Nature mental health最新文献

{"title":"Self-perceived gender conformity relates to depressive symptoms across Europe","authors":"Hanna Wierenga, Birgit Derntl, Pia Schober","doi":"10.1038/s44220-026-00670-0","DOIUrl":"10.1038/s44220-026-00670-0","url":null,"abstract":"Gender is a known social determinant of mental health, yet research often reduces it to binary sex/gender. Here we explored how conformity to gender norms relates to depressive symptoms across varying societal contexts. Using 2023 European Social Survey data from 194 regions across 24 countries, we combined interviewer-coded sex/gender (female or male), self-identified gender (woman, man or other) and gradational femininity and masculinity scales to create a continuous and categorical gender conformity measure, covering lower to higher self-perceived gender conformity and non-conforming individuals. Multilevel models showed that depressive symptoms were highest among non-conforming individuals. Within the same sex/gender category, less conforming individuals generally reported higher depressive symptoms compared with more conforming individuals. Crucially, these disparities were more pronounced in regions with more traditional gender regimes that had lower levels of gender equality. These findings underscore the mental health burden of gender non-conformity, especially in restrictive cultural contexts. In this study, the authors report the secondary data analysis of cross-country data examining the impact of gender on depression across 24 European countries.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"1035-1044"},"PeriodicalIF":8.7,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00670-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215301","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":"Adolescent multi-omics and Mendelian randomization reveal transdiagnostic molecular mechanisms in psychiatric disorders","authors":"Luheng Qian, Runye Shi, Xinyang Yu, Di Chen, Tobias Banaschewski, Arun L. W. Bokde, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Sarah Hohmann, Nathalie Holz, Michael N. Smolka, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Gunter Schumann, Xiaolei Lin, Sylvane Desrivières, IMAGEN Consortium","doi":"10.1038/s44220-026-00660-2","DOIUrl":"10.1038/s44220-026-00660-2","url":null,"abstract":"The biological mechanisms underlying major neuropsychiatric disorders remain largely elusive. Given the frequent association of immune dysregulation with these conditions, we used blood-derived multi-omics data from 1,274 healthy adolescents in the IMAGEN cohort to identify transdiagnostic biomarkers and mechanisms that could inform diagnosis and treatment. We first conducted genome-wide analyses to identify single nucleotide polymorphisms associated with DNA methylation and gene expression, with findings replicated in external datasets. These quantitative trait loci were further explored through Mendelian randomization analyses across 6 neuropsychiatric disorders (attention deficit hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia and insomnia), leading to the identification of 73 putatively causal CpG sites and 62 genes that were either unique to individual disorders or, as in the case of MRPL2, shared among the disorders. Notably, the identified genes were significantly enriched in pathways linked to both psychiatric and autoimmune diseases, suggesting a shared genomic architecture between autoimmune and neuropsychiatric disorders. Two-step Mendelian randomization and colocalization analyses revealed potential transdiagnostic regulatory pathways, in which the expression of three genes (MAD1L1, MRPL2 and HLA-DRB1) mediated the effects of CpG methylation on schizophrenia and insomnia. Specifically, DNA methylation at cg06770790 repressed MRPL2, which was putatively causal for insomnia (β = −0.38, P = 1.29 × 10−4) and schizophrenia (β = −0.38, P = 1 × 10−4). Conversely, increased expression of MAD1L1 and HLA-DRB1, driven by methylation at several CpG sites, was potentially causal for schizophrenia. Our findings highlight key molecular mechanisms and genes implicated in neuropsychiatric disorders, offering promising new targets for therapeutic intervention. This research utilized multi-omics data from 1,274 adolescents to identify transdiagnostic biomarkers for neuropsychiatric disorders, employing genome-wide analyses and Mendelian randomization to uncover causal pathways linking immune dysregulation to psychiatric conditions and revealing potential therapeutic targets.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 8","pages":"1248-1261"},"PeriodicalIF":9.3,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13441900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686825","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":"Advocating Indigenous mental health","authors":"Natalia Gass","doi":"10.1038/s44220-026-00651-3","DOIUrl":"10.1038/s44220-026-00651-3","url":null,"abstract":"","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 7","pages":"1053-1055"},"PeriodicalIF":9.3,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148409636","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":"Moving beyond accuracy to overcome translational barriers in depression relapse prediction","authors":"Nils R. Winter, Marius Gruber, Tim Hahn, Jonathan Repple","doi":"10.1038/s44220-026-00661-1","DOIUrl":"10.1038/s44220-026-00661-1","url":null,"abstract":"This Comment argues for better consideration of additional factors, such as external validation, real-world feasibility, and clinical utility, to improve the translation of predictive models for relapse prediction in depression.