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

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  • George Hindy
  • Peter Dornbos
  • Mark D. Chaffin
  • Dajiang J. Liu
  • Minxian Wang
  • Margaret Sunitha Selvaraj
  • David Zhang
  • Joseph Park
  • Carlos A. Aguilar-Salinas
  • Lucinda Antonacci-Fulton
  • Diego Ardissino
  • Donna K. Arnett
  • Stella Aslibekyan
  • Gil Atzmon
  • Christie M. Ballantyne
  • Francisco Barajas-Olmos
  • Nir Barzilai
  • Lewis C. Becker
  • Lawrence F. Bielak
  • Joshua C. Bis
  • John Blangero
  • Eric Boerwinkle
  • Lori L. Bonnycastle
  • Erwin Bottinger
  • Donald W. Bowden
  • Matthew J. Bown
  • Jennifer A. Brody
  • Jai G. Broome
  • Noël P. Burtt
  • Brian E. Cade
  • Federico Centeno-Cruz
  • Edmund Chan
  • Yi Cheng Chang
  • Yii Der I. Chen
  • Ching Yu Cheng
  • Won Jung Choi
  • Rajiv Chowdhury
  • Cecilia Contreras-Cubas
  • Emilio J. Córdova
  • Adolfo Correa
  • L. Adrienne Cupples
  • Joanne E. Curran
  • John Danesh
  • Paul S. de Vries
  • Grarup, Niels
  • Hansen, Torben
  • Linneberg, Allan René
  • Ruth J.F. Loos
  • Pedersen, Oluf Borbye
  • Daniel R. Witte
  • AMP-T2D-GENES, Myocardial Infarction Genetics Consortium
  • NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
  • NHLBI TOPMed Lipids Working Group

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.

Original languageEnglish
JournalAmerican Journal of Human Genetics
Issue number1
Pages (from-to)81-96
Number of pages16
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2021 American Society of Human Genetics

    Research areas

  • association, cholesterol, exome sequencing, gene-based association, lipid

ID: 289392068