Psychedelic use and bipolar disorder - An investigation of recreational use and its impact on mental health.

Psychedelic substances such as psilocybin have recently gained attention for their potential therapeutic benefits in treating depression and other mental health problems. However, individuals with bipolar disorder (BD) have been excluded from most clinical trials due to concerns about manic switches or psychosis. This study aimed to systematically examine the effects of recreational psychedelic use in individuals with BD.

White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals.

Although specific risk factors for brain alterations in bipolar disorders (BD) are currently unknown, obesity impacts the brain and is highly prevalent in BD. Gray matter correlates of obesity in BD have been well documented, but we know much less about brain white matter abnormalities in people who have both obesity and BD. We obtained body mass index (BMI) and diffusion tensor imaging derived fractional anisotropy (FA) from 22 white matter tracts in 899 individuals with BD, and 1287 control individuals from 20 cohorts in the ENIGMA-BD working group.

Exploring accelerated aging as a target of bipolar disorder treatment: A systematic review.

Bipolar disorder (BD) has been linked to accelerated aging processes, with many studies suggesting that drugs used to treat BD may modulate pathways related to aging. This systematic review aimed to determine whether FDA-approved pharmacotherapies for BD have reported effects on aging biomarkers across clinical and preclinical studies. We conducted searches in PubMed and PsychINFO and followed PRISMA guidelines.

Home-based transcranial direct current stimulation treatment for major depressive disorder: a fully remote phase 2 randomized sham-controlled trial.

Transcranial direct current stimulation (tDCS) has been proposed as a new treatment in major depressive disorder (MDD). This is a fully remote, multisite, double-blind, placebo-controlled, randomized superiority trial of 10-week home-based tDCS in MDD. Participants were 18 years or older, with MDD in current depressive episode of at least moderate severity as measured using the Hamilton Depression Rating Scale (mean = 19.

The effect of intranasal (R,S)-ketamine on symptoms of fatigue in severe major depressive disorder or bipolar depression with and without comorbid alcohol use disorder: Results from a randomized, double-blind, placebo-controlled trial.

Background: Fatigue is a multidimensional condition that may overlap with depression. Initial studies found that fatigue responds in only a limited way to standard monoaminergic antidepressants and mood stabilizers but does respond positively to intravenous (IV) racemic (R,S)-ketamine (ketamine). However, IV ketamine's use is limited by cost and access barriers.

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model.

Physical comorbidities of older age bipolar disorder (OABD) patients: A global replication analysis of prevalence and sex differences.

Objectives: To compare the prevalence of physical morbidities between older aged patients with bipolar disorder (OABD) and non-psychiatric comparisons (NC), and to analyze sex differences in prevalence.

Methods: OABD was defined as bipolar disorder among adults aged ≥50 years. Outcomes analyzed were the prevalence of diseases affecting the cardiovascular, respiratory, gastrointestinal, genitourinary, renal, musculoskeletal, and endocrine systems.

Use of a virtual environment to promote self-management and lifestyle changes in persons with bipolar disorder.

Purpose: Self-management and lifestyle interventions are a key factor in treatment outcomes for persons with bipolar disorder (BD). A virtual environment (VE), due to it's ability to provide flexibility of involvement in its platform, may be an alternative to face-to-face treatment to provide support for self-management. The purpose of this study is to explore how a VE, developed for chronic illness self-management, may be modified to promote self-management and lifestyle changes in those with BD.

Bipolar symptoms, somatic burden and functioning in older-age bipolar disorder: A replication study from the global aging & geriatric experiments in bipolar disorder database (GAGE-BD) project.

Objectives: The Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD) project pools archival datasets on older age bipolar disorder (OABD). An initial Wave 1 (W1; n = 1369) analysis found both manic and depressive symptoms reduced among older patients. To replicate this finding, we gathered an independent Wave 2 (W2; n = 1232, mean ± standard deviation age 47.

Opportunities and challenges for the use of deep brain stimulation in the treatment of refractory major depression.

Major Depressive Disorder continues to remain one of the most prevalent psychiatric diseases globally. Despite multiple trials of conventional therapies, a subset of patients fail to have adequate benefit to treatment. Deep brain stimulation (DBS) is a promising treatment in this difficult to treat population and has shown strong antidepressant effects across multiple cohorts.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates.

Pharmacotherapies Targeting GABA-Glutamate Neurotransmission for Treatment-Resistant Depression.

Treatment-resistant depression (TRD) is a term used to describe a particular type of major depressive disorder (MDD). There is no consensus about what defines TRD, with various studies describing between 1 and 4 failures of antidepressant therapies, with or without electroconvulsive therapy (ECT). That is why TRD is such a growing concern among clinicians and researchers, and it explains the necessity for investigating novel therapeutic targets beyond conventional monoamine pathways.

Explainable drug side effect prediction via biologically informed graph neural network.

Early detection of potential side effects (SE) is a critical and challenging task for drug discovery and patient care. In-vitro or in-vivo approach to detect potential SEs is not scalable for many drug candidates during the preclinical stage. Recent advances in explainable machine learning may facilitate detecting potential SEs of new drugs before market release and elucidating the critical mechanism of biological actions.