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Fu Y, Kenttämies A, Ruotsalainen S, Pirinen M, Tukiainen T. Role of X chromosome and dosage-compensation mechanisms in complex trait genetics. Am J Hum Genet 2025:S0002-9297(25)00145-4. [PMID: 40359939 DOI: 10.1016/j.ajhg.2025.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2025] [Revised: 04/16/2025] [Accepted: 04/16/2025] [Indexed: 05/15/2025] Open
Abstract
The X chromosome (chrX) is often excluded from genome-wide association studies due to its unique biology complicating the analysis and interpretation of genetic data. Consequently, the influence of chrX on human complex traits remains debated. Here, we systematically assessed the relevance of chrX and the effect of its biology on complex traits by analyzing 48 quantitative traits in 343,695 individuals in UK Biobank with replication in 412,181 individuals from FinnGen. We show that, in the general population, chrX contributes to complex trait heritability at a rate of 3% of the autosomal heritability, consistent with the amount of genetic variation observed in chrX. We find that a pronounced male bias in chrX heritability supports the presence of near-complete dosage compensation between sexes through X chromosome inactivation (XCI). However, we also find subtle yet plausible evidence of escape from XCI contributing to human height. Assuming full XCI, the observed chrX contribution to complex trait heritability in both sexes is greater than expected given the presence of only a single active copy of chrX, mirroring potential dosage compensation between chrX and the autosomes. We find this enhanced contribution attributable to systematically larger active allele effects from chrX compared to autosomes in both sexes, independent of allele frequency and variant deleteriousness. Together, these findings support a model in which the two dosage-compensation mechanisms work in concert to balance the influence of chrX across the population while preserving sex-specific differences at a manageable level. Overall, our study advocates for more comprehensive locus discovery efforts in chrX.
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Affiliation(s)
- Yu Fu
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland
| | - Aino Kenttämies
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland; Department of Public Health, University of Helsinki, 00014 Helsinki, Finland; Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014 Helsinki, Finland.
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He W, Luo Q, Zhao J, Wang M, Zhao A, Feng L, Reda A, Lindgren E, Stukenborg J, Chen J, Deng Q. X-Linked Gene Dosage and SOX2 Act as Key Roadblocks for Human Germ Cell Specification in Klinefelter Syndrome. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2410533. [PMID: 39996497 PMCID: PMC12005746 DOI: 10.1002/advs.202410533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 02/03/2025] [Indexed: 02/26/2025]
Abstract
Klinefelter syndrome (KS), characterized by the presence of at least one extra X-chromosome, is a common cause of male infertility. However, the mechanism underlying the failure of germline specification is not well studied. Intriguingly, the differentiation efficiency of female human pluripotent stem cells (hPSCs) is often lower than that of male. This study investigates how X-linked gene dosage affects human primordial germ cell-like cells (hPGCLCs) specification in both healthy and diseased conditions. This work reveals that X-linked genes play a multifaceted role against the fate competency to hPGCLCs, with escape genes IGSF1 and CHRDL1 inhibiting the TGF-beta/Activin A and BMP pathways, respectively. Notably, this work identifies a previously unrecognized role of SOX2, upregulated by the escape gene USP9X, elucidating a species-specific function in the mammalian germline. The USP9X-SOX2 regulatory axis profoundly influenced cellular metabolism, mitochondrial morphology, and progenitor competence in hPGCLCs specification. Furthermore, the inability to downregulate SOX2 and upregulate SOX17 in response to BMP signaling impedes downstream gene activation due to motif binding competition. These findings shed novel insights into the human germline specification by elucidating the divergent roles of SOX2 versus SOX17 in mammals, influenced by X-linked gene dosage effects. These results offer potential applications for improving the induction efficiency of hPGCLCs, facilitating disease mechanistic studies.
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Affiliation(s)
- Wenteng He
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Qing Luo
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Jian Zhao
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
- Department of Oncology‐PathologyKarolinska InstitutetStockholm171 77Sweden
| | - Mengting Wang
- Clinical and Translational Research Center of Shanghai First Maternity and Infant HospitalShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai200092China
| | - Allan Zhao
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Luohua Feng
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Ahmed Reda
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Eva Lindgren
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
| | - Jan‐Bernd Stukenborg
- NORDFERTIL Research Lab StockholmChildhood Cancer Research UnitDepartment of Women's and Children's HealthKarolinska InstitutetKarolinska University HospitalStockholm17 165Sweden
| | - Jiayu Chen
- Clinical and Translational Research Center of Shanghai First Maternity and Infant HospitalShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai200092China
- Frontier Science Center for Stem Cell ResearchTongji UniversityShanghai200092China
| | - Qiaolin Deng
- Department of Physiology and PharmacologyKarolinska InstitutetStockholm171 77Sweden
- Department of Molecular Biosciences, The Wenner‐Gren InstituteStockholm UnviersityStockholm11418Sweden
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3
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Groeneweg S, van Geest FS, Martín M, Dias M, Frazer J, Medina-Gomez C, Sterenborg RBTM, Wang H, Dolcetta-Capuzzo A, de Rooij LJ, Teumer A, Abaci A, van den Akker ELT, Ambegaonkar GP, Armour CM, Bacos I, Bakhtiani P, Barca D, Bauer AJ, van den Berg SAA, van den Berge A, Bertini E, van Beynum IM, Brunetti-Pierri N, Brunner D, Cappa M, Cappuccio G, Castellotti B, Castiglioni C, Chatterjee K, Chesover A, Christian P, Coenen-van der Spek J, de Coo IFM, Coutant R, Craiu D, Crock P, DeGoede C, Demir K, Dewey C, Dica A, Dimitri P, Dremmen MHG, Dubey R, Enderli A, Fairchild J, Gallichan J, Garibaldi L, George B, Gevers EF, Greenup E, Hackenberg A, Halász Z, Heinrich B, Hurst AC, Huynh T, Isaza AR, Klosowska A, van der Knoop MM, Konrad D, Koolen DA, Krude H, Kulkarni A, Laemmle A, LaFranchi SH, Lawson-Yuen A, Lebl J, Leeuwenburgh S, Linder-Lucht M, López Martí A, Lorea CF, Lourenço CM, Lunsing RJ, Lyons G, Malikova JK, Mancilla EE, McCormick KL, McGowan A, Mericq V, Lora FM, Moran C, Muller KE, Nicol LE, Oliver-Petit I, Paone L, Paul PG, Polak M, Porta F, Poswar FO, Reinauer C, Rozenkova K, Seckold R, Seven Menevse T, Simm P, Simon A, Singh Y, Spada M, Stals MAM, Stegenga MT, Stoupa A, et alGroeneweg S, van Geest FS, Martín M, Dias M, Frazer J, Medina-Gomez C, Sterenborg RBTM, Wang H, Dolcetta-Capuzzo A, de Rooij LJ, Teumer A, Abaci A, van den Akker ELT, Ambegaonkar GP, Armour CM, Bacos I, Bakhtiani P, Barca D, Bauer AJ, van den Berg SAA, van den Berge A, Bertini E, van Beynum IM, Brunetti-Pierri N, Brunner D, Cappa M, Cappuccio G, Castellotti B, Castiglioni C, Chatterjee K, Chesover A, Christian P, Coenen-van der Spek J, de Coo IFM, Coutant R, Craiu D, Crock P, DeGoede C, Demir K, Dewey C, Dica A, Dimitri P, Dremmen MHG, Dubey R, Enderli A, Fairchild J, Gallichan J, Garibaldi L, George B, Gevers EF, Greenup E, Hackenberg A, Halász Z, Heinrich B, Hurst AC, Huynh T, Isaza AR, Klosowska A, van der Knoop MM, Konrad D, Koolen DA, Krude H, Kulkarni A, Laemmle A, LaFranchi SH, Lawson-Yuen A, Lebl J, Leeuwenburgh S, Linder-Lucht M, López Martí A, Lorea CF, Lourenço CM, Lunsing RJ, Lyons G, Malikova JK, Mancilla EE, McCormick KL, McGowan A, Mericq V, Lora FM, Moran C, Muller KE, Nicol LE, Oliver-Petit I, Paone L, Paul PG, Polak M, Porta F, Poswar FO, Reinauer C, Rozenkova K, Seckold R, Seven Menevse T, Simm P, Simon A, Singh Y, Spada M, Stals MAM, Stegenga MT, Stoupa A, Subramanian GM, Szeifert L, Tonduti D, Turan S, Vanderniet J, van der Walt A, Wémeau JL, van Wermeskerken AM, Wierzba J, de Wit MCY, Wolf NI, Wurm M, Zibordi F, Zung A, Zwaveling-Soonawala N, Rivadeneira F, Meima ME, Marks DS, Nicola JP, Chen CH, Medici M, Visser WE. Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration. Nat Commun 2025; 16:2479. [PMID: 40075072 PMCID: PMC11904026 DOI: 10.1038/s41467-025-56628-w] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 01/23/2025] [Indexed: 03/14/2025] Open
Abstract
Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for 'actionable' genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-of-function (LoF) variants cause a rare neurodevelopmental and (treatable) metabolic disorder in males. The combination of deep phenotyping data with functional and computational tests and with outcomes in population cohorts, enabled us to: (i) identify the genetic aetiology of divergent clinical phenotypes of MCT8 deficiency with genotype-phenotype relationships present across survival and 24 out of 32 disease features; (ii) demonstrate a mild phenocopy in ~400,000 individuals with common genetic variants in MCT8; (iii) assess therapeutic effectiveness, which did not differ among LoF-categories; (iv) advance structural insights in normal and mutated MCT8 by delineating seven critical functional domains; (v) create a pathogenicity-severity MCT8 variant classifier that accurately predicted pathogenicity (AUC:0.91) and severity (AUC:0.86) for 8151 variants. Our information-dense mapping provides a generalizable approach to advance multiple dimensions of rare genetic disorders.