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 7","pages":"1047-1049"},"PeriodicalIF":9.3,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148409635","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":"Modeling how autistic and non-autistic groups learn about their own and each other’s preferences","authors":"Shannon Cahalan, Raphael Perla, Sophia Block, Mikaila Loughlin, Christoph W. Korn, Gabriela Rosenblau","doi":"10.1038/s44220-026-00650-4","DOIUrl":"10.1038/s44220-026-00650-4","url":null,"abstract":"Recent theories propose that altered social understanding in autism stems from mismatches in social representations and inferential processes between non-autistic and autistic groups. Here, using a cross-sectional design, we examined whether these groups apply different types of social knowledge and learning strategies when inferring preferences of individuals from their own versus another diagnostic group. When comparing food and activity self-preferences in large samples, autistic adolescents’ preferences showed greater group-level variability compared with non-autistic adults and adolescents. A sample of non-autistic adults (18–30 years) and autistic adolescents (12–17 years) learned about non-autistic and autistic adolescents. A computational modeling framework assessed how prior knowledge was integrated during learning. Aggregated group preference structures constituted the prior knowledge base. Both groups relied on a similar learning strategy—that is, integrating feedback via reinforcement learning scaled by fine-grained, in-group social knowledge—but showed reduced accuracy when learning about autistic individuals. As autistic adolescents’ preferences are more variable, aggregate knowledge about this group was less predictive. Within the autistic group, greater autistic traits, including rigidity, were associated with lower learning rates and accuracy, highlighting how our social learning models capture autistic trait-related variability. This research investigated differences in social learning in autism, finding that non-autistic young adults and autistic adolescents were more accurate at inferring preferences of non-autistic adolescents than those of autistic adolescents.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"978-993"},"PeriodicalIF":8.7,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215266","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":"The association between autistic traits and trajectories of anxiety in middle-aged and older adults: an 8-year growth mixture model analysis","authors":"Aphrodite Eshetu, Saloni Ghai, Anne Corbett, Clive Ballard, Adam Hampshire, Elizabeth O’Nions, William Mandy, Joshua Stott, Amber John, Gavin R. Stewart","doi":"10.1038/s44220-026-00654-0","DOIUrl":"10.1038/s44220-026-00654-0","url":null,"abstract":"Anxiety is a highly prevalent mental health condition, and it is particularly common in autistic populations. However, little is known about its course beyond midlife in autistic populations owing to limited longitudinal research. Here we analyzed data from 5,270 adults aged 50–91 years (median 62 years; 75% female) in the PROTECT study. Participants completed measures of autistic traits (the Autistic Spectrum Traits Questionnaire) and current anxiety symptoms (the Generalized Anxiety Disorder-7 questionnaire). In total, 66 participants (~1.3%; 72.3% female) had high autistic traits (AST group), while 3,874 (~73.5%; 77.8% female) reported none (comparison adults). Growth mixture modeling identified anxiety symptom trajectories over an 8-year annual follow-up period. Associations between AST group and trajectory membership were examined using multinomial logistic regression. Growth mixture modeling revealed three class trajectories: two representing persistently minimal anxiety symptoms (class 1, ‘lower range minimal’, 85.6% of sample; class 2, ‘upper-range minimal’, 12.4% of sample) and one showing rising anxiety from ‘mild to clinical’ levels (class 3, 2% of sample). Regressions showed that AST participants were more likely than comparison adults to follow the mild-to-clinical trajectory (relative risk 4.41, 95% confidence interval 1.70–11.44). Elevated autistic traits are associated with an increased risk of worsening anxiety with age, highlighting the need for tailored support. Eshetu and collaborators investigated anxiety comorbidity in later life among adults with elevated autistic traits, examining how anxiety symptoms unfold with aging in a large UK community sample.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"971-977"},"PeriodicalIF":8.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00654-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215265","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":"Multiscale heterogeneity of atypical functional connectivity in autism","authors":"Iva Ilioska, Marianne Oldehinkel, Alberto Llera, Maroš Rovný, Ting Mei, Seyed Mostafa Kia, Dorothea L. Floris, Julian Tillmann, Rosemary J. Holt, Eva Loth, Tony Charman, Declan G. M. Murphy, Christine Ecker, Tobias Banaschewski, Maarten Mennes, Christian F. Beckmann, Andre Marquand, Jan K. Buitelaar, Alex Fornito","doi":"10.1038/s44220-026-00656-y","DOIUrl":"10.1038/s44220-026-00656-y","url":null,"abstract":"Group-mean comparisons often identify atypical functional connectivity in autism, but it remains unclear whether these findings consistently manifest at the individual level. Here we use normative modeling to quantify the interindividual heterogeneity of atypical functional connectivity across multiple brain scales using multicenter resting-state functional magnetic resonance imaging data from 1,824 participants (796 autistic individuals and 1,028 neurotypical controls) in a cross-sectional study across 32 sites. We find that no single functional connectivity estimate showed extreme deviation from normative expectations in more than 4% of people in either group. However, these deviations converged on common regions and networks in autistic people, who showed up to double the level of overlap compared with controls. Specifically, autistic participants demonstrated convergent hypoconnectivity in sensorimotor and attention regions and convergent hyperconnectivity between frontoparietal and default mode networks. Functional connectivity deviation patterns significantly predicted social and cognitive abilities. These findings demonstrate that autism exhibits scale-dependent heterogeneity, characterized by normative variability at the connection level but significant convergence at regional and network scales. These convergent regions and networks may be used to identify targets for individualized therapeutic development. Using normative modeling to measure the interindividual variability of atypical brain functional connectivity in autism, the authors identify heterogeneity at the level of specific connections alongside high convergence at regional and network scales. These findings offer a neurobiological framework for understanding both individual differences and shared clinical features in autism.