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A saturated map of common genetic variants associated with human height

Yengo, L. ; Hindy, G. LU ; Kurbasic, A. LU ; Lyssenko, V. LU ; Poveda, A. LU orcid ; Elmståhl, S. LU ; Franks, P.W. LU ; Smith, J. Gustav LU ; Tuomi, T. LU orcid and Consortium, The PRACTICAL , et al. (2022) In Nature p.704-712
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... (More)
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. © 2022, The Author(s). (Less)
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organization
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type
Contribution to journal
publication status
published
subject
keywords
adult, allele, article, effect size, female, gene frequency, gene linkage disequilibrium, genetic association, genetic variability, genome-wide association study, haplotype map, heritability, human, human experiment, major clinical study, male, prediction, sample size, single nucleotide polymorphism, genetics, genome, Gene Frequency, Genome, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide
in
Nature
pages
9 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85139748621
  • pmid:36224396
ISSN
0028-0836
DOI
10.1038/s41586-022-05275-y
language
English
LU publication?
yes
id
7546239f-d9c4-4336-8042-9065fea480f7
date added to LUP
2023-01-11 14:11:29
date last changed
2024-04-04 13:20:33
@article{7546239f-d9c4-4336-8042-9065fea480f7,
  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. © 2022, The Author(s).}},
  author       = {{Yengo, L. and Hindy, G. and Kurbasic, A. and Lyssenko, V. and Poveda, A. and Elmståhl, S. and Franks, P.W. and Smith, J. Gustav and Tuomi, T. and Consortium, The PRACTICAL and Group, Understanding Society Scientific and Hirschhorn, Joel N.}},
  issn         = {{0028-0836}},
  keywords     = {{adult; allele; article; effect size; female; gene frequency; gene linkage disequilibrium; genetic association; genetic variability; genome-wide association study; haplotype map; heritability; human; human experiment; major clinical study; male; prediction; sample size; single nucleotide polymorphism; genetics; genome; Gene Frequency; Genome; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Polymorphism, Single Nucleotide}},
  language     = {{eng}},
  pages        = {{704--712}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature}},
  title        = {{A saturated map of common genetic variants associated with human height}},
  url          = {{http://dx.doi.org/10.1038/s41586-022-05275-y}},
  doi          = {{10.1038/s41586-022-05275-y}},
  year         = {{2022}},
}