Is Precision Medicine All That Precise?

Authored by: Charlene Lin

Art by: Fiona Reilly

Precision medicine, also known as personalized medicine, is a revolutionary approach that tailors medicine to genetic factors, environment, lifestyle, and many more [1]. But what if I told you that many personalized treatments are only precise for people of European descent? Genome-wide association studies (GWAS) are at the very core of precision medicine approaches, in which large scale biobank data is used to identify genetic differences linked to genetic risk [1]. It turns out that ethnic bias remains prevalent within the realm of medicine, and not in the way one might think. Unlike the inequalities in healthcare we would typically think of, ethnic bias in precision medicine refers to the fact that genetic data used for GWAS are sourced primarily from European populations. As a result, there is a lack of representation from other populations. 

Eurocentric genetic data, which includes people from Iceland, the UK, and the US, account for 86.5% of participants in the 2023 GWAS Catalog [2]. The association results, which are essential to the development of personalized drug treatment, have deeper clinical implications. Previous research has revealed that there are important differences between populations of different ancestral origins [2]. Such differences include genetics, rates of disease susceptibility, and fundamental lifestyle choices. Given the variety of factors that must be considered, genetic models built off of European populations usually do not work as well for people of Asian, African, or other ancestral backgrounds. In fact, people of African and Asian descent are more likely than people of European descent to receive ambiguous results in their genetic tests. In addition, people of African descent are more likely to receive false positives for a life-threatening heart condition known as hypertrophic cardiomyopathy [3]. There may even be drugs developed that work negatively in non-European populations. Naturally, this would be incredibly frustrating and anxiety-inducing, and the continual use of solely European genetic data sets would be, quite frankly, unethical. Thus, it is extremely important to collect data from people of non-European backgrounds.

Important work has already been done through the Taiwan Precision Medicine Initiative in Taiwan. Taiwan's relatively homogeneous population background, national health insurance, and advanced medical system make it an ideal place for innovation in the field of precision medicine. As one of the largest precision medicine cohorts in East Asia, its efforts to collect comprehensive data from individuals in Taiwan are an outstanding model for propelling precision medicine innovations tailored to specific populations beyond European ones [4].

In addition to Taiwanese populations, African populations are another especially important group to collect data from. Due to their demographic diversity and lengthy evolutionary history, the lack of African genetic representation in genomic research data is a missing piece that needs to be remedied. Although the COVID-19 pandemic disrupted genomic studies as efforts were centralized to fight the respiratory disease, the spotlight on African healthcare drew attention to the severe deficiency of genomic studies in Africa [5]. As a result, different African countries and scientists began sharing data, leading to improved genomic research and analysis capabilities. Through initiatives like H3Africa and collaborations with the biotechnology company Illumina, Africa has seen rapid development in the area of precision medicine [5]. The development of a 2.3 M SNP H3Africa genotyping chip allowed for the conduction of GWAS in African populations [5].

Ultimately, precision medicine has enormous potential. However, it cannot be called precise if it paves the way for treatments for only a very specific population. If precision medicine is to be truly precise, it should cater to every population. There should be incentives in place to obtain genetic data that reflect the amazing diversity of the human population.

References:

1. Evans, W., Meslin, E. M., Kai, J., & Qureshi, N. (2024). Precision medicine—Are we there yet? A narrative review of precision medicine’s applicability in primary care. Journal of Personalized Medicine, 14(4), 418. https://doi.org/10.3390/jpm14040418

2. Corpas, M., Pius, M., Poburennaya, M., Guio, H., Dwek, M., Nagaraj, S., Lopez-Correa, C., Popejoy, A., & Fatumo, S. (2025). Bridging genomics’ greatest challenge: The diversity gap. Cell Genomics, 5(1), Article 100724. https://doi.org/10.1016/j.xgen.2024.100724 

3. Popejoy, A. B., & Fullerton, S. M. (2016). Genomics is failing on diversity. Nature, 538(7624), 161–164. https://doi.org/10.1038/538161 

4. Yang, H.-C., Kwok, P.-Y., Li, L.-H., et al. (2025). The Taiwan Precision Medicine Initiative provides a cohort for large-scale studies. Nature, 648, 117–127. https://doi.org/10.1038/s41586-025-09680-x

5. Ojewunmi, O. O., & Fatumo, S. (2025). Driving global health equity and precision medicine through African genomic data. Human Molecular Genetics. Advance online publication. https://doi.org/10.1093/hmg/ddaf025