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

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机构： [1]Department of Clinical Acupuncture and Moxibustion, Nanjing University of Chinese Medicine, Nanjing, China [2]Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China [3]Institute for Advanced Research, Wenzhou Medical University, Wenzhou, China [4]Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China [5]Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China. [6]Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China. [7]Department of Epidemiology, School of Public Health, Peking University Health Science Center, Beijing, China [8]Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China [9]The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China [10]Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. [11]School of Medicine, Southern University of Science and Technology, Shenzhen, China. [12]Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, China [13]VA Palo Alto Health Care System, Palo Alto, CA, USA. [14]Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA. [15]Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA. [16]Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA [17]Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA [18]Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.

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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.© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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Q1 MULTIDISCIPLINARY SCIENCES

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Q1 MULTIDISCIPLINARY SCIENCES

影响因子： 50.5 最新[2023版] 54.4 最新五年平均 42.779 出版当年[2019版] 46.488 出版当年五年平均 43.07 出版前一年[2018版] 49.962 出版后一年[2020版]

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第一作者机构： [1]Department of Clinical Acupuncture and Moxibustion, Nanjing University of Chinese Medicine, Nanjing, China

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通讯机构： [13]VA Palo Alto Health Care System, Palo Alto, CA, USA. [14]Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA. [15]Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA. [16]Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA [17]Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA [18]Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.

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The power of genetic diversity in genome-wide association studies of lipids. $(function () { $("[data-toggle='tooltip']").tooltip(); });

文献详情

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