Pub Date : 2026-02-06DOI: 10.1038/s41588-026-02511-3
Childhood brain tumors release antigens and cytokines into the cerebrospinal fluid that reprogram skull marrow toward the differentiation of myeloid cells and expansion of regulatory T cells; disrupting this tumor–marrow circuit collapses tolerance and induces tumor regression in vivo.
{"title":"Targeting skull bone marrow hematopoiesis for the treatment of childhood brain tumors","authors":"","doi":"10.1038/s41588-026-02511-3","DOIUrl":"10.1038/s41588-026-02511-3","url":null,"abstract":"Childhood brain tumors release antigens and cytokines into the cerebrospinal fluid that reprogram skull marrow toward the differentiation of myeloid cells and expansion of regulatory T cells; disrupting this tumor–marrow circuit collapses tolerance and induces tumor regression in vivo.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"249-250"},"PeriodicalIF":29.0,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-06DOI: 10.1038/s41588-025-02488-5
The three-dimensional (3D) organization of chromosomes is emerging as an important determinant of multiple cellular processes. We now show that 3D chromatin structures, maintained by the Polycomb complex, record epigenetic perturbation events.
{"title":"How chromosome folding records events of a cell’s past","authors":"","doi":"10.1038/s41588-025-02488-5","DOIUrl":"10.1038/s41588-025-02488-5","url":null,"abstract":"The three-dimensional (3D) organization of chromosomes is emerging as an important determinant of multiple cellular processes. We now show that 3D chromatin structures, maintained by the Polycomb complex, record epigenetic perturbation events.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"251-252"},"PeriodicalIF":29.0,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-05DOI: 10.1038/s41588-025-02481-y
Marco Medici
Current diagnostic work-up and management of thyroid nodules and cancer leads to unnecessary investigations and suboptimal treatment. This study provides insights into the genetic basis of thyroid cancer, including the potential application of polygenic risk scores across multiple stages of thyroid cancer screening, diagnosis and management.
{"title":"Polygenic risk scores in thyroid cancer screening, diagnosis and management","authors":"Marco Medici","doi":"10.1038/s41588-025-02481-y","DOIUrl":"10.1038/s41588-025-02481-y","url":null,"abstract":"Current diagnostic work-up and management of thyroid nodules and cancer leads to unnecessary investigations and suboptimal treatment. This study provides insights into the genetic basis of thyroid cancer, including the potential application of polygenic risk scores across multiple stages of thyroid cancer screening, diagnosis and management.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"241-242"},"PeriodicalIF":29.0,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146125213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-05DOI: 10.1038/s41588-025-02483-w
Samantha L. White, Maizy S. Brasher, Jack Pattee, Wei Zhou, Sinéad Chapman, Yon Ho Jee, Caitlin C. Bell, Taylor L. Jamil, Martin Barrio, Christopher H. Arehart, Luke M. Evans, Jibril Hirbo, Nancy J. Cox, Peter Straub, Shinichi Namba, Emily Bertucci-Richter, Lindsay Guare, Ahmed Edris, Sam Morris, Ashley J. Mulford, Haoyu Zhang, Brian Fennessy, Martin D. Tobin, Jing Chen, Alexander T. Williams, Catherine John, David A. van Heel, Rohini Mathur, Sarah Finer, Marta R. Moksnes, Ben M. Brumpton, Bjørn Olav Åsvold, Raitis Peculis, Vita Rovite, Ilze Konrade, Ying Wang, Kristy Crooks, Sameer Chavan, Matthew J. Fisher, Nicholas Rafaels, Meng Lin, Jonathan