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Genetic Risk Analysis Shows Ethnic Bias

DNA puzzle

(Arek Socha, Pixabay)

29 Mar. 2019. Techniques analyzing data from across the genome that reveal risks of diseases, better predict disorders in the main ethnicity of the population studied than other ethnic groups. A team from the Broad Institute, a genetic research center affiliated with Harvard and MIT, and Massachusetts General Hospital in Boston, reports its findings in today’s issue of the journal Nature Genetics (paid subscription required).

The team led by population geneticist and postdoctoral researcher Alicia Martin at Mass. General is investigating health disparities in an emerging analytical technique called polygenic risk scoring. This technique takes advantage of large data sets and the availability of powerful new analytical tools that allow for exploring common genetic variants found throughout the genome, rather than looking for specific mutations in an individual gene indicating a risk of disease. These polygenic risks scores are believed to to reveal susceptibility for developing common conditions such as heart disease, type 2 diabetes, and breast cancer, which allow for early interventions possibly preventing those disorders later on.

Even as genetic testing becomes easier to do and less expensive for larger numbers of people, many genetic data sets are believed to represent mainly Europeans or people of European descent. A report on ethnic participation in genome-wide analyses show as of 2016, 8 in 10 participants in genetic studies are of European descent, an improvement from a similar inquiry in 2009 showing 96 percent are of European ethnicity, while Europeans still comprise only about 16 percent of the world’s population.

For example, colleagues from Broad Institute and others conducted a study of polygenic risk scoring published in August 2018, calculating scores showing a threefold increased in risks of coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer each affecting from 1.5 to 8 percent of the population. Data from the analysis were drawn from the U.K. Biobank, with genomic data from some 500,000 participants in the U.K. collected between 2006 and 2010. Earlier this month, Science & Enterprise reported on one of the first reports of disease associations from the U.K. Biobank.

However, data from the U.K. Biobank represent by and large (94%) people of European descent. Fewer than 1 in 10 come from other ethnicities, including African, South Asian, East Asian, and Hispanic, or Latino heritage.

In their new study, Martin and colleagues demonstrate that these biases may not inherently favor one ethnicity over another, as much as reflect the nature of ethnicity in the population being studied. The Mass. General – Broad Institute team analyzed data from a similar genomic project called BioBank Japan, collecting data from 200,000 participants between 2003 and 2007, with reports from those data continuing today. Comparing polygenic risk scores derived from the two data sets, the researchers found BioBank Japan data predict disease risks almost 50 percent more accurately for people of East Asian descent than data from U.K. Biobank.

“This further confirms that risk predictors are more precise if they are drawn from genetic data derived from a similar ancestry,” says Martin in a Broad Institute statement. “It is crucial that researchers should recruit more minority populations in future genetic studies and also make data from such studies accessible and open.” Martin adds that without taking these steps, genomic studies could lead to further disparities in the health care system.

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