Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.,Nature Genetics

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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.
Nature Genetics ( IF 30.8 ) Pub Date : 2020-08-24 , DOI: 10.1038/s41588-020-0676-4
Xihao Li ₁ , Zilin Li ₁ , Hufeng Zhou ₁ , Sheila M Gaynor ₁ , Yaowu Liu ₂ , Han Chen _{3,

4} , Ryan Sun ₅ , Rounak Dey ₁ , Donna K Arnett ₆ , Stella Aslibekyan ₇ , Christie M Ballantyne ₈ , Lawrence F Bielak ₉ , John Blangero ₁₀ , Eric Boerwinkle _{3,

11} , Donald W Bowden ₁₂ , Jai G Broome ₁₃ , Matthew P Conomos ₁₄ , Adolfo Correa ₁₅ , L Adrienne Cupples _{16,

17} , Joanne E Curran ₁₀ , Barry I Freedman ₁₈ , Xiuqing Guo ₁₉ , George Hindy ₂₀ , Marguerite R Irvin ₇ , Sharon L R Kardia ₉ , Sekar Kathiresan _{21,

22,

23} , Alyna T Khan ₁₄ , Charles L Kooperberg ₂₄ , Cathy C Laurie ₁₄ , X Shirley Liu _{25,

26} , Michael C Mahaney ₁₀ , Ani W Manichaikul ₂₇ , Lisa W Martin ₂₈ , Rasika A Mathias ₂₉ , Stephen T McGarvey ₃₀ , Braxton D Mitchell _{31,

32} , May E Montasser ₃₃ , Jill E Moore ₃₄ , Alanna C Morrison ₃ , Jeffrey R O'Connell ₃₁ , Nicholette D Palmer ₁₂ , Akhil Pampana _{35,

36} , Juan M Peralta ₁₀ , Patricia A Peyser ₉ , Bruce M Psaty _{37,

38} , Susan Redline _{39,

40,

41} , Kenneth M Rice ₁₄ , Stephen S Rich ₂₇ , Jennifer A Smith _{9,

42} , Hemant K Tiwari ₄₃ , Michael Y Tsai ₄₄ , Ramachandran S Vasan _{17,

45} , Fei Fei Wang ₁₄ , Daniel E Weeks ₄₆ , Zhiping Weng ₃₄ , James G Wilson _{47,

48} , Lisa R Yanek ₂₉ , , , Benjamin M Neale _{35,

49,

50} , Shamil R Sunyaev _{35,

51,

52} , Gonçalo R Abecasis _{53,

54} , Jerome I Rotter ₁₉ , Cristen J Willer _{55,

56,

57} , Gina M Peloso ₁₆ , Pradeep Natarajan _{23,

35,

36} , Xihong Lin _{1,

26,

35}

Affiliation

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
School of Statistics, Southwestern University of Finance and Economics, Chengdu, China.
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.
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.
Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
College of Public Health, University of Kentucky, Lexington, KY, USA.
Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA.
Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Division of Medical Genetics, University of Washington, Seattle, WA, USA.
Department of Biostatistics, University of Washington, Seattle, WA, USA.
Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Framingham Heart Study, National Heart, Lung, and Blood Institute and Boston University, Framingham, MA, USA.
Department of Internal Medicine, Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
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.
Department of Population Medicine, Qatar University College of Medicine, QU Health, Doha, Qatar.
Verve Therapeutics, Cambridge, MA, USA.
Cardiology Division, Massachusetts General Hospital, Boston, MA, USA.
Department of Medicine, Harvard Medical School, Boston, MA, USA.
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Department of Statistics, Harvard University, Cambridge, MA, USA.
Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.
Division of Cardiology, George Washington School of Medicine and Health Sciences, Washington, DC, USA.
GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Department of Epidemiology, International Health Institute, Department of Anthropology, Brown University, Providence, RI, USA.
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Geriatrics Research and Education Clinical Center, Baltimore VA Medical Center, Baltimore, MD, USA.
Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA.
Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.
Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Department of Human Genetics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA.
Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.

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.

中文翻译：

多个计算机功能注释的动态整合使得大规模全基因组测序研究的罕见变异关联分析成为可能。

大规模全基因组测序研究使得能够分析与复杂表型相关的罕见变异（RV）。常用的 RV 关联测试利用变体功能的范围有限。我们提出了 STAAR（使用注释信息进行关联的变体集测试），这是一种可扩展且强大的 RV 关联测试方法，它使用动态加权方案有效地结合了变体类别和多个互补注释。对于后者，我们引入“注释主成分”，即计算机变体注释的多维摘要。STAAR 考虑了群体结构和相关性，并且可扩展用于分析连续和二分性状的大型队列和生物库全基因组测序研究。我们应用 STAAR 在精准医学跨组学计划的 12,316 个发现样本和 17,822 个复制样本中识别了与四种脂质特征相关的 RV。我们发现并复制了新的 RV 关联，包括NPC1L1的破坏性错义 RV以及APOC1P1附近与低密度脂蛋白胆固醇相关的基因间区域。

更新日期：2020-08-24

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