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Affiliation(s)
- Stefan Groeneweg
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ferdy S van Geest
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Mariano Martín
- Department of Clinical Biochemistry (CIBICI-CONICET), Faculty of Chemical Sciences, National University of Córdoba, Córdoba, Argentina
- Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Mafalda Dias
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Jonathan Frazer
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Rosalie B T M Sterenborg
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hao Wang
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Anna Dolcetta-Capuzzo
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Linda J de Rooij
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Ayhan Abaci
- Division of Pediatric Endocrinology, Faculty of Medicine, Dokuz Eylul University, İzmir, Turkey
| | - Erica L T van den Akker
- Department of Paediatrics, Division of Endocrinology, Erasmus Medical Centre -Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Gautam P Ambegaonkar
- Department of Paediatric Neurology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Christine M Armour
- Regional Genetics Program, Children's Hospital of Eastern Ontario and Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Iiuliu Bacos
- Centrul Medical Dr. Bacos Cosma, Timisoara, Romania
| | - Priyanka Bakhtiani
- University of Louisville, Louisville, KY, USA
- Childrens Hospital Los Angeles, Los Angeles, CA, USA
| | - Diana Barca
- Carol Davila University of Medicine, Department of Clinical Neurosciences, Paediatric Neurology Discipline II, Bucharest, Romania
| | - Andrew J Bauer
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sjoerd A A van den Berg
- Diagnostic Laboratory for Endocrinology, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Amanda van den Berge
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Enrico Bertini
- Unit of Neuromuscular and Neurodegenerative Disorders, Bambino Gesu' Children's Research Hospital IRCCS, Rome, Italy
| | - Ingrid M van Beynum
- Department of Pediatrics, Division of Pediatric Cardiology, Erasmus Medical Centre - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Nicola Brunetti-Pierri
- Department of Translational Medicine, Federico II University, 80131, Naples, Italy
- Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Naples, Italy
- Scuola Superiore Meridionale (SSM, School of Advanced Studies), Genomics and Experimental Medicine Program, University of Naples Federico II, Naples, Italy
| | - Doris Brunner
- Gottfried Preyer's Children Hospital, Vienna, Austria
| | - Marco Cappa
- Research Area for Innovative Therapies in Endocrinopathies, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Gerarda Cappuccio
- Department of Translational Medicine, Federico II University, 80131, Naples, Italy
- Neurological Research Institute and Baylor College of Medicine, Houston, TX, USA
| | - Barbara Castellotti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Claudia Castiglioni
- Department of Neurology, Clinica Meds, School of Medicine, Universidad Finis Terrae, Santiago, Chile
| | - Krishna Chatterjee
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Alexander Chesover
- Division of Endocrinology, The Hospital for Sick Children and Department of Paediatrics, University of Toronto, Toronto, M5G 1×8, Canada
- Department of Endocrinology, Great Ormond Street Hospital for Children, London, UK
| | - Peter Christian
- East Kent Hospitals University NHS Foundation Trust, Ashford, UK
| | - Jet Coenen-van der Spek
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center (Radboudumc), Nijmegen, The Netherlands
| | - Irenaeus F M de Coo
- Department of Toxicogenomics, Unit Clinical Genomics, Maastricht University, MHeNs School for Mental Health and Neuroscience, Maastricht, The Netherlands
| | - Regis Coutant
- Department of Pediatric Endocrinology and Diabetology, University Hospital, Angers, France
| | - Dana Craiu
- Carol Davila University of Medicine, Department of Clinical Neurosciences, Paediatric Neurology Discipline II, Bucharest, Romania
| | - Patricia Crock
- John Hunter Children's Hospital, Hunter Medical Research Institute, University of Newcastle, New Lambton Heights, Australia
| | - Christian DeGoede
- Department of Paediatric Neurology, Clinical Research Facility, Lancashire Teaching Hospitals NHS Trust, Lancashire, UK
| | - Korcan Demir
- Division of Pediatric Endocrinology, Faculty of Medicine, Dokuz Eylul University, İzmir, Turkey
| | - Cheyenne Dewey
- Genomics Institute Mary Bridge Children's Hospital, MultiCare Health System, Tacoma, WA, USA
| | - Alice Dica
- Carol Davila University of Medicine, Department of Clinical Neurosciences, Paediatric Neurology Discipline II, Bucharest, Romania
| | - Paul Dimitri
- The Department of Oncology and Metabolism, The University of Sheffield, Western Bank, Sheffield, S10, 2TH, UK
| | - Marjolein H G Dremmen
- Division of Paediatric Radiology, Erasmus Medical Centre - Sophia's Children Hospital, Rotterdam, The Netherlands
| | | | - Anina Enderli
- Department of Neuropediatrics, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - Jan Fairchild
- Department of Diabetes and Endocrinology, Women's and Children's Hospital, North Adelaide, 5066, South Australia, Australia
| | | | | | - Belinda George
- Department of Endocrinology, St. John's Medical College Hospital, Bengaluru, India
| | - Evelien F Gevers
- Centre for Endocrinology, William Harvey Research institute, Queen Mary University of London, London, UK
| | - Erin Greenup
- Department of Pediatrics, Division of Pediatric Endocrinology, University of Alabama at Birmingham, Birmingham, AL, USA
- Division of Pediatric Endocrinology, Department of Pediatrics, Orlando Health Arnold Palmer Hospital for Children, Orlando, FL, USA
| | - Annette Hackenberg
- Department of Neuropediatrics, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - Zita Halász
- Pediatric Center, Semmelweis University Budapest, Budapest, Hungary
| | - Bianka Heinrich
- Department of Neuropediatrics, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - Anna C Hurst
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tony Huynh
- Department of Endocrinology & Diabetes, Queensland Children's Hospital, South Brisbane, Queensland, Australia
| | - Amber R Isaza
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Anna Klosowska
- Department of Pediatrics, Hematology and Oncology, Medical University of Gdańsk, Gdańsk, Poland
| | | | - Daniel Konrad
- Division of Pediatric Endocrinology and Diabetology and Children's Research Center, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - David A Koolen
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center (Radboudumc), Nijmegen, The Netherlands
| | - Heiko Krude
- Institute of Experimental Paediatric Endocrinology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Abhishek Kulkarni
- Department of Paediatric Endocrinology, SRCC Children's Hospital, Mumbai, India
| | - Alexander Laemmle
- Institute of Clinical Chemistry and Department of Pediatrics, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Stephen H LaFranchi
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Sciences University, Portland, OR, USA
| | - Amy Lawson-Yuen
- Genomics Institute Mary Bridge Children's Hospital, MultiCare Health System, Tacoma, WA, USA
- Department of Genetics, Kaiser Permanente Washington, Seattle, WA, USA
| | - Jan Lebl
- Department of Paediatrics, Second Faculty of Medicine, Charles University, University Hospital Motol, Prague, Czech Republic
| | - Selmar Leeuwenburgh
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Michaela Linder-Lucht
- Division of Neuropediatrics and Muscular Disorders, Department of Pediatrics and Adolescent Medicine, University Hospital Freiburg, Freiburg, Germany
| | - Anna López Martí
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Cláudia F Lorea
- Teaching Hospital of Universidade Federal de Pelotas, Pelotas, Brazil
- Federal University of Rio Grande do Sul, Porto Alegre-RS, Brazil
| | - Charles M Lourenço
- National Reference Center for Rare Diseases, Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto, Brazil
- Personalized Medicine area -Special Education Sector at DLE/Grupo Pardini, Rio de Janeiro, Brazil
| | - Roelineke J Lunsing
- Department of Child Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Greta Lyons
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Jana Krenek Malikova
- Department of Paediatrics, Second Faculty of Medicine, Charles University, University Hospital Motol, Prague, Czech Republic
| | - Edna E Mancilla
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kenneth L McCormick
- Department of Pediatrics, Division of Pediatric Endocrinology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anne McGowan
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Veronica Mericq
- Institute of Maternal and Child Research, University of Chile, Santiago, Chile, Department of Pediatrics, Clinica Las Condes, Santiago, Chile
| | - Felipe Monti Lora
- Pediatric Endocrinology Group, Sabara Children's Hospital, São Paulo, Brazil
| | - Carla Moran
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Lindsey E Nicol
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Sciences University, Portland, OR, USA
| | - Isabelle Oliver-Petit
- Department of Paediatric Endocrinology and Genetics, Children's Hospital, Toulouse University Hospital, Toulouse, France
| | - Laura Paone
- Endocrinology and Diabetology Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Praveen G Paul
- Department of Paediatrics, Christian Medical College, Vellore, India
| | - Michel Polak
- Paediatric Endocrinology, Diabetology and Gynaecology, Department, Necker Children's University Hospital, Imagine Institute Affiliate, Université de Paris Cité, Paris, France
| | - Francesco Porta
- Department of Paediatrics, AOU Città della Salute e della Scienza di Torino, University of Torino, Turin, Italy
| | - Fabiano O Poswar
- Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Christina Reinauer
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, University Children's Hospital, Medical Faculty, Dusseldorf, Germany
| | - Klara Rozenkova
- Department of Paediatrics, Second Faculty of Medicine, Charles University, University Hospital Motol, Prague, Czech Republic
| | - Rowen Seckold
- John Hunter Children's Hospital, Hunter Medical Research Institute, University of Newcastle, New Lambton Heights, Australia
| | - Tuba Seven Menevse
- Marmara University School of Medicine Department of Pediatric Endocrinology, Istanbul, Turkey
| | - Peter Simm
- Royal Children's Hospital/University of Melbourne, Parkville, Australia
| | - Anna Simon
- Department of Paediatrics, Christian Medical College, Vellore, India
| | - Yogen Singh
- Department of Paediatric Cardiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Pediatrics, University of California - UC Davis Children's Hospital, Sacramento, CA, USA
| | - Marco Spada
- Department of Paediatrics, AOU Città della Salute e della Scienza di Torino, University of Torino, Turin, Italy
| | - Milou A M Stals
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Merel T Stegenga
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Athanasia Stoupa
- Paediatric Endocrinology, Diabetology and Gynaecology, Department, Necker Children's University Hospital, Imagine Institute Affiliate, Université de Paris Cité, Paris, France
| | - Gopinath M Subramanian
- John Hunter Children's Hospital, Hunter Medical Research Institute, University of Newcastle, New Lambton Heights, Australia
| | - Lilla Szeifert
- Pediatric Center, Semmelweis University Budapest, Budapest, Hungary
| | - Davide Tonduti
- Child Neurology Unit - C.O.A.L.A. (Center for diagnosis and treatment of leukodystrophies), V. Buzzi Children's Hospital, Milano, Italy
- Department of Clinical and Biomedical Science, Università degli Studi di Milano, Milano, Italy
| | - Serap Turan
- Marmara University School of Medicine Department of Pediatric Endocrinology, Istanbul, Turkey
| | - Joel Vanderniet
- John Hunter Children's Hospital, Hunter Medical Research Institute, University of Newcastle, New Lambton Heights, Australia
| | - Adri van der Walt
- Private paediatric Neurology practice Dr A van der Walt, Durbanville, South Africa
| | | | | | - Jolanta Wierzba
- Department of Internal and Pediatric Nursing, Institute of Nursing and Midwifery, Medical University of Gdańsk, Gdańsk, Poland
| | - Marie-Claire Y de Wit
- Department of Paediatric Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nicole I Wolf
- Department of Child Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Cellular & Molecular Mechanisms, Amsterdam, The Netherlands
| | - Michael Wurm
- University Children's Hospital Regensburg (KUNO), University of Regensburg, Campus St. Hedwig, Regensburg, Germany
| | - Federica Zibordi
- Child Neurology Unit, Fondazione IRCCS, Istituto Neurologico Carlo Besta, Milan, Italy
| | - Amnon Zung
- Pediatric Endocrinology Unit, Kaplan Medical center, Rehovot and the Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nitash Zwaveling-Soonawala
- Emma Children's Hospital, Department of Paediatric Endocrinology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Marcel E Meima
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Debora S Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Juan P Nicola
- Department of Clinical Biochemistry (CIBICI-CONICET), Faculty of Chemical Sciences, National University of Córdoba, Córdoba, Argentina
| | - Chi-Hua Chen
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Marco Medici
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - W Edward Visser
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands.
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Jiang Z, Sullivan PF, Li T, Zhao B, Wang X, Luo T, Huang S, Guan PY, Chen J, Yang Y, Stein JL, Li Y, Liu D, Sun L, Zhu H. The X chromosome's influences on the human brain. SCIENCE ADVANCES 2025; 11:eadq5360. [PMID: 39854466 PMCID: PMC11759047 DOI: 10.1126/sciadv.adq5360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Accepted: 12/23/2024] [Indexed: 01/26/2025]
Abstract
Genes on the X chromosome are extensively expressed in the human brain. However, little is known for the X chromosome's impact on the brain anatomy, microstructure, and functional networks. We examined 1045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X chromosome interactions while proposing an atlas outlining dosage compensation for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we found unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.
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Affiliation(s)
- Zhiwen Jiang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Shuai Huang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Peter Y. Guan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jie Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Dajiang Liu
- Department of Public Health Sciences, Penn State University, Hershey, PA 17033, USA
- Department of Biochemistry and Molecular Biology, Penn State University, Hershey, PA 17033, USA
| | - Lei Sun
- Department of Statistical Sciences, University of Toronto, Toronto, ON M5G 1Z5, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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5
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de Carvalho FE, Ferraz JBS, Pedrosa VB, Matos EC, Eler JP, Silva MR, Guimarães JD, Bussiman F, Silva BCA, Mulim HA, Rocha AO, Araujo AC, Wen H, Campos GS, Brito LF. Genetic parameters and genome-wide association studies including the X chromosome for various reproduction and semen quality traits in Nellore cattle. BMC Genomics 2025; 26:26. [PMID: 39794685 PMCID: PMC11720523 DOI: 10.1186/s12864-024-11193-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 12/27/2024] [Indexed: 01/13/2025] Open
Abstract
BACKGROUND The profitability of the beef industry is directly influenced by the fertility rate and reproductive performance of both males and females, which can be improved through selective breeding. When performing genomic analyses, genetic markers located on the X chromosome have been commonly ignored despite the X chromosome being one of the largest chromosomes in the cattle genome. Therefore, the primary objectives of this study were to: (1) estimate variance components and genetic parameters for eighteen male and five female fertility and reproductive traits in Nellore cattle including X chromosome markers in the analyses; and (2) perform genome-wide association studies and functional genomic analyses to better understand the genetic background of male and female fertility and reproductive performance traits in Nellore cattle. RESULTS The percentage of the total direct heritability (h2total) explained by the X chromosome markers (h2x) ranged from 3 to 32% (average: 16.4%) and from 9 to 67% (average: 25.61%) for female reproductive performance and male fertility traits, respectively. Among the traits related to breeding soundness evaluation, the overall bull and semen evaluation and semen quality traits accounted for the highest proportion of h2x relative to h2total with an average of 39.5% and 38.75%, respectively. The total number of significant genomic markers per trait ranged from 7 (seminal vesicle width) to 43 (total major defects). The number of significant markers located on the X chromosome ranged from zero to five. A total of 683, 252, 694, 382, 61, and 77 genes overlapped with the genomic regions identified for traits related to female reproductive performance, semen quality, semen morphology, semen defects, overall bulls' fertility evaluation, and overall semen evaluation traits, respectively. The key candidate genes located on the X chromosome are PRR32, STK26, TMSB4X, TLR7, PRPS2, SMS, SMARCA1, UTP14A, and BCORL1. The main gene ontology terms identified are "Oocyte Meiosis", "Progesterone Mediated Oocyte Maturation", "Thermogenesis", "Sperm Flagellum", and "Innate Immune Response". CONCLUSIONS Our findings indicate the key role of genes located on the X chromosome on the phenotypic variability of male and female reproduction and fertility traits in Nellore cattle. Breeding programs aiming to improve these traits should consider adding the information from X chromosome markers in their genomic analyses.
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Affiliation(s)
- Felipe E de Carvalho
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil.
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA.
| | - José Bento S Ferraz
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil
| | - Victor B Pedrosa
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Elisangela C Matos
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil
| | - Joanir P Eler
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil
| | - Marcio R Silva
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil
| | - José D Guimarães
- Department of Veterinary Medicine, Federal University of Vicosa, Vicosa, MG, Brazil
| | - Fernando Bussiman
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA
| | - Barbara C A Silva
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil
| | - Henrique A Mulim
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Artur Oliveira Rocha
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Andre C Araujo
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Hui Wen
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Gabriel S Campos
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN, 47907, USA.
