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Rare coding variants in 35 genes associate with circulating lipid levels—A multi-ancestry analysis of 170,000 exomes

Hindy, George LU ; Groop, Leif LU ; Lyssenko, Valeriya LU ; Melander, Olle LU orcid ; Nilsson, Peter M LU ; Orho-Melander, Marju LU and Peloso, Gina M. (2022) In American Journal of Human Genetics 109(1). p.81-96
Abstract
Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci... (More)
Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels. © 2021 American Society of Human Genetics (Less)
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keywords
association, cholesterol, exome sequencing, gene-based association, lipid, high density lipoprotein cholesterol, low density lipoprotein cholesterol, triacylglycerol, African, ALB gene, ancestry group, Article, cholesterol blood level, CREB3L3 gene, East Asian, European, exosome, gene, gene frequency, gene identification, gene sequence, genetic association, genetic code, genetic trait, genetic variability, genome-wide association study, high density lipoprotein cholesterol level, Hispanic, human, JAK2 gene, lipid blood level, lipid level, lipid metabolism, low density lipoprotein cholesterol level, molecular genetics, NR1H3 gene, PLA2G12A gene, population genetics, PPARG gene, Samoan (people), single nucleotide polymorphism, South Asian, SRSF2 gene, STAB1 gene, TMEM136 gene, triacylglycerol blood level, VARS gene, whole exome sequencing, allele, biology, blood, case control study, exome, genetic database, genetic predisposition, genetic variation, genetics, glucose blood level, liver, metabolism, multifactorial inheritance, non insulin dependent diabetes mellitus, open reading frame, pathology, phenotype, procedures, Alleles, Blood Glucose, Case-Control Studies, Computational Biology, Databases, Genetic, Diabetes Mellitus, Type 2, Exome, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Lipids, Liver, Molecular Sequence Annotation, Multifactorial Inheritance, Open Reading Frames, Phenotype, Polymorphism, Single Nucleotide
in
American Journal of Human Genetics
volume
109
issue
1
pages
81 - 96
publisher
Cell Press
external identifiers
  • pmid:34932938
  • scopus:85122004213
ISSN
0002-9297
DOI
10.1016/j.ajhg.2021.11.021
language
English
LU publication?
yes
additional info
Cited By :7 Export Date: 13 January 2023
id
5fc85684-9e8d-441d-82a9-0fe12c103c56
date added to LUP
2023-01-13 08:52:51
date last changed
2024-04-04 15:43:04
@article{5fc85684-9e8d-441d-82a9-0fe12c103c56,
  abstract     = {{Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency &lt; 1%) predicted damaging coding variation by using sequence data from &gt;170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels. © 2021 American Society of Human Genetics}},
  author       = {{Hindy, George and Groop, Leif and Lyssenko, Valeriya and Melander, Olle and Nilsson, Peter M and Orho-Melander, Marju and Peloso, Gina M.}},
  issn         = {{0002-9297}},
  keywords     = {{association; cholesterol; exome sequencing; gene-based association; lipid; high density lipoprotein cholesterol; low density lipoprotein cholesterol; triacylglycerol; African; ALB gene; ancestry group; Article; cholesterol blood level; CREB3L3 gene; East Asian; European; exosome; gene; gene frequency; gene identification; gene sequence; genetic association; genetic code; genetic trait; genetic variability; genome-wide association study; high density lipoprotein cholesterol level; Hispanic; human; JAK2 gene; lipid blood level; lipid level; lipid metabolism; low density lipoprotein cholesterol level; molecular genetics; NR1H3 gene; PLA2G12A gene; population genetics; PPARG gene; Samoan (people); single nucleotide polymorphism; South Asian; SRSF2 gene; STAB1 gene; TMEM136 gene; triacylglycerol blood level; VARS gene; whole exome sequencing; allele; biology; blood; case control study; exome; genetic database; genetic predisposition; genetic variation; genetics; glucose blood level; liver; metabolism; multifactorial inheritance; non insulin dependent diabetes mellitus; open reading frame; pathology; phenotype; procedures; Alleles; Blood Glucose; Case-Control Studies; Computational Biology; Databases, Genetic; Diabetes Mellitus, Type 2; Exome; Genetic Predisposition to Disease; Genetic Variation; Genetics, Population; Genome-Wide Association Study; Humans; Lipid Metabolism; Lipids; Liver; Molecular Sequence Annotation; Multifactorial Inheritance; Open Reading Frames; Phenotype; Polymorphism, Single Nucleotide}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{81--96}},
  publisher    = {{Cell Press}},
  series       = {{American Journal of Human Genetics}},
  title        = {{Rare coding variants in 35 genes associate with circulating lipid levels—A multi-ancestry analysis of 170,000 exomes}},
  url          = {{http://dx.doi.org/10.1016/j.ajhg.2021.11.021}},
  doi          = {{10.1016/j.ajhg.2021.11.021}},
  volume       = {{109}},
  year         = {{2022}},
}