A saturated map of common genetic variants associated with human height

23andMe Res Team, VA Million Vet Program, DiscovEHR DiscovEHR MyCode Communi, eEMERGE Elect Med Records Genomics, Lifelines Cohort Study, PRACTICAl Consortium, Understanding Soc Sci Grp, Loic Yengo, Sailaja Vedantam, Eirini Marouli, Julia Sidorenko, Eric Bartell, Saori Sakaue, Marielisa Graff, Anders U. Eliasen, Yunxuan Jiang, Sridharan Raghavan, Jenkai Miao, Joshua D. Arias, Sarah E. GrahamRonen E. Mukamel, Cassandra N. Spracklen, Xianyong Yin, Shyh-Huei Chen, Teresa Ferreira, Heather H. Highland, Yingjie Ji, Tugce Karaderi, Kuang Lin, Kreete Lull, Deborah E. Malden, Carolina Medina-Gomez, Alireza Ani, Ayse Demirkan, Jie Huang, Young Jin Kim, Phuong Le, Ilja M. Nolte, Dennis Raven, Albert Smith, Sander W. van der Laan, Peter J. van der Most, Niek Verweij, Tian Xie, Jing-Hua Zhao, Wei Zhao, Folkert W. Asselbergs, Catharina A. Hartman, Wei Huang, Meena Kumari, Albertine J. Oldehinkel, Brenda W. J. H. Penninx, Michiel Rienstra, Harold Snieder, Pim van der Harst, Ya Xing Wang, Peter M. Visscher

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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 sizes(1). 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 panel(2)) 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.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

Original languageEnglish
Pages (from-to)704–712
Number of pages9
Early online date12-Oct-2022
Publication statusPublished - Oct-2022


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