A. Shortt, Alan R. Sanders, David C. Whiteman, Stuart MacGregor, Sarah E. Medland, Unnur Thorsteinsdóttir, Kári Stefánsson, Tugce Karaderi, Kathleen M. Egan, Therese Bocklage, Hilary C. McCrary, Gregory Riedlinger, Bodour Salhia, Craig Shriver, Minh D. Phan, Janice L. Farlow, Stephen Edge, Varinder Kaur, Michelle L. Churchman, Robert J. Rounbehler, Pamela L. Brock, Matthew D. Ringel, Milton Pividori, Rebecca Schweppe, Christopher D. Raeburn, Robin G. Walters, Zhengming Chen, Liming Li, Koichi Matsuda, Yukinori Okada, Sebastian Zöllner, Anurag Verma, Penn Medicine BioBank, Michael H. Preuss, Eimear Kenny, Audrey E. Hendricks, Lauren Fishbein, Peter Kraft, Mark J. Daly, Benjamin M. Neale, Virtual Thyroid Biopsy Consortium, Colorado Center for Personalized Medicine, Genes & Health Research Team, The BioBank Japan Project, Alicia R. Martin, Joanne B. Cole, Bryan R. Haugen, Global Biobank Meta-analysis Initiative, Christopher R. Gignoux, Nikita Pozdeyev
Thyroid diseases are common and highly heritable. We performed a meta-analysis of genome-wide association studies from 19 biobanks for five thyroid diseases: thyroid cancer (ThC), benign nodular goiter, Graves’ disease, lymphocytic thyroiditis and primary hypothyroidism. We analyzed genetic association data from ~2.9 million genomes and identified 313 known and 570 new independent loci linked to thyroid diseases. We discovered genetic correlations between ThC, benign nodular goiter and autoimmune thyroid diseases (rg = 0.16–0.97). Telomere maintenance genes contributed to benign and malignant thyroid nodular disease risk, whereas cell cycle, DNA repair and damage response genes were associated with ThC. We propose a paradigm that explains genetic predisposition to benign and malignant thyroid nodules. We found polygenic risk score associations with ThC risk of structural disease recurrence, tumor size, multifocality, lymph node metastases and extranodal extension. Polygenic risk scores identified individuals with aggressive ThC in a biobank, creating an opportunity for genetically informed population screening. Genome-wide association analyses using data from 19 biobanks identify variants influencing risk of thyroid diseases and yield polygenic risk scores associated with features of aggressive thyroid cancer.
{"title":"Global multi-ancestry genome-wide analyses identify genes and biological pathways associated with thyroid cancer and benign thyroid diseases","authors":"Samantha L. White, Maizy S. Brasher, Jack Pattee, Wei Zhou, Sinéad Chapman, Yon Ho Jee, Caitlin C. Bell, Taylor L. Jamil, Martin Barrio, Christopher H. Arehart, Luke M. Evans, Jibril Hirbo, Nancy J. Cox, Peter Straub, Shinichi Namba, Emily Bertucci-Richter, Lindsay Guare, Ahmed Edris, Sam Morris, Ashley J. Mulford, Haoyu Zhang, Brian Fennessy, Martin D. Tobin, Jing Chen, Alexander T. Williams, Catherine John, David A. van Heel, Rohini Mathur, Sarah Finer, Marta R. Moksnes, Ben M. Brumpton, Bjørn Olav Åsvold, Raitis Peculis, Vita Rovite, Ilze Konrade, Ying Wang, Kristy Crooks, Sameer Chavan, Matthew J. Fisher, Nicholas Rafaels, Meng Lin, Jonathan A. Shortt, Alan R. Sanders, David C. Whiteman, Stuart MacGregor, Sarah E. Medland, Unnur Thorsteinsdóttir, Kári Stefánsson, Tugce Karaderi, Kathleen M. Egan, Therese Bocklage, Hilary C. McCrary, Gregory Riedlinger, Bodour Salhia, Craig Shriver, Minh D. Phan, Janice L. Farlow, Stephen Edge, Varinder Kaur, Michelle L. Churchman, Robert J. Rounbehler, Pamela L. Brock, Matthew D. Ringel, Milton Pividori, Rebecca Schweppe, Christopher D. Raeburn, Robin G. Walters, Zhengming Chen, Liming Li, Koichi Matsuda, Yukinori Okada, Sebastian