Department of Economics and Business Economics

A saturated map of common genetic variants associated with human height

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Loïc Yengo, The University of Queensland Diamantina Institute, University of Queensland, Australia.
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  • Sailaja Vedantam, Division of Genetics, Boston Children's Hospital, Boston, MA, USA; Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA.
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  • Eirini Marouli, Queen Mary University of London
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  • Julia Sidorenko, The University of Queensland Diamantina Institute, University of Queensland, Australia.
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  • Eric Bartell, Division of Genetics, Boston Children's Hospital, Boston, MA, USA; Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA.
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  • Saori Sakaue, Broad Institute
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  • Marielisa Graff, University of North Carolina
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  • Anders U Eliasen, University of Copenhagen, Technical University of Denmark
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  • Yunxuan Jiang, Parkinson's Institute, Sunnyvale, California, USA.
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  • Sridharan Raghavan, Department of Veterans Affairs
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  • Jenkai Miao, Division of Genetics, Boston Children's Hospital, Boston, MA, USA; Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA.
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  • Joshua D Arias, National Institute of Health's National Cancer Institute: Quantitative Imaging Network
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  • Sarah E Graham, Michigan State University
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  • Ronen E Mukamel, Broad Institute
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  • Cassandra N Spracklen, University of North Carolina
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  • Xianyong Yin, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA; Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
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  • Shyh-Huei Chen, Wake Forest School of Medicine
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  • Teresa Ferreira, University of Oxford
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  • Heather H Highland, University of North Carolina
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  • Yingjie Ji, NIHR Exeter Clinical Research Facility, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW, UK.
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  • Tugce Karaderi, University of Copenhagen, University of Oxford
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  • Kuang Lin, University of Oxford
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  • Kreete Lüll, University of Tartu
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  • Deborah E Malden, University of Oxford
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  • Carolina Medina-Gomez, Erasmus University Rotterdam
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  • Moara Machado, National Institute of Health's National Cancer Institute: Quantitative Imaging Network
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  • Amy Moore, Division of Epidemiology and Biostatistics, University of Illinois at Chicago
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  • Sina Rüeger, Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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  • Xueling Sim, National University of Singapore and National University Health System
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  • Scott Vrieze, Univ Minnesota, University of Minnesota Twin Cities, University of Minnesota System, University of Minnesota Duluth, Dept Earth & Environm Sci
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  • Tarunveer S Ahluwalia, Steno Diabetes Centre
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  • Masato Akiyama, Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
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  • Mette K Andersen, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen
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  • Jakob Grove
  • Thomas F Hansen, NovoNordic Center for Protein Research, Danish Headache Center, University of Copenhagen
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  • Torben Jørgensen, Center for Clinical Research and Prevention, University of Copenhagen
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  • Manuel Mattheisen, Dalhousie University, LMU Munich
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  • Liselotte V Petersen
  • Zhe Wang, The Charles Bronfman Institute for Personalized Medicine, Ichan School of Medicine at Mount Sinai, New York, New York, USA.
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  • Anders D Børglum
  • Thomas M Dantoft, Center for Clinical Research and Prevention, University of Copenhagen
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  • Niels Grarup, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen
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  • Torben Hansen, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen
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  • Wei Huang, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute
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  • Christopher S Nielsen, Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, 0213, Norway., Norwegian Inst Publ Hlth, Norwegian Institute of Public Health (NIPH), Department of Pain Management and Research, Oslo University Hospital, Oslo, University of Oslo, Norway; Department of Pain Management and Research, Oslo University Hospital, Oslo, Norway; Department of Anaesthesiology, Oslo University Hospital, Oslo, Norway. Electronic address: harald.breivik@medsin.uio.no.
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  • Oluf Pedersen, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen
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  • Maggie C Y Ng, Center for Precision Medicine, Wake Forest School of Medicine, Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA., Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America., Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.
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  • Yan V Sun, Rollins School of Public Health, Emory University, Atlanta, Georgia, Atlanta VA Health Care System, Decatur
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  • Thomas W Winkler, Department of Genetic Epidemiology, University of Regensburg
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  • Jian Yang, Institute for Molecular Bioscience, The University of Queensland Diamantina Institute, University of Queensland, Australia., Faculty of Health and Life Sciences, School of Life Sciences, Coventry University, Coventry, United Kingdom., Westlake University, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou ivy dental clinic Co., Limited , Hangzhou , China.
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  • 23andMe Research Team
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  • VA Million Vet Program
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  • DiscovEHR Collaboration
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  • eMERGE Consortium
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  • Lifelines Cohort Study
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  • The PRACTICAL Consortium
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  • Understanding Society Scientific Group

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Original languageEnglish
JournalNature
Volume610
Issue7933
Pages (from-to)704–712
ISSN0028-0836
DOIs
Publication statusPublished - Oct 2022

Bibliographical note

© 2022. The Author(s).

    Research areas

  • Body Height/genetics, Chromosome Mapping, Europe/ethnology, Gene Frequency/genetics, Genome, Human/genetics, Genome-Wide Association Study, Haplotypes/genetics, Humans, Linkage Disequilibrium/genetics, Phenotype, Polymorphism, Single Nucleotide/genetics, Sample Size

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