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Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.
Li, Xihao; Li, Zilin; Zhou, Hufeng; Gaynor, Sheila M; Liu, Yaowu; Chen, Han; Sun, Ryan; Dey, Rounak; Arnett, Donna K; Aslibekyan, Stella; Ballantyne, Christie M; Bielak, Lawrence F; Blangero, John; Boerwinkle, Eric; Bowden, Donald W; Broome, Jai G; Conomos, Matthew P; Correa, Adolfo; Cupples, L Adrienne; Curran, Joanne E; Freedman, Barry I; Guo, Xiuqing; Hindy, George; Irvin, Marguerite R; Kardia, Sharon L R; Kathiresan, Sekar; Khan, Alyna T; Kooperberg, Charles L; Laurie, Cathy C; Liu, X Shirley; Mahaney, Michael C; Manichaikul, Ani W; Martin, Lisa W; Mathias, Rasika A; McGarvey, Stephen T; Mitchell, Braxton D; Montasser, May E; Moore, Jill E; Morrison, Alanna C; O'Connell, Jeffrey R; Palmer, Nicholette D; Pampana, Akhil; Peralta, Juan M; Peyser, Patricia A; Psaty, Bruce M; Redline, Susan; Rice, Kenneth M; Rich, Stephen S; Smith, Jennifer A; Tiwari, Hemant K.
Afiliação
  • Li X; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Li Z; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Zhou H; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Gaynor SM; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Liu Y; School of Statistics, Southwestern University of Finance and Economics, Chengdu, China.
  • Chen H; 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, TX, USA.
  • Sun R; Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Dey R; Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Arnett DK; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Aslibekyan S; College of Public Health, University of Kentucky, Lexington, KY, USA.
  • Ballantyne CM; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Bielak LF; Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
  • Blangero J; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
  • Boerwinkle E; Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA.
  • Bowden DW; 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, TX, USA.
  • Broome JG; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
  • Conomos MP; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
  • Correa A; Division of Medical Genetics, University of Washington, Seattle, WA, USA.
  • Cupples LA; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Curran JE; Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
  • Freedman BI; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • Guo X; Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, MA, USA.
  • Hindy G; Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA.
  • Irvin MR; Department of Internal Medicine, Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Kardia SLR; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Kathiresan S; Department of Population Medicine, Qatar University College of Medicine, QU Health, Doha, Qatar.
  • Khan AT; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Kooperberg CL; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
  • Laurie CC; Verve Therapeutics, Cambridge, MA, USA.
  • Liu XS; Cardiology Division, Massachusetts General Hospital, Boston, MA, USA.
  • Mahaney MC; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Manichaikul AW; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Martin LW; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Mathias RA; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • McGarvey ST; Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Mitchell BD; Department of Statistics, Harvard University, Cambridge, MA, USA.
  • Montasser ME; Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA.
  • Moore JE; Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
  • Morrison AC; Division of Cardiology, George Washington School of Medicine and Health Sciences, Washington, DC, USA.
  • O'Connell JR; GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Palmer ND; Department of Epidemiology, International Health Institute, Department of Anthropology, Brown University, Providence, RI, USA.
  • Pampana A; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Peralta JM; Geriatrics Research and Education Clinical Center, Baltimore VA Medical Center, Baltimore, MD, USA.
  • Peyser PA; Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Psaty BM; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
  • Redline S; 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, TX, USA.
  • Rice KM; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Rich SS; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
  • Smith JA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Tiwari HK; Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
Nat Genet ; 52(9): 969-983, 2020 09.
Article em En | MEDLINE | ID: mdl-32839606
ABSTRACT
Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma / Predisposição Genética para Doença Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma / Predisposição Genética para Doença Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article