Zöllner, Anurag Verma, Penn Medicine BioBank, Michael H. Preuss, Eimear Kenny, Audrey E. Hendricks, Lauren Fishbein, Peter Kraft, Mark J. Daly, Benjamin M. Neale, Virtual Thyroid Biopsy Consortium, Colorado Center for Personalized Medicine, Genes & Health Research Team, The BioBank Japan Project, Alicia R. Martin, Joanne B. Cole, Bryan R. Haugen, Global Biobank Meta-analysis Initiative, Christopher R. Gignoux, Nikita Pozdeyev","doi":"10.1038/s41588-025-02483-w","DOIUrl":"10.1038/s41588-025-02483-w","url":null,"abstract":"Thyroid diseases are common and highly heritable. We performed a meta-analysis of genome-wide association studies from 19 biobanks for five thyroid diseases: thyroid cancer (ThC), benign nodular goiter, Graves’ disease, lymphocytic thyroiditis and primary hypothyroidism. We analyzed genetic association data from ~2.9 million genomes and identified 313 known and 570 new independent loci linked to thyroid diseases. We discovered genetic correlations between ThC, benign nodular goiter and autoimmune thyroid diseases (rg = 0.16–0.97). Telomere maintenance genes contributed to benign and malignant thyroid nodular disease risk, whereas cell cycle, DNA repair and damage response genes were associated with ThC. We propose a paradigm that explains genetic predisposition to benign and malignant thyroid nodules. We found polygenic risk score associations with ThC risk of structural disease recurrence, tumor size, multifocality, lymph node metastases and extranodal extension. Polygenic risk scores identified individuals with aggressive ThC in a biobank, creating an opportunity for genetically informed population screening. Genome-wide association analyses using data from 19 biobanks identify variants influencing risk of thyroid diseases and yield polygenic risk scores associated with features of aggressive thyroid cancer.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"307-316"},"PeriodicalIF":29.0,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02483-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146125201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1038/s41588-025-02489-4
Flora Paldi, Michael-Florian Szalay, Solène Dufau, Marco Di Stefano, Hadrien Reboul, Daniel Jost, Frédéric Bantignies, Giacomo Cavalli
Epigenetic memory enables the propagation of gene expression patterns following transient stimuli. Although three-dimensional chromatin organization is emerging as a key regulator of genome function, it is unknown whether it contributes to cellular memory. Here we establish that acute perturbation of the epigenome can induce cellular memory of gene expression in mouse embryonic stem cells. We uncover how a pulse of histone deacetylase inhibition translates to changes in transcription, histone modifications and genome folding. While most epigenomic and transcriptional changes are initially reversed once the perturbation is removed, some loci remain transcriptionally deregulated and genome architecture partially maintains its perturbed conformation. Consequently, a second pulse of transient hyperacetylation induces stronger memory of transcriptional deregulation. Using ultradeep Micro-C, we associate memory of gene expression with repressive Polycomb-mediated chromatin topology. These results demonstrate how cells can record transient stresses in their genome architecture, thereby enabling an enhanced response to subsequent perturbations. Acute perturbation of histone acetylation induces changes in chromatin organization that are only partially reversed once the perturbation is removed and are associated with transcriptional memory effects.
