Biological Psychiatry最新文献

Pharmacological interventions are a cornerstone of psychiatric practice. The taxonomies used to classify these interventions influence the treatment and interpretation of psychiatric symptoms. Disease-based classification systems (e.g., 'antidepressant' and 'antipsychotic') do not reflect the fact that psychotropic agents are used across diagnostic categories, nor account for the dimensional nature of both the psychopathology and biology of psychiatric illnesses. In this review we discuss the history of psychotropic drug taxonomies and their influence on both clinical practice and drug development. We frame taxonomies as existing on a spectrum, with high-level disease-based approaches at one end and target-based molecular approaches at the other. Finally, we consider how data-driven methods might address the issue of classification at an intermediate level, based around transdiagnostic neurobiological and psychopathological markers.

Background: Self-injurious behaviours (SIB) are repetitive, non-accidental movements that result in physical damage inflicted upon oneself, without suicidal intent. SIB are prevalent among children with autism spectrum disorder and can lead to permanent disability or death. Neuromodulation at a locus of neural circuitry implicated in SIB, the nucleus accumbens (NAc), may directly influence these behaviours.

Methods: We completed a phase I, open-label clinical trial of deep brain stimulation (DBS) of the NAc in children with severe, treatment-refractory SIB (ClinicalTrials.gov Identifier NCT03982888). Participants were monitored for 12 months following NAc-DBS to assess the primary outcomes of safety and feasibility. Secondary outcomes included serial assessments of SIB and SIB-associated behaviours, ambulatory actigraphy, and changes in brain glucose metabolism induced by DBS.

Results: Six children (ages 7-14 years) underwent NAc-DBS without serious adverse events. One child was found to have a delayed asymptomatic intracranial hemorrhage adjacent to a DBS electrode that did not require intervention, and three children experienced transient worsening in irritability or SIB with titration of stimulation parameters. NAc-DBS resulted in significant reductions in SIB and SIB-associated behaviours across multiple standardized scales, concurrent with clinically meaningful improvements in quality-of-life. Ambulatory actigraphy showed reductions in high-amplitude limb movements and positron emission tomography revealed treatment-induced reductions in metabolic activity within the thalamus, striatum, and temporoinsular cortex.

Conclusions: This first-in-children phase 1 clinical trial demonstrates the safety and feasibility of NAc-DBS in children with severe, refractory SIB at high risk of physical injury and death and supports further investigations.

Copy number variations (CNVs) have emerged as crucial genetic factors influencing a wide spectrum of human health outcomes, with particularly strong associations to psychiatric disorders. This review presents a synthesis of diverse impacts of psychiatric disorder-associated CNVs on neurodevelopment, brain function, and physical health across the lifespan. Large-scale studies have revealed that CNV carriers exhibit an increased risk for psychiatric disorders, cognitive deficits, sleep disturbances, neurological disorders, and other physical conditions, including cardiovascular diseases, diabetes, and renal disease, highlighting the wide-ranging impact of CNVs beyond the brain. Neuroimaging studies reveal substantial CNV effects on brain structure, from cortical and subcortical alterations to white matter microstructure, with effect sizes often exceeding those observed in idiopathic psychiatric disorders. Cellular and animal models have begun to elucidate dynamic CNV effects on neurodevelopment, neuronal function, and cellular energy metabolism, while revealing complex CNV-environment interactions and cell type-specific responses, particularly in studies of 22q11.2 deletion syndrome. This review also explores the complex interplay between psychiatric and physical health conditions in CNV carriers, and how these interactions contribute to adverse socioeconomic outcomes, including reduced educational attainment and income levels, creating a feedback loop that further impacts health outcomes. Finally, this review also highlights research limitations and proposes key priorities for clinical implementation, including the need for longitudinal studies, standardized guidelines for CNV result reporting and genetic counseling, and integrated care networks, providing a foundation for advancing the field of precision psychiatry.

Background: Glutamatergic signaling is essential for modulating synaptic plasticity and cognition. However, the dynamics of glutamatergic activity over the 24-hour sleep-wake cycle, particularly in relation to sleep, remain poorly understood. This study aims to investigate diurnal variations in brain Glx levels-representing the combined concentrations of glutamate and glutamine-in humans and to explore their implications for cognitive performance and sleep pressure.

Methods: We conducted two independent experiments to measure Glx levels across the sleep-wake cycle using proton magnetic resonance spectroscopy. In Experiment 1, 14 participants underwent 13 hours of Glx measurements during a typical sleep-wake cycle. Experiment 2 extended these measurements to an around-the-clock observation over a 6-day period. This period included two days of normal sleep-wake cycles, 24 hours of enforced wakefulness, and a three-day recovery phase. Seven participants took part in Experiment 2.

Results: The study observed that brain Glx levels increased during wakefulness and decreased during sleep. Notably, Glx levels were lower during enforced wakefulness compared to those during normal wakefulness. Reduced Glx levels were associated with diminished cognitive performance, while greater Glx exposure over the preceding 24 hours correlated with increased sleep pressure.

Conclusions: These findings suggest that Glx accumulation may contribute to increased sleep pressure, while its reduction appears to support wakefulness. These observations, together with the diurnal variations in Glx levels, underscore the dynamic nature of glutamatergic activity across the daily cycle. Further research is warranted to explore the potential role of sleep in regulating glutamatergic homeostasis.

Background: Psychiatric disorders pose an enormous economic and emotional burden on individuals, their families and society. Given that the current analysis of the pathogenesis of psychiatric disorders remains challenging and time-consuming, elucidating the modifiable risk factors becomes crucial for the diagnosis and management of psychiatric disorders. However, inferring the causal risk factors in these disorders from disparate data sources is challenging due to constraints in data collection and analytical capabilities.

