We are at the beginning of a revolution in medicine, in which a burgeoning knowledge of the genetics of disease promises treatments tailored to individual needs. But there is a big obstacle in the way: our failure to incorporate diverse, representative populations in our studies. The incomplete knowledge of the genetics of disease and treatment response across populations is not only affecting treatment outcomes for individuals 鈥� it is also hampering our understanding of the basic science.
Genetic research includes several types of studies. Recently, genome-wide association studies (GWAS), which use data sets comparing millions of genetic variants in those with a specific disease to those without it, have come to predominate. Environmental risks can also be included to paint a more complete picture of disease risk.
These types of studies have successfully identified many genetic variants that correlate with the likelihood of disease or treatment efficacy and safety. But they don鈥檛 always carry explanatory power across the whole population: GWAS findings often aren鈥檛 replicated across all ethnic groups. This makes it particularly important to have representative samples in such studies.
Advertisement
In a paper published in Cell, together with my colleagues Giorgio Sirugo and Sarah Tishkoff at the University of Pennsylvania, I analysed ethnic diversity in studies held in the jointly maintained by the US National Human Genome Research Institute and the European Bioinformatics Institute.
White and European
Over half of the GWAS had been conducted in populations of white European descent, far outweighing the proportion of the world鈥檚 population this group represents. When we looked at the numbers of individuals of different ethnicities within the studies, the findings were even more stark: more than 78 per cent were white European. Just 2 per cent were African and 1 per cent Hispanic.
There are many specific examples illustrating how this pattern fails to serve both basic science and clinical care. With the blood thinner warfarin, for instance, a set of genetic tests may be used to adjust dose. But how warfarin is metabolised varies across individuals and between ethnic groups. Dosing recommendations based on European-derived data may have grave consequences for people from different ethnic backgrounds.
What are the solutions? Researchers, as well as funders, need to allocate the resources necessary to include diverse populations in their studies. That will require outreach and education among populations that historically have been underserved by medical research to help people understand how their data are used and to allay concerns about research ethics and personal privacy.
We will also need to broaden and strengthen collaborations around the world to develop the scientific and intellectual resources needed to increase inclusion in human genetic studies. The falling cost of genome sequencing is allowing us to become truly inclusive in genetic studies. The reality on the ground must now catch up.
Cell
