Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

The power of genetic diversity in genome-wide association studies of lipids

Sarah E. Graham, Shoa L. Clarke, Kuan-Han H. Wu, Stavroula Kanoni, Greg J. M. Zajac, Shweta Ramdas, Ida Surakka, Ioanna Ntalla, Sailaja Vedantam, Thomas W. Winkler, Adam E. Locke, Eirini Marouli, Mi Yeong Hwang, Sohee Han, Akira Narita, Ananyo Choudhury, Amy R. Bentley, Kenneth Ekoru, Anurag Verma, Bhavi Trivedi, Hilary C. Martin, Karen A. Hunt, Qin Hui, Derek Klarin, Xiang Zhu, Gudmar Thorleifsson, Anna Helgadóttir, Daníel F. Guðbjartsson, Hilma Hólm, Isleifur Olafsson, Masato Akiyama, Saori Sakaue, Chikashi Terao, Masahiro Kanai, Wei Zhou, Ben Brumpton, Humaira Rasheed, Sanni Ruotsalainen, Aki S. Havulinna, Yogasudha Veturi, QiPing Feng, Elisabeth A. Rosenthal, Todd Lingren, Jennifer A. Pacheco, Sarah A. Pendergrass, Jeffrey Haessler, Franco Giulianini, Yuki Bradford, Jason E. Miller, Archie Campbell, Kuang Lin, Iona Y. Millwood, George Hindy, Asif Rasheed, Jessica D. Faul, Wei Zhao, David R. Weir, Constance Turman, Hongyan Huang, Mariaelisa Graff, Anubha Mahajan, Michael R. Brown, Weihua Zhang, Ketian Yu, Ellen M. Schmidt, Anita Pandit, Stefan Gustafsson, Xianyong Yin, Jian’an Luan, Jing-Hua Zhao, Fumihiko Matsuda, Hye-Mi Jang, Kyungheon Yoon, Carolina Medina‐Gómez, Achilleas Pitsillides, Jouke‐Jan Hottenga, Gonneke Willemsen, Andrew R. Wood, Yingji Ji, Zishan Gao, Simon Haworth, Ruth E. Mitchell, Jin Fang Chai, Mette Aadahl, Jie Yao, Ani Manichaikul, Helen R. Warren, Julia Ramírez, Jette Bork‐Jensen, Line Lund Kårhus, Anuj Goel, Maria Sabater‐Lleal, Raymond Noordam, Carlo Sidore, Edoardo Fiorillo, Aaron F. McDaid, Pedro Marques‐Vidal, Matthias Wielscher, Stella Trompet, Naveed Sattar

Nature · 2021

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Summary

This large-scale genome-wide association meta-analysis leveraged ancestral diversity to identify and refine genetic variants associated with circulating lipid levels. By including non-European ancestry participants alongside European cohorts, the study demonstrated that genetic diversity substantially improves the power to detect lipid-associated loci and characterises the generalisability of findings across populations. The work suggests that inclusive study design strengthens the biological and clinical utility of genetic discovery in cardiometabolic traits.

Regional applicability

The findings are relevant to UK clinical genomics and cardiovascular risk stratification, though direct applicability depends on the ancestry composition of UK biobanks and NHS genomic medicine programmes. Improved lipid-associated variant discovery may refine polygenic risk scores for dyslipidaemia in diverse UK populations.

Key measures

Genome-wide association study signals for total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and apolipoprotein variants; ancestry-specific and cross-ancestry effect sizes

Outcomes reported

The study identified genetic variants associated with lipid traits (cholesterol, triglycerides, HDL, LDL) using genome-wide association studies in a large, ancestrally diverse population cohort. The research examined how genetic diversity improves the discovery and characterisation of lipid-associated loci.

Theme
Nutrition & health
Subject
Dietary fats & fatty acids
Study type
Meta-analysis
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Human clinical
DOI
10.1038/s41586-021-04064-3
Catalogue ID
SNmois85jd-kz1dx7

Topic tags

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