Abstract
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
Original language | English |
---|---|
Pages (from-to) | 675-679 |
Number of pages | 5 |
Journal | Nature |
Volume | 600 |
Issue number | 7890 |
DOIs | |
State | Published - Dec 23 2021 |
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In: Nature, Vol. 600, No. 7890, 23.12.2021, p. 675-679.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - The power of genetic diversity in genome-wide association studies of lipids
AU - VA Million Veteran Program
AU - Global Lipids Genetics Consortium
AU - Graham, Sarah E.
AU - Clarke, Shoa L.
AU - Wu, Kuan Han H.
AU - Kanoni, Stavroula
AU - Zajac, Greg J.M.
AU - Ramdas, Shweta
AU - Surakka, Ida
AU - Ntalla, Ioanna
AU - Vedantam, Sailaja
AU - Winkler, Thomas W.
AU - Locke, Adam E.
AU - Marouli, Eirini
AU - Hwang, Mi Yeong
AU - Han, Sohee
AU - Narita, Akira
AU - Choudhury, Ananyo
AU - Bentley, Amy R.
AU - Ekoru, Kenneth
AU - Verma, Anurag
AU - Trivedi, Bhavi
AU - Martin, Hilary C.
AU - Hunt, Karen A.
AU - Hui, Qin
AU - Klarin, Derek
AU - Zhu, Xiang
AU - Thorleifsson, Gudmar
AU - Helgadottir, Anna
AU - Gudbjartsson, Daniel F.
AU - Holm, Hilma
AU - Olafsson, Isleifur
AU - Akiyama, Masato
AU - Sakaue, Saori
AU - Terao, Chikashi
AU - Kanai, Masahiro
AU - Zhou, Wei
AU - Brumpton, Ben M.
AU - Rasheed, Humaira
AU - Ruotsalainen, Sanni E.
AU - Havulinna, Aki S.
AU - Veturi, Yogasudha
AU - Feng, Qi Ping
AU - Rosenthal, Elisabeth A.
AU - Lingren, Todd
AU - Pacheco, Jennifer Allen
AU - Pendergrass, Sarah A.
AU - Haessler, Jeffrey
AU - Giulianini, Franco
AU - Bradford, Yuki
AU - Miller, Jason E.
AU - Campbell, Archie
AU - Lin, Kuang
AU - Millwood, Iona Y.
AU - Hindy, George
AU - Rasheed, Asif
AU - Faul, Jessica D.
AU - Zhao, Wei
AU - Weir, David R.
AU - Turman, Constance
AU - Huang, Hongyan
AU - Graff, Mariaelisa
AU - Mahajan, Anubha
AU - Brown, Michael R.
AU - Zhang, Weihua
AU - Yu, Ketian
AU - Schmidt, Ellen M.
AU - Pandit, Anita
AU - Gustafsson, Stefan
AU - Yin, Xianyong
AU - Luan, Jian’an
AU - Zhao, Jing Hua
AU - Matsuda, Fumihiko
AU - Jang, Hye Mi
AU - Yoon, Kyungheon
AU - Medina-Gomez, Carolina
AU - Pitsillides, Achilleas
AU - Hottenga, Jouke Jan
AU - Willemsen, Gonneke
AU - Wood, Andrew R.
AU - Ji, Yingji
AU - Gao, Zishan
AU - Haworth, Simon
AU - Mitchell, Ruth E.
AU - Chai, Jin Fang
AU - Aadahl, Mette
AU - Yao, Jie
AU - Manichaikul, Ani
AU - Warren, Helen R.
AU - Ramirez, Julia
AU - Bork-Jensen, Jette
AU - Kårhus, Line L.
AU - Goel, Anuj
AU - Sabater-Lleal, Maria
AU - Noordam, Raymond
AU - Sidore, Carlo
AU - Fiorillo, Edoardo
AU - McDaid, Aaron F.
AU - Marques-Vidal, Pedro
AU - Wielscher, Matthias
AU - Trompet, Stella
AU - Sattar, Naveed
AU - Møllehave, Line T.
AU - Thuesen, Betina H.
AU - Munz, Matthias
AU - Zeng, Lingyao
AU - Huang, Jianfeng
AU - Yang, Bin
AU - Poveda, Alaitz
AU - Kurbasic, Azra
AU - Lamina, Claudia
AU - Forer, Lukas
AU - Scholz, Markus
AU - Galesloot, Tessel E.
AU - Bradfield, Jonathan P.
AU - Daw, E. Warwick
AU - Zmuda, Joseph M.
AU - Mitchell, Jonathan S.
AU - Fuchsberger, Christian
AU - Christensen, Henry
AU - Brody, Jennifer A.
AU - Feitosa, Mary F.
AU - Wojczynski, Mary K.
AU - Preuss, Michael
AU - Mangino, Massimo
AU - Christofidou, Paraskevi
AU - Verweij, Niek
AU - Benjamins, Jan W.
AU - Engmann, Jorgen
AU - Kember, Rachel L.
AU - Slieker, Roderick C.
AU - Lo, Ken Sin
AU - Zilhao, Nuno R.
AU - Le, Phuong
AU - Kleber, Marcus E.
AU - Delgado, Graciela E.
AU - Huo, Shaofeng
AU - Ikeda, Daisuke D.
AU - Iha, Hiroyuki
AU - Yang, Jian
AU - Liu, Jun
AU - Leonard, Hampton L.
AU - Marten, Jonathan
AU - Schmidt, Börge
AU - Arendt, Marina
AU - Smyth, Laura J.
AU - Cañadas-Garre, Marisa
AU - Wang, Chaolong
AU - Nakatochi, Masahiro
AU - Wong, Andrew
AU - Hutri-Kähönen, Nina
AU - Sim, Xueling
AU - Xia, Rui
AU - Huerta-Chagoya, Alicia
AU - Fernandez-Lopez, Juan Carlos
AU - Lyssenko, Valeriya
AU - Ahmed, Meraj
AU - Jackson, Anne U.