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6
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Mokhtaridoost M, Chalmers JJ, Soleimanpoor M, McMurray BJ, Lato DF, Nguyen SC, Musienko V, Nash JO, Espeso-Gil S, Ahmed S, Delfosse K, Browning JWL, Barutcu AR, Wilson MD, Liehr T, Shlien A, Aref S, Joyce EF, Weise A, Maass PG. Inter-chromosomal contacts demarcate genome topology along a spatial gradient. Nat Commun 2024; 15:9813. [PMID: 39532865 PMCID: PMC11557711 DOI: 10.1038/s41467-024-53983-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 10/28/2024] [Indexed: 11/16/2024] Open
Abstract
Non-homologous chromosomal contacts (NHCCs) between different chromosomes participate considerably in gene and genome regulation. Due to analytical challenges, NHCCs are currently considered as singular, stochastic events, and their extent and fundamental principles across cell types remain controversial. We develop a supervised and unsupervised learning algorithm, termed Signature, to call NHCCs in Hi-C datasets to advance our understanding of genome topology. Signature reveals 40,282 NHCCs and their properties across 62 Hi-C datasets of 53 diploid human cell types. Genomic regions of NHCCs are gene-dense, highly expressed, and harbor genes for cell-specific and sex-specific functions. Extensive inter-telomeric and inter-centromeric clustering occurs across cell types [Rabl's configuration] and 61 NHCCs are consistently found at the nuclear speckles. These constitutive 'anchor loci' facilitate an axis of genome activity whilst cell-type-specific NHCCs act in discrete hubs. Our results suggest that non-random chromosome positioning is supported by constitutive NHCCs that shape genome topology along an off-centered spatial gradient of genome activity.
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Affiliation(s)
- Milad Mokhtaridoost
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Jordan J Chalmers
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Marzieh Soleimanpoor
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Brandon J McMurray
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Daniella F Lato
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Son C Nguyen
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Viktoria Musienko
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, 07747, Jena, Germany
| | - Joshua O Nash
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Laboratory of Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Sergio Espeso-Gil
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Sameen Ahmed
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Kate Delfosse
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
| | - Jared W L Browning
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - A Rasim Barutcu
- Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
| | - Michael D Wilson
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Thomas Liehr
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, 07747, Jena, Germany
| | - Adam Shlien
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada
- Laboratory of Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Samin Aref
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, M5S3G8, Canada
| | - Eric F Joyce
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anja Weise
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, 07747, Jena, Germany
| | - Philipp G Maass
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, ON, M5G 0A4, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada.
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7
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Belloy ME, Le Guen Y, Stewart I, Williams K, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue M, Napolioni V, Greicius MD. Role of the X Chromosome in Alzheimer Disease Genetics. JAMA Neurol 2024; 81:1032-1042. [PMID: 39250132 PMCID: PMC11385320 DOI: 10.1001/jamaneurol.2024.2843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 07/11/2024] [Indexed: 09/10/2024]
Abstract
Importance The X chromosome has remained enigmatic in Alzheimer disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. Objectives To perform the first large-scale X chromosome-wide association study (XWAS) of AD. Design, Setting, and Participants This was a meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium, the Alzheimer's Disease Sequencing Project, the UK Biobank, the Finnish health registry, and the US Million Veterans Program. Risk of AD was evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Genetic data available from high-density single-nucleotide variant microarrays and whole-genome sequencing and summary statistics for multitissue expression and protein quantitative trait loci available from published studies were included, enabling follow-up genetic colocalization analyses. A total of 1 629 863 eligible participants were selected from referred and volunteer samples, 477 596 of whom were excluded for analysis exclusion criteria. The number of participants who declined to participate in original studies was not available. Main Outcome and Measures Risk of AD, reported as odds ratios (ORs) with 95% CIs. Associations were considered at X chromosome-wide (P < 1 × 10-5) and genome-wide (P < 5 × 10-8) significance. Primary analyses are nonstratified, while secondary analyses evaluate sex-stratified effects. Results Analyses included 1 152 284 participants of non-Hispanic White, European ancestry (664 403 [57.7%] female and 487 881 [42.3%] male), including 138 558 individuals with AD. Six independent genetic loci passed X chromosome-wide significance, with 4 showing support for links between the genetic signal for AD and expression of nearby genes in brain and nonbrain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR, 1.03; 95% CI, 1.02-1.04) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Of these 6 loci, 4 displayed evidence for escape from X chromosome inactivation with regard to AD risk. Conclusion and Relevance This large-scale XWAS of AD identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid β accumulation. Overall, this study advances our knowledge of AD genetics and may provide novel biological drug targets. The results further provide initial insights into elucidating the role of the X chromosome in sex-based differences in AD.
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Affiliation(s)
- Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, Missouri
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Kennedy Williams
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Joachim Herz
- Center for Translational Neurodegeneration Research, Department of Molecular Genetics University of Texas Southwestern Medical Center at Dallas, Dallas
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego, La Jolla
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
| | - Richard L. Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
| | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Mark Logue
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
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8
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Burren OS, Dhindsa RS, Deevi SVV, Wen S, Nag A, Mitchell J, Hu F, Loesch DP, Smith KR, Razdan N, Olsson H, Platt A, Vitsios D, Wu Q, Codd V, Nelson CP, Samani NJ, March RE, Wasilewski S, Carss K, Fabre M, Wang Q, Pangalos MN, Petrovski S. Genetic architecture of telomere length in 462,666 UK Biobank whole-genome sequences. Nat Genet 2024; 56:1832-1840. [PMID: 39192095 PMCID: PMC11387196 DOI: 10.1038/s41588-024-01884-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 07/25/2024] [Indexed: 08/29/2024]
Abstract
Telomeres protect chromosome ends from damage and their length is linked with human disease and aging. We developed a joint telomere length metric, combining quantitative PCR and whole-genome sequencing measurements from 462,666 UK Biobank participants. This metric increased SNP heritability, suggesting that it better captures genetic regulation of telomere length. Exome-wide rare-variant and gene-level collapsing association studies identified 64 variants and 30 genes significantly associated with telomere length, including allelic series in ACD and RTEL1. Notably, 16% of these genes are known drivers of clonal hematopoiesis-an age-related somatic mosaicism associated with myeloid cancers and several nonmalignant diseases. Somatic variant analyses revealed gene-specific associations with telomere length, including lengthened telomeres in individuals with large SRSF2-mutant clones, compared with shortened telomeres in individuals with clonal expansions driven by other genes. Collectively, our findings demonstrate the impact of rare variants on telomere length, with larger effects observed among genes also associated with clonal hematopoiesis.
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Affiliation(s)
- Oliver S Burren
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S Dhindsa
- Center for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Sri V V Deevi
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Sean Wen
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Jonathan Mitchell
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Fengyuan Hu
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Douglas P Loesch
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Katherine R Smith
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Neetu Razdan
- Biosciences COPD & IPF, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Henric Olsson
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Adam Platt
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dimitrios Vitsios
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Qiang Wu
- Center for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN, USA
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester and Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester and Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester and Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Ruth E March
- Precision Medicine & Biosamples, Oncology R&D, AstraZeneca, Dublin, Ireland
| | - Sebastian Wasilewski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Margarete Fabre
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Department of Haematology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Quanli Wang
- Center for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | | | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
- Department of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.
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9
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Tomofuji Y, Edahiro R, Sonehara K, Shirai Y, Kock KH, Wang QS, Namba S, Moody J, Ando Y, Suzuki A, Yata T, Ogawa K, Naito T, Namkoong H, Xuan Lin QX, Buyamin EV, Tan LM, Sonthalia R, Han KY, Tanaka H, Lee H, Okuno T, Liu B, Matsuda K, Fukunaga K, Mochizuki H, Park WY, Yamamoto K, Hon CC, Shin JW, Prabhakar S, Kumanogoh A, Okada Y. Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues. CELL GENOMICS 2024; 4:100625. [PMID: 39084228 PMCID: PMC11406184 DOI: 10.1016/j.xgen.2024.100625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 05/09/2024] [Accepted: 07/05/2024] [Indexed: 08/02/2024]
Abstract
Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood scRNA-seq datasets consistently identified the stronger escape in lymphocytes than in myeloid cells. An extension of scLinaX to a 10x multiome dataset (scLinaX-multi) suggested a stronger escape in lymphocytes than in myeloid cells at the chromatin-accessibility level. The scLinaX analysis of human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes suggested the underlying impact of escape on the genotype-phenotype association. Overall, scLinaX and the quantified escape catalog identified the heterogeneity of escape across cell types and tissues.
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Affiliation(s)
- Yoshihiko Tomofuji
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan.
| | - Ryuya Edahiro
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Yuya Shirai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kian Hong Kock
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Qingbo S Wang
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan
| | - Jonathan Moody
- Laboratory for Genome Information Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Yoshinari Ando
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Akari Suzuki
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Tomohiro Yata
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kotaro Ogawa
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Ho Namkoong
- Department of Infectious Diseases, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Quy Xiao Xuan Lin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Eliora Violain Buyamin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Le Min Tan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Radhika Sonthalia
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore
| | - Kyung Yeon Han
- Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Hiromu Tanaka
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Ho Lee
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Tatsusada Okuno
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Boxiang Liu
- Department of Pharmacy, National University of Singapore, Singapore 117549, Republic of Singapore
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Shirokanedai 108-8639, Japan
| | - Koichi Fukunaga
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinanomachi 160-8582, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Woong-Yang Park
- Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Chung-Chau Hon
- Laboratory for Genome Information Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Jay W Shin
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore; Laboratory for Advanced Genomics Circuit, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Shyam Prabhakar
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore 138672, Republic of Singapore; Lee Kong Chian School of Medicine, Singapore 308232, Republic of Singapore; Cancer Science Institute of Singapore, Singapore 117599, Republic of Singapore
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8654, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan; Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita 565-0871, Japan.
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10
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Neale N, Lona-Durazo F, Ryten M, Gagliano Taliun SA. Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps. Brain Commun 2024; 6:fcae192. [PMID: 38894947 PMCID: PMC11184352 DOI: 10.1093/braincomms/fcae192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 04/11/2024] [Accepted: 05/30/2024] [Indexed: 06/21/2024] Open
Abstract
It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.
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Affiliation(s)
- Nikita Neale
- Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
| | - Frida Lona-Durazo
- Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
- Research Centre, Montreal Heart Institute, Québec, H1T 1C8 Canada
| | - Mina Ryten
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, WC1N 1EH London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, 20815 MD, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, Great Ormond Street Institute of Child Health, Bloomsbury, WC1N 1EH London, UK
| | - Sarah A Gagliano Taliun
- Research Centre, Montreal Heart Institute, Québec, H1T 1C8 Canada
- Department of Medicine & Department of Neurosciences, Faculty of Medicine, Université de Montréal, Québec, H3C 3J7 Canada
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11
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Jiang Z, Sullivan PF, Li T, Zhao B, Wang X, Luo T, Huang S, Guan PY, Chen J, Yang Y, Stein JL, Li Y, Liu D, Sun L, Zhu H. The pivotal role of the X-chromosome in the genetic architecture of the human brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294848. [PMID: 37693466 PMCID: PMC10491353 DOI: 10.1101/2023.08.30.23294848] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Genes on the X-chromosome are extensively expressed in the human brain. However, little is known for the X-chromosome's impact on the brain anatomy, microstructure, and functional network. We examined 1,045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X-chromosome interactions, while proposing an atlas outlining dosage compensation (DC) for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we discovered unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X-chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.
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12
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Farzaneh M, Anbiyaee O, Azizidoost S, Nasrolahi A, Ghaedrahmati F, Kempisty B, Mozdziak P, Khoshnam SE, Najafi S. The Mechanisms of Long Non-coding RNA-XIST in Ischemic Stroke: Insights into Functional Roles and Therapeutic Potential. Mol Neurobiol 2024; 61:2745-2753. [PMID: 37932544 DOI: 10.1007/s12035-023-03740-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 10/18/2023] [Indexed: 11/08/2023]
Abstract
Ischemic stroke, which occurs due to the occlusion of cerebral arteries, is a common type of stroke. Recent research has highlighted the important role of long non-coding RNAs (lncRNAs) in the development of cerebrovascular diseases, specifically ischemic stroke. Understanding the functional roles of lncRNAs in ischemic stroke is crucial, given their potential contribution to the disease pathology. One noteworthy lncRNA is X-inactive specific transcript (XIST), which exhibits downregulation during the early stages of ischemic stroke and subsequent upregulation in later stages. XIST exert its influence on the development of ischemic stroke through interactions with multiple miRNAs and transcription factors. These interactions play a significant role in the pathogenesis of the condition. In this review, we have provided a comprehensive summary of the functional roles of XIST in ischemic stroke. By investigating the involvement of XIST in the disease process, we aim to enhance our understanding of the mechanisms underlying ischemic stroke and potentially identify novel therapeutic targets.
