Pub Date : 2025-11-14DOI: 10.1038/s41588-025-02410-z
Søren A. Rand, Gustav Ahlberg, Vinicius Tragante, Laia M. Monfort, Chaoqun Zheng, Ulla Feldt-Rasmussen, Marianne C. Klose, Maris Teder-Laving, Andres Metspalu, Henrik E. Poulsen, Christina Ellervik, Birte Nygaard, Christian Erikstrup, Mie T. Bruun, Bitten A. Jensen, Henrik Ullum, Søren Brunak, DBDS Genomic Consortium, Estonian Biobank Research Team, 23andMe Research Team, Michael Schwinn, Sisse R. Ostrowski, Ole B. Pedersen, Erik Sørensen, Ingileif Jonsdottir, Daniel F. Gudbjartsson, Gudmar Thorleifsson, Hilma Holm, Saedis Saevarsdottir, Kari Stefansson, Morten Salling Olesen, Henning Bundgaard, Jonas Ghouse
We performed a genome-wide meta-analysis of hypothyroidism (113,393 cases and 1,065,268 controls), free thyroxine (191,449 individuals) and thyroid-stimulating hormone (482,873 individuals). We identified 350 loci associated with hypothyroidism, including 179 not previously reported, 29 of which were linked through thyroid-stimulating hormone. We found that many hypothyroidism risk loci regulate blood cell counts and the circulating inflammasome, and through multiple gene-mapping strategies, we prioritized 259 putative causal genes enriched in immune-related functions. We developed a polygenic risk score (PRS) based on more than 115,000 hypothyroidism cases to address diagnostic challenges in individuals with or at risk of thyroid hormone deficiency. We show that the highest predictive accuracy for hypothyroidism was achieved when combining the PRS with thyroid hormones and thyroid-peroxidase autoantibodies, and that the PRS was able to stratify risk of progression among individuals with subclinical hypothyroidism. These findings demonstrate the potential for a hypothyroidism PRS to support the prediction of disease progression and onset in thyroid hormone deficiency. Large-scale genome-wide analyses identify hundreds of genetic loci associated with hypothyroidism and thyroid hormone levels, demonstrating the potential of using polygenic risk scores to predict disease onset and progression.
{"title":"Genome-wide association study and polygenic risk prediction of hypothyroidism","authors":"Søren A. Rand, Gustav Ahlberg, Vinicius Tragante, Laia M. Monfort, Chaoqun Zheng, Ulla Feldt-Rasmussen, Marianne C. Klose, Maris Teder-Laving, Andres Metspalu, Henrik E. Poulsen, Christina Ellervik, Birte Nygaard, Christian Erikstrup, Mie T. Bruun, Bitten A. Jensen, Henrik Ullum, Søren Brunak, DBDS Genomic Consortium, Estonian Biobank Research Team, 23andMe Research Team, Michael Schwinn, Sisse R. Ostrowski, Ole B. Pedersen, Erik Sørensen, Ingileif Jonsdottir, Daniel F. Gudbjartsson, Gudmar Thorleifsson, Hilma Holm, Saedis Saevarsdottir, Kari Stefansson, Morten Salling Olesen, Henning Bundgaard, Jonas Ghouse","doi":"10.1038/s41588-025-02410-z","DOIUrl":"10.1038/s41588-025-02410-z","url":null,"abstract":"We performed a genome-wide meta-analysis of hypothyroidism (113,393 cases and 1,065,268 controls), free thyroxine (191,449 individuals) and thyroid-stimulating hormone (482,873 individuals). We identified 350 loci associated with hypothyroidism, including 179 not previously reported, 29 of which were linked through thyroid-stimulating hormone. We found that many hypothyroidism risk loci regulate blood cell counts and the circulating inflammasome, and through multiple gene-mapping strategies, we prioritized 259 putative causal genes enriched in immune-related functions. We developed a polygenic risk score (PRS) based on more than 115,000 hypothyroidism cases to address diagnostic challenges in individuals with or at risk of thyroid hormone deficiency. We show that the highest predictive accuracy for hypothyroidism was achieved when combining the PRS with thyroid hormones and thyroid-peroxidase autoantibodies, and that the PRS was able to stratify risk of progression among individuals with subclinical hypothyroidism. These findings demonstrate the potential for a hypothyroidism PRS to support the prediction of disease progression and onset in thyroid hormone deficiency. Large-scale genome-wide analyses identify hundreds of genetic loci associated with hypothyroidism and thyroid hormone levels, demonstrating the potential of using polygenic risk scores to predict disease onset and progression.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3007-3015"},"PeriodicalIF":29.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02410-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145516231","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 : 2025-11-14DOI: 10.1038/s41588-025-02406-9
