TY - JOUR
T1 - Rare coding variants in 35 genes associate with circulating lipid levels—A multi-ancestry analysis of 170,000 exomes
AU - Hindy, George
AU - Dornbos, Peter
AU - Chaffin, Mark D.
AU - Liu, Dajiang J.
AU - Wang, Minxian
AU - Selvaraj, Margaret Sunitha
AU - Zhang, David
AU - Park, Joseph
AU - Aguilar-Salinas, Carlos A.
AU - Antonacci-Fulton, Lucinda
AU - Ardissino, Diego
AU - Arnett, Donna K.
AU - Aslibekyan, Stella
AU - Atzmon, Gil
AU - Ballantyne, Christie M.
AU - Barajas-Olmos, Francisco
AU - Barzilai, Nir
AU - Becker, Lewis C.
AU - Bielak, Lawrence F.
AU - Bis, Joshua C.
AU - Blangero, John
AU - Boerwinkle, Eric
AU - Bonnycastle, Lori L.
AU - Bottinger, Erwin
AU - Bowden, Donald W.
AU - Bown, Matthew J.
AU - Brody, Jennifer A.
AU - Broome, Jai G.
AU - Burtt, Noël P.
AU - Cade, Brian E.
AU - Centeno-Cruz, Federico
AU - Chan, Edmund
AU - Chang, Yi Cheng
AU - Chen, Yii Der I.
AU - Cheng, Ching Yu
AU - Choi, Won Jung
AU - Chowdhury, Rajiv
AU - Contreras-Cubas, Cecilia
AU - Córdova, Emilio J.
AU - Correa, Adolfo
AU - Cupples, L. Adrienne
AU - Curran, Joanne E.
AU - Danesh, John
AU - de Vries, Paul S.
AU - DeFronzo, Ralph A.
AU - Doddapaneni, Harsha
AU - Duggirala, Ravindranath
AU - Dutcher, Susan K.
AU - Ellinor, Patrick T.
AU - Emery, Leslie S.
N1 - Copyright © 2021 American Society of Human Genetics. All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
KW - Alleles
KW - Blood Glucose/genetics
KW - Case-Control Studies
KW - Computational Biology/methods
KW - Databases, Genetic
KW - Diabetes Mellitus, Type 2/genetics
KW - Exome
KW - Genetic Predisposition to Disease
KW - Genetic Variation
KW - Genetics, Population
KW - Genome-Wide Association Study/methods
KW - Humans
KW - Lipid Metabolism/genetics
KW - Lipids/blood
KW - Liver/metabolism
KW - Molecular Sequence Annotation
KW - Multifactorial Inheritance
KW - Open Reading Frames
KW - Phenotype
KW - Polymorphism, Single Nucleotide
UR - http://www.scopus.com/inward/record.url?scp=85122004213&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.ajhg.2021.11.021
DO - https://doi.org/10.1016/j.ajhg.2021.11.021
M3 - Article
C2 - 34932938
SN - 0002-9297
VL - 109
SP - 81
EP - 96
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 1
ER -