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Affiliation(s)
- Maryam Farzaneh
- Fertility, Infertility and Perinatology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Omid Anbiyaee
- Cardiovascular Research Center, Namazi Hospital, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Shirin Azizidoost
- Atherosclerosis Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Ava Nasrolahi
- Infectious Ophthalmologic Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Farhoodeh Ghaedrahmati
- Department of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Bartosz Kempisty
- Department of Human Morphology and Embryology, Division of Anatomy, Wroclaw Medical University, Wrocław, Poland
- Institute of Veterinary Medicine, Department of Veterinary Surgery, Nicolaus Copernicus University, Torun, Poland
- North Carolina State University College of Agriculture and Life Sciences, Raleigh, NC, 27695, USA
| | - Paul Mozdziak
- North Carolina State University College of Agriculture and Life Sciences, Raleigh, NC, 27695, USA
| | - Seyed Esmaeil Khoshnam
- Persian Gulf Physiology Research Center, Medical Basic Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
| | - Sajad Najafi
- Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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13
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Pottmeier P, Nikolantonaki D, Lanner F, Peuckert C, Jazin E. Sex-biased gene expression during neural differentiation of human embryonic stem cells. Front Cell Dev Biol 2024; 12:1341373. [PMID: 38764741 PMCID: PMC11101176 DOI: 10.3389/fcell.2024.1341373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 04/16/2024] [Indexed: 05/21/2024] Open
Abstract
Sex differences in the developing human brain are primarily attributed to hormonal influence. Recently however, genetic differences and their impact on the developing nervous system have attracted increased attention. To understand genetically driven sexual dimorphisms in neurodevelopment, we investigated genome-wide gene expression in an in vitro differentiation model of male and female human embryonic stem cell lines (hESC), independent of the effects of human sex hormones. Four male and four female-derived hESC lines were differentiated into a population of mixed neurons over 37 days. Differential gene expression and gene set enrichment analyses were conducted on bulk RNA sequencing data. While similar differentiation tendencies in all cell lines demonstrated the robustness and reproducibility of our differentiation protocol, we found sex-biased gene expression already in undifferentiated ESCs at day 0, but most profoundly after 37 days of differentiation. Male and female cell lines exhibited sex-biased expression of genes involved in neurodevelopment, suggesting that sex influences the differentiation trajectory. Interestingly, the highest contribution to sex differences was found to arise from the male transcriptome, involving both Y chromosome and autosomal genes. We propose 13 sex-biased candidate genes (10 upregulated in male cell lines and 3 in female lines) that are likely to affect neuronal development. Additionally, we confirmed gene dosage compensation of X/Y homologs escaping X chromosome inactivation through their Y homologs and identified a significant overexpression of the Y-linked demethylase UTY and KDM5D in male hESC during neuron development, confirming previous results in neural stem cells. Our results suggest that genetic sex differences affect neuronal differentiation trajectories, which could ultimately contribute to sex biases during human brain development.
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Affiliation(s)
- Philipp Pottmeier
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Danai Nikolantonaki
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Fredrik Lanner
- Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Christiane Peuckert
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
- The Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden
| | - Elena Jazin
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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14
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Belloy ME, Guen YL, Stewart I, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, VA Million Veteran Program, Gaziano JM, Logue M, Napolioni V, Greicius MD. The Role of X Chromosome in Alzheimer's Disease Genetics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.22.24306094. [PMID: 38712163 PMCID: PMC11071554 DOI: 10.1101/2024.04.22.24306094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Importance The X chromosome has remained enigmatic in Alzheimer's disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. Objectives Perform the first large-scale X chromosome-wide association study (XWAS) of AD. Primary analyses are non-stratified, while secondary analyses evaluate sex-stratified effects. Design Meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium (ADGC) and Alzheimer's Disease Sequencing Project (ADSP), the UK Biobank (UKB), the Finnish health registry (FinnGen), and the US Million Veterans Program (MVP). Risk for AD evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Setting Genetic data available from high-density single-nucleotide polymorphism (SNP) microarrays and whole-genome sequencing (WGS). Summary statistics for multi-tissue expression and protein quantitative trait loci (QTL) available from published studies, enabling follow-up genetic colocalization analyses. Participants 1,629,863 eligible participants were selected from referred and volunteer samples, of which 477,596 were excluded for analysis exclusion criteria. Number of participants who declined to participate in original studies was not available. Main Outcome and Measures Risk for AD (odds ratio; OR) with 95% confidence intervals (CI). Associations were considered at X-chromosome-wide (P-value<1e-5) and genome-wide (P-value<5e-8) significance. Results Analyses included 1,152,284 non-Hispanic White European ancestry subjects (57.3% females), including 138,558 cases. 6 independent genetic loci passed X-chromosome-wide significance, with 4 showing support for causal links between the genetic signal for AD and expression of nearby genes in brain and non-brain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR=1.054, 95%-CI=[1.035, 1.075]) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Conclusion and Relevance We performed the first large-scale XWAS of AD and identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid beta accumulation. Overall, this study significantly advances our knowledge of AD genetics and may provide novel biological drug targets.
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Affiliation(s)
- Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St.Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St.Louis, MO, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Joachim Herz
- Center for Translational Neurodegeneration Research, Department of Molecular Genetics University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Richard L. Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Logue
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
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15
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Lin B, Paterson AD, Sun L. Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank. PLoS Genet 2024; 20:e1011221. [PMID: 38656964 PMCID: PMC11073786 DOI: 10.1371/journal.pgen.1011221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 05/06/2024] [Accepted: 03/11/2024] [Indexed: 04/26/2024] Open
Abstract
Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.
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Affiliation(s)
- Boxi Lin
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Andrew D. Paterson
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Lei Sun
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
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16
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Muralidhar P, Coop G. Polygenic response of sex chromosomes to sexual antagonism. Evolution 2024; 78:539-554. [PMID: 38153370 PMCID: PMC10903542 DOI: 10.1093/evolut/qpad231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 11/30/2023] [Accepted: 12/22/2023] [Indexed: 12/29/2023]
Abstract
Sexual antagonism occurs when males and females differ in their phenotypic fitness optima but are constrained in their evolution to these optima because of their shared genome. The sex chromosomes, which have distinct evolutionary "interests" relative to the autosomes, are theorized to play an important role in sexually antagonistic conflict. However, the evolutionary responses of sex chromosomes and autosomes have usually been considered independently, that is, via contrasting the response of a gene located on either an X chromosome or an autosome. Here, we study the coevolutionary response of the X chromosome and autosomes to sexually antagonistic selection acting on a polygenic phenotype. We model a phenotype initially under stabilizing selection around a single optimum, followed by a sudden divergence of the male and female optima. We find that, in the absence of dosage compensation, the X chromosome promotes evolution toward the female optimum, inducing coevolutionary male-biased responses on the autosomes. Dosage compensation obscures the female-biased interests of the X, causing it to contribute equally to male and female phenotypic change. We further demonstrate that fluctuations in an adaptive landscape can generate prolonged intragenomic conflict and accentuate the differential responses of the X and autosomes to this conflict.
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Affiliation(s)
- Pavitra Muralidhar
- Center for Population Biology, University of California, Davis, CA, United States
- Department of Evolution and Ecology, University of California, Davis, CA, United States
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States
| | - Graham Coop
- Center for Population Biology, University of California, Davis, CA, United States
- Department of Evolution and Ecology, University of California, Davis, CA, United States
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17
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Borbye-Lorenzen N, Zhu Z, Agerbo E, Albiñana C, Benros ME, Bian B, Børglum AD, Bulik CM, Debost JCPG, Grove J, Hougaard DM, McRae AF, Mors O, Mortensen PB, Musliner KL, Nordentoft M, Petersen LV, Privé F, Sidorenko J, Skogstrand K, Werge T, Wray NR, Vilhjálmsson BJ, McGrath JJ. The correlates of neonatal complement component 3 and 4 protein concentrations with a focus on psychiatric and autoimmune disorders. CELL GENOMICS 2023; 3:100457. [PMID: 38116117 PMCID: PMC10726496 DOI: 10.1016/j.xgen.2023.100457] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 09/03/2023] [Accepted: 11/08/2023] [Indexed: 12/21/2023]
Abstract
Complement components have been linked to schizophrenia and autoimmune disorders. We examined the association between neonatal circulating C3 and C4 protein concentrations in 68,768 neonates and the risk of six mental disorders. We completed genome-wide association studies (GWASs) for C3 and C4 and applied the summary statistics in Mendelian randomization and phenome-wide association studies related to mental and autoimmune disorders. The GWASs for C3 and C4 protein concentrations identified 15 and 36 independent loci, respectively. We found no associations between neonatal C3 and C4 concentrations and mental disorders in the total sample (both sexes combined); however, post-hoc analyses found that a higher C3 concentration was associated with a reduced risk of schizophrenia in females. Mendelian randomization based on C4 summary statistics found an altered risk of five types of autoimmune disorders. Our study adds to our understanding of the associations between C3 and C4 concentrations and subsequent mental and autoimmune disorders.
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Affiliation(s)
- Nis Borbye-Lorenzen
- Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Zhihong Zhu
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark.
| | - Esben Agerbo
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Center for Integrated Register-based Research, Aarhus University, CIRRAU, 8210 Aarhus V, Denmark
| | - Clara Albiñana
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark
| | - Michael E Benros
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Hellerup, Denmark; Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Beilei Bian
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Department of Biomedicine and the iSEQ Center, Aarhus University, Aarhus, Denmark; Center for Genomics and Personalized Medicine, CGPM, Aarhus, Denmark
| | - Cynthia M Bulik
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jean-Christophe Philippe Goldtsche Debost
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; Department of Psychosis, Aarhus University Hospital Skejby, Aarhus Nord, Denmark
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Center for Genomics and Personalized Medicine, CGPM, Aarhus, Denmark; Department of Biomedicine (Human Genetics), Aarhus University, Aarhus, Denmark; Bioinformatics Research Center, Aarhus University, 8000 Aarhus C, Denmark
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen S, Denmark
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
| | - Preben Bo Mortensen
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Center for Integrated Register-based Research, Aarhus University, CIRRAU, 8210 Aarhus V, Denmark
| | - Katherine L Musliner
- Department of Affective Disorders, Aarhus University and Aarhus University Hospital -Psychiatry, Aarhus, Denmark
| | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Mental Health Services in the Capital Region of Denmark, Mental Health Center Copenhagen, University of Copenhagen, 2100 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Liselotte V Petersen
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
| | - Florian Privé
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
| | - Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Kristin Skogstrand
- Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen N, Denmark; Department of Clinical Medicine, Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, University of Copenhagen, 2200 Copenhagen N, Denmark; Lundbeck Center for Geogenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia; Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; Big Data Institute, University of Oxford, Oxford OX3 7LF, UK
| | - Bjarni J Vilhjálmsson
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus V, Denmark; Bioinformatics Research Center, Aarhus University, 8000 Aarhus C, Denmark
| | - John J McGrath
- National Center for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark; Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia; Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Brisbane, QLD 4076, Australia.
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18
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Gouveia GC, Ribeiro VMP, Fortes MRS, Raidan FSS, Reverter A, Porto-Neto LR, Moraes MMD, Gonçalves DR, Silva MVGBD, Toral FLB. Unravelling the genetic variability of host resilience to endo- and ectoparasites in Nellore commercial herds. Genet Sel Evol 2023; 55:81. [PMID: 37990289 PMCID: PMC10664541 DOI: 10.1186/s12711-023-00844-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 09/19/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Host resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR. RESULTS Posterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium. CONCLUSIONS Selection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.
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Affiliation(s)
- Gabriela Canabrava Gouveia
- Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Marina Rufino Salinas Fortes
- School of Chemistry and Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia
| | - Fernanda Santos Silva Raidan
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organization (CSIRO), Brisbane, QLD, Australia
- Swine Business Unit, Hendrix Genetics, 5831 CK, Boxmeer, The Netherlands
| | - Antonio Reverter
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organization (CSIRO), Brisbane, QLD, Australia
| | - Laercio Ribeiro Porto-Neto
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organization (CSIRO), Brisbane, QLD, Australia
| | - Mariana Mamedes de Moraes
- Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | | | - Fabio Luiz Buranelo Toral
- Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
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19
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Sánchez-Valle J, Valencia A. Molecular bases of comorbidities: present and future perspectives. Trends Genet 2023; 39:773-786. [PMID: 37482451 DOI: 10.1016/j.tig.2023.06.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023]
Abstract
Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health records present a complex scenario of comorbidity relationships that vary by age, sex, and cohort under study. The study of similarities between diseases using 'omics data, such as genes altered in diseases, gene expression, proteome, and microbiome, are fundamental to uncovering the origin of, and potential treatment for, comorbidities. Recent studies have produced a first generation of genetic interpretations for as much as 46% of the comorbidities described in large cohorts. Integrating different sources of molecular information and using artificial intelligence (AI) methods are promising approaches for the study of comorbidities. They may help to improve the treatment of comorbidities, including the potential repositioning of drugs.
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Affiliation(s)
- Jon Sánchez-Valle
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain.
| | - Alfonso Valencia
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain; ICREA, Barcelona, 08010, Spain.
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20
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Campos AI, Namba S, Lin SC, Nam K, Sidorenko J, Wang H, Kamatani Y, Wang LH, Lee S, Lin YF, Feng YCA, Okada Y, Visscher PM, Yengo L. Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores. Nat Genet 2023; 55:1769-1776. [PMID: 37723263 DOI: 10.1038/s41588-023-01500-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 08/14/2023] [Indexed: 09/20/2023]
Abstract
Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.
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Affiliation(s)
- Adrian I Campos
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Shu-Chin Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Kisung Nam
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Huanwei Wang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Ling-Hua Wang
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Yen-Chen Anne Feng
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan
- Division of Biostatistics and Data Science, Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
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21
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Wang H, Makowski C, Zhang Y, Qi A, Kaufmann T, Smeland OB, Fiecas M, Yang J, Visscher PM, Chen CH. Chromosomal inversion polymorphisms shape human brain morphology. Cell Rep 2023; 42:112896. [PMID: 37505983 PMCID: PMC10508191 DOI: 10.1016/j.celrep.2023.112896] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/27/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.
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Affiliation(s)
- Hao Wang
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Anna Qi
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Tobias Kaufmann
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, 72076 Tübingen, Germany; Norwegian Centre for Mental Disorders Research, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway
| | - Mark Fiecas
- Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, MN 55455, USA
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Chi-Hua Chen
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA.
