title: Meta-Analysis of Rare Variant Association Tests in Multiethnic Populations.
abstract: Several methods have been proposed to increase power in rare variant association testing by aggregating information from individual rare variants (MAF < 0.005). However, how to best combine rare variants across multiple ethnicities and the relative performance of designs using different ethnic sampling fractions remains unknown. In this study, we compare the performance of several statistical approaches for assessing rare variant associations across multiple ethnicities. We also explore how different ethnic sampling fractions perform, including single-ethnicity studies and studies that sample up to four ethnicities. We conducted simulations based on targeted sequencing data from 4,611 women in four ethnicities (African, European, Japanese American, and Latina). As with single-ethnicity studies, burden tests had greater power when all causal rare variants were deleterious, and variance component-based tests had greater power when some causal rare variants were deleterious and some were protective. Multiethnic studies had greater power than single-ethnicity studies at many loci, with inclusion of African Americans providing the largest impact. On average, studies including African Americans had as much as 20% greater power than equivalently sized studies without African Americans. This suggests that association studies between rare variants and complex disease should consider including subjects from multiple ethnicities, with preference given to genetically diverse groups.
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Akweley
authors.initials: A
authors.lastname: Mensah-Ablorh
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Sara
authors.initials: S
authors.lastname: Lindstrom
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America.
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Haiman
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America.
authors.forename: Brian E
authors.initials: BE
authors.lastname: Henderson
authors.affiliation: Epidemiology Program, University of Hawaii Cancer Research Center, Honolulu, Hawaii, United States of America.
authors.forename: Loic Le
authors.initials: LL
authors.lastname: Marchand
authors.affiliation: Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, United States of America.
authors.forename: Seunngeun
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America.
authors.forename: Daniel O
authors.initials: DO
authors.lastname: Stram
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
authors.forename: A Heather
authors.initials: AH
authors.lastname: Eliassen
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Alkes
authors.initials: A
authors.lastname: Price
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Peter
authors.initials: P
authors.lastname: Kraft
mesh_terms: D001741:Black or African American / Q000235:genetics; D001213:Asian / Q000235:genetics; D044383:Black People / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics; D016022:Case-Control Studies; D005006:Ethnicity / Q000235:genetics*; D005260:Female; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D006630:Hispanic or Latino / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D017422:Sequence Analysis, DNA; D044465:White People / Q000235:genetics
keywords: fine mapping; multiethnic meta-analysis; sequencing study design; statistical genetics; study subject selection