Bias Complicates the Role of Genomics in Biomedical Research
Researchers gathered to discuss how the use of genomic data can create healthcare disparities.
Bias with regard to race and ethnicity is a concern with genomic information, and scientists and medical journal editors must tackle how to report on human genomic variation without describing racial and ethnic groups inappropriately as discrete population groups, according to an opinion piece published in JAMA.
Vence L. Bonham, JD, of the National Human Genome Research Institute (NHGRI) at the National Institutes of Health in Bethesda, Maryland, and colleagues explained how, while advances in genomics have provided medical science with a better understanding of many diseases, the inaccurate use of race and ethnicity data as population descriptors in genomics research has the potential to misconstrue the complex interrelationships between social identity, ancestry, socioeconomic status and health. This may perpetuate the misconception that there are discrete population groups that can be identified genetically.
In an effort to remedy this situation, the NHGRI and the National Institute on Minority Health and Health Disparities (NIMHD) organized a workshop in 2016 to discuss the use of self-identified race and ethnicity data in genomics, biomedical, and clinical research, as well as the potential consequences of such use for minority health and disparities in health.
The consensus was that scientists must be rigorous in collecting data on race and ethnicity and ensure that such data reflect the complex nature of an individual's identity, especially with regard to race, ethnicity, socioeconomic status, and geographic ancestry.
The authors noted that some researchers use race and ethnicity as surrogate markers for inferring disease risk; however at the individual level, population level risks may not be relevant and offer little guidance on appropriate treatment. Furthermore, populations with a significant admixture of different groups such as Latinos cannot easily be classified racially. Another issue is that genome-wide association studies, which are designed to explore the relationship between genomic variants and complex diseases, are usually made using populations of European ancestry.
Mr Bonham and colleagues contended that to understand the human genome more fully, participation of people from all population groups is necessary. They call upon those with “expertise to identify common ground and to help the public understand the rich diversity and common history of humankind.”