{"title":"Transient histone deacetylase inhibition induces cellular memory of gene expression and 3D genome folding","authors":"Flora Paldi, Michael-Florian Szalay, Solène Dufau, Marco Di Stefano, Hadrien Reboul, Daniel Jost, Frédéric Bantignies, Giacomo Cavalli","doi":"10.1038/s41588-025-02489-4","DOIUrl":"10.1038/s41588-025-02489-4","url":null,"abstract":"Epigenetic memory enables the propagation of gene expression patterns following transient stimuli. Although three-dimensional chromatin organization is emerging as a key regulator of genome function, it is unknown whether it contributes to cellular memory. Here we establish that acute perturbation of the epigenome can induce cellular memory of gene expression in mouse embryonic stem cells. We uncover how a pulse of histone deacetylase inhibition translates to changes in transcription, histone modifications and genome folding. While most epigenomic and transcriptional changes are initially reversed once the perturbation is removed, some loci remain transcriptionally deregulated and genome architecture partially maintains its perturbed conformation. Consequently, a second pulse of transient hyperacetylation induces stronger memory of transcriptional deregulation. Using ultradeep Micro-C, we associate memory of gene expression with repressive Polycomb-mediated chromatin topology. These results demonstrate how cells can record transient stresses in their genome architecture, thereby enabling an enhanced response to subsequent perturbations. Acute perturbation of histone acetylation induces changes in chromatin organization that are only partially reversed once the perturbation is removed and are associated with transcriptional memory effects.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"404-417"},"PeriodicalIF":29.0,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02489-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-04DOI: 10.1038/s41588-025-02491-w
Saranya Arirangan, Leticia F. de Oliveira, Md Nazmul Hasan, Autumn B. Sherman, Mitchell Tuinstra, Luiz F. Brito, Robbee Wedow, Matthew Tegtmeyer
Genomic prediction has become central to human, animal and plant biology, enabling quantitative inference of how genetic variation shapes complex traits. Although these domains share statistical foundations, such as linear mixed models, Bayesian regression and deep-learning frameworks, they have advanced largely in parallel. Here we synthesize their methodological evolution and highlight opportunities for integration and deeper collaborations. Agricultural genetics contributed to the mixed-model and Bayesian frameworks underlying modern polygenic scores, while human genomics has driven advances in nonlinear modeling, federated learning and biology-informed artificial intelligence. We propose a roadmap centered on interoperable data standards, shared benchmarks and cross-disciplinary training to unify predictive genomics across species. Together, these efforts establish genomic prediction as a comparative science capable of explaining how genetic information drives form and function across the diversity of life. We emphasize that shared biological architectures and knowledge transfer across species can directly improve the robustness, interpretability and generalizability of predictive models. This Review compares predictive genomics across humans, animals and plants, and outlines shared statistical foundations and key differences in phenotype structure, as well as opportunities for biologically grounded, generalizable artificial intelligence models.
{"title":"Sharing approaches in predictive genomics across animals, plants and humans","authors":"Saranya Arirangan, Leticia F. de Oliveira, Md Nazmul Hasan, Autumn B. Sherman, Mitchell Tuinstra, Luiz F. Brito, Robbee Wedow, Matthew Tegtmeyer","doi":"10.1038/s41588-025-02491-w","DOIUrl":"10.1038/s41588-025-02491-w","url":null,"abstract":"Genomic prediction has become central to human, animal and plant biology, enabling quantitative inference of how genetic variation shapes complex traits. Although these domains share statistical foundations, such as linear mixed models, Bayesian regression and deep-learning frameworks, they have advanced largely in parallel. Here we synthesize their methodological evolution and highlight opportunities for integration and deeper collaborations. Agricultural genetics contributed to the mixed-model and Bayesian frameworks underlying modern polygenic scores, while human genomics has driven advances in nonlinear modeling, federated learning and biology-informed artificial intelligence. We propose a roadmap centered on interoperable data standards, shared benchmarks and cross-disciplinary training to unify predictive genomics across species. Together, these efforts establish genomic prediction as a comparative science capable of explaining how genetic information drives form and function across the diversity of life. We emphasize that shared biological architectures and knowledge transfer across species can directly improve the robustness, interpretability and generalizability of predictive models. This Review compares predictive genomics across humans, animals and plants, and outlines shared statistical foundations and key differences in phenotype structure, as well as opportunities for biologically grounded, generalizable artificial intelligence models.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 3","pages":"503-516"},"PeriodicalIF":29.0,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1038/s41588-025-02486-7
Yuxin Zou, Peter Carbonetto, Dongyue Xie, Gao Wang, Matthew Stephens
We introduce mvSuSiE, a multitrait fine-mapping method, to identify putative causal variants from genetic association data (individual-level or summary). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal single nucleotide polymorphisms (SNPs). Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multitrait methods, and uniformly improves over single-trait fine-mapping (Sum of Single Effects) performed separately for each trait. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing traits and modeling heterogeneous effect-sharing patterns, we identified a substantially larger number of causal SNPs (>3,000) than single-trait fine-mapping and achieved narrower credible sets. mvSuSiE also more comprehensively characterized how genetic variants affect blood cell traits; 68% of causal SNPs showed significant effects across more than one blood cell type. A multitrait fine-mapping method, mvSuSiE, improves power and resolution over single-trait methods for identifying putative causal variants from genetic association data.