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22
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Abstract
10 years ago, a detailed analysis showed that only 33% of genome-wide association study (GWAS) results included the X chromosome. Multiple recommendations were made to combat such exclusion. Here, we re-surveyed the research landscape to determine whether these earlier recommendations had been translated. Unfortunately, among the genome-wide summary statistics reported in 2021 in the NHGRI-EBI GWAS Catalog, only 25% provided results for the X chromosome and 3% for the Y chromosome, suggesting that the exclusion phenomenon not only persists but has also expanded into an exclusionary problem. Normalizing by physical length of the chromosome, the average number of studies published through November 2022 with genome-wide-significant findings on the X chromosome is ∼1 study/Mb. By contrast, it ranges from ∼6 to ∼16 studies/Mb for chromosomes 4 and 19, respectively. Compared with the autosomal growth rate of ∼0.086 studies/Mb/year over the last decade, studies of the X chromosome grew at less than one-seventh that rate, only ∼0.012 studies/Mb/year. Among the studies that reported significant associations on the X chromosome, we noted extreme heterogeneities in data analysis and reporting of results, suggesting the need for clear guidelines. Unsurprisingly, among the 430 scores sampled from the PolyGenic Score Catalog, 0% contained weights for sex chromosomal SNPs. To overcome the dearth of sex chromosome analyses, we provide five sets of recommendations and future directions. Finally, until the sex chromosomes are included in a whole-genome study, instead of GWASs, we propose such studies would more properly be referred to as "AWASs," meaning "autosome-wide scans."
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Affiliation(s)
- Lei Sun
- Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, ON, Canada; Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
| | - Zhong Wang
- Department of Statistics and Data Science, Faculty of Science, National University of Singapore, Singapore
| | - Tianyuan Lu
- Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, ON, Canada; Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
| | - Teri A Manolio
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Andrew D Paterson
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
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23
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Khramtsova EA, Wilson MA, Martin J, Winham SJ, He KY, Davis LK, Stranger BE. Quality control and analytic best practices for testing genetic models of sex differences in large populations. Cell 2023; 186:2044-2061. [PMID: 37172561 PMCID: PMC10266536 DOI: 10.1016/j.cell.2023.04.014] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 01/31/2023] [Accepted: 04/07/2023] [Indexed: 05/15/2023]
Abstract
Phenotypic sex-based differences exist for many complex traits. In other cases, phenotypes may be similar, but underlying biology may vary. Thus, sex-aware genetic analyses are becoming increasingly important for understanding the mechanisms driving these differences. To this end, we provide a guide outlining the current best practices for testing various models of sex-dependent genetic effects in complex traits and disease conditions, noting that this is an evolving field. Insights from sex-aware analyses will not only teach us about the biology of complex traits but also aid in achieving the goals of precision medicine and health equity for all.
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Affiliation(s)
- Ekaterina A Khramtsova
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA.
| | - Melissa A Wilson
- School of Life Sciences, Center for Evolution and Medicine, Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85282, USA
| | - Joanna Martin
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Stacey J Winham
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN, USA
| | - Karen Y He
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Barbara E Stranger
- Center for Genetic Medicine, Department of Pharmacology, Northwestern University, Chicago, IL, USA.
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24
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Romanowska J, Nustad HE, Page CM, Denault WRP, Lee Y, Magnus MC, Haftorn KL, Gjerdevik M, Novakovic B, Saffery R, Gjessing HK, Lyle R, Magnus P, Håberg SE, Jugessur A. The X-factor in ART: does the use of assisted reproductive technologies influence DNA methylation on the X chromosome? Hum Genomics 2023; 17:35. [PMID: 37085889 PMCID: PMC10122315 DOI: 10.1186/s40246-023-00484-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 04/10/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Assisted reproductive technologies (ART) may perturb DNA methylation (DNAm) in early embryonic development. Although a handful of epigenome-wide association studies of ART have been published, none have investigated CpGs on the X chromosome. To bridge this knowledge gap, we leveraged one of the largest collections of mother-father-newborn trios of ART and non-ART (natural) conceptions to date to investigate sex-specific DNAm differences on the X chromosome. The discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). To verify our results from the MoBa cohort, we used an external cohort of 149 ART and 58 non-ART neonates from the Australian 'Clinical review of the Health of adults conceived following Assisted Reproductive Technologies' (CHART) study. The Illumina EPIC array was used to measure DNAm in both datasets. In the MoBa cohort, we performed a set of X-chromosome-wide association studies ('XWASs' hereafter) to search for sex-specific DNAm differences between ART and non-ART newborns. We tested several models to investigate the influence of various confounders, including parental DNAm. We also searched for differentially methylated regions (DMRs) and regions of co-methylation flanking the most significant CpGs. Additionally, we ran an analogous model to our main model on the external CHART dataset. RESULTS In the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted after controlling for parental DNAm and other confounders. Many of the significant CpGs and DMRs were in gene-promoter regions, and several of the genes linked to these CpGs are expressed in tissues relevant for both ART and sex (testis, placenta, and fallopian tube). We found no support for parental DNAm-dependent features as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was in UBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were in EIF2S3 and AMOT. These three loci also displayed differential DNAm in the CHART cohort. CONCLUSIONS Genes that co-localized with the significant CpGs and DMRs associated with ART are implicated in several key biological processes (e.g., neurodevelopment) and disorders (e.g., intellectual disability and autism). These connections are particularly compelling in light of previous findings indicating that neurodevelopmental outcomes differ in ART-conceived children compared to those naturally conceived.
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Affiliation(s)
- Julia Romanowska
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
| | - Haakon E Nustad
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- DeepInsight, 0154, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - William R P Denault
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Kristine L Haftorn
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Miriam Gjerdevik
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Boris Novakovic
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Håkon K Gjessing
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Robert Lyle
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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25
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Bölte S, Neufeld J, Marschik PB, Williams ZJ, Gallagher L, Lai MC. Sex and gender in neurodevelopmental conditions. Nat Rev Neurol 2023; 19:136-159. [PMID: 36747038 PMCID: PMC10154737 DOI: 10.1038/s41582-023-00774-6] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2023] [Indexed: 02/08/2023]
Abstract
Health-related conditions often differ qualitatively or quantitatively between individuals of different birth-assigned sexes and gender identities, and/or with different gendered experiences, requiring tailored care. Studying the moderating and mediating effects of sex-related and gender-related factors on impairment, disability, wellbeing and health is of paramount importance especially for neurodivergent individuals, who are diagnosed with neurodevelopmental conditions with uneven sex/gender distributions. Researchers have become aware of the myriad influences that sex-related and gender-related variables have on the manifestations of neurodevelopmental conditions, and contemporary work has begun to investigate the mechanisms through which these effects are mediated. Here we describe topical concepts of sex and gender science, summarize current knowledge, and discuss research and clinical challenges related to autism, attention-deficit/hyperactivity disorder and other neurodevelopmental conditions. We consider sex and gender in the context of epidemiology, behavioural phenotypes, neurobiology, genetics, endocrinology and neighbouring disciplines. The available evidence supports the view that sex and gender are important contributors to the biological and behavioural variability in neurodevelopmental conditions. Methodological caveats such as frequent conflation of sex and gender constructs, inappropriate measurement of these constructs and under-representation of specific demographic groups (for example, female and gender minority individuals and people with intellectual disabilities) limit the translational potential of research so far. Future research and clinical implementation should integrate sex and gender into next-generation diagnostics, mechanistic investigations and support practices.
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Affiliation(s)
- Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, WA, Australia.
| | - Janina Neufeld
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Swedish Collegium for Advanced Study (SCAS), Uppsala, Sweden
| | - Peter B Marschik
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen and Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
- iDN - interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria
| | - Zachary J Williams
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN, USA
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
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26
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Landen S, Hiam D, Voisin S, Jacques M, Lamon S, Eynon N. Physiological and molecular sex differences in human skeletal muscle in response to exercise training. J Physiol 2023; 601:419-434. [PMID: 34762308 DOI: 10.1113/jp279499] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/01/2021] [Indexed: 02/04/2023] Open
Abstract
Sex differences in exercise physiology, such as substrate metabolism and skeletal muscle fatigability, stem from inherent biological factors, including endogenous hormones and genetics. Studies investigating exercise physiology frequently include only males or do not take sex differences into consideration. Although there is still an underrepresentation of female participants in exercise research, existing studies have identified sex differences in physiological and molecular responses to exercise training. The observed sex differences in exercise physiology are underpinned by the sex chromosome complement, sex hormones and, on a molecular level, the epigenome and transcriptome. Future research in the field should aim to include both sexes, control for menstrual cycle factors, conduct large-scale and ethnically diverse studies, conduct meta-analyses to consolidate findings from various studies, leverage unique cohorts (such as post-menopausal, transgender, and those with sex chromosome abnormalities), as well as integrate tissue and cell-specific -omics data. This knowledge is essential for developing deeper insight into sex-specific physiological responses to exercise training, thus directing future exercise physiology studies and practical application.
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Affiliation(s)
- Shanie Landen
- Institute for Health and Sport (iHeS), Victoria University, Melbourne, Australia
| | - Danielle Hiam
- Institute for Health and Sport (iHeS), Victoria University, Melbourne, Australia.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Melbourne, Australia
| | - Macsue Jacques
- Institute for Health and Sport (iHeS), Victoria University, Melbourne, Australia
| | - Séverine Lamon
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Nir Eynon
- Institute for Health and Sport (iHeS), Victoria University, Melbourne, Australia
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27
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Dorak MT. Sexual dimorphism in molecular biology of cancer. PRINCIPLES OF GENDER-SPECIFIC MEDICINE 2023:463-476. [DOI: 10.1016/b978-0-323-88534-8.00003-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
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28
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Li J, Ming Z, Yang L, Wang T, Liu G, Ma Q. Long noncoding RNA XIST: Mechanisms for X chromosome inactivation, roles in sex-biased diseases, and therapeutic opportunities. Genes Dis 2022; 9:1478-1492. [PMID: 36157489 PMCID: PMC9485286 DOI: 10.1016/j.gendis.2022.04.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 04/16/2022] [Accepted: 04/18/2022] [Indexed: 11/30/2022] Open
Abstract
Sexual dimorphism has been reported in various human diseases including autoimmune diseases, neurological diseases, pulmonary arterial hypertension, and some types of cancers, although the underlying mechanisms remain poorly understood. The long noncoding RNA (lncRNA) X-inactive specific transcript (XIST) is involved in X chromosome inactivation (XCI) in female placental mammals, a process that ensures the balanced expression dosage of X-linked genes between sexes. XIST is abnormally expressed in many sex-biased diseases. In addition, escape from XIST-mediated XCI and skewed XCI also contribute to sex-biased diseases. Therefore, its expression or modification can be regarded as a biomarker for the diagnosis and prognosis of many sex-biased diseases. Genetic manipulation of XIST expression can inhibit the progression of some of these diseases in animal models, and therefore XIST has been proposed as a potential therapeutic target. In this manuscript, we summarize the current knowledge about the mechanisms for XIST-mediated XCI and the roles of XIST in sex-biased diseases, and discuss potential therapeutic strategies targeting XIST.
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29
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Vaura F, Palmu J, Aittokallio J, Kauko A, Niiranen T. Genetic, Molecular, and Cellular Determinants of Sex-Specific Cardiovascular Traits. Circ Res 2022; 130:611-631. [PMID: 35175841 DOI: 10.1161/circresaha.121.319891] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Despite the well-known sex dimorphism in cardiovascular disease traits, the exact genetic, molecular, and cellular underpinnings of these differences are not well understood. A growing body of evidence currently points at the links between cardiovascular disease traits and the genome, epigenome, transcriptome, and metabolome. However, the sex-specific differences in these links remain largely unstudied due to challenges in bioinformatic methods, inadequate statistical power, analytic costs, and paucity of valid experimental models. This review article provides an overview of the literature on sex differences in genetic architecture, heritability, epigenetic changes, transcriptomic signatures, and metabolomic profiles in relation to cardiovascular disease traits. We also review the literature on the associations between sex hormones and cardiovascular disease traits and discuss the potential mechanisms underlying these associations, focusing on human studies.
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Affiliation(s)
- Felix Vaura
- Department of Internal Medicine (F.V., J.P., A.K., T.N.), University of Turku, Finland
| | - Joonatan Palmu
- Department of Internal Medicine (F.V., J.P., A.K., T.N.), University of Turku, Finland
| | - Jenni Aittokallio
- Department of Anesthesiology and Intensive Care (J.A.), University of Turku, Finland.,Division of Perioperative Services, Intensive Care and Pain Medicine (J.A.), Turku University Hospital, Finland
| | - Anni Kauko
- Department of Internal Medicine (F.V., J.P., A.K., T.N.), University of Turku, Finland
| | - Teemu Niiranen
- Department of Internal Medicine (F.V., J.P., A.K., T.N.), University of Turku, Finland.,Division of Medicine (T.N.), Turku University Hospital, Finland.,Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (T.N.)
