Biological Psychiatry最新文献

{"title":"Selection Biases in Precision Psychiatric Neuroimaging","authors":"Patrick G. Bissett, Russell A. Poldrack","doi":"10.1016/j.biopsych.2026.08.001","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.08.001","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":"1 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148717151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward a Definitive Neonatal MicroRNA Signature for Attention-Deficit/Hyperactivity Disorder Risk Stratification.","authors":"Fengchun Sun, Shan Tao, Chengqiang Jin","doi":"10.1016/j.biopsych.2026.03.1009","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.03.1009","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148711307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting the Links Between Asthma and the Psychosis Spectrum: shared molecular mechanisms.","authors":"Christina Dardani, Jamie W Robinson, Alexandra Havdahl, Liza Darrous, Hannah J Jones, Stan Zammit, Sarah A Sullivan, Dheeraj Rai, Evie Stergiakouli, Zhaozhong Zhu, Liming Liang, George W Nava, Renee Gardner, Jakob Grove, Tom G Richardson, George Davey Smith, James W Dodd, Gibran Hemani, Tom R Gaunt, Golam M Khandaker","doi":"10.1016/j.biopsych.2026.07.023","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.07.023","url":null,"abstract":"<p><strong>Background: </strong>Epidemiological studies suggest associations of asthma with the psychosis spectrum (psychotic experiences, bipolar disorder, schizophrenia), but the mechanisms underlying these associations remain unclear.</p><p><strong>Methods: </strong>We examined the relationship between asthma and psychosis-related outcomes using observational cohort, polygenic score, and Mendelian randomization (MR) analyses, and assessed the possibility of shared genetic underpinnings between these traits using genetic colocalisation.</p><p><strong>Results: </strong>Results from a UK population-based prospective birth cohort suggest that asthma at age 7 and polygenic risk for asthma are associated with psychotic experiences in early adulthood. Results from two-sample MR analyses do not support causal relationships of genetic liability to asthma with bipolar disorder or schizophrenia. Instead, genetic correlation and colocalization analyses point to the presence of shared genetic etiology between the conditions. We identified 8 genomic regions with potentially shared causal genes between asthma and bipolar disorder or asthma and schizophrenia. Using genetically predicted mRNA expression in condition-relevant tissues (brain and lung), we identified 16 genes shared between conditions, which include FADS1, SLC4A10, BDH2, and CISD2.</p><p><strong>Conclusions: </strong>Our results suggest that population-level associations of asthma with psychosis spectrum conditions could be due to shared molecular mechanisms involving fatty acid metabolism, ion channel activity, and iron homeostasis.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148683332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Contrastive Framework for Modeling Brain Heterogeneity in Precision Mental Health.","authors":"Xiaoyu Tong, Kanhao Zhao, Feng Vankee Lin, Yu Zhang","doi":"10.1016/j.biopsych.2026.07.022","DOIUrl":"10.1016/j.biopsych.2026.07.022","url":null,"abstract":"<p><p>Precision mental health aims to enable personalized care for mental disorders via the identification of brain-behavior associations at the individual level, yet current frameworks often face challenges in generalizability, interpretability, and clinical translation. Contrastive machine learning (CML) has emerged as a promising paradigm for characterizing individual brain variations by extracting brain dimensions that capture both disease-relevant aberrations and inter-subject heterogeneity. In this Review, we synthesize the conceptual foundations and recent methodological advances of CML. We compare CML with related frameworks and illustrate how it integrates with subtyping and predictive modeling pipelines, situating it within the broader landscape of precision mental health. We then review emerging applications that use CML to link brain structure and function to cognition, emotion, and treatment response. Finally, we outline future directions of applications and methodological innovations where CML could further advance personalized diagnosis and intervention in mental health.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13477595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148677100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining Personalization in Functional Brain Imaging: Conceptual, Methodological, and Translational Considerations.","authors":"Sarah E Chang, Signe Bray, Caterina Gratton, Deanna J Greene","doi":"10.1016/j.biopsych.2026.07.020","DOIUrl":"10.1016/j.biopsych.2026.07.020","url":null,"abstract":"","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148648164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuromodulation in Alzheimer's disease: a review with illustrative pilot data using focused ultrasound.","authors":"Marc W Haut, Camila Vieira Ligo Teixeira, Manish Ranjan, Jeffrey Carpenter, Rashi I Mehta, Patrick Worhunsky, Pierre-François D'Haese, Tasneem Arsiwala, Kiley Everson, Jacob Suffridge, Cierra Keith, Holly E Phelps, Michael Ebbert, Victor Finomore, Ali Rezai","doi":"10.1016/j.biopsych.2026.07.019","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.07.019","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is increasingly characterized as a disorder of large-scale brain networks driven by synaptic dysfunction, excitation-inhibition imbalance, and progressive breakdown of hippocampal-cortical communication. While recently developed disease-modifying therapies target molecular pathology, their clinical benefits