我们引入了mvSuSiE，一种多性状精细定位方法，从遗传关联数据（个体水平或汇总水平）中识别假定的因果变异。mvSuSiE从数据中学习共享遗传效应的模式，并利用这些模式来提高识别因果单核苷酸多态性（snp）的能力。仿真数据的比较表明，mvSuSiE在速度、功率和精度方面与现有的多性状方法具有竞争力，并且比单个性状单独进行的单性状精细映射（Sum of Single Effects）有统一的提高。我们利用英国生物银行（UK Biobank）的数据，应用mvSuSiE共同绘制了16种血细胞特征的精细图谱。通过共同分析性状和建模异质效应共享模式，我们确定了比单性状精细映射多得多的因果snp（约3000个），并获得了更窄的可信集。mvSuSiE还更全面地描述了基因变异如何影响血细胞特征；68%的因果snp在一种以上的血细胞类型中显示出显著影响。
{"title":"Fast and flexible joint fine-mapping of multiple traits via the Sum of Single Effects model","authors":"Yuxin Zou, Peter Carbonetto, Dongyue Xie, Gao Wang, Matthew Stephens","doi":"10.1038/s41588-025-02486-7","DOIUrl":"10.1038/s41588-025-02486-7","url":null,"abstract":"We introduce mvSuSiE, a multitrait fine-mapping method, to identify putative causal variants from genetic association data (individual-level or summary). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal single nucleotide polymorphisms (SNPs). Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multitrait methods, and uniformly improves over single-trait fine-mapping (Sum of Single Effects) performed separately for each trait. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing traits and modeling heterogeneous effect-sharing patterns, we identified a substantially larger number of causal SNPs (>3,000) than single-trait fine-mapping and achieved narrower credible sets. mvSuSiE also more comprehensively characterized how genetic variants affect blood cell traits; 68% of causal SNPs showed significant effects across more than one blood cell type. A multitrait fine-mapping method, mvSuSiE, improves power and resolution over single-trait methods for identifying putative causal variants from genetic association data.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"454-462"},"PeriodicalIF":29.0,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02486-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1038/s41588-025-02485-8
Nora I. Strom, Brad Verhulst, Silviu-Alin Bacanu, Rosa Cheesman, Kirstin L. Purves, Hüseyin Gedik, Brittany L. Mitchell, Alex S. Kwong, Annika B. Faucon, Kritika Singh, Sarah Medland, Lucia Colodro-Conde, Kristi Krebs, Per Hoffmann, Stefan Herms, Jan Gehlen, Stephan Ripke, Swapnil Awasthi, Teemu Palviainen, Elisa M. Tasanko, Roseann E. Peterson, Daniel E. Adkins, Andrey A. Shabalin, Mark J. Adams, Matthew H. Iveson, Archie Campbell, Laurent F. Thomas, Bendik S. Winsvold, Ole Kristian Drange, Sigrid Børte, Abigail R. ter Kuile, Joonas Naamanka, Tan-Hoang Nguyen, Sandra M. Meier, Elizabeth C. Corfield, Laurie Hannigan, Daniel F. Levey, Darina Czamara, Heike Weber, Karmel W. Choi, Giorgio Pistis, Baptiste Couvy-Duchesne, Sandra Van der Auwera, Alexander Teumer, Robert Karlsson, Miguel Garcia-Argibay, Donghyung Lee, Rujia Wang, Ottar Bjerkeset, Eystein Stordal, Julia Bäckman, Giovanni A. Salum, Clement C. Zai, James L. Kennedy, Gwyneth Zai, Arun K. Tiwari, Stefanie Heilmann-Heimbach, Börge Schmidt, Jaakko Kaprio, Martin M. Kennedy, Joseph Boden, Alexandra Havdahl, Christel M. Middeldorp, Fabiana L. Lopes, Nirmala Akula, Francis J. McMahon, Elisabeth B. Binder, Lydia Fehm, Andreas Ströhle, Enrique Castelao, Henning Tiemeier, Dan J. Stein, David Whiteman, Catherine Olsen, Zachary Fuller, Xin Wang, Naomi R. Wray, Enda M. Byrne, Glyn Lewis, Nicholas J. Timpson, Lea K. Davis, Ian B. Hickie, Nathan A. Gillespie, Lili Milani, Johannes Schumacher, David P. Woldbye, Andreas J. Forstner, Markus M. Nöthen, Iiris Hovatta, John Horwood, William E. Copeland, Hermine H. Maes, Andrew M. McIntosh, Ole