The DNA of any two human beings is 99.9 percent identical, with only a 0.1% of difference. While that percentage seems unbelievably small, it is in fact representative of a relatively large number of base pairs. 

The human genome has roughly 3.2 billion base pairs, meaning that 0.1% is equivalent to roughly 3.2 million base pairs.

3.2 million opportunities for mutations.

3.2 million opportunities for genetic variation.

3.2 million opportunities for geneticists to understand how biological makeup interacts with environmental factors.

These opportunities have not been seized, however, because research on these genetic variations centers around those of European descent, therefore ignoring the wealth of information found in the DNA of those of African descent, Asian descent, Pacific Islander descent, etc. This oversight is not one to be taken lightly: it has severe repercussions on the validity of past genetic studies, public health, and has stagnated the evolution of genetic research.

It is important to note that genetics cannot divide a population into racial subcategories. Instead, the social concept of “race” is generally dependent on phenotypic features like skin color, eye color, facial structure, etc. There are relatively few genes that control said features and therefore are susceptible to change in response to extreme environmental pressure. Many will latch onto this blur between race and genetics stating that since there are no clear racial subcategories the research performed by one population should apply to another. However, this is a harmful generalization because it excludes the effect ancestry has on epigenetic changes, genetic drift, and various environmental pressures.

For example, a study conducted in 2017 discovered that a mutation in the PCSK9 gene, which regulates cholesterol levels, was recurring in a population of those with African descent while nominal in white populations. This mutation in particular increased anti-PCSK9 antibodies which significantly lowered the risk of LDL cholesterol and coronary heart disease. The specific reason for this discrepancy is thought to be in response to extreme environmental factors like malaria or even genetic drift. Whatever the cause, this study is a remarkable breakthrough for a wide range of patients who are at high cardiovascular risk and/or cannot achieve LDL-C ideal values with current drugs.

This study shows the value of expanding genetic research into less represented populations. By simply expanding their interest group to African Americans, they were able to uncover a potential treatment of LDL cholesterol that would benefit all individuals.

Contrastingly, the present racial bias in genetic research has led to severe risks in public health, specifically targeting those in underrepresented communities. Pharmacogenetics is a promising new field of research where genetics can inform a physician’s prescription of medication. However, many of the genotype-guided algorithms used are based on data from volunteers of European descent: a dangerously narrow scope. For example, in one study consisting of 274 African American patients, one of those algorithms consistently prescribed too much warfarin, resulting in a high risk of uncontrolled bleeding but worked relatively well for white populations.

This lack of diversity does not only affect prescription: it affects initial diagnosis as well. One study looked at the results of the diagnosis for hypertrophic cardiomyopathy in populations of both European and African descent. Some of the pathogenic variants for this condition were found at an unusually high frequency in the African American general population. Yet, these variants were misclassified due to their scarcity among white populations. These misclassifications severely affect one’s quality of life and could have been prevented by simply sequencing the genomes of more diverse populations.

In light of these misclassifications and lack of representation, it has become clear that genetic information/studies that rely on genomic sequencing of DNA from those of European descent are not reliable for a diverse population.  Whether it be due to the aforementioned cases or the infamous Tuskegee study, minorities all over the world have lost faith in biological research, a harsh reality that is even more dangerous during this global pandemic. It is high time that the medical community stops with false promises of inclusivity and empty legislation (e.g. NIH Revitalization Act of 1993 Public Law 103-43) and truly makes an effort to collect genomic data outside of the US and Europe. While there are difficulties that accompany this endeavor, e.g. lack of proper funding or medical care facilities in developing countries, it must be done- for the sake of public health and the evolution of genetics as a whole.

Works Cited

ASHG Denounces Attempts to Link Genetics and Racial Supremacy. (2018). American journal of human genetics, 103(5), 636. doi.org/10.1016/j.ajhg.2018.10.011 

Bentley, A. R., Callier, S., & Rotimi, C. N. (2017). Diversity and inclusion in genomic research: why the uneven progress?. Journal of community genetics, 8(4), 255–266. doi.org/10.1007/s12687-017-0316-6 

Briggs, S. (2017). Genetics has proven that you’re unique—just like everyone else. Quartz. Retrieved 2 March 2021, from

Chou, V. (2017). How Science and Genetics are Reshaping the Race Debate of the 21st Century - Science in the News. Science in the News. Retrieved 2 March 2021, from sitn.hms.harvard.edu/flash/2017/science-genetics-reshaping-race-debate-21st-century/

Drozda, K., Wong, S., Patel, S. R., Bress, A. P., Nutescu, E. A., Kittles, R. A., & Cavallari, L. H. (2015). Poor warfarin dose prediction with pharmacogenetic algorithms that exclude genotypes important for African Americans. Pharmacogenetics and genomics, 25(2), 73–81. doi.org/10.1097/FPC.0000000000000108

Horvath, S., Gurven, M., Levine, M. E., Trumble, B. C., Kaplan, H., Allayee, H., Ritz, B. R., Chen, B., Lu, A. T., Rickabaugh, T. M., Jamieson, B. D., Sun, D., Li, S., Chen, W., Quintana-Murci, L., Fagny, M., Kobor, M. S., Tsao, P. S., Reiner, A. P., Edlefsen, K. L., … Assimes, T. L. (2016). An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome biology, 17(1), 171. doi.org/10.1186/s13059-016-1030-0 

Jaworski, K., Jankowski, P., & Kosior, D. A. (2017). PCSK9 inhibitors - from discovery of a single mutation to a groundbreaking therapy of lipid disorders in one decade. Archives of medical science : AMS, 13(4), 914–929. doi.org/10.5114/aoms.2017.65239

Manrai, A. K., Funke, B. H., Rehm, H. L., Olesen, M. S., Maron, B. A., Szolovits, P., Margulies, D. M., Loscalzo, J., & Kohane, I. S. (2016). Genetic Misdiagnoses and the Potential for Health Disparities. The New England journal of medicine, 375(7), 655–665. doi.org/10.1056/NEJMsa1507092 

Stein, V. (2019). Genetic research has a white bias, and it may be hurting everyone's health. PBS NewsHour. Retrieved 2 March 2021, from pbs.org/newshour/science/genetic-research-has-a-white-bias-and-it-may-be-hurting-everyones-health.