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

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

^aDepartment of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
^bDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
^cVA Palo Alto Health Care System, Palo Alto, CA, USA
^dDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
^eWilliam Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
^fDepartment of Biostatistics and Center for Statistics Genetics, University of Michigan, Ann Arbor, MI, USA
^gDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
^hClinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
ⁱEndocrinology, Boston Children's Hospital, Boston, MA, USA
^jMedical and Population Genetics, Broad Institute, Cambridge, MA, USA
^kDepartment of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
^lMcDonnell Genome Institute and Department of Medicine, Washington University, St Louis, MO, USA
^mDepartment of Precision Medicine, Division of Genome Science, National Institute of Health, Cheongju-si, South Korea
ⁿTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
^oSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
^pCenter for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
^qBlizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
^rWellcome Sanger Institute, Hinxton, UK
^sAtlanta VA Health Care System, Decatur, GA, USA
^tDepartment of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
^uDivision of Vascular Surgery and Endovascular Therapy, University of Florida College of Medicine, Gainesville, FL, USA
^vMalcolm Randall VA Medical Center, Gainesville, FL, USA
^wProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
^xDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
^yDepartment of Statistics, Stanford University, Stanford, CA, USA
^zDepartment of Statistics, The Pennsylvania State University, University Park, PA, USA
^aaHuck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
^abdeCODE genetics/Amgen, Reykjavik, Iceland
^acSchool of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
^adDepartment of Clinical Biochemistry, Landspitali-National University Hospital of Iceland, Reykjavik, Iceland
^aeDepartment of Clinical Biochemistry, Landspitali–National University Hospital of Iceland, Reykjavik, Iceland

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. A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

TL;DRA genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size. (Semantic Scholar)

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

Abstract

Plain-language summary

Discussion