A. Andreassen, John-Anker Zwart, Ole Mors, Anders D. Børglum, Preben B. Mortensen, Helga Ask, Ted Reichborn-Kjennerud, Jackob M. Najman, Murray B. Stein, Joel Gelernter, Yuri Milaneschi, Brenda W. Penninx, Dorret I. Boomsma, Eduard Maron, Angelika Erhardt-Lehmann, Christian Rück, Tilo T. Kircher, Christiane A. Melzig, Georg W. Alpers, Volker Arolt, Katharina Domschke, Jordan W. Smoller, Martin Preisig, Nicholas G. Martin, Michelle K. Lupton, Annemarie I. Luik, Andreas Reif, Hans J. Grabe, Henrik Larsson, Patrik K. Magnusson, Albertine J. Oldehinkel, Catharina A. Hartman, Gerome Breen, Anna R. Docherty, Hilary Coon, Rupert Conrad, Kelli Lehto, Veterans Affairs Million Veteran Program, FinnGen, 23andMe Research Team, Jürgen Deckert, Thalia C. Eley, Manuel Mattheisen, John M. Hettema
The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder and phobias) are highly prevalent, often onset early and cause substantial global disability. Although distinct in their clinical presentations, they probably represent differential expressions of a dysregulated threat–response system. Here, we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 out of the 58 associations replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism implicated in ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies. Genome-wide association meta-analysis identifies 58 independent risk loci for major anxiety disorders among individuals of European ancestry and implicates GABAergic signaling as a potential mechanism underlying genetic risk for these disorders.
{"title":"Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling","authors":"Nora I. Strom, Brad Verhulst, Silviu-Alin Bacanu, Rosa Cheesman, Kirstin L. Purves, Hüseyin Gedik, Brittany L. Mitchell, Alex S. Kwong, Annika B. Faucon, Kritika Singh, Sarah Medland, Lucia Colodro-Conde, Kristi Krebs, Per Hoffmann, Stefan Herms, Jan Gehlen, Stephan Ripke, Swapnil Awasthi, Teemu Palviainen, Elisa M. Tasanko, Roseann E. Peterson, Daniel E. Adkins, Andrey A. Shabalin, Mark J. Adams, Matthew H. Iveson, Archie Campbell, Laurent F. Thomas, Bendik S. Winsvold, Ole Kristian Drange, Sigrid Børte, Abigail R. ter Kuile, Joonas Naamanka, Tan-Hoang Nguyen, Sandra M. Meier, Elizabeth C. Corfield, Laurie Hannigan, Daniel F. Levey, Darina Czamara, Heike Weber, Karmel W. Choi, Giorgio Pistis, Baptiste Couvy-Duchesne, Sandra Van der Auwera, Alexander Teumer, Robert Karlsson, Miguel Garcia-Argibay, Donghyung Lee, Rujia Wang, Ottar Bjerkeset, Eystein Stordal, Julia Bäckman, Giovanni A. Salum, Clement C. Zai, James L. Kennedy, Gwyneth Zai, Arun K. Tiwari, Stefanie Heilmann-Heimbach, Börge Schmidt, Jaakko Kaprio, Martin M. Kennedy, Joseph Boden, Alexandra Havdahl, Christel M. Middeldorp, Fabiana L. Lopes, Nirmala Akula, Francis J. McMahon, Elisabeth B. Binder, Lydia Fehm, Andreas Ströhle, Enrique Castelao, Henning Tiemeier, Dan J. Stein, David Whiteman, Catherine Olsen, Zachary Fuller, Xin Wang, Naomi R. Wray, Enda M. Byrne, Glyn Lewis, Nicholas J. Timpson, Lea K. Davis, Ian B. Hickie, Nathan A. Gillespie, Lili Milani, Johannes Schumacher, David P. Woldbye, Andreas J. Forstner, Markus M. Nöthen, Iiris Hovatta, John Horwood, William E. Copeland, Hermine H. Maes, Andrew M. McIntosh, Ole A. Andreassen, John-Anker Zwart, Ole Mors, Anders D. Børglum, Preben B. Mortensen, Helga Ask, Ted Reichborn-Kjennerud, Jackob M. Najman, Murray B. Stein, Joel Gelernter, Yuri Milaneschi, Brenda W. Penninx, Dorret I. Boomsma, Eduard Maron, Angelika Erhardt-Lehmann, Christian Rück, Tilo T. Kircher, Christiane