A saturated map of common genetic variants associated with human height

23andMe Research Team, Loïc Yengo (Lead / Corresponding author), 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. Graham, Ronen E. Mukamel, Cassandra N. Spracklen, Xianyong Yin, Shyh-Huei Chen, Teresa Ferreira, Heather H. HighlandYingjie Ji, Tugce Karaderi, Kuang Lin, Kreete Lüll, Deborah E. Malden, Carolina Medina-Gomez, Moara Machado, Amy Moore, Sina Rüeger, Xueling Sim, Scott Vrieze, Tarunveer S. Ahluwalia, Masato Akiyama, Matthew A. Allison, Marcus Alvarez, Mette K. Andersen, Alireza Ani, Vivek Appadurai, Liubov Arbeeva, Seema Bhaskar, Lawrence F. Bielak, Ruth E. Mitchell, Jennifer A. Smith, Hannah Young, David A. Bennett, Bong-Jo Kim, Paul Mitchell, Andrew D. Morris, Colin N. A. Palmer, Laura J. Scott, Yukinori Okada (Lead / Corresponding author), Andrew R. Wood (Lead / Corresponding author), Peter M. Visscher (Lead / Corresponding author), Joel N. Hirschhorn (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
2 Downloads (Pure)

Abstract

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
Pages (from-to)704-712
Number of pages9
JournalNature
Volume610
Issue number7933
Early online date12 Oct 2022
DOIs
Publication statusPublished - 27 Oct 2022

Keywords

  • Genetic markers
  • Genome-wide association studies
  • Quantitative trait

Fingerprint

Dive into the research topics of 'A saturated map of common genetic variants associated with human height'. Together they form a unique fingerprint.

Cite this