A saturated map of common genetic variants associated with human height
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A saturated map of common genetic variants associated with human height. / Yengo, Loic; Vedantam, Sailaja; Marouli, Eirini; Sidorenko, Julia; Bartell, Eric; Sakaue, Saori; Graff, Marielisa; Eliasen, Anders U.; Jiang, Yunxuan; Raghavan, Sridharan; Miao, Jenkai; Arias, Joshua D.; Graham, Sarah E.; Mukamel, Ronen E.; Spracklen, Cassandra N.; Yin, Xianyong; Chen, Shyh-Huei; Ferreira, Teresa; Highland, Heather H.; Ji, Yingjie; Karaderi, Tugce; Lin, Kuang; Lull, Kreete; Malden, Deborah E.; Andersen, Mette K.; Appadurai, Vivek; Bork-Jensen, Jette; Burgdorf, Kristoffer S.; Hansen, Thomas F.; Jonsson, Anna; Jorgensen, Torben; Liu, Jun; Mollehave, Line T.; Smit, Roelof A. J.; Zhao, Jing-Hua; Bisgaard, Hans; Bonnelykke, Klaus; Dantoft, Thomas M.; Grarup, Niels; Hansen, Torben; Jackson, Rebecca D.; Karpe, Fredrik; Kovacs, Peter; Lind, Lars; Linneberg, Allan; Pedersen, Oluf; Werge, Thomas M.; Sun, Yan; Loos, Ruth J. F.; Winkler, Thomas W.; 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.
In: Nature, Vol. 610, 2022, p. 704–712.Research output: Contribution to journal › Journal article › Research › peer-review
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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 -
ID: 323096745