Methods: By leveraging the largest available genome-wide association studies (GWAS) summary statistics for ten psychiatric disorders and compiling an extensive set of risk factor datasets, including 71 psychiatric disorders-specific phenotypes, 3,935 brain imaging traits, and over 30 brain tissue/cell-specific xQTL datasets (covering 6 types of QTLs), we performed comprehensive Mendelian randomization (MR) analyses to explore the potential causal links between various exposures and psychiatric outcomes using genetic variants as instrumental variables.

Results: After Bonferroni correction for multiple testing, we identified multiple potential risk factors for psychiatric disorders (including phenotypic level and molecular level traits), and provided robust MR evidence supporting these associations utilizing rigorous sensitivity analyses and colocalization analyses. Furthermore. we have established the PsyRiskMR database (http://bioinfo.ahu.edu.cn/PsyRiskMR/), which serves as an interactive platform for showcasing and querying risk factors for psychiatric disorders.

Conclusions: Our study offered a user-friendly PsyRiskMR database for the research community to browse, search, and download all MR results, potentially revealing new insights into the biological etiology of psychiatric disorders.

Background: Chronic social defeat stress is a widely used depression model in male mice. Several proposed adaptations extend this model to females with variable, often marginal effects. We examined if the widely used male-defined metrics of stress are suboptimal in females witnessing defeat.

Methods: Using a data-driven method, we comprehensively classified social interaction behavior in 761 male and female mice after chronic social witness/defeat stress, examining social modulation of behavior and associations with conventional metrics (i.e., social interaction ratio).

Results: Social stress induced distinct behavioral adaptation patterns in defeated males and witness females. Social interaction ratio led to underpowered analyses in witness females with limited utility to differentiate susceptibility/resilience. Data-driven analyses revealed changes in social adaptation in witness females that were captured in attenuated velocity change from no target to target trials. We explored the utility of this metric in 4 female social stress models and in male witnesses. Combining social interaction ratio and velocity change optimally differentiated susceptibility/resilience in witness females and revealed resilient-specific adaptation in a resilience-associated neural circuit in female mice.

Conclusions: Chronic witness stress induced behavioral changes in females that were qualitatively distinct from those observed in defeated males and not adequately sampled by standard male-defined metrics. Modulation of locomotion is a robust and easily implementable metric for rigorous research in witness female mice. Overall, our findings highlight the need to critically evaluate sex differences in behavior and implement sex-based considerations in preclinical model design.

Background: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed.

Methods: To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies of opioid use disorder and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex of people who died of opioid overdose and control individuals.

Results: We identified 211 highly interrelated genes identified by genome-wide association studies or dysregulation in the dorsolateral prefrontal cortex of people who died of opioid overdose that implicated the Akt, BDNF (brain-derived neurotrophic factor), and ERK (extracellular signal-regulated kinase) pathways, identifying 414 drugs targeting 48 of these opioid addiction-associated genes. Some of the identified drugs are approved to treat other substance use disorders or depression.

Conclusions: Our synthesis of multiomics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.

Background: The computational mechanisms underlying psychiatric disorders are hotly debated. One hypothesis, grounded in the Bayesian predictive coding framework, proposes that patients with schizophrenia have abnormalities in encoding prior beliefs about the environment, resulting in abnormal sensory inference, which can explain core aspects of the psychopathology, such as some of its symptoms.

Methods: Here, we tested this hypothesis by identifying oscillatory traveling waves as neural signatures of predictive coding. We analyzed an electroencephalography dataset comprising 146 patients with schizophrenia and 96 age-matched healthy control participants during resting states and a visual backward masking task.

Results: We found that patients with schizophrenia had stronger top-down alpha-band traveling waves compared with healthy control participants during resting state, supposedly reflecting overly precise priors at higher levels of the predictive processing hierarchy. We also found stronger bottom-up alpha-band waves in patients with schizophrenia during a visual task, consistent with the notion of enhanced signaling of sensory precision errors.

Conclusions: Our results yield a novel spatial-based characterization of oscillatory dynamics in schizophrenia, considering brain rhythms as traveling waves and providing a unique framework to study the different components involved in a predictive coding scheme. All together, our findings significantly advance our understanding of the mechanisms involved in fundamental pathophysiological aspects of schizophrenia, promoting a more comprehensive and hypothesis-driven approach to psychiatric disorders.

The devastating effects of the COVID-19 pandemic have underscored the significant threat that infectious diseases pose to our society. Pregnancy represents a period of heightened vulnerability to infections, which can compromise maternal health and increase the risk of neurodevelopmental disorders in offspring. Preclinical and clinical investigations suggest a potential association between maternal immune activation (MIA), which is triggered by viral or bacterial infections, and increased risk for neurodevelopmental disorders such as autism and schizophrenia. Genetic and environmental factors may contribute to the overall risk. Therefore, the two-hit hypothesis of schizophrenia suggests that MIA could act as a first trigger, with subsequent factors, such as stress or drug abuse, exacerbating latent abnormalities. A growing body of research is focused on the interaction between MIA and cannabis use during adolescence, considering the role of the endocannabinoid (eCB) system in neurodevelopment and in neurodevelopmental disorders. The eCB system, crucial for fetal brain development, may be disrupted by MIA, leading to adverse outcomes in adulthood. Recent research indicates the eCB system's significant role in the pathophysiology of neurodevelopmental disorders in preclinical models. However, findings on adolescent cannabinoid exposure in MIA-exposed animals have revealed unexpected complexities, with several studies failing to support the exacerbation of MIA-related abnormalities. In this review, we delve into the functional implications of the eCB system in MIA models, emphasizing the role of 2-AG (2-arachidonoylglycerol) signaling in synaptic plasticity and neuroinflammation and its relevance to the two-hit model of schizophrenia.