Chipping away at disparities in genetic studies

Science Spotlight

Chipping away at disparities in genetic studies

From the Carlson Lab, Public Health Sciences Division.

Feb. 20, 2017

To date, the majority of genotyping platforms have been designed to capture genetic variation that is most commonly found among people of European ancestry. While the data generated by these platforms has led to many successful discoveries, these tools may be less effective for diverse populations. Genetic heterogeneity in disease loci across populations can mean that previous findings in European-ancestry populations could potentially be less relevant in other ancestral groups. On the other hand, transethnic studies can be highly beneficial for driving understanding of underlying disease etiology. To enable such research in multiethnic populations, Dr. Stephanie Bien, along with Dr. Chris Carlson and colleagues in the Public Health Sciences Division, developed a new custom-content genotyping array specifically designed to capture genetic variation expected to be associated with disease. As recently reported in PLoS One, this new array should be highly useful for driving future insights into the genetic architecture of complex disease in multiethnic populations.

Initial genome-wide genotyping arrays were designed to prioritize capturing common genetic variation in populations of European ancestry and allow efficient imputation of variant reference panels derived from large sets of European-descent controls. Such focus on homogeneous populations was partially done to help prevent spurious findings that could result from population stratification. While initially successful, this approach has also limited investigations into genetic contributions to disease in multiethnic populations. Such populations often have greater genetic diversity and less linkage disequilibrium among variants, meaning that variants identified in European-descent populations may not be equally representative of disease risk in other populations. This can mean not only decreased ability to evaluate genetic loci, but also the potential exacerbation of existing health disparities in many complex diseases.

Besides equity, there are many scientifically beneficial reasons to conduct genetic analyses in multiethnic populations. Because of differing patterns of genetic architecture between ancestral backgrounds, comparing linkage disequilibrium values in a region can help hone in on which variants are more likely to be causal for a particular disease or trait. Such findings can drive rich insights into the underlying biology of complex disease that would not be possible in single populations, and may lead to improved risk modeling across diverse populations.

It was for these reasons that the Population Architecture using Genomics and Epidemiology (PAGE) study investigators designed the Multi-Ethnic Genotyping Array (MEGA), a custom-content Illumina platform with improved variant coverage across multiple ethnicities. To enable both fine-mapping and discovery analyses, the chip content consists of both a genome-wide backbone and PAGE hand-curated custom content. This content of the chip prioritized coverage at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits which are well-represented in the PAGE study population. This custom content includes variants identified from databases of known disease associations, functional regulatory variants, clinically important variants, and variants in candidate biological pathways.

Having developed this chip, the PAGE study is now moving rapidly into evaluating genetic associations with various diseases in their large multiethnic study populations. A consortium of studies across the United States, the PAGE study is using this chip to evaluate genetic associations with multiple diseases in over 50,000 African American, American Indian, Asian/Pacific Islander, and Hispanic/Latino participants. These investigations are expected to generate important insights and a deeper biological understanding of the genetic etiology of many complex diseases, including diabetes, stroke, obesity, and cardiovascular disease. Just as importantly, said lead author Bien, “these and future studies using data generated from this new assay should help ensure that all ethnic/racial groups stand to benefit from genetic research.”

Also contributing to this project from the Fred Hutch were Drs. Charles Kooperberg, Ulrike Peters, Jonathan Kocarnik, Niha Zubair, and Jeffrey Haessler.



Bien SA, Wojcik GL, Zubair N, Gignoux CR, Martin AR, Kocarnik JM, Martin LW, Buyske S, Haessler J, Walker RW, Cheng I, Graff M, Xia L, Franceschini N, Matise T, James R, Hindorff L, Le Marchand L, North KE, Haiman CA, Peters U, Loos RJ, Kooperberg CL, Bustamante CD, Kenny EE, Carlson CS; PAGE Study. Strategies for enriching variant coverage in candidate disease loci on a multiethnic genotyping array. PLoS One 2016; 11(12):e0167758. doi: 10.1371/journal.pone.0167758.



Funding for this study was provided by the National Institutes of Health (NCI, NHGRI, NHLBI, NINDS).



Types of content on the assay

Genetic variant allocation used for the design of the Multi-Ethnic Genotyping Array (MEGA), consisting of either genome-wide backbone or hand-curated custom content.

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