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Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study

Authors :
Martha L. Daviglus
Daniel J. Schaid
Jeffrey Haessler
Adolfo Correa
Iona Cheng
Austin T. Hilliard
Yingchang Lu
Ozan Dikilitas
Gail P. Jarvik
Stephanie A. Bien
Lynne R. Wilkens
Yao Hu
Patrick M. A. Sleiman
Ulrike Peters
Laura J. Rasmussen-Torvik
Frank D. Mentch
Christopher J. O'Donnell
Lauren E. Petty
Kari E. North
Mariaelisa Graff
Christopher A. Haiman
Loic Le Marchand
Marie Verbanck
Peter W.F. Wilson
Steven Buyske
Ruth J. F. Loos
QiPing Feng
VA Million Veteran Program
Tara C. Matise
Charles Kooperberg
Ron Do
Kelly Cho
Scott M. Damrauer
Iftikhar J. Kullo
Christopher S. Carlson
Jennifer E. Below
Berta Almoguera
Philip S. Tsao
Themistocles L. Assimes
Lisa W. Martin
Wei-Qi Wei
Yuk-Lam Ho
Eric B. Larson
Ran Tao
Lucia A. Hindorff
Katherine K. Nishimura
José Luis Ambite
Matthew L. Kosel
Kyong-Mi Chang
Derek Klarin
Daniel O. Stram
Laura M. Raffield
Niha Zubair
Heather M. Highland
Source :
PLoS Genetics, Vol 16, Iss 3, p e1008684 (2020), PLoS Genetics
Publication Year :
2020
Publisher :
Public Library of Science (PLoS), 2020.

Abstract

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.<br />Author summary Blood lipid levels are closely linked to cardio-metabolic diseases, and genetic factors play an important role in their metabolism and regulation. Although over 400 loci have been identified through genetic association studies, the genetic architecture of lipid levels is not fully characterized. The lack of representation of diverse populations in previous studies resulted in a large gap in understanding the genetic background of lipid traits between European and minority populations, including African Americans, Hispanics, Hawaiians, and Native Americans. In our current analyses which included ancestrally diverse populations, we identified nine novel loci, one novel gene, and minority-specific independent signals at eight known loci, and pinpointed potential functional variants at two known loci. We further observed smaller effect sizes of reported lipids-associated loci in African Americans and Hispanics than those in Europeans, and better performance of polygenic risk scores using minority-specific instead of European-derived effect sizes when estimating genetic predisposition in minority populations. Our findings showed the benefits of including multi-ethnic studies in identification and refinement of lipids-associated loci, which will help to reduce the existing disparities and to pave the road to precision medicine.

Details

ISSN :
15537404
Volume :
16
Database :
OpenAIRE
Journal :
PLOS Genetics
Accession number :
edsair.doi.dedup.....78ed14ab2ad129e1dddce6575507a8b1
Full Text :
https://doi.org/10.1371/journal.pgen.1008684