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30
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Blomquist GE, Hinde K, Capitanio JP. Inheritance of hormonal stress response and temperament in infant rhesus macaques (Macaca Mulatta): Nonadditive and sex-specific effects. Behav Neurosci 2022; 136:61-71. [PMID: 34516165 PMCID: PMC9373718 DOI: 10.1037/bne0000493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Early life interindividual variation in hypothalamic-pituitary-adrenal (HPA) reactivity to stress is predictive of later life psychological and physical well-being, including the development of many pathological syndromes that are often sex-biased. A complex and interactive set of environmental and genetic causes for such variation has been implicated by previous studies, though little attention has been paid to nonadditive effects (e.g. dominance, X-linked) or sex-specific genetic effects. METHOD We used a large pedigreed sample of captive 3-4 months old infant rhesus macaques (N = 2,661, 54% female) to fit univariate and multivariate linear mixed quantitative genetic models for four longitudinal blood cortisol samples and three reliable ratings of infant temperament (nervousness, gentleness, confidence) during a mother-infant separation protocol. RESULTS Each trait had a moderate narrow-sense heritability (h², 0.26-0.46), but dominance effects caused the first two cortisol samples to have much larger broad-sense heritabilities (H², 0.57 and 0.77). We found no evidence for X-linked variance or common maternal environment variance. There was a sex difference in heritability of the first cortisol sample (hf² < hm²), suggesting differing genetic architecture of perception of maternal separation and relocation during infancy. Otherwise, genetic covariance matrices for the sexes were very similar. Genetic correlations between cortisol levels and temperament were weak (< |0.4|) but stronger than residual or phenotypic correlations. CONCLUSIONS HPA reactivity and temperament had a primarily additive genetic basis in infant macaques, but there were important complexities to the genetic architecture of including genetic dominance and sex differences in heritability at this early life stage. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Gregory E. Blomquist
- Corresponding author contact information: 112 Swallow Hall, Department of Anthropology, University of Missouri, Columbia, MO 65211, 573-882-4731,
| | - Katie Hinde
- School of Human Evolution and Social Change, Arizona State University
| | - John P. Capitanio
- California National Primate Research Center and Department of Psychology, University of California, Davis
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31
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Ruzicka F, Connallon T, Reuter M. Sex differences in deleterious mutational effects in Drosophila melanogaster: combining quantitative and population genetic insights. Genetics 2021; 219:6362879. [PMID: 34740242 DOI: 10.1093/genetics/iyab143] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 08/25/2021] [Indexed: 11/14/2022] Open
Abstract
Fitness effects of deleterious mutations can differ between females and males due to: (i) sex differences in the strength of purifying selection; and (ii) sex differences in ploidy. Although sex differences in fitness effects have important broader implications (e.g., for the evolution of sex and lifespan), few studies have quantified their scope. Those that have belong to one of two distinct empirical traditions: (i) quantitative genetics, which focusses on multi-locus genetic variances in each sex, but is largely agnostic about their genetic basis; and (ii) molecular population genetics, which focusses on comparing autosomal and X-linked polymorphism, but is poorly suited for inferring contemporary sex differences. Here, we combine both traditions to present a comprehensive analysis of female and male adult reproductive fitness among 202 outbred, laboratory-adapted, hemiclonal genomes of Drosophila melanogaster. While we find no clear evidence for sex differences in the strength of purifying selection, sex differences in ploidy generate multiple signals of enhanced purifying selection for X-linked loci. These signals are present in quantitative genetic metrics-i.e., a disproportionate contribution of the X to male (but not female) fitness variation-and population genetic metrics-i.e., steeper regressions of an allele's average fitness effect on its frequency, and proportionally less nonsynonymous polymorphism on the X than autosomes. Fitting our data to models for both sets of metrics, we infer that deleterious alleles are partially recessive. Given the often-large gap between quantitative and population genetic estimates of evolutionary parameters, our study showcases the benefits of combining genomic and fitness data when estimating such parameters.
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Affiliation(s)
- Filip Ruzicka
- School of Biological Sciences and Centre for Geometric Biology, Monash University, Clayton 3800, VIC, Australia.,Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK
| | - Tim Connallon
- School of Biological Sciences and Centre for Geometric Biology, Monash University, Clayton 3800, VIC, Australia
| | - Max Reuter
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK.,Centre for Life's Origins and Evolution, University College London, London WC1E 6BT, UK
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32
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Landen S, Jacques M, Hiam D, Alvarez-Romero J, Harvey NR, Haupt LM, Griffiths LR, Ashton KJ, Lamon S, Voisin S, Eynon N. Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism. Clin Epigenetics 2021; 13:202. [PMID: 34732242 PMCID: PMC8567658 DOI: 10.1186/s13148-021-01188-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 10/19/2021] [Indexed: 12/29/2022] Open
Abstract
Nearly all human complex traits and diseases exhibit some degree of sex differences, with epigenetics being one of the main contributing factors. Various tissues display sex differences in DNA methylation; however, this has not yet been explored in skeletal muscle, despite skeletal muscle being among the tissues with the most transcriptomic sex differences. For the first time, we investigated the effect of sex on autosomal DNA methylation in human skeletal muscle across three independent cohorts (Gene SMART, FUSION, and GSE38291) using a meta-analysis approach, totalling 369 human muscle samples (222 males and 147 females), and integrated this with known sex-biased transcriptomics. We found 10,240 differentially methylated regions (DMRs) at FDR < 0.005, 94% of which were hypomethylated in males, and gene set enrichment analysis revealed that differentially methylated genes were involved in muscle contraction and substrate metabolism. We then investigated biological factors underlying DNA methylation sex differences and found that circulating hormones were not associated with differential methylation at sex-biased DNA methylation loci; however, these sex-specific loci were enriched for binding sites of hormone-related transcription factors (with top TFs including androgen (AR), estrogen (ESR1), and glucocorticoid (NR3C1) receptors). Fibre type proportions were associated with differential methylation across the genome, as well as across 16% of sex-biased DNA methylation loci (FDR < 0.005). Integration of DNA methylomic results with transcriptomic data from the GTEx database and the FUSION cohort revealed 326 autosomal genes that display sex differences at both the epigenome and transcriptome levels. Importantly, transcriptional sex-biased genes were overrepresented among epigenetic sex-biased genes (p value = 4.6e−13), suggesting differential DNA methylation and gene expression between male and female muscle are functionally linked. Finally, we validated expression of three genes with large effect sizes (FOXO3A, ALDH1A1, and GGT7) in the Gene SMART cohort with qPCR. GGT7, involved in antioxidant metabolism, displays male-biased expression as well as lower methylation in males across the three cohorts. In conclusion, we uncovered 8420 genes that exhibit DNA methylation differences between males and females in human skeletal muscle that may modulate mechanisms controlling muscle metabolism and health.
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Affiliation(s)
- Shanie Landen
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia
| | - Macsue Jacques
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia
| | - Danielle Hiam
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Javier Alvarez-Romero
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia
| | - Nicholas R Harvey
- Faculty of Health Sciences and Medicine, Bond University, Gold Coast, QLD, 4226, Australia.,Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Larisa M Haupt
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Lyn R Griffiths
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), 60 Musk Ave., Kelvin Grove, QLD, 4059, Australia
| | - Kevin J Ashton
- Faculty of Health Sciences and Medicine, Bond University, Gold Coast, QLD, 4226, Australia
| | - Séverine Lamon
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia
| | - Nir Eynon
- Institute for Health and Sport (iHeS), Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia.
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Davis EJ, Solsberg CW, White CC, Miñones-Moyano E, Sirota M, Chibnik L, Bennett DA, De Jager PL, Yokoyama JS, Dubal DB. Sex-Specific Association of the X Chromosome With Cognitive Change and Tau Pathology in Aging and Alzheimer Disease. JAMA Neurol 2021; 78:1249-1254. [PMID: 34424272 PMCID: PMC8383157 DOI: 10.1001/jamaneurol.2021.2806] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 06/25/2021] [Indexed: 12/28/2022]
Abstract
Importance The X chromosome represents 5% of the human genome in women and men, and its influence on cognitive aging and Alzheimer disease (AD) is largely unknown. Objective To determine whether the X chromosome is associated with sex-specific cognitive change and tau pathology in aging and AD. Design, Setting, Participants This study examined differential gene expression profiling of the X chromosome from an RNA sequencing data set of the dorsolateral prefrontal cortex obtained from autopsied, elderly individuals enrolled in the Religious Orders Study and Rush Memory and Aging Project joint cohorts. Samples were collected from the cohort study with enrollment from 1994 to 2017. Data were last analyzed in May 2021. Main Outcomes and Measures The main analysis examined whether X chromosome gene expression measured by RNA sequencing of the dorsolateral prefrontal cortex was associated with cognitive change during aging and AD, independent of AD pathology and at the transcriptome-wide level in women and men. Whether X chromosome gene expression was associated with neurofibrillary tangle burden, a measure of tau pathology that influences cognition, in women and men was also explored. Results Samples for RNA sequencing of the dorsolateral prefrontal cortex were obtained from 508 individuals (mean [SD] age at death, 88.4 [6.6] years; 315 [62.0%] were female; 197 [38.8%] had clinical diagnosis of AD at death; 293 [58.2%] had pathological diagnosis of AD at death) enrolled in the Religious Orders Study and Rush Memory and Aging Project joint cohorts and were followed up annually for a mean (SD) of 6.3 (3.9) years. X chromosome gene expression (29 genes), adjusted for age at death, education, and AD pathology, was significantly associated with cognitive change at the genome-wide level in women but not men. In the majority of identified X genes (19 genes), increased expression was associated with slower cognitive decline in women. In contrast with cognition, X chromosome gene expression (3 genes), adjusted for age at death and education, was associated with neuropathological tau burden at the genome-wide level in men but not women. Conclusions and Relevance In this study, the X chromosome was associated with cognitive trajectories and neuropathological tau burden in aging and AD in a sex-specific manner. This is important because specific X chromosome factors could contribute risk or resilience to biological pathways of aging and AD in women, men, or both.
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Affiliation(s)
- Emily J. Davis
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco
| | - Caroline W. Solsberg
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Pharmaceutical Sciences and Pharmacogenetics Graduate Program, University of California, San Francisco, San Francisco
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco
- Memory and Aging Center, University of California, San Francisco, San Francisco
| | - Charles C. White
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York
| | - Elena Miñones-Moyano
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco
- Department of Pediatrics, University of California, San Francisco, San Francisco
| | - Lori Chibnik
- Biostatistics Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Philip L. De Jager
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York
| | - Jennifer S. Yokoyama
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Memory and Aging Center, University of California, San Francisco, San Francisco
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco
| | - Dena B. Dubal
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco
- Associate Editor, JAMA Neurology
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34
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Sauteraud R, Stahl JM, James J, Englebright M, Chen F, Zhan X, Carrel L, Liu DJ. Inferring genes that escape X-Chromosome inactivation reveals important contribution of variable escape genes to sex-biased diseases. Genome Res 2021; 31:1629-1637. [PMID: 34426515 PMCID: PMC8415373 DOI: 10.1101/gr.275677.121] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/23/2021] [Indexed: 01/07/2023]
Abstract
The X Chromosome plays an important role in human development and disease. However, functional genomic and disease association studies of X genes greatly lag behind autosomal gene studies, in part owing to the unique biology of X-Chromosome inactivation (XCI). Because of XCI, most genes are only expressed from one allele. Yet, ∼30% of X genes “escape” XCI and are transcribed from both alleles, many only in a proportion of the population. Such interindividual differences are likely to be disease relevant, particularly for sex-biased disorders. To understand the functional biology for X-linked genes, we developed X-Chromosome inactivation for RNA-seq (XCIR), a novel approach to identify escape genes using bulk RNA-seq data. Our method, available as an R package, is more powerful than alternative approaches and is computationally efficient to handle large population-scale data sets. Using annotated XCI states, we examined the contribution of X-linked genes to the disease heritability in the United Kingdom Biobank data set. We show that escape and variable escape genes explain the largest proportion of X heritability, which is in large part attributable to X genes with Y homology. Finally, we investigated the role of each XCI state in sex-biased diseases and found that although XY homologous gene pairs have a larger overall effect size, enrichment for variable escape genes is significantly increased in female-biased diseases. Our results, for the first time, quantitate the importance of variable escape genes for the etiology of sex-biased disease, and our pipeline allows analysis of larger data sets for a broad range of phenotypes.
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Affiliation(s)
- Renan Sauteraud
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Jill M Stahl
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Jesica James
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Marisa Englebright
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Fang Chen
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA.,Institute for Personalized Medicine, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Xiaowei Zhan
- Department of Clinical Science, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390-8821, USA
| | - Laura Carrel
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA.,Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA.,Institute for Personalized Medicine, Penn State College of Medicine, Hershey, Pennsylvania 17033, USA
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35
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The genetic architecture of primary biliary cholangitis. Eur J Med Genet 2021; 64:104292. [PMID: 34303876 DOI: 10.1016/j.ejmg.2021.104292] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 07/03/2021] [Accepted: 07/21/2021] [Indexed: 12/12/2022]
Abstract
Primary biliary cholangitis (PBC) is a rare autoimmune disease of the liver affecting the small bile ducts. From a genetic point of view, PBC is a complex trait and several genetic and environmental factors have been called in action to explain its etiopathogenesis. Similarly to other complex traits, PBC has benefited from the introduction of genome-wide association studies (GWAS), which identified many variants predisposing or protecting toward the development of the disease. While a progressive endeavour toward the characterization of candidate loci and downstream pathways is currently ongoing, there is still a relatively large portion of heritability of PBC to be revealed. In addition, genetic variation behind progression of the disease and therapeutic response are mostly to be investigated yet. This review outlines the state-of-the-art regarding the genetic architecture of PBC and provides some hints for future investigations, focusing on the study of gene-gene interactions, the application of whole-genome sequencing techniques, and the investigation of X chromosome that can be helpful to cover the missing heritability gap in PBC.