remain modest, underscoring the need for interventions that target dysfunctional circuits. Neuromodulatory techniques such as transcranial magnetic stimulation, transcranial electrical stimulation, and deep brain stimulation demonstrate safety and act at network/system levels to engage target sites yet are limited by their ability to modulate deep anatomic structures and/or their invasiveness. Focused ultrasound (FUS) offers the distinct capability of modulating cortical and deep subcortical networks noninvasively and with anatomic precision. Preclinical studies demonstrate that FUS neuromodulation can influence mechanosensitive ion channels, synaptic plasticity, neurotrophic signaling, and oscillatory dynamics, with downstream effects on distributed memory networks. Early human investigations similarly suggest FUS neuromodulation can alter functional connectivity within default mode, frontoparietal, and limbic networks. Together, these findings support a framework in which FUS may help reshape pathological network states that emerge prior to irreversible neurodegeneration. Here, we present a narrative review of evidence across neuromodulation approaches to define principles of circuit engagement in AD and discuss a network-based rationale for ultrasound interventions. As an illustration of this framework, we also report preliminary findings from a Phase I pilot study of FUS neuromodulation in amyloid-positive mild cognitive impairment demonstrating safety, tolerability, and measurable modulation of hippocampal connectivity. We conclude mechanistic biomarkers of network response may accelerate translational development and guide future controlled trials.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148629605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Frequency EEG Connectomics Uncovers Insula-Network Subtypes in Somatic Symptom Disorder.","authors":"Shuzhi Zhao, Chongyuan Lian, Xue Shi, Ge Dang, Zi'an Pei, Xiaoyong Lan, Hanjun Liu, Hiu Ching Hung, Dezhong Yao, Lan Wang, Xin Jiang, Yi Guo, Nan Yan","doi":"10.1016/j.biopsych.2026.07.017","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.07.017","url":null,"abstract":"<p><strong>Background: </strong>Somatic symptom disorder (SSD) exhibits substantial clinical heterogeneity that limits treatment efficacy, with over 40% of patients failing to respond to standard interventions. Here, we developed a framework that integrates multi-frequency electroencephalography (EEG) connectomics with contrastive learning to identify distinct subtypes of SSD.</p><p><strong>Methods: </strong>A contrastive variational autoencoder with Gaussian mixture modeling (CVAE-GM) was developed using resting-state EEG connectomics from a discovery cohort of 1,419 patients with SSD. The derived subtypes were clinically correlated with symptom dimensions and validated for reproducibility in an independent external cohort (n=530).</p><p><strong>Results: </strong>We identified three robust subtypes, characterized by dominant connectivity in somatomotor, central executive, and limbic networks. Cross-validated canonical correlation analysis revealed distinct associations between subtype-related neural features and Neuro-11 clinical dimensions: the SMN-dominant subtype was associated with greater somatic symptom burden (cross-validated r_cv = 0.42, fold-wise SD = 0.021, permutation p < 0.001), the CEN-dominant subtype with lower negative event reactivity (r_cv = -0.38, SD = 0.017, p < 0.001), and the LN-dominant subtype with greater emotional symptoms (r_cv = 0.36, SD = 0.014, p = 0.002). Notably, the insula emerged as a convergent hub across subtypes, whereas subtype differentiation was characterized by preferential insula coupling with the anterior cingulate cortex, dorsolateral prefrontal cortex, and thalamus, respectively. Independent validation in an external cohort confirmed subtype reproducibility with superior classification performance (accuracy=0.85, AUC=0.87).</p><p><strong>Conclusions: </strong>These findings support an EEG-based connectomic framework for investigating neurobiological heterogeneity in SSD and highlight insula-centered network features as promising candidates for future mechanistic stratification studies.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148618361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cortical Hub Vulnerability and Molecular Signatures of Sulcal Widening in Schizophrenia.","authors":"Javier González-Peñas, Hugo G Schnack, Carmen Rueda Hernández, Covadonga M Díaz-Caneja, Celia de la Fuente Montero, Marta Martín Echave, Alberto Mora, Niels Janssen, Pedro M Gordaliza, Alberto Fernández-Pena, Daniel Martín de Blas, Susana Carmona, Wiepke Cahn, Neeltje E M van Haren, René S Kahn, Hilleke Hulshoff Pol, Celso Arango, Yasser Alemán-Gómez, Joost Janssen","doi":"10.1016/j.biopsych.2026.07.016","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.07.016","url":null,"abstract":"<p><strong>Background: </strong>Schizophrenia is increasingly conceptualized as a disorder of large-scale brain network organization arising from atypical neurodevelopment. However, the relationship between early-emerging cortical folding patterns and the maturation of the structural connectome remains poorly understood.</p><p><strong>Methods: </strong>We introduced a sulcal morphology-centered framework that integrated normative modeling of sulcal width with diffusion-derived structural connectivity and cortical transcriptomics in a large multisite cohort (n=5,392; 377 schizophrenia). Deviations from normative folding patterns were mapped to the structural connectome and the Allen Human Brain Atlas.