Strategies for Enriching Variant Coverage in Candidate Disease Loci on a Multiethnic Genotyping Array

Abstract

Investigating genetic architecture of complex traits in ancestrally diverse populations is imperative to understand the etiology of disease. However, the current paucity of genetic research in people of African and Latin American ancestry, Hispanic and indigenous peoples in the United States is likely to exacerbate existing health disparities for many common diseases. The Population Architecture using Genomics and Epidemiology, Phase II (PAGE II), Study was initiated in 2013 by the National Human Genome Research Institute to expand our understanding of complex trait loci in ethnically diverse and well characterized study populations. To meet this goal, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially improve fine-mapping and functional discovery by increasing variant coverage across multiple ethnicities at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits. Studying the frequency distribution of clinically relevant mutations, putative risk alleles, and known functional variants across multiple populations will provide important insight into the genetic architecture of complex diseases and facilitate the discovery of novel, sometimes population-specific, disease associations. DNA samples from 51,650 self-identified African ancestry (17,328), Hispanic/Latino (22,379), Asian/Pacific Islander (8,640), and American Indian (653) and an additional 2,650 participants of either South Asian or European ancestry, and other reference panels have been genotyped on MEGA by PAGE II. MEGA was designed as a new resource for studying ancestrally diverse populations. Here, we describe the methodology for selecting trait-specific content for use in multi-ethnic populations and how enriching MEGA for this content may contribute to deeper biological understanding of the genetic etiology of complex disease.

Ancestry‐specific and sex‐specific risk alleles identified in a genome‐wide gene‐by‐alcohol dependence interaction study of risky sexual behaviors

“…Additionally, our results support that future studies should be specifically designed to take ancestry-specific and sex-specific genetic associations into account. The use of newer genotyping arrays with better representation of different population groups and updated imputation reference panels can permit us to improve the coverage in ethnically diverse samples significantly, increasing the statistical power of future multi-ancestry analysis [Bien et al, 2016]. The inclusion of sex chromosomes in GWAS is highly desirable but not straightforward; it requires the application of specific analytic approaches to overcome complications in genotype calling, imputation, and selection of test statistics.…”

The Advantages and Challenges of Diversity in Pharmacogenomics: Can Minority Populations Bring Us Closer to Implementation?

“…The Population Architecture Using Genomics and Epidemiology, Phase II (PAGE II) was initiated by the National Human Genome Research Institute to expand our understanding of complex trait loci in diverse ancestral populations. Toward this effort, the Multi‐Ethnic Genotyping Array (MEGA) was designed to substantially increase variant coverage across multiple ethnicities that would improve fine mapping and functional discovery of clinically relevant mutations and uncover novel, population‐specific, disease associations . Genome‐wide SNP panels have continued to improve their coverage of genetic variation in populations outside of Europe.…”

“…Toward this effort, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially increase variant coverage across multiple ethnicities that would improve fine mapping and functional discovery of clinically relevant mutations and uncover novel, population-specific, disease associations. 89 Genome-wide SNP panels have continued to improve their coverage of genetic variation in populations outside of Europe. This effort was specifically highlighted in the work of H3Africa and the Wellcome Trust, which developed a pan-African genotyping array.…”

Genetics of Obesity in Diverse Populations

“…A commercial version of the MEGA array is now available. [45] For the MEGA analysis, PAGE collated and harmonized data from a subset of the PAGE MetaboChip samples, including: The Coronary Artery Risk Development in Young Adults Study (CARDIA), The Hispanic Community Health Study/Study of Latinos (HCHS/SOL), The Multiethnic Cohort Study (MEC), and the Women’s Health Initiative (WHI), and added data from the Mount Sinai BioMe BioBank (BioMe)(Table 1). PAGE Investigators also developed new statistical methods to analyze genetic data from admixed populations, as well as handle cryptic relatedness and complex sampling designs.…”