Thomas Sabaté, Benoît Lelandais, Marie-Cécile Robert, Michael Szalay, Jean-Yves Tinevez, Edouard Bertrand, Christophe Zimmer
Most animal genomes are partitioned into topologically associating domains (TADs), created by cohesin-mediated loop extrusion and defined by convergently oriented CCCTC-binding factor (CTCF) sites. The dynamics of loop extrusion and its regulation remain poorly characterized in vivo. Here we tracked the motion of TAD anchors in living human cells to visualize and quantify cohesin-dependent loop extrusion across multiple endogenous genomic regions. We show that TADs are dynamic structures whose anchors are brought in proximity about once per hour and for 6–19 min (~16% of the time). Moreover, TADs are continuously extruded by multiple cohesin complexes. Remarkably, despite strong differences in Hi-C patterns across chromatin regions, their dynamics is consistent with the same density, residence time and speed of cohesin. Our results suggest that TAD dynamics is primarily governed by the location and affinity of CTCF sites, enabling genome-wide predictive models of cohesin-dependent chromatin interactions. Live-cell fluorescence microscopy and polymer simulations in human HCT116 cells show similar cohesin density, residence times and extrusion speed across multiple genomic regions.
{"title":"Uniform dynamics of cohesin-mediated loop extrusion in living human cells","authors":"Thomas Sabaté, Benoît Lelandais, Marie-Cécile Robert, Michael Szalay, Jean-Yves Tinevez, Edouard Bertrand, Christophe Zimmer","doi":"10.1038/s41588-025-02406-9","DOIUrl":"10.1038/s41588-025-02406-9","url":null,"abstract":"Most animal genomes are partitioned into topologically associating domains (TADs), created by cohesin-mediated loop extrusion and defined by convergently oriented CCCTC-binding factor (CTCF) sites. The dynamics of loop extrusion and its regulation remain poorly characterized in vivo. Here we tracked the motion of TAD anchors in living human cells to visualize and quantify cohesin-dependent loop extrusion across multiple endogenous genomic regions. We show that TADs are dynamic structures whose anchors are brought in proximity about once per hour and for 6–19 min (~16% of the time). Moreover, TADs are continuously extruded by multiple cohesin complexes. Remarkably, despite strong differences in Hi-C patterns across chromatin regions, their dynamics is consistent with the same density, residence time and speed of cohesin. Our results suggest that TAD dynamics is primarily governed by the location and affinity of CTCF sites, enabling genome-wide predictive models of cohesin-dependent chromatin interactions. Live-cell fluorescence microscopy and polymer simulations in human HCT116 cells show similar cohesin density, residence times and extrusion speed across multiple genomic regions.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3152-3164"},"PeriodicalIF":29.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02406-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145509021","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 : 2025-11-13DOI: 10.1038/s41588-025-02402-z
Na Cai
A study drawing on biobank and registry data from five Nordic countries reveals distinct genetic associations for early- and late-onset major depressive disorder and differences in their genetic architectures and relationships with other traits. Stratification by age at onset can uncover risk effects relevant to severe outcomes and inform prevention strategies.
