Biological Psychiatry最新文献

Understanding the heterogeneity of Alzheimer's disease (AD) is crucial for advancing precision medicine specifically tailored to this disorder. Recent research has deepened our understanding of AD heterogeneity, yet translating these insights from bench to bedside via neuroimaging heterogeneity frameworks presents significant challenges. In this review, we systematically revisit prior studies and summarize the existing methodology of data-driven neuroimaging studies for AD heterogeneity. We organized the present methodology into (i) a subtyping cluster strategy for AD patients, and we also subdivided it into subtyping analysis based on cross-sectional multimodal neuroimaging profiles, and the identification of long-term disease progression from short-term datasets; (ii) a stratified strategy that integrates neuroimaging measures with biomarkers; (iii) individual-specific abnormal patterns based on the Normative model. We then evaluated the characteristics of these studies along two dimensions: (i) the understanding of pathology and (ii) clinical application. We systematically address the limitations, challenges, and future directions of research into AD heterogeneity. Our goal is to enhance the neuroimaging heterogeneity framework for AD, facilitating its transition from bench to bedside.

The rise of social media has profoundly altered the social world - introducing new behaviours which can satisfy our social needs. However, it is yet unknown whether human social strategies, which are well-adapted to the offline world we developed in, operate as effectively within this new social environment. Here, we describe how the computational framework of Reinforcement Learning can help us to precisely frame this problem and diagnose where behaviour-environment mismatches emerge. The Reinforcement Learning framework describes a process by which an agent can learn to maximise their long-term reward. Reinforcement Learning, which has proven successful in characterising human social behaviour, consists of three stages: updating expected reward, valuating expected reward by integrating subjective costs such as effort, and selecting an action. Specific social media affordances, such as the quantifiability of social feedback, might interact with the Reinforcement Learning process at each of these stages. In some cases, affordances can exploit Reinforcement Learning biases which are beneficial offline, by violating the environmental conditions under which such biases are optimal - such as when algorithmic personalisation of content interacts with confirmation bias. Characterising the impact of specific aspects of social media through this lens can improve our understanding of how digital environments shape human behaviour. Ultimately, this formal framework could help address pressing open questions about social media use, including its changing role across human development, and its impact on outcomes such as mental health.

Background: Identifying neurobiological targets predictive of the molecular neuropathophysiological signature of human opioid use disorder (OUD) could expedite new treatments. OUD is characterized by dysregulated cognition and goal-directed behavior mediated by the orbitofrontal cortex (OFC), and next-generation sequencing could provide insights regarding novel targets.

Methods: Here, we used machine learning to evaluate human post-mortem OFC RNA-sequencing datasets from heroin-users and controls to identify transcripts predictive of heroin use. To determine a causal link to OUD-related behaviors, we examined the effects of overexpressing the top target gene in a translational rat model of heroin-seeking and behavioral updating. Additionally, we determined the effects of overexpression on the rat OFC transcriptome compared to that of human heroin users. Co-immunoprecipitation/mass-spectrometry from rat OFC elucidated the protein complex of the novel target.

Results: Our machine learning approach identified SHISA7 as predictive of human heroin users. Shisa7 is understudied but appears to be an auxiliary protein of GABAA or AMPA receptors. In rats, Shisa7 expression positively-correlated with heroin-seeking behavior. Overexpressing Shisa7 in the OFC augmented heroin-seeking and impaired behavioral updating for sucrose-based operant contingency. RNA-sequencing of rat OFC revealed gene co-expression networks regulated by Shisa7-overexpression similar to human heroin-users. Finally, co-immunoprecipitation/mass-spectrometry showed that heroin influences Shisa7 binding to glutamatergic and GABAergic receptor subunits. Both gene expression signatures and Shisa7 protein complex emphasized perturbations of neurodegenerative and neuroimmune processes.

Conclusions: Our findings suggest that OFC Shisa7 is a critical driver of neurobehavioral pathology related to drug-seeking behavior and behavioral updating, identifying a potential therapeutic target for OUD.

Objective: Obsessive-compulsive disorder (OCD) is associated with altered brain function related to processing of negative emotions. To investigate neural correlates of negative valence in OCD, we pooled fMRI data of 633 individuals with OCD and 453 healthy controls from 16 studies using different negatively-valenced tasks across the ENIGMA-OCD Working-Group.

Methods: Participant data were processed uniformly using HALFpipe, to extract voxelwise participant-level statistical images of one common first-level contrast: negative vs. neutral stimuli. In pre-registered analyses, parameter estimates were entered into Bayesian multilevel models to examine whole-brain and regional effects of OCD and its clinically relevant features - symptom severity, age of onset, and medication status.

Results: We provided a proof-of-concept that participant-level data can be combined across several task paradigms and observed one common task activation pattern across individuals with OCD and controls that encompasses fronto-limbic and visual areas implicated in negative valence. Compared to controls, individuals with OCD showed very strong evidence of weaker activation of the bilateral occipital cortex (P+<0.001) and adjacent visual processing regions during negative valence processing that was related to greater OCD severity, late-onset of disease and an unmedicated status. Individuals with OCD also showed stronger activation in the orbitofrontal, subgenual anterior cingulate and ventromedial prefrontal cortex (all P+<0.1) that was related to greater OCD severity and late onset.

Conclusion: In the first mega-analysis of this kind, we replicate previous findings of stronger ventral prefrontal activation in OCD during negative valence processing and highlight the lateral occipital cortex as an important region implicated in altered negative valence processing.

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 examine 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 (SI) ratio).

Results: Social stress induces distinct behavioral adaptation patterns in defeated males and witness females. SI ratio leads to underpowered analyses in witness females with limited utility to differentiate susceptibility/resilience. Data-driven analyses reveal changes in social adaptation in witness females that are captured in attenuated velocity change from no target to target tests (ΔVelocity). We explore the utility of this metric in four female social stress models and in male witnesses. Combining SI ratio and ΔVelocity optimally differentiates susceptibility/resilience in witness females and reveals resilient-specific adaptation in a resilience-associated neural circuit in female mice.

Conclusions: We demonstrate that chronic witness stress induces behavioral changes in females that are qualitatively distinct from those observed in defeated males and not adequately sampled by standard male-defined metrics. We identify modulation of locomotion as 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.