A. Melzig, Georg W. Alpers, Volker Arolt, Katharina Domschke, Jordan W. Smoller, Martin Preisig, Nicholas G. Martin, Michelle K. Lupton, Annemarie I. Luik, Andreas Reif, Hans J. Grabe, Henrik Larsson, Patrik K. Magnusson, Albertine J. Oldehinkel, Catharina A. Hartman, Gerome Breen, Anna R. Docherty, Hilary Coon, Rupert Conrad, Kelli Lehto, Veterans Affairs Million Veteran Program, FinnGen, 23andMe Research Team, Jürgen Deckert, Thalia C. Eley, Manuel Mattheisen, John M. Hettema","doi":"10.1038/s41588-025-02485-8","DOIUrl":"10.1038/s41588-025-02485-8","url":null,"abstract":"The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder and phobias) are highly prevalent, often onset early and cause substantial global disability. Although distinct in their clinical presentations, they probably represent differential expressions of a dysregulated threat–response system. Here, we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 out of the 58 associations replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism implicated in ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies. Genome-wide association meta-analysis identifies 58 independent risk loci for major anxiety disorders among individuals of European ancestry and implicates GABAergic signaling as a potential mechanism underlying genetic risk for these disorders.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"275-288"},"PeriodicalIF":29.0,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02485-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1038/s41588-025-02499-2
Elizabeth Cooper, David A. Posner, Colin Y. C. Lee, Linda Hu, Sigourney Bonner, Jessica T. Taylor, Oscar Baldwin, Rocio Jimenez-Guerrero, Katherine E. Masih, Katherine Wickham Rahrmann, Jason Eigenbrood, Gina Ngo, Valar Nila Roamio Franklin, Clive S. D’Santos, Richard Mair, Thomas Santarius, Claudia Craven, Ibrahim Jalloh, Julia Moreno Vicente, Timotheus Y. F. Halim, Li Wang, Arnold R. Kreigstien, Brandon Wainwright, Fredrik J. Swartling, Javed Khan, Menna R. Clatworthy, Richard J. Gilbertson
Recent research has challenged a long-held view of the brain as an immune-privileged organ, revealing active immunosurveillance with therapeutic relevance. Using a new genetically engineered mouse model of ZFTA–RELA ependymoma, a childhood brain tumor, we characterized an immune circuit between the tumor and antigen-presenting hematopoietic stem and progenitor cells (HSPCs) in the skull bone marrow. The presentation of antigens by HSPCs to CD4+ T cells biased HSPC lineages toward myelopoiesis and polarized CD4+ T cells to regulatory T cells, culminating in tumor immunotolerance. Remarkably, normalizing hematopoiesis with a single infusion of antibodies directed against cytokines enriched in the cerebrospinal fluid of mice bearing ZFTA–RELA ependymomas, choroid plexus carcinomas or group 3 medulloblastoma—all aggressive childhood brain tumors—disrupted this process and caused profound tumor regression. These findings demonstrate the existence of a skull bone marrow–tumor immunological interface and suggest that modulating the local supply of myeloid cells could represent a less toxic therapeutic strategy for aggressive childhood brain tumors. Antigen presentation in skull bone marrow by hematopoietic stem and progenitor cells induces myelopoiesis and generates CD4+ regulatory T cells in a mouse model of ependymoma, promoting immune tolerance. Treatment with anti-GM-CSF antibody has antitumor effects that are augmented by immunotherapy.
