Nature mental health最新文献

{"title":"Partnering for progress in mental health interventions","authors":"","doi":"10.1038/s44220-026-00655-z","DOIUrl":"10.1038/s44220-026-00655-z","url":null,"abstract":"Mental health care is entering a defining era shaped not only by reflection on past challenges, but also by a growing sense of possibility. As more integrative, context-aware interventions emerge, collaboration across disciplines and sectors is opening new pathways for meaningful progress. The Wellcome Prize for Mental Health Science with aims to accelerate this shift by supporting innovative, scalable interventions with the potential for transformative impact.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"689-690"},"PeriodicalIF":8.7,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00655-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Key challenges in advancing research on depression phenotyping","authors":"Jonathan Repple, Astrid Chevance, Eiko Fried, Moritz Elsaesser, Tim Hahn, Henricus G. Ruhe, Nils Opel, Claudi L. Bockting, Roger S. McIntyre, Allan H. Young, Paolo Fusar-Poli, Elisabeth Schramm, Jessica Schleider, Christian Otte, Alix Choppin, Udo Dannlowski, Brenda W.J.H. Penninx, Andreas Reif","doi":"10.1038/s44220-026-00629-1","DOIUrl":"10.1038/s44220-026-00629-1","url":null,"abstract":"Despite decades of effort, depression research has made limited progress in improving predictive models and treatment outcomes. Biomarker studies, in particular, have yielded few clinically translatable findings. This Review argues that such limitations stem not from a lack of research activity, but from fundamental conceptual issues in defining and measuring major depression, specifically its theoretical construct, diagnostic criteria, subtyping, measurement tools and staging frameworks. We highlight three major challenges: (1) the heterogeneity of depression measurement, (2) insufficient attention to longitudinal disease trajectories and (3) underrepresentation of lived-experience perspectives. Here, to advance precision psychiatry, we propose focusing on specific symptom domains (for example, anhedonia, cognitive impairment and insomnia), modeling trajectories across multiple timescales with dynamic symptom assessments and improved staging, and integrating patient-defined outcomes into research via a core outcome set. These strategies aim to resolve conceptual limitations and support the development of more targeted, person-centered approaches to understanding and treating depression. In this Review the authors discuss the reasons behind the limited advance in depression phenotyping and provide strategic points for addressing this gap.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"898-911"},"PeriodicalIF":8.7,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming artificial intelligence into artificial wisdom","authors":"Dilip V. Jeste, Martin P. Paulus, George S. Alexopoulos, Marcel Barnard, Willem M. Otte, Yuto Satake, Peter Jongho Na, John Torous, Ante Prodan, Jo-An Occhipinti","doi":"10.1038/s44220-026-00640-6","DOIUrl":"10.1038/s44220-026-00640-6","url":null,"abstract":"A rapidly expanding behavioral epidemic of loneliness is profoundly affecting mental and physical health of individuals and communities worldwide. Empirical research shows that, unlike intelligence, human wisdom can mitigate loneliness and promote mental well-being. However, there is a severe global shortage of mental healthcare workforce required to support population-level well-being. Although artificial intelligence is advancing rapidly, it lacks core attributes of wisdom, including compassion, self-reflection, emotional regulation and acceptance of diverse perspectives. The development of artificial wisdom systems could operationalize wisdom-related functions and provide scalable tools to promote mental well-being without implying machine consciousness or subjective experience. While wisdom presents substantial conceptual challenges for computational implementation, recent large language models have demonstrated emerging capabilities in domains previously considered uniquely human. Progress toward artificial wisdom will require new computational frameworks, including mixture-of-experts architectures and agentic systems designed to model human psychosocial needs. Key challenges include ethical and safety considerations requiring rigorous evaluation, validated grounding data, longitudinal assessment and privacy protection. Close collaboration among experts in mental health, technology and ethics is crucial. A strategic shift from artificial intelligence toward artificial wisdom, at both individual and population levels, is critical for advancing global mental health and well-being. In this Perspective, the authors discuss reframing digital mental health tools by transforming artificial intelligence into artificial wisdom.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"886-897"},"PeriodicalIF":8.7,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping histamine pathway networks in the human brain across cognition and psychiatric disorders","authors":"Daniel Martins, Mattia Veronese, Daniel van Wamelen, Ling Shan, Oliver Howes, Adam Hampshire, Federico Turkheimer, Steven CR Williams","doi":"10.1038/s44220-026-00637-1","DOIUrl":"10.1038/s44220-026-00637-1","url":null,"abstract":"Histamine is a key neuromodulator shaping cognition, emotion and behavioral flexibility, yet its organization in the human brain remains incompletely characterized. We conducted a multimodal analysis integrating transcriptomic, neuroimaging, developmental and functional datasets to map the architecture of the histaminergic system. At the single-cell level, histamine receptor H1 and histamine receptor H2 were enriched in excitatory neurons, whereas histamine receptor H3 showed preferential expression in inhibitory populations. Regional expression of core histaminergic genes was captured by a single latent component (41.1% of