{"title":"Depression genetics through the lens of age at onset","authors":"Na Cai","doi":"10.1038/s41588-025-02402-z","DOIUrl":"10.1038/s41588-025-02402-z","url":null,"abstract":"A study drawing on biobank and registry data from five Nordic countries reveals distinct genetic associations for early- and late-onset major depressive disorder and differences in their genetic architectures and relationships with other traits. Stratification by age at onset can uncover risk effects relevant to severe outcomes and inform prevention strategies.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2944-2945"},"PeriodicalIF":29.0,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145498275","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 : 2025-11-13DOI: 10.1038/s41588-025-02396-8
John R. Shorter, Joëlle A. Pasman, Siim Kurvits, Andreas Jangmo, Joonas Naamanka, Arvid Harder, Espen Hagen, Kaarina Kowalec, Nelli Frilander, Richard Zetterberg, Joeri J. Meijsen, Jesper R. Gådin, Jacob Bergstedt, Ying Xiong, Sara Hägg, Mikael Landén, Christian Rück, John Wallert, Alkistis Skalkidou, Elise Koch, Bayram C. Akdeniz, Oleksandr Frei, FinnGen, Iiris Hovatta, Ted Reichborn-Kjennerud, Thomas M. Werge, Patrick F. Sullivan, Ole A. Andreassen, Martin Tesli, Kelli Lehto, Alfonso Buil, Yi Lu
Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n = 46,708 cases) and late-onset (loMDD; n = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, rg = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have partially distinct genetic signatures, with a specific developmental brain signature for eoMDD. Importantly, we demonstrate that polygenic risk scores (PRS) for eoMDD predict suicide attempts within the first 10 years after the initial diagnosis: the absolute risk for suicide attempt was 26% in the top PRS decile, compared to 12% and 20% in the bottom decile and the intermediate group, respectively. Taken together, our findings can inform precision psychiatry approaches for MDD. Genome-wide association analyses leveraging Nordic biobanks with longitudinal health registries identify differences in the genetic architectures of early-onset and late-onset major depressive disorder and in their genetic correlations with related traits.
重度抑郁症（MDD）是一种病因复杂的常见病和异质性疾病。根据临床特征（如发病年龄）分层研究更均匀的人群，可以提高对潜在遗传原因的识别，并制定更有针对性的治疗策略。我们利用北欧生物银行和纵向健康登记来调查早发性（eoMDD, n = 46,708例）和晚发性（loMDD, n = 37,168例）MDD遗传结构的差异。我们确定了12个eoMDD和2个loMDD的基因组位点。总体而言，两种MDD亚型相关性中等（遗传相关，rg = 0.58），但与相关性状的遗传相关性存在差异。这些发现表明，eoMDD和loMDD具有部分不同的遗传特征，其中eoMDD具有特定的发育性大脑特征。重要的是，我们证明了eoMDD的多基因风险评分（PRS）预测了最初诊断后最初10年内的自杀企图：在PRS的前十分位数中，自杀企图的绝对风险为26%，而在最低十分位数和中间组中分别为12%和20%。综上所述，我们的发现可以为重度抑郁症的精确精神病学方法提供信息。
{"title":"Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression","authors":"John R. Shorter, Joëlle A. Pasman, Siim Kurvits, Andreas Jangmo, Joonas Naamanka, Arvid Harder, Espen Hagen, Kaarina Kowalec, Nelli Frilander, Richard Zetterberg, Joeri J. Meijsen, Jesper R. Gådin, Jacob Bergstedt, Ying Xiong, Sara Hägg, Mikael Landén, Christian Rück, John Wallert, Alkistis Skalkidou, Elise Koch, Bayram C. Akdeniz, Oleksandr Frei, FinnGen, Iiris Hovatta, Ted Reichborn-Kjennerud, Thomas M. Werge, Patrick F. Sullivan, Ole A. Andreassen, Martin Tesli, Kelli Lehto, Alfonso Buil, Yi Lu","doi":"10.1038/s41588-025-02396-8","DOIUrl":"10.1038/s41588-025-02396-8","url":null,"abstract":"Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n = 46,708 cases) and late-onset (loMDD; n = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, rg = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have partially distinct genetic signatures, with a specific developmental brain signature for eoMDD. Importantly, we demonstrate that polygenic risk scores (PRS) for eoMDD predict suicide attempts within the first 10 years after the initial diagnosis: the absolute risk for suicide attempt was 26% in the top PRS decile, compared to 12% and 20% in the bottom decile and the intermediate group, respectively. Taken together, our findings can inform precision psychiatry approaches for MDD. Genome-wide association analyses leveraging Nordic biobanks with longitudinal health registries identify differences in the genetic architectures of early-onset and late-onset major depressive disorder and in their genetic correlations with related traits.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2972-2979"},"PeriodicalIF":29.0,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02396-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145513631","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 : 2025-11-13DOI: 10.1038/s41588-025-02392-y
We found that two key transcription factors contribute to disease progression in the classical subtype of pancreatic ductal adenocarcinoma. In the primary tumor context, the nuclear receptor HNF4G is the critical driver, but during the transition to metastasis, FOXA1 is derepressed and mediates metastatic potential.
