TY - JOUR

T1 - A saturated map of common genetic variants associated with human height

AU - Yengo, Loic

AU - Vedantam, Sailaja

AU - Marouli, Eirini

AU - Sidorenko, Julia

AU - Bartell, Eric

AU - Sakaue, Saori

AU - Graff, Marielisa

AU - Eliasen, Anders U.

AU - Jiang, Yunxuan

AU - Raghavan, Sridharan

AU - Miao, Jenkai

AU - Arias, Joshua D.

AU - Graham, Sarah E.

AU - Mukamel, Ronen E.

AU - Spracklen, Cassandra N.

AU - Yin, Xianyong

AU - Chen, Shyh-Huei

AU - Ferreira, Teresa

AU - Highland, Heather H.

AU - Ji, Yingjie

AU - Karaderi, Tugce

AU - Lin, Kuang

AU - Lull, Kreete

AU - Malden, Deborah E.

AU - Andersen, Mette K.

AU - Appadurai, Vivek

AU - Bork-Jensen, Jette

AU - Burgdorf, Kristoffer S.

AU - Hansen, Thomas F.

AU - Jonsson, Anna

AU - Jorgensen, Torben

AU - Liu, Jun

AU - Mollehave, Line T.

AU - Smit, Roelof A. J.

AU - Zhao, Jing-Hua

AU - Bisgaard, Hans

AU - Bonnelykke, Klaus

AU - Dantoft, Thomas M.

AU - Grarup, Niels

AU - Hansen, Torben

AU - Jackson, Rebecca D.

AU - Karpe, Fredrik

AU - Kovacs, Peter

AU - Lind, Lars

AU - Linneberg, Allan

AU - Pedersen, Oluf

AU - Werge, Thomas M.

AU - Sun, Yan

AU - Loos, Ruth J. F.

AU - Winkler, Thomas W.

AU - 23andMe Res Team

AU - VA Million Vet Program

AU - DiscovEHR DiscovEHR MyCode Communi

AU - eEMERGE Elect Med Records Genomics

AU - LifeLines Cohort Study

AU - PRACTICAL consortium

AU - Understanding Soc Sci Grp

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - GENOME-WIDE ASSOCIATION

KW - UK BIOBANK

KW - RARE

KW - HERITABILITY

KW - GWAS

KW - ARCHITECTURE

KW - IMPUTATION

KW - RESOURCE

KW - REVEALS

KW - SCORES

U2 - 10.1038/s41586-022-05275-y

DO - 10.1038/s41586-022-05275-y

M3 - Journal article

C2 - 36224396

VL - 610

SP - 704

EP - 712

JO - Nature

JF - Nature

SN - 0028-0836

ER -