AU - Irvin, Marguerite R.
AU - Oldmeadow, Christopher
AU - Kim, Han Na
AU - Ryu, Seungho
AU - Timmers, Paul R.H.J.
AU - Arbeeva, Liubov
AU - Dorajoo, Rajkumar
AU - Lange, Leslie A.
AU - Chai, Xiaoran
AU - Prasad, Gauri
AU - Lorés-Motta, Laura
AU - Pauper, Marc
AU - Long, Jirong
AU - Li, Xiaohui
AU - Theusch, Elizabeth
AU - Takeuchi, Fumihiko
AU - Spracklen, Cassandra N.
AU - Loukola, Anu
AU - Bollepalli, Sailalitha
AU - Warner, Sophie C.
AU - Wang, Ya Xing
AU - Wei, Wen B.
AU - Nutile, Teresa
AU - Ruggiero, Daniela
AU - Sung, Yun Ju
AU - Hung, Yi Jen
AU - Chen, Shufeng
AU - Liu, Fangchao
AU - Yang, Jingyun
AU - Kentistou, Katherine A.
AU - Gorski, Mathias
AU - Brumat, Marco
AU - Meidtner, Karina
AU - Bielak, Lawrence F.
AU - Smith, Jennifer A.
AU - Hebbar, Prashantha
AU - Farmaki, Aliki Eleni
AU - Hofer, Edith
AU - Lin, Maoxuan
AU - Xue, Chao
AU - Zhang, Jifeng
AU - Concas, Maria Pina
AU - Rao, D. C.
AU - Province, Michael A.
N1 - Funding Information: Competing interests G.J.M.Z. is an employee of Incyte Corporation. G.C.-P. is currently an employee of 23andMe. M.J.C. is the Chief Scientist for Genomics England, a UK Government company. B.M.P. serves on the steering committee of the Yale Open Data Access Project funded by Johnson & Johnson. G.T., A. Helgadottir, D.F.G., H. Holm., U.T. and K. Stefansson are employees of deCODE/Amgen. V.S. has received honoraria for consultations from Novo Nordisk and Sanofi and has an ongoing research collaboration with Bayer. M. McCarthy has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier and Takeda. M. McCarthy and A. Mahajan are employees of Genentech and are holders of Roche stock. M. Scholz receives funding from Pfizer for a project unrelated to this work. M.E.K. is employed by Synlab. W.M. has received grants from Siemens Healthineers, grants and personal fees from Aegerion Pharmaceuticals, grants and personal fees from Amgen, grants from AstraZeneca, grants and personal fees from Sanofi, grants and personal fees from Alexion Pharmaceuticals, grants and personal fees from BASF, grants and personal fees from Abbott Diagnostics, grants and personal fees from Numares, grants and personal fees from Berlin-Chemie, grants and personal fees from Akzea Therapeutics, grants from Bayer Vital, grants from bestbion dx, grants from Boehringer Ingelheim, grants from Immundiagnostik, grants from Merck Chemicals, grants from MSD Sharp and Dohme, grants from Novartis Pharma, grants from Olink Proteomics, and is employed by Synlab Holding Deutschland, all outside the submitted work. A.V.K. has served as a consultant to Sanofi, Medicines Company, Maze Pharmaceuticals, Navitor Pharmaceuticals, Verve Therapeutics, Amgen and Color Genomics; received speaking fees from Illumina, the Novartis Institute for Biomedical Research; received sponsored research agreements from the Novartis Institute for Biomedical Research and IBM Research; and reports a patent related to a genetic risk predictor (20190017119). S.K. is an employee of Verve Therapeutics and holds equity in Verve Therapeutics, Maze Therapeutics, Catabasis and San Therapeutics. He is a member of the scientific advisory boards for Regeneron Genetics Center and Corvidia Therapeutics; he has served as a consultant for Acceleron, Eli Lilly, Novartis, Merck, Novo Nordisk, Novo Ventures, Ionis, Alnylam, Aegerion, Haug Partners, Noble Insights, Leerink Partners, Bayer Healthcare, Illumina, Color Genomics, MedGenome, Quest and Medscape; and reports patents related to a method of identifying and treating a person having a predisposition to or afflicted with cardiometabolic disease (20180010185) and a genetics risk predictor (20190017119). D.K. accepts consulting fees from Regeneron Pharmaceuticals. D.O.M.-K. is a part-time clinical research consultant for Metabolon. D.S. has received support from the British Heart Foundation, Pfizer, Regeneron, Genentech and Eli Lilly pharmaceuticals. The spouse of C.J.W. is employed by Regeneron. Funding Information: Acknowledgements Funding for the Global Lipids Genetics Consortium was provided by the NIH (R01-HL127564). This research was conducted using the UK Biobank Resource under application number 24460. Computing support and file management for central meta-analysis by S. Caron is acknowledged. This research is based on data from the MVP, Office of Research and Development, Veterans Health Administration, and was supported by awards 2I01BX003362-03A1 and 1I01BX004821-01A1. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. Study-specific acknowledgements are provided in the Supplementary Information. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/12/23
Y1 - 2021/12/23
N2 - Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
AB - Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
UR - http://www.scopus.com/inward/record.url?scp=85121605114&partnerID=8YFLogxK
U2 - 10.1038/s41586-021-04064-3
DO - 10.1038/s41586-021-04064-3
M3 - Article
C2 - 34887591
AN - SCOPUS:85121605114
SN - 0028-0836
VL - 600
SP - 675
EP - 679
JO - Nature
JF - Nature
IS - 7890
ER -