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36
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Effect of genomic X-chromosome regions on Nelore bull fertility. J Appl Genet 2021; 62:655-659. [PMID: 34145524 DOI: 10.1007/s13353-021-00645-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 06/07/2021] [Accepted: 06/10/2021] [Indexed: 10/21/2022]
Abstract
Scrotal circumference (SC) is a commonly used trait related to sexual precocity in bulls. Genome-wide association studies have uncovered a lot of genes related to this trait, however, only those present on autosomes. The inclusion of the second biggest chromosome (BTAX) can improve the knowledge of the genetic architecture of this trait. In this study, we performed a weighted, single-step, genome-wide association study using a 777 k BovineHD BeadChip (IllumHD) to analyze the association between SNPs and SC in Brazilian Nelore cattle. Phenotypes from 79,300 males and 3263 genotypes (2017 from females and 1246 from males)-(39,367 SNPs markers located at ChrX) were used. We identified eight regions on chromosome X that displayed important associations with SC. The results showed that together the genomic windows explained 28.52% of the genetic variance for the examined trait. Genes with potential functions in reproduction and fertility regulation were highlighted as candidates for sexual precocity rates in Nelore cattle (AFF2 and PJA1). Moreover, we found 10 genes that had not previously been identified as being associated with sexual precocity traits in cattle. These findings will further advance our understanding of the genetic architecture, considering mainly the presence of the chromosome X, for indicine cattle reproductive traits, being useful in the context of genomic prediction in beef cattle.
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37
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Chen SY, Freitas PHF, Oliveira HR, Lázaro SF, Huang YJ, Howard JT, Gu Y, Schinckel AP, Brito LF. Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms. Genet Sel Evol 2021; 53:51. [PMID: 34139991 PMCID: PMC8212483 DOI: 10.1186/s12711-021-00645-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 06/07/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait. RESULTS The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs. CONCLUSIONS We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.
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Affiliation(s)
- Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, 611130 Sichuan China
| | - Pedro H. F. Freitas
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1 Canada
| | - Sirlene F. Lázaro
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
- Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, SP 14884-900 Brazil
| | | | | | - Youping Gu
- Smithfield Premium Genetics, Rose Hill, NC USA
| | - Allan P. Schinckel
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 USA
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38
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Wang W, Min L, Qiu X, Wu X, Liu C, Ma J, Zhang D, Zhu L. Biological Function of Long Non-coding RNA (LncRNA) Xist. Front Cell Dev Biol 2021; 9:645647. [PMID: 34178980 PMCID: PMC8222981 DOI: 10.3389/fcell.2021.645647] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/12/2021] [Indexed: 12/24/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) regulate gene expression in a variety of ways at epigenetic, chromatin remodeling, transcriptional, and translational levels. Accumulating evidence suggests that lncRNA X-inactive specific transcript (lncRNA Xist) serves as an important regulator of cell growth and development. Despites its original roles in X-chromosome dosage compensation, lncRNA Xist also participates in the development of tumor and other human diseases by functioning as a competing endogenous RNA (ceRNA). In this review, we comprehensively summarized recent progress in understanding the cellular functions of lncRNA Xist in mammalian cells and discussed current knowledge regarding the ceRNA network of lncRNA Xist in various diseases. Long non-coding RNAs (lncRNAs) are transcripts that are more than 200 nt in length and without an apparent protein-coding capacity (Furlan and Rougeulle, 2016; Maduro et al., 2016). These RNAs are believed to be transcribed by the approximately 98-99% non-coding regions of the human genome (Derrien et al., 2012; Fu, 2014; Montalbano et al., 2017; Slack and Chinnaiyan, 2019), as well as a large variety of genomic regions, such as exonic, tronic, and intergenic regions. Hence, lncRNAs are also divided into eight categories: Intergenic lncRNAs, Intronic lncRNAs, Enhancer lncRNAs, Promoter lncRNAs, Natural antisense/sense lncRNAs, Small nucleolar RNA-ended lncRNAs (sno-lncRNAs), Bidirectional lncRNAs, and non-poly(A) lncRNAs (Ma et al., 2013; Devaux et al., 2015; St Laurent et al., 2015; Chen, 2016; Quinn and Chang, 2016; Richard and Eichhorn, 2018; Connerty et al., 2020). A range of evidence has suggested that lncRNAs function as key regulators in crucial cellular functions, including proliferation, differentiation, apoptosis, migration, and invasion, by regulating the expression level of target genes via epigenomic, transcriptional, or post-transcriptional approaches (Cao et al., 2018). Moreover, lncRNAs detected in body fluids were also believed to serve as potential biomarkers for the diagnosis, prognosis, and monitoring of disease progression, and act as novel and potential drug targets for therapeutic exploitation in human disease (Jiang W. et al., 2018; Zhou et al., 2019a). Long non-coding RNA X-inactive specific transcript (lncRNA Xist) are a set of 15,000-20,000 nt sequences localized in the X chromosome inactivation center (XIC) of chromosome Xq13.2 (Brown et al., 1992; Debrand et al., 1998; Kay, 1998; Lee et al., 2013; da Rocha and Heard, 2017; Yang Z. et al., 2018; Brockdorff, 2019). Previous studies have indicated that lncRNA Xist regulate X chromosome inactivation (XCI), resulting in the inheritable silencing of one of the X-chromosomes during female cell development. Also, it serves a vital regulatory function in the whole spectrum of human disease (notably cancer) and can be used as a novel diagnostic and prognostic biomarker and as a potential therapeutic target for human disease in the clinic (Liu et al., 2018b; Deng et al., 2019; Dinescu et al., 2019; Mutzel and Schulz, 2020; Patrat et al., 2020; Wang et al., 2020a). In particular, lncRNA Xist have been demonstrated to be involved in the development of multiple types of tumors including brain tumor, Leukemia, lung cancer, breast cancer, and liver cancer, with the prominent examples outlined in Table 1. It was also believed that lncRNA Xist (Chaligne and Heard, 2014; Yang Z. et al., 2018) contributed to other diseases, such as pulmonary fibrosis, inflammation, neuropathic pain, cardiomyocyte hypertrophy, and osteoarthritis chondrocytes, and more specific details can be found in Table 2. This review summarizes the current knowledge on the regulatory mechanisms of lncRNA Xist on both chromosome dosage compensation and pathogenesis (especially cancer) processes, with a focus on the regulatory network of lncRNA Xist in human disease.
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Affiliation(s)
| | | | | | | | | | | | - Dongyi Zhang
- Department of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China
| | - Lingyun Zhu
- Department of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China
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Arner AM, Grogan KE, Grabowski M, Reyes-Centeno H, Perry GH. Patterns of recent natural selection on genetic loci associated with sexually differentiated human body size and shape phenotypes. PLoS Genet 2021; 17:e1009562. [PMID: 34081690 PMCID: PMC8174730 DOI: 10.1371/journal.pgen.1009562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 04/20/2021] [Indexed: 01/21/2023] Open
Abstract
Levels of sex differences for human body size and shape phenotypes are hypothesized to have adaptively reduced following the agricultural transition as part of an evolutionary response to relatively more equal divisions of labor and new technology adoption. In this study, we tested this hypothesis by studying genetic variants associated with five sexually differentiated human phenotypes: height, body mass, hip circumference, body fat percentage, and waist circumference. We first analyzed genome-wide association (GWAS) results for UK Biobank individuals (~194,000 females and ~167,000 males) to identify a total of 114,199 single nucleotide polymorphisms (SNPs) significantly associated with at least one of the studied phenotypes in females, males, or both sexes (P<5x10-8). From these loci we then identified 3,016 SNPs (2.6%) with significant differences in the strength of association between the female- and male-specific GWAS results at a low false-discovery rate (FDR<0.001). Genes with known roles in sexual differentiation are significantly enriched for co-localization with one or more of these SNPs versus SNPs associated with the phenotypes generally but not with sex differences (2.73-fold enrichment; permutation test; P = 0.0041). We also confirmed that the identified variants are disproportionately associated with greater phenotype effect sizes in the sex with the stronger association value. We then used the singleton density score statistic, which quantifies recent (within the last ~3,000 years; post-agriculture adoption in Britain) changes in the frequencies of alleles underlying polygenic traits, to identify a signature of recent positive selection on alleles associated with greater body fat percentage in females (permutation test; P = 0.0038; FDR = 0.0380), directionally opposite to that predicted by the sex differences reduction hypothesis. Otherwise, we found no evidence of positive selection for sex difference-associated alleles for any other trait. Overall, our results challenge the longstanding hypothesis that sex differences adaptively decreased following subsistence transitions from hunting and gathering to agriculture. There is uncertainty regarding the evolutionary history of human sex differences for quantitative body size and shape phenotypes. In this study we identified thousands of genetic loci that differentially impact body size and shape trait variation between females and males using a large sample of UK Biobank individuals. After confirming the biological plausibility of these loci, we used a population genomics approach to study the recent (over the past ~3,000 years) evolutionary histories of these loci in this population. We observed significant increases in the frequencies of alleles associated with greater body fat percentage in females. This result is contradictory to longstanding hypotheses that sex differences have adaptively decreased following subsistence transitions from hunting and gathering to agriculture.
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Affiliation(s)
- Audrey M. Arner
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- * E-mail: (AMA); (GHP)
| | - Kathleen E. Grogan
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Departments of Anthropology and Biology, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Mark Grabowski
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Research Centre in Evolutionary Anthropology and Palaeoecology, Liverpool John Moores University, Liverpool, United Kingdom
| | - Hugo Reyes-Centeno
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Department of Anthropology & William S. Webb Museum of Anthropology, University of Kentucky, Lexington, Kentucky, United States of America
| | - George H. Perry
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- * E-mail: (AMA); (GHP)
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Del Pilar Solar Diaz I, de Camargo GMF, Rocha da Cruz VA, da Costa Hermisdorff I, Carvalho CVD, de Albuquerque LG, Costa RB. Effect of the X chromosome in genomic evaluations of reproductive traits in beef cattle. Anim Reprod Sci 2020; 225:106682. [PMID: 33360620 DOI: 10.1016/j.anireprosci.2020.106682] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 12/14/2020] [Accepted: 12/15/2020] [Indexed: 01/19/2023]
Abstract
The aim of this study was to evaluate whether there are predictive advantages for breeding values with inclusion of X chromosome genomic markers for reproductive (occurrence of early pregnancy - P16 and age at first calving - AFC) and andrological (scrotal circumference -SC) variables in beef cattle. There were 3263 genotypes of females and males evaluated. There were breeding value estimates for SC, AFC and P16 considering two scenarios: 1) only autosomal markers or 2) autosomal and X chromosome markers. To evaluate effects of inclusion of X chromosome markers on selection, responses to selection were compared including or not including genomic marker information from the X chromosome. There were greater heritability estimates for SC (0.40 and 0.31), AFC (0.11 and 0.09) and P16 (0.43 and 0.38) when analyses included, compared with not including, genomic marker information from the X chromosome. When selection is based on results from analyses that did not include information for the X chromosome, there was about a 7 % lesser mean genomic breeding value for the SC traits for selected animals. For P16, there was an approximate 4% lesser breeding value without inclusion of genomic marker information from the X chromosome, while this inclusion did not have as great an effect on the breeding value for AFC. There was an average predictive correlation of 0.79, 0.98 and 0.84 for SC, AFC and P16, respectively. These estimates indicate inclusion of the X chromosome genomic marker information in the analysis can improve prediction of genomic breeding values, especially for SC.
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Affiliation(s)
- Iara Del Pilar Solar Diaz
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), 40170-110, Salvador, BA, Brazil
| | | | | | - Isis da Costa Hermisdorff
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), 40170-110, Salvador, BA, Brazil
| | | | - Lucia Galvão de Albuquerque
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, SP, Brazil
| | - Raphael Bermal Costa
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), 40170-110, Salvador, BA, Brazil.
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Melia T, Waxman DJ. Genetic factors contributing to extensive variability of sex-specific hepatic gene expression in Diversity Outbred mice. PLoS One 2020; 15:e0242665. [PMID: 33264334 PMCID: PMC7710091 DOI: 10.1371/journal.pone.0242665] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022] Open
Abstract
Sex-specific transcription characterizes hundreds of genes in mouse liver, many implicated in sex-differential drug and lipid metabolism and disease susceptibility. While the regulation of liver sex differences by growth hormone-activated STAT5 is well established, little is known about autosomal genetic factors regulating the sex-specific liver transcriptome. Here we show, using genotyping and expression data from a large population of Diversity Outbred mice, that genetic factors work in tandem with growth hormone to control the individual variability of hundreds of sex-biased genes, including many long non-coding RNA genes. Significant associations between single nucleotide polymorphisms and sex-specific gene expression were identified as expression quantitative trait loci (eQTLs), many of which showed strong sex-dependent associations. Remarkably, autosomal genetic modifiers of sex-specific genes were found to account for more than 200 instances of gain or loss of sex-specificity across eight Diversity Outbred mouse founder strains. Sex-biased STAT5 binding sites and open chromatin regions with strain-specific variants were significantly enriched at eQTL regions regulating correspondingly sex-specific genes, supporting the proposed functional regulatory nature of the eQTL regions identified. Binding of the male-biased, growth hormone-regulated repressor BCL6 was most highly enriched at trans-eQTL regions controlling female-specific genes. Co-regulated gene clusters defined by overlapping eQTLs included sets of highly correlated genes from different chromosomes, further supporting trans-eQTL action. These findings elucidate how an unexpectedly large number of autosomal factors work in tandem with growth hormone signaling pathways to regulate the individual variability associated with sex differences in liver metabolism and disease.