variance), with higher expression in frontal and limbic regions and lower expression in the occipital cortex. This spatial signature predicted in vivo H3 receptor binding across independent positron emission tomography datasets. Functional decoding linked histaminergic expression to emotion regulation, salience processing, impulsivity, sleep, memory and reward. Developmentally, histidine decarboxylase expression peaked early, whereas histamine receptor H3 increased into adulthood. Finally, histaminergic expression correlated with structural alteration patterns in attention deficit hyperactivity disorder, major depressive disorder, schizophrenia and anorexia nervosa, suggesting relevance for regional vulnerability in psychiatric disorders. In this study, Martins and colleagues provide an integrated characterization of the human brain histaminergic system, using transcriptomic and neuroimaging datasets to describe the molecular organization of this system and its relevance to mental health.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"816-828"},"PeriodicalIF":8.7,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00637-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cannabis and tobacco co-use predicts psychosis in clinical high risk cohorts","authors":"Daniel Bello, Sophia H. Blyth, Rachel A. Rabin, Jean Addington, Carrie E. Bearden, Kristin Cadenhead, Tyrone D. Cannon, Ricardo E. Carrión, Barbara Cornblatt, Matcheri Keshavan, Daniel H. Mathalon, Diana O. Perkins, Larry Seidman, William S. Stone, Ming T. Tsuang, Elaine F. Walker, Scott Woods, Roscoe O. Brady Jr, Heather Burrell Ward","doi":"10.1038/s44220-026-00648-y","DOIUrl":"10.1038/s44220-026-00648-y","url":null,"abstract":"Cannabis and tobacco use are highly prevalent among people with psychosis and are associated with medical comorbidities and poor prognosis. Concurrent use of cannabis and tobacco (‘co-use’) is rising in the general population, but has not been studied in psychosis. Given the devastating consequences of cannabis and tobacco use, it is critical to understand how their co-use affects psychiatric symptoms and the development of psychosis. Here we used the North American Prodrome Longitudinal Study-2, a multisite prospective study of individuals at clinical high risk for psychosis (CHR), and healthy controls to examine baseline differences in psychiatric symptoms and conversion to psychosis across substance groups: (1) CHR tobacco use, (2) CHR cannabis use, (3) CHR co-use, (4) CHR non-tobacco or cannabis use, (5) CHR without substance use and (6) healthy controls. Among 1,012 participants (734 CHR, 278 controls), more frequent cannabis and tobacco use was linked to greater psychiatric symptom severity. In survival analyses, heavy cannabis and light tobacco co-use (HR = 2.93, 95% confidence interval (CI) [1.23–6.97], P = 0.015) was associated with higher risk of conversion than no use of either substance. Co-use of tobacco and cannabis was not associated with psychiatric symptom severity but did predict higher risk of conversion to psychosis. These results highlight the need for strategies that address co-use in CHR populations to mitigate potential long-term psychiatric consequences. In individuals at clinical high risk for psychosis, the concurrent use of cannabis and tobacco predicted an elevated risk of transitioning to psychosis. Heavy cannabis use combined with light tobacco use was linked to a threefold increase in the risk of transition.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"941-950"},"PeriodicalIF":8.7,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00648-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the human brain histamine system at the molecular, structural and functional levels","authors":"","doi":"10.1038/s44220-026-00641-5","DOIUrl":"10.1038/s44220-026-00641-5","url":null,"abstract":"This study presents a multimodal, systems-level map of the human brain histamine system, integrating transcriptomics, molecular imaging, developmental trajectories and cognitive meta-analysis. The findings link histaminergic system architecture to higher-order cognition and vulnerability to major psychiatric disorders.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"694-695"},"PeriodicalIF":8.7,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychotropic medication use, lifestyle, genetic risk for high BMI and the incidence of cardiovascular disease","authors":"Nini de Boer, Iris Hanskamp, Bochao Danae Lin, Liese Boonstra, Marte van der Horst, Kristel van Eijk, Marco P. Boks, Wouter J. Peyrot, Jos Twisk, Thomas Goldschmidt, Hanno Pijl, Christiaan H. Vinkers, Christoph U. Correll, Marc De Hert, Sinan Guloksuz, Wiepke Cahn, Jurjen J. Luykx","doi":"10.1038/s44220-026-00620-w","DOIUrl":"10.1038/s44220-026-00620-w","url":null,"abstract":"Psychotropic medication use, unhealthy lifestyle behavior and polygenic risk for high BMI (PGS-BMI) may contribute to weight gain and thereby increase cardiovascular disease (CVD) risk in people with mental illness. Using a sample of UK Biobank participants, we examined associations of psychotropic use, lifestyle and PGS-BMI with two coprimary outcomes, BMI and incident CVD, using regression, interaction and mediation models. Among 496,662 participants (mean (s.d.) age = 56.5 (8.1) yr, 54.3% female), psychotropic medication use was positively associated with BMI relative to no use (β = 0.053, R2 = 0.019). This association was more pronounced for multiple psychotropic use than psychotropic monotherapy (9.12% and 5.08% BMI increases, respectively). Unhealthy lifestyle was associated with increased CVD risk among participants with psychotropic use (HR = 1.69, 95% CI = 1.59-1.80). Among users of psychotropics we found consistently positive and linear associations of increasing PGS-BMI and increasingly unhealthy lifestyle with higher BMI and CVD incidence, with highest CVD risks detected in people with high PGS-BMI and unhealthy lifestyle (HR relative to