{"title":"Childhood brain tumors instruct cranial hematopoiesis and immunotolerance","authors":"Elizabeth Cooper, David A. Posner, Colin Y. C. Lee, Linda Hu, Sigourney Bonner, Jessica T. Taylor, Oscar Baldwin, Rocio Jimenez-Guerrero, Katherine E. Masih, Katherine Wickham Rahrmann, Jason Eigenbrood, Gina Ngo, Valar Nila Roamio Franklin, Clive S. D’Santos, Richard Mair, Thomas Santarius, Claudia Craven, Ibrahim Jalloh, Julia Moreno Vicente, Timotheus Y. F. Halim, Li Wang, Arnold R. Kreigstien, Brandon Wainwright, Fredrik J. Swartling, Javed Khan, Menna R. Clatworthy, Richard J. Gilbertson","doi":"10.1038/s41588-025-02499-2","DOIUrl":"10.1038/s41588-025-02499-2","url":null,"abstract":"Recent research has challenged a long-held view of the brain as an immune-privileged organ, revealing active immunosurveillance with therapeutic relevance. Using a new genetically engineered mouse model of ZFTA–RELA ependymoma, a childhood brain tumor, we characterized an immune circuit between the tumor and antigen-presenting hematopoietic stem and progenitor cells (HSPCs) in the skull bone marrow. The presentation of antigens by HSPCs to CD4+ T cells biased HSPC lineages toward myelopoiesis and polarized CD4+ T cells to regulatory T cells, culminating in tumor immunotolerance. Remarkably, normalizing hematopoiesis with a single infusion of antibodies directed against cytokines enriched in the cerebrospinal fluid of mice bearing ZFTA–RELA ependymomas, choroid plexus carcinomas or group 3 medulloblastoma—all aggressive childhood brain tumors—disrupted this process and caused profound tumor regression. These findings demonstrate the existence of a skull bone marrow–tumor immunological interface and suggest that modulating the local supply of myeloid cells could represent a less toxic therapeutic strategy for aggressive childhood brain tumors. Antigen presentation in skull bone marrow by hematopoietic stem and progenitor cells induces myelopoiesis and generates CD4+ regulatory T cells in a mouse model of ependymoma, promoting immune tolerance. Treatment with anti-GM-CSF antibody has antitumor effects that are augmented by immunotherapy.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"317-328"},"PeriodicalIF":29.0,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02499-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-02DOI: 10.1038/s41588-026-02514-0
Single-nucleus DNA sequencing analyses elucidated the heterogeneous evolution of the genomes of pancreatic cancer cells. The key features uncovered highlighted mechanisms of resistance to therapy that might support ongoing precision medicine efforts.
{"title":"Single-nucleus DNA sequencing delves into the varied genomic evolution of pancreatic cancer","authors":"","doi":"10.1038/s41588-026-02514-0","DOIUrl":"10.1038/s41588-026-02514-0","url":null,"abstract":"Single-nucleus DNA sequencing analyses elucidated the heterogeneous evolution of the genomes of pancreatic cancer cells. The key features uncovered highlighted mechanisms of resistance to therapy that might support ongoing precision medicine efforts.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 2","pages":"247-248"},"PeriodicalIF":29.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146106290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：