Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations
Autoři:
Madeline H. Kowalski aff001; Huijun Qian aff002; Ziyi Hou aff003; Jonathan D. Rosen aff001; Amanda L. Tapia aff001; Yue Shan aff001; Deepti Jain aff004; Maria Argos aff005; Donna K. Arnett aff006; Christy Avery aff007; Kathleen C. Barnes aff008; Lewis C. Becker aff009; Stephanie A. Bien aff010; Joshua C. Bis aff011; John Blangero aff012; Eric Boerwinkle aff013; Donald W. Bowden aff015; Steve Buyske aff016; Jianwen Cai aff017; Michael H. Cho aff018; Seung Hoan Choi aff020; Hélène Choquet aff021; L. Adrienne Cupples aff022; Mary Cushman aff024; Michelle Daya aff008; Paul S. de Vries aff014; Patrick T. Ellinor aff020; Nauder Faraday aff009; Myriam Fornage aff026; Stacey Gabriel aff027; Santhi K. Ganesh aff028; Misa Graff aff007; Namrata Gupta aff027; Jiang He aff030; Susan R. Heckbert aff031; Bertha Hidalgo aff033; Chani J. Hodonsky aff007; Marguerite R. Irvin aff033; Andrew D. Johnson aff023; Eric Jorgenson aff021; Robert Kaplan aff035; Sharon L. R. Kardia aff036; Tanika N. Kelly aff030; Charles Kooperberg aff010; Jessica A. Lasky-Su aff018; Ruth J. F. Loos aff037; Steven A. Lubitz aff020; Rasika A. Mathias aff009; Caitlin P. McHugh aff004; Courtney Montgomery aff039; Jee-Young Moon aff035; Alanna C. Morrison aff014; Nicholette D. Palmer aff015; Nathan Pankratz aff040; George J. Papanicolaou aff041; Juan M. Peralta aff012; Patricia A. Peyser aff036; Stephen S. Rich aff042; Jerome I. Rotter aff043; Edwin K. Silverman aff018; Jennifer A. Smith aff044; Nicholas L. Smith aff031; Kent D. Taylor aff043; Timothy A. Thornton aff004; Hemant K. Tiwari aff046; Russell P. Tracy aff047; Tao Wang aff048; Scott T. Weiss aff018; Lu-Chen Weng aff020; Kerri L. Wiggins aff011; James G. Wilson aff049; Lisa R. Yanek aff009; Sebastian Zöllner aff050; Kari E. North aff007; Paul L. Auer aff053; ; ; Laura M. Raffield aff054; Alexander P. Reiner aff031; Yun Li aff001
Působiště autorů:
Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff001; Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff002; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
aff003; Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
aff004; Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, Illinois, United States of America
aff005; College of Public Health, University of Kentucky, Lexington, Kentucky, United States of America
aff006; Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff007; Department of Medicine, Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, United States of America
aff008; GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
aff009; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
aff010; Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
aff011; Department of Human Genetics and South Texas Diabetes Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas, United States of America
aff012; Human Genome Sequencing Center, University of Texas Health Science Center at Houston; Baylor College of Medicine, Houston, Texas, United States of America
aff013; Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
aff014; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
aff015; Department of Statistics, Rutgers University, Piscataway, New Jersey, United States of America
aff016; Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff017; Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
aff018; Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
aff019; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
aff020; Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
aff021; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
aff022; Framingham Heart Study, Framingham, Massachusetts, United States of America
aff023; Departments of Medicine & Pathology, Larner College of Medicine, University of Vermont, Colchester, Vermont, United States of America
aff024; Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America
aff025; School of Public Health, The University of Texas Health Science Center, Houston, Texas, United States of America
aff026; Genomics Platform, Broad Institute, Cambridge, Massachusetts, United States of America
aff027; Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
aff028; Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
aff029; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Los Angeles, United States of America
aff030; Department of Epidemiology, University of Washington, Seattle, Washington, United states of America
aff031; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, United States of America
aff032; Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
aff033; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, United States of America
aff034; Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
aff035; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
aff036; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
aff037; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
aff038; Department of Genes and Human Disease, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
aff039; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
aff040; National Heart, Lung, and Blood Institute, Division of Cardiovascular Sciences, PPSP/EB, NIH, Bethesda, Maryland, United States of America
aff041; Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
aff042; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
aff043; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
aff044; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, United States of America
aff045; Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
aff046; Departments of Pathology & Laboratory Medicine and Biochemistry, Larrner College of Medicine, University of Vermont, Colchester, Vermont, United States of America
aff047; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
aff048; Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
aff049; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
aff050; Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, United States of America
aff051; Carolina Center of Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
aff052; Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, United States of America
aff053; Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff054; Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, United States of America
aff055
Vyšlo v časopise:
Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations. PLoS Genet 15(12): e32767. doi:10.1371/journal.pgen.1008500
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008500
Souhrn
Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11–34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.
Klíčová slova:
Alleles – Consortia – Genome-wide association studies – Genotyping – Haplotypes – Hematology – Hemoglobin – Variant genotypes
Zdroje
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Štítky
Genetika Reprodukční medicínaČlánek vyšel v časopise
PLOS Genetics
2019 Číslo 12
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