those not using psychotropics, with low PGS-BMI and healthy lifestyle, 3.33, 95% CI = 2.36-4.70). Among participants with a psychiatric diagnosis, CVD risk was not increased in those using psychotropics relative to those not using psychotropics (HR = 0.98, 95% CI = 0.92–1.05). These results suggest that, among psychotropic medication users, those with both a high PGS-BMI and unhealthy lifestyle had the highest BMI and CVD risk, whereas those with both a low PGS-BMI and healthy lifestyle had the lowest risk. Notably, the association between psychotropic medication use and CVD risk was modified by psychiatric diagnosis: among people with a psychiatric diagnosis, psychotropic medication use was not associated with increased CVD risk. Psychotropic medication use, unhealthy lifestyle behaviors and polygenic risk for high body mass index (PGS-BMI) may elevate cardiovascular disease (CVD) risk in individuals with mental illness. In this study, the authors analyze UK Biobank data, revealing that psychotropic users with high PGS-BMI and unhealthy lifestyles face the greatest BMI and CVD risk, highlighting the need for targeted interventions.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"766-774"},"PeriodicalIF":8.7,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"‘Sticky’ beliefs about the state of the world relate to obsessions and are decreased by serotonin","authors":"","doi":"10.1038/s44220-026-00622-8","DOIUrl":"10.1038/s44220-026-00622-8","url":null,"abstract":"Difficulty updating one’s beliefs to reflect changing circumstances — ‘belief stickiness’ — might underpin some forms of inflexibility. We found that increasing serotonin decreased belief stickiness and that obsessions were associated with increased belief stickiness. These findings uncover a new role for serotonin and could have implications for the treatment of obsessions.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"692-693"},"PeriodicalIF":8.7,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconceptualizing cognitive-behavioral processes in youth anxiety in the digital age","authors":"Nora Skjerdingstad, Eleanor Leigh","doi":"10.1038/s44220-026-00633-5","DOIUrl":"10.1038/s44220-026-00633-5","url":null,"abstract":"Digital environments and social media have fundamentally transformed social interactions for young people, offering both opportunities and challenges for mental health. Individuals with social anxiety disorder, a condition characterized by an intense fear of negative evaluation in social situations, may be particularly vulnerable to the dynamics of these digital environments, which now constitute a large part of the social worlds of adolescents. This Perspective examines the intersection of computer-mediated communication and social anxiety in adolescence. We propose a framework that reconceptualizes the Clark and Wells cognitive model of social anxiety in light of the distinctive affordances of social digital environments. Specifically, we integrate the key components of the model by considering how digital contexts influence the interpretation of social cues, processing the self as a social object, the use of safety behaviors, and pre- and post-event processing. We outline directions for future research and clinical implications. This Perspective considers the impact of social anxiety disorder on adolescents within digital environments, proposing a revised framework that incorporates computer-mediated communication’s effects on social cue interpretation, self-perception, safety behaviors and event processing, highlighting future research and clinical implications.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"696-706"},"PeriodicalIF":8.7,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Depression and anxiety characterization and detection with multimodal deep learning","authors":"Tianchi Lu, Ling Cho, Zhenyu Qiu, Yiran Wang, Wenjin Niu, Yat Wah Leung, Yuchen Wang, He Zhang, Wing Chung Chang, M. Tanveer, Zhaolei Zhang, LI Xiangtao, Ka-Chun Wong","doi":"10.1038/s44220-026-00632-6","DOIUrl":"10.1038/s44220-026-00632-6","url":null,"abstract":"Depression and anxiety are among the most prevalent mental disorders, necessitating accurate characterization for effective diagnosis and treatment. Multimodal deep learning has emerged as an effective approach to enhance diagnostic precision by integrating diverse data sources, including electronic health records, physiological signals and neuroimaging. This Review provides an overview of the recent advancements in multimodal deep learning for depression and anxiety estimation. Key neural network architectures—such as convolutional neural networks for image analysis, recurrent and transformer models for sequential and textual data, and graph neural networks for capturing complex neuroimaging connectivity patterns—are examined. Challenges in data fusion, feature extraction and model interpretability are discussed, alongside strategies to improve generalizability through transfer learning. Future challenges and opportunities are discussed: large-scale datasets, standardized evaluation protocols and interdisciplinary collaboration to bridge the gap between multimodal deep learning and clinical relevance. By summarizing current practices and identifying critical challenges, this Review highlights the transformative potential of multimodal deep learning in advancing the characterization and detection of depression and anxiety. In this Review, the authors highlight the role of multimodal deep learning in diagnosing depression and anxiety, utilizing diverse data sources. Key methods include convolutional, recurrent and graph neural networks, addressing challenges in data fusion, feature extraction and model interpretability for enhanced clinical relevance.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 5","pages":"727-745"},"PeriodicalIF":8.7,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147924308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}