{"title":"Defining the transcriptional landscape in the classical subtype of pancreatic cancer","authors":"","doi":"10.1038/s41588-025-02392-y","DOIUrl":"10.1038/s41588-025-02392-y","url":null,"abstract":"We found that two key transcription factors contribute to disease progression in the classical subtype of pancreatic ductal adenocarcinoma. In the primary tumor context, the nuclear receptor HNF4G is the critical driver, but during the transition to metastasis, FOXA1 is derepressed and mediates metastatic potential.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2950-2951"},"PeriodicalIF":29.0,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145498276","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 : 2025-11-12DOI: 10.1038/s41588-025-02432-7
Most aggressive metastatic prostate cancers are driven by activity of the androgen receptor (AR). This steroid-responsive transcription factor has a complex series of regulatory interactions with ligands, proteins and DNA that are required for normal biology and cancer phenotypes. We performed experiments to systematically identify genes required for maintaining AR protein levels, revealing mechanisms of regulating AR activity in the nucleus.
{"title":"Regulators of androgen receptor activity revealed by CRISPR interference screens","authors":"","doi":"10.1038/s41588-025-02432-7","DOIUrl":"10.1038/s41588-025-02432-7","url":null,"abstract":"Most aggressive metastatic prostate cancers are driven by activity of the androgen receptor (AR). This steroid-responsive transcription factor has a complex series of regulatory interactions with ligands, proteins and DNA that are required for normal biology and cancer phenotypes. We performed experiments to systematically identify genes required for maintaining AR protein levels, revealing mechanisms of regulating AR activity in the nucleus.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2952-2953"},"PeriodicalIF":29.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145492623","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 : 2025-11-12DOI: 10.1038/s41588-025-02390-0
Tyler A. Joseph, Joelle Mbatchou, Arkopravo Ghosh, Anthony Marcketta, Christopher E. Gillies, Jing Tang, Priyanka Nakka, Xinyuan Zhang, Jack A. Kosmicki, Carlo Sidore, Lauren Gurski, Regeneron Genetics Center, Maya Ghoussaini, Manuel A. R. Ferreira, Gonçalo Abecasis, Jonathan Marchini
Meta-analysis of gene-based tests using single-variant summary statistics is a powerful strategy for genetic association studies. However, current approaches require sharing the covariance matrix between variants for each study and trait of interest. For large-scale studies with many phenotypes, these matrices can be cumbersome to calculate, store and share. Here, to address this challenge, we present REMETA—an efficient tool for meta-analysis of gene-based tests. REMETA uses a single sparse covariance reference file per study that is rescaled for each phenotype using single-variant summary statistics. We develop new methods for binary traits with case–control imbalance, and to estimate allele frequencies, genotype counts and effect sizes of burden tests. We demonstrate the performance and advantages of our approach through meta-analysis of five traits in 469,376 samples in UK Biobank. The open-source REMETA software will facilitate meta-analysis across large-scale exome sequencing studies from diverse studies that cannot easily be combined. REMETA is a method for meta-analyzing gene-based associations using summary statistics, integrating with REGENIE and improving computational efficiency for large studies with many phenotypes.
{"title":"Computationally efficient meta-analysis of gene-based tests using summary statistics in large-scale genetic studies","authors":"Tyler A. Joseph, Joelle Mbatchou, Arkopravo Ghosh, Anthony Marcketta, Christopher E. Gillies, Jing Tang, Priyanka Nakka, Xinyuan Zhang, Jack A. Kosmicki, Carlo Sidore, Lauren Gurski, Regeneron Genetics Center, Maya Ghoussaini, Manuel A. R. Ferreira, Gonçalo Abecasis, Jonathan Marchini","doi":"10.1038/s41588-025-02390-0","DOIUrl":"10.1038/s41588-025-02390-0","url":null,"abstract":"Meta-analysis of gene-based tests using single-variant summary statistics is a powerful strategy for genetic association studies. However, current approaches require sharing the covariance matrix between variants for each study and trait of interest. For large-scale studies with many phenotypes, these matrices can be cumbersome to calculate, store and share. Here, to address this challenge, we present REMETA—an efficient tool for meta-analysis of gene-based tests. REMETA uses a single sparse covariance reference file per study that is rescaled for each phenotype using single-variant summary statistics. We develop new methods for binary traits with case–control imbalance, and to estimate allele frequencies, genotype counts and effect sizes of burden tests. We demonstrate the performance and advantages of our approach through meta-analysis of five traits in 469,376 samples in UK Biobank. The open-source REMETA software will facilitate meta-analysis across large-scale exome sequencing studies from diverse studies that cannot easily be combined. REMETA is a method for meta-analyzing gene-based associations using summary statistics, integrating with REGENIE and improving computational efficiency for large studies with many phenotypes.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3193-3200"},"PeriodicalIF":29.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02390-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145505697","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 : 2025-11-11DOI: 10.1038/s41588-025-02405-w