</p><p><strong>Results: </strong>Individuals with schizophrenia exhibited widespread sulcal widening (30/40 sulci), primarily in frontal, temporal, and occipital regions. Nodal vulnerability followed a clear topological principle: sulci with higher degree centrality (sulcal network hubs) showed disproportionately greater widening (p_spin=0.02). Transcriptomic integration identified a gene expression profile explaining 56.5% of the spatial variance in sulcal abnormalities (p ​=0.049). This profile was significantly enriched for synaptic signaling and energy metabolism genes, showed adult-onset expression bias, and was associated with common cross-disorder genetic risk. Conversely, genes with the opposite spatial weight showed significant prenatal expression bias and enrichment for rare disruptive variants associated with autism spectrum disorder.</p><p><strong>Conclusions: </strong>These findings demonstrate that aberrant cortical folding in schizophrenia is constrained by network topology and molecular architecture. By linking macroscopic folding to metabolic and synaptic pathways, this work establishes sulcal morphology as a mechanistically grounded biomarker that may help differentiate the neurodevelopmental trajectories of psychiatric disorders.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148618340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mood and Psychosis Risk-Associated Genes Regulate Neuronal Circadian Rhythms Across the Transcriptome.","authors":"Xiangning Xue, Zoe Adelsheim, Michael T Gorczyca, Heather Wei, Michael J Leone, Ryan W Logan, Michael J McCarthy","doi":"10.1016/j.biopsych.2026.07.015","DOIUrl":"https://doi.org/10.1016/j.biopsych.2026.07.015","url":null,"abstract":"<p><strong>Background: </strong>Mood and psychotic disorders are associated with disrupted circadian rhythms in sleep and activity. While mood and psychosis risk-associated genes (MPRGs) have been linked with sleep and circadian phenotypes, their contributions to molecular clock pathways and cellular circadian rhythms remain unknown.</p><p><strong>Methods: </strong>To understand how MPRGs affect temporal dynamics and contribute to circadian rhythms in transcription across the genome, we knocked down expression of ARNTL, ANK3, CACNA1C, or TCF4 in human iPSC-derived neuronal precursor cells (NPCs) from healthy donors. Gene expression was examined serially over 24 h using whole-transcriptome RNA sequencing. Rhythm and pathway analyses were performed to identify rhythmic genes, and gene sets impacted by MPRG knockdown using small interfering RNA (siRNA).</p><p><strong>Results: </strong>Each siRNA distinctly altered phase and/or amplitude of rhythmic genes. Knockdown of ARNTL resulted in widespread loss of rhythms in core clock and other genes but also caused unexpected gains in rhythm. CACNA1C knockdown increased the number of rhythmic genes. ANK3 and TCF4 knockdown had modest effects on gain/loss of rhythm, but caused significant phase shifts. Functional analyses revealed widespread changes in rhythmic genes previously implicated in mood and psychotic disorders, including synaptic transmission, cellular stress response, and gated ion channels.</p><p><strong>Conclusions: </strong>Our findings are the first to indicate MPRGs contribute widely to neuronal circadian rhythms across the transcriptome. Altered rhythms may disrupt biological pathways implicated across a range of psychiatric disorders.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148598604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dorsolateral prefrontal cortex circuitry at the intersection of cognition and disease.","authors":"Dibyadeep Datta, Amy Arnsten, Stacey J Sukoff Rizzo, Afonso C Silva, Mary Kate Joyce, Shreejoy J Tripathy, Angela Roberts, David A Lewis","doi":"10.1016/j.biopsych.2026.07.012","DOIUrl":"10.1016/j.biopsych.2026.07.012","url":null,"abstract":"<p><p>Schizophrenia, major depressive disorder (MDD), and Alzheimer's disease (AD) involve dysfunction of distributed cortical-subcortical networks that support complex cognitive processes and emotion regulation. Convergent evidence identifies the dorsolateral prefrontal cortex (dlPFC) as a critical site of molecular, cellular, and circuitry alterations in these disorders. The primate dlPFC contains recurrent, excitatory microcircuits in layer III that sustain working memory and top-down control through specialized forms of neurotransmission and intracellular signaling. Specifically, NMDA receptor and cholinergic modulation, as well as tightly regulated calcium-cAMP signaling within dendritic spines, support task-specific firing of layer III pyramidal neurons, but may also increase vulnerability to genetic risk, stress, inflammation and aging. This review integrates findings from human postmortem studies, neuroimaging, and genetics to examine how dlPFC circuitry is altered in these disease states. In schizophrenia, layer III pyramidal neurons exhibit altered synaptic and cytoskeletal signaling, lower dendritic spine density, and compensatory shifts in inhibitory inputs that likely weaken recurrent excitation and network synchrony. In MDD, dysfunction of dlPFC pathways regulating subgenual cingulate cortex contributes to impaired top-down control of emotion and motivation. In AD and frontotemporal lobar degeneration, tau pathology and neurodegeneration target association cortices, including layer III dlPFC circuits, contributing to progressive cognitive decline and impaired executive function. The review also highlights how studies in rhesus macaques and genetically engineered marmosets have provided important insight into the organization, physiology, and disease vulnerability of primate dlPFC circuits. Together, these findings inform the development of emerging therapeutic strategies aimed at strengthening prefrontal network function.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":10.3,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148598537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}