGL2 PDZome-binding profile documented so far, using orthogonal methods. The results of our holdup approach support VANGL2 interactions with a large panel of both long-recognized and unprecedented PDZ domains.