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Affiliation(s)
- Tisha Melia
- Department of Biology and Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
| | - David J. Waxman
- Department of Biology and Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
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Diaz IDPS, de Camargo GMF, Cruz VARD, Hermisdorff IDC, Carvalho CVD, de Albuquerque LG, Costa RB. Mapping genomic regions for reproductive traits in beef cattle: Inclusion of the X chromosome. Reprod Domest Anim 2020; 55:1650-1654. [PMID: 32853424 DOI: 10.1111/rda.13810] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/19/2020] [Indexed: 12/15/2022]
Abstract
Although the second largest chromosome of the genome, the X chromosome is usually excluded from genome-wide association studies (GWAS). Considering the presence and importance of genes on this chromosome that are involved in reproduction, the aim of this study was to evaluate the effect of its inclusion in GWAS on reproductive traits (scrotal circumference [SC], early pregnancy [P16] and age at first calving [AFC]) in a Nelore herd. Genotype data from 3,263 animals with the above-mentioned phenotypes were used. The results showed an increase in the variances explained by the autosomal markers for all traits when the X chromosome was not included. For SC, there was an increase of more than 10% for the windows on chromosomes 2 and 6. For P16, the effect was increased by almost 20% for windows on chromosome 5. The same pattern was found for AFC, with an increase of more than 10% for the most important windows. The results indicate that the noninclusion of the X chromosome can overestimate the effects of autosomes on SC, P16 and AFC not only because of the additive effect of the X chromosome itself but also because of its epistatic effect on autosomal genes.
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Affiliation(s)
| | | | | | | | | | - Lucia Galvão de Albuquerque
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, Brazil
| | - Raphael Bermal Costa
- Escola de Medicina Veterinária e Zootecnia, Universidade Federal da Bahia (UFBA), Salvador, Brazil
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Druet T, Legarra A. Theoretical and empirical comparisons of expected and realized relationships for the X-chromosome. Genet Sel Evol 2020; 52:50. [PMID: 32819272 PMCID: PMC7441635 DOI: 10.1186/s12711-020-00570-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 08/12/2020] [Indexed: 01/08/2023] Open
Abstract
Background X-chromosomal loci present different inheritance patterns compared to autosomal loci and must be modeled accordingly. Sexual chromosomes are not systematically considered in whole-genome relationship matrices although rules based on genealogical or marker information have been derived. Loci on the X-chromosome could have a significant contribution to the additive genetic variance, in particular for some traits such as those related to reproduction. Thus, accounting for the X-chromosome relationship matrix might be informative to better understand the architecture of complex traits (e.g., by estimating the variance associated to this chromosome) and to improve their genomic prediction. For such applications, previous studies have shown the benefits of combining information from genotyped and ungenotyped individuals. Results In this paper, we start by presenting rules to compute a genomic relationship matrix (GRM) for the X-chromosome (GX) without making any assumption on dosage compensation, and based on coding of gene content with 0/1 for males and 0/1/2 for females. This coding adjusts naturally to previously derived pedigree-based relationships (S) for the X-chromosome. When needed, we propose to accommodate and estimate dosage compensation and genetic heterogeneity across sexes via multiple trait models. Using a Holstein dairy cattle dataset, including males and females, we then empirically illustrate that realized relationships (GX) matches expectations (S). However, GX presents high deviations from S. GX has also a lower dimensionality compared to the autosomal GRM. In particular, individuals are frequently identical along the entire chromosome. Finally, we confirm that the heritability of gene content for markers on the X-chromosome that are estimated by using S is 1, further demonstrating that S and GX can be combined. For the pseudo-autosomal region, we demonstrate that the expected relationships vary according to position because of the sex-gradient. We end by presenting the rules to construct the 'H matrix’ by combining both relationship matrices. Conclusions This work shows theoretically and empirically that a pedigree-based relationship matrix built with rules specifically developed for the X-chromosome (S) matches the realized GRM for the X-chromosome. Therefore, applications that combine expected relationships and genotypes for markers on the X-chromosome should use S and GX.
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Affiliation(s)
- Tom Druet
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
| | - Andres Legarra
- GenPhySE, INPT, INRAE, ENVT, 31326, Castanet Tolosan, France.
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Leong A, Lim VJY, Wang C, Chai JF, Dorajoo R, Heng CK, van Dam RM, Koh WP, Yuan JM, Jonas JB, Wang YX, Wei WB, Liu J, Reilly DF, Wong TY, Cheng CY, Sim X. Association of G6PD variants with hemoglobin A1c and impact on diabetes diagnosis in East Asian individuals. BMJ Open Diabetes Res Care 2020; 8:8/1/e001091. [PMID: 32209585 PMCID: PMC7103857 DOI: 10.1136/bmjdrc-2019-001091] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 01/20/2020] [Accepted: 02/14/2020] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE Hemoglobin A1c (HbA1c) accuracy is important for diabetes diagnosis and estimation of overall glycemia. The G6PD-Asahi variant which causes glucose-6-phosphate dehydrogenase (G6PD) deficiency has been shown to lower HbA1c independently of glycemia in African ancestry populations. As different G6PD variants occur in Asian ancestry, we sought to identify Asian-specific G6PD variants associated with HbA1c. RESEARCH DESIGN AND METHODS In eight Asian population-based cohorts, we performed imputation on the X chromosome using the 1000 Genomes reference panel and tested for association with HbA1c (10 005 East Asians and 2051 South Asians). Results were meta-analyzed across studies. We compared the proportion of individuals classified as having diabetes/pre-diabetes by fasting glucose ≥100 mg/dL or HbA1c ≥5.7% units among carriers and non-carriers of HbA1c-associated variants. RESULTS The strongest association was a missense variant (G6PD-Canton, rs72554665, minor allele frequency=2.2%, effect in men=-0.76% unit, 95% CI -0.88 to -0.64, p=1.25×10-27, n=2844). Conditional analyses identified a secondary distinct signal, missense variant (G6PD-Kaiping, rs72554664, minor allele frequency=1.6%, effect in men=-1.12 % unit, 95% CI -1.32 to -0.92, p=3.12×10-15, pconditional_Canton=7.57×10-11). Adjusting for glucose did not attenuate their effects. The proportion of individuals with fasting glucose ≥100 mg/dL did not differ by carrier status of G6PD-Canton (p=0.21). Whereas the proportion of individuals with HbA1c ≥5.7% units was lower in carriers (5%) compared with non-carriers of G6PD-Canton (30%, p=0.03). CONCLUSIONS We identified two G6PD variants in East Asian men associated with non-glycemic lowering of HbA1c. Carriers of these variants are more likely to be underdiagnosed for diabetes or pre-diabetes than non-carriers if screened by HbA1c without confirmation by direct glucose measurements.
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Affiliation(s)
- Aaron Leong
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Victor Jun Yu Lim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Woon-Puay Koh
- Health Services and Systems Research, Duke NUS Medical School, Singapore
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Baden-Württemberg, Germany
- Ophthalmology and Visual Sciences Key Laboratory, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ya Xing Wang
- Ophthalmology and Visual Sciences Key Laboratory, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Wen-Bin Wei
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Dermot F Reilly
- Genetics, Merck Sharp and Dohme IA, Kenilworth, New Jersey, USA
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
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Jons WA, Colby CL, McElroy SL, Frye MA, Biernacka JM, Winham SJ. Statistical methods for testing X chromosome variant associations: application to sex-specific characteristics of bipolar disorder. Biol Sex Differ 2019; 10:57. [PMID: 31818333 PMCID: PMC6902568 DOI: 10.1186/s13293-019-0272-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 11/21/2019] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) affects both sexes, but important sex differences exist with respect to its symptoms and comorbidities. For example, rapid cycling (RC) is more prevalent in females, and alcohol use disorder (AUD) is more prevalent in males. We hypothesize that X chromosome variants may be associated with sex-specific characteristics of BD. Few studies have explored the role of the X chromosome in BD, which is complicated by X chromosome inactivation (XCI). This process achieves "dosage compensation" for many X chromosome genes by silencing one of the two copies in females, and most statistical methods either ignore that XCI occurs or falsely assume that one copy is inactivated at all loci. We introduce new statistical methods that do not make these assumptions. METHODS We investigated this hypothesis in 1001 BD patients from the Genetic Association Information Network (GAIN) and 957 BD patients from the Mayo Clinic Bipolar Disorder Biobank. We examined the association of over 14,000 X chromosome single nucleotide polymorphisms (SNPs) with sex-associated BD traits using two statistical approaches that account for whether a SNP may be undergoing or escaping XCI. In the "XCI-informed approach," we fit a sex-adjusted logistic regression model assuming additive genetic effects where we coded the SNP either assuming one copy is expressed or two copies are expressed based on prior knowledge about which regions are inactivated. In the "XCI-robust approach," we fit a logistic regression model with sex, SNP, and SNP-sex interaction effects that is flexible to whether the region is inactivated or escaping XCI. RESULTS Using the "XCI-informed approach," which considers only the main effect of SNP and does not allow the SNP effect to differ by sex, no significant associations were identified for any of the phenotypes. Using the "XCI-robust approach," intergenic SNP rs5932307 was associated with BD (P = 8.3 × 10-8), with a stronger effect in females (odds ratio in males (ORM) = 1.13, odds ratio in females for a change of two allele copies (ORW2) = 3.86). CONCLUSION X chromosome association studies should employ methods which account for its unique biology. Future work is needed to validate the identified associations with BD, to formally assess the performance of both approaches under different true genetic architectures, and to apply these approaches to study sex differences in other conditions.
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Affiliation(s)
- William A. Jons
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
| | - Colin L. Colby
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
| | - Susan L. McElroy
- Lindner Center of HOPE, University of Cincinnati College of Medicine, Mason, OH 45040 USA
| | - Mark A. Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905 USA
| | - Joanna M. Biernacka
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905 USA
| | - Stacey J. Winham
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905 USA
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Sarnowski C, Leong A, Raffield LM, Wu P, de Vries PS, DiCorpo D, Guo X, Xu H, Liu Y, Zheng X, Hu Y, Brody JA, Goodarzi MO, Hidalgo BA, Highland HM, Jain D, Liu CT, Naik RP, O'Connell JR, Perry JA, Porneala BC, Selvin E, Wessel J, Psaty BM, Curran JE, Peralta JM, Blangero J, Kooperberg C, Mathias R, Johnson AD, Reiner AP, Mitchell BD, Cupples LA, Vasan RS, Correa A, Morrison AC, Boerwinkle E, Rotter JI, Rich SS, Manning AK, Dupuis J, Meigs JB. Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. Am J Hum Genet 2019; 105:706-718. [PMID: 31564435 DOI: 10.1016/j.ajhg.2019.08.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 08/20/2019] [Indexed: 01/21/2023] Open
Abstract
Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
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Affiliation(s)
- Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA.
| | - Aaron Leong
- Division of General Internal Medicine, Massachusetts General Hospital, Boston 02114, MA USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Xiuwen Zheng
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98108, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Bertha A Hidalgo
- University of Alabama at Birmingham, Department of Epidemiology, Birmingham, AL 35294, USA
| | - Heather M Highland
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Rakhi P Naik
- Division of Hematology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | | | - James A Perry
- University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Bianca C Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston 02114, MA USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Jennifer Wessel
- Department of Epidemiology, Indiana University Fairbanks School of Public Health, Indianapolis, IN 46202, USA; Department of Medicine and Diabetes Translational Research Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, USA; Departments of Epidemiology and Health Services, University of Washington, Seattle, WA 98195, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520, USA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98108, USA
| | - Rasika Mathias
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; GeneSTAR Research Program, Department of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Andrew D Johnson
- National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98108, USA; Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD 21201, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA; National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA
| | - Ramachandran S Vasan
- National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Section of Preventive Medicine and Epidemiology, Evans Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA; Whitaker Cardiovascular Institute and Cardiology Section, Evans Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Adolfo Correa
- Departments of Medicine, Pediatrics, and Population Health Science, University of Mississippi Medical Center, Jackson, MS 39216, USA; The Jackson Heart Study, Jackson, MS 39213, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Alisa K Manning
- Division of General Internal Medicine, Massachusetts General Hospital, Boston 02114, MA USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA; National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Boston 02114, MA USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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47
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Naqvi S, Godfrey AK, Hughes JF, Goodheart ML, Mitchell RN, Page DC. Conservation, acquisition, and functional impact of sex-biased gene expression in mammals. Science 2019; 365:eaaw7317. [PMID: 31320509 PMCID: PMC6896219 DOI: 10.1126/science.aaw7317] [Citation(s) in RCA: 151] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Accepted: 06/12/2019] [Indexed: 12/15/2022]
Abstract
Sex differences abound in human health and disease, as they do in other mammals used as models. The extent to which sex differences are conserved at the molecular level across species and tissues is unknown. We surveyed sex differences in gene expression in human, macaque, mouse, rat, and dog, across 12 tissues. In each tissue, we identified hundreds of genes with conserved sex-biased expression-findings that, combined with genomic analyses of human height, explain ~12% of the difference in height between females and males. We surmise that conserved sex biases in expression of genes otherwise operating equivalently in females and males contribute to sex differences in traits. However, most sex-biased expression arose during the mammalian radiation, which suggests that careful attention to interspecies divergence is needed when modeling human sex differences.
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Affiliation(s)
- Sahin Naqvi
- Whitehead Institute, Cambridge, MA 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alexander K Godfrey
- Whitehead Institute, Cambridge, MA 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Mary L Goodheart
- Whitehead Institute, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Whitehead Institute, Cambridge, MA 02142, USA
| | - Richard N Mitchell
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - David C Page
- Whitehead Institute, Cambridge, MA 02142, USA.
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Howard Hughes Medical Institute, Whitehead Institute, Cambridge, MA 02142, USA
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