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"1010-1020"},"PeriodicalIF":8.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00656-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215299","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":"A systematic review and meta-analysis of pharmacological and nonpharmacological interventions for autism spectrum disorder","authors":"Yunhao Gu, Mia Fox, Di Zhao","doi":"10.1038/s44220-026-00652-2","DOIUrl":"10.1038/s44220-026-00652-2","url":null,"abstract":"Autism spectrum disorder (ASD) is characterized by persistent deficits in social communication and restricted, repetitive behaviors, yet the comparative effectiveness of pharmacological and nonpharmacological interventions remains unclear. Here we conducted a systematic review and meta-analysis of randomized controlled trials to evaluate interventions targeting core ASD symptoms. PubMed, Embase, PsycINFO and Cochrane databases were searched through April 2025. Eligible studies included randomized trials with active or inactive controls assessing social communication, restricted or repetitive behaviors, or overall symptom severity. Data from 149 trials (N = 9,011), including 69 nonpharmacological studies (n = 2,889) and 217 pharmacological or dietary-supplement studies (n = 6,122), were pooled using random-effects models. The primary outcome was standardized improvement in core symptoms (Hedges’ g). Nonpharmacological interventions showed a significantly larger pooled effect size (g = 0.70; s.e. = 0.071; I2 = 75.6%) compared with pharmacological approaches (g = 0.20; s.e. = 0.025; I2 = 44.1%), with a significant between-group difference (Δ = 0.43; s.e. = 0.058; P < 0.0001). Moderator analyses indicated that smaller sample size, shorter duration, non-Western settings, clinician-rated outcomes and earlier publication were associated with larger effect sizes; meta-regression identified sample size and publication year as significant predictors. These findings suggest that behavioral and psychosocial interventions demonstrate greater efficacy for core ASD symptoms, while study design and contextual factors substantially influence reported outcomes, highlighting the need for rigorous, well-controlled clinical trials. This systematic review and meta-analysis of 149 randomized controlled trials finds that behavioral and psychosocial interventions outperform medications in improving core autism symptoms, while study design and context strongly influence reported treatment effects.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 7","pages":"1154-1163"},"PeriodicalIF":9.3,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148409627","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":"Intersecting trajectories of childhood ADHD, socioeconomic deprivation and distinct multimorbidity patterns in women","authors":"Naomi Wilson, Kirstie O’Hare, Helen Minnis, Michael Fleming, Ian Kelleher, Ruchika Gajwani","doi":"10.1038/s44220-026-00653-1","DOIUrl":"10.1038/s44220-026-00653-1","url":null,"abstract":"The long-term consequences of attention deficit hyperactivity disorder (ADHD) in females remain underrecognized both in research and clinical practice. Multimorbidity (two or more long-term conditions) is increasingly viewed as a key outcome yet its prevalence, complexity and sociodemographic determinants are understudied in this group. Here, in this longitudinal cohort study, we examined the combined influence of childhood socioeconomic deprivation and ADHD diagnosis on multimorbidity risk in women in early adulthood (that is, aged 18–32 years) and used latent class analysis to explore clustering patterns. Three findings emerged: females with childhood ADHD had a significantly higher risk of adult multimorbidity; childhood ADHD and socioeconomic deprivation increased this risk both in isolation and synergistically, with 39% of the multimorbidity burden attributable to their interaction; and distinct multimorbidity clusters emerged, with the most adverse marked by psychiatric complexity. These results highlight girls with ADHD from disadvantaged backgrounds as a high-risk group requiring earlier, integrated care. Women diagnosed with attention deficit hyperactivity disorder (ADHD) in childhood have a significantly higher risk of developing physical and mental health conditions (multimorbidity) in early adulthood. ADHD and socioeconomic deprivation independently increase this risk, and in combination have a synergistic effect.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 8","pages":"1239-1247"},"PeriodicalIF":9.3,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13441990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686766","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":"The Precision Mental Health Commission: transforming mental health through brain circuit science","authors":"Leanne M. Williams, Lara C. Foland-Ross, Max Wintermark","doi":"10.1038/s44220-026-00649-x","DOIUrl":"10.1038/s44220-026-00649-x","url":null,"abstract":"This Comment announces the Precision Mental Health Commission and its initiative to redefine mental disorders through brain circuit function analysis, promoting stratified, circuit-informed care that enhances treatment accuracy and efficiency. The approach mirrors advances in cardiovascular and cancer research, moving beyond trial and error toward personalized care.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"4 6","pages":"883-885"},"PeriodicalIF":8.7,"publicationDate":"2026-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44220-026-00649-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148215291","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}