HGG Advances (Jul 2021)
BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion
- Tamar Sofer,
- Jiwon Lee,
- Nuzulul Kurniansyah,
- Deepti Jain,
- Cecelia A. Laurie,
- Stephanie M. Gogarten,
- Matthew P. Conomos,
- Ben Heavner,
- Yao Hu,
- Charles Kooperberg,
- Jeffrey Haessler,
- Ramachandran S. Vasan,
- L. Adrienne Cupples,
- Brandon J. Coombes,
- Amanda Seyerle,
- Sina A. Gharib,
- Han Chen,
- Jeffrey R. O’Connell,
- Man Zhang,
- Daniel J. Gottlieb,
- Bruce M. Psaty,
- W.T. Longstreth, Jr.,
- Jerome I. Rotter,
- Kent D. Taylor,
- Stephen S. Rich,
- Xiuqing Guo,
- Eric Boerwinkle,
- Alanna C. Morrison,
- James S. Pankow,
- Andrew D. Johnson,
- Nathan Pankratz,
- Alex P. Reiner,
- Susan Redline,
- Nicholas L. Smith,
- Kenneth M. Rice,
- Elizabeth D. Schifano
Affiliations
- Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA; Corresponding author
- Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Cecelia A. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Stephanie M. Gogarten
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Matthew P. Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Ben Heavner
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Ramachandran S. Vasan
- Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
- L. Adrienne Cupples
- Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University, Boston, MA, USA
- Brandon J. Coombes
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Amanda Seyerle
- Division of Pharmaceutical Outcomes and Policy, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Sina A. Gharib
- Computational Medicine Core, Center for Lung Biology, Department of Medicine, University of Washington, Seattle, WA, USA
- Han Chen
- 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 Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Jeffrey R. O’Connell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Man Zhang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Daniel J. Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA; Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
- W.T. Longstreth, Jr.
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
- Jerome I. Rotter
- 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
- Kent D. Taylor
- 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
- Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Xiuqing Guo
- 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
- Eric Boerwinkle
- 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; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Alanna C. Morrison
- 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
- James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
- Andrew D. Johnson
- Framingham Heart Study, Framingham, MA, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA, USA
- Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
- Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Susan Redline
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Nicholas L. Smith
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
- Kenneth M. Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Elizabeth D. Schifano
- Department of Statistics, University of Connecticut, Storrs, CT, USA
- Journal volume & issue
-
Vol. 2,
no. 3
p. 100040
Abstract
Summary: Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