Tetsuichi Yoshizato, Christer Nilsson, Francesca Grasso, Kari Högstrand, Stefania Mazzi, Axel Winroth, Madeleine Lehander, Indira Barbosa, Gunilla Waldin, Teresa Mortera-Blanco, Monika Jansson, Mikaela Hillberg Widfeldt, Affaf Aliouat, Margs S. Brennan, Ellen Markljung, Amy Hillen, Edwin Chari, Eva Hellström-Lindberg, Warren W. Kretzschmar, Petter S. Woll, Sten Eirik W. Jacobsen
Dynamic steady-state lineage contribution of human hematopoietic stem cell (HSC) clones needs to be assessed over time. However, clonal contribution of HSCs has only been investigated at single time points and without assessing the critical erythroid and platelet lineages. Here we screened for somatic mutations in healthy aged individuals, identifying expanded HSC clones accessible for lineage tracing of all major blood cell lineages. In addition to HSC clones with balanced contribution to all lineages, we identified clones with all myeloid lineages but no or few B and T lymphocytes or all myeloid lineages and B cells but no T cells. No other lineage restriction patterns were reproducibly observed. Retrospective phylogenetic inferences uncovered a ‘hierarchical’ pattern of descendant subclones more lineage biased than their ancestral clone and a more common ‘stable’ pattern with descendant subclones showing highly concordant lineage contributions with their ancestral clone, despite decades of separation. Prospective lineage tracing confirmed remarkable stability over years of HSC clones with distinct lineage replenishment patterns. This study uses somatic mutations as a natural barcoding system to retrospectively and prospectively trace the fate of hematopoietic stem cells across all major blood cell lineages in healthy aged individuals. It reveals the existence of intrinsically fate-biased hematopoietic stem cells in native human hematopoiesis, validated by transplantation assays.
{"title":"Stable clonal contribution of lineage-restricted stem cells to human hematopoiesis","authors":"Tetsuichi Yoshizato, Christer Nilsson, Francesca Grasso, Kari Högstrand, Stefania Mazzi, Axel Winroth, Madeleine Lehander, Indira Barbosa, Gunilla Waldin, Teresa Mortera-Blanco, Monika Jansson, Mikaela Hillberg Widfeldt, Affaf Aliouat, Margs S. Brennan, Ellen Markljung, Amy Hillen, Edwin Chari, Eva Hellström-Lindberg, Warren W. Kretzschmar, Petter S. Woll, Sten Eirik W. Jacobsen","doi":"10.1038/s41588-025-02405-w","DOIUrl":"10.1038/s41588-025-02405-w","url":null,"abstract":"Dynamic steady-state lineage contribution of human hematopoietic stem cell (HSC) clones needs to be assessed over time. However, clonal contribution of HSCs has only been investigated at single time points and without assessing the critical erythroid and platelet lineages. Here we screened for somatic mutations in healthy aged individuals, identifying expanded HSC clones accessible for lineage tracing of all major blood cell lineages. In addition to HSC clones with balanced contribution to all lineages, we identified clones with all myeloid lineages but no or few B and T lymphocytes or all myeloid lineages and B cells but no T cells. No other lineage restriction patterns were reproducibly observed. Retrospective phylogenetic inferences uncovered a ‘hierarchical’ pattern of descendant subclones more lineage biased than their ancestral clone and a more common ‘stable’ pattern with descendant subclones showing highly concordant lineage contributions with their ancestral clone, despite decades of separation. Prospective lineage tracing confirmed remarkable stability over years of HSC clones with distinct lineage replenishment patterns. This study uses somatic mutations as a natural barcoding system to retrospectively and prospectively trace the fate of hematopoietic stem cells across all major blood cell lineages in healthy aged individuals. It reveals the existence of intrinsically fate-biased hematopoietic stem cells in native human hematopoiesis, validated by transplantation assays.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3088-3100"},"PeriodicalIF":29.0,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02405-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484918","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}
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