Examining the clinical relevance of variants in the genomes of Singaporean individuals from different ancestral groups has increased our understanding of how genetic disease risk is linked to ancestry-specific variation.
This web page was produced as an assignment for an undergraduate course at Davidson College. Read more here.
Precision medicine is an innovative approach for individualizing medical treatments based on genetics, which relies on having data that captures the genomic variation that exists across humans. However, most sequencing studies have focused on European populations, causing an imbalance in who is benefitting from advancements in precision medicine. Asian genomes are especially underrepresented in sequencing studies, and the Asian genomes that are included tend to be East and South Asian, with Southeast Asian populations remaining largely excluded. Some progress has been made in recent years to expand the representation of Asian populations in genomic studies, such as the development of the GenomeAsia 100K Project. This project draws data from 1,739 individuals from 219 population groups and 64 countries across Asia to create a reference dataset based on whole genome sequencing (Wall et al., 2019).
In a 2022 study, Chan et al. addressed the underrepresentation of Southeast Asian genomes in population databases by sequencing Singaporean genomes (Chan et al., 2022). By studying clinically significant variants in genomes from 9,051 Singaporean individuals, they assessed how prevalent autosomal dominant disorders were, along with determining the carrier frequency of autosomal recessive and X-linked conditions. They also looked at three specific ancestry groups (Chinese, Malay, and Indian) within the Singaporean population to study how pharmacogenetic variation, or differences in drug response based on genetics, was distributed across these groups.
Genetic ancestry is distinct from race and ethnicity because it’s not socially constructed, and is therefore a better indicator of how likely a variant is to be present in an individual. Many populations, such as in Singapore, also have high levels of admixture, which is when several ancestries are represented in the genome. Admixture can affect genetic disease risk, which is why it’s essential to understand variation among ancestry groups (Borrell et al., 2021). Efforts to increase the representation of Asian genomes within clinical interpretation are crucial for helping healthcare workers become more aware of genetic conditions that have a higher prevalence in Asian populations. As noted in an article about equity in precision medicine (Nature Medicine, 2021), variants that are pathogenic in European genomes may not be harmful to people with non-European ancestry, while pathogenic variants in underrepresented groups can easily go undetected if there isn’t broader representation in sequencing studies. Additionally, expanding what is included in variant databases can be beneficial for advancing rare variant reporting and improving the information that is publicly available.
Chan et al. used a source dataset from the SG10K Health project and performed whole genome sequencing. They then analyzed the sequences and selected variants from 4,143 genes that were linked to autosomal dominant, autosomal recessive, and X-linked genetic conditions. From this analysis, they identified 4,960 variants as pathogenic or likely pathogenic. 82% of those variants were associated with a change in protein length. They also assessed the current recommendations for screening panels and compared them to the carrier burden of recessive conditions in the Singaporean population to identify gaps in screening recommendations for individuals with Asian ancestry.
Chan et al.’s work identified similarities in the overall frequency of clinically significant variants between European and Singaporean individuals, but found differences in disease burden across ancestry groups. For example, they identified a higher risk of familial hypercholesterolemia in Chinese populations, compared to a higher risk of hereditary breast and ovarian cancer in European populations. Among Asian ancestry groups, they found variation in disease risk and carrier burden that was attributed to ancestry-specific variants. Notably, 27% of the severe recessive disorder genes identified in the Singaporean samples with carrier frequencies greater than 1 in 200 were not included in current ACMG carrier screening recommendations. Their examination of pharmacogenetics indicated that variation in allele frequencies among ancestry groups was also associated with different drug profiles between ancestry groups.
Another key finding from the study was that susceptibility to genetic conditions extends beyond ethnic categorizations, which is important to consider as admixture increases with human migration patterns over time. The authors noted that relying too heavily on how participants self-report their race and ethnicity can lead to inaccurate data because an individual’s genetic ancestry may not necessarily align with their socially determined racial or ethnic categorization.
Based on the insights gained from this study, it is essential that more work focuses on including all ancestry groups in genomic studies to allow for precision medicine to be implemented more equitably. This goal may be achieved by extending the methodology used by Chan et al. to other groups that have been historically underrepresented in genomics research. A major strength of this study was its ability to address gaps in current research that have significant clinical applications. However, because it only focused on three major ethnic groups in Singapore, expanding this study to include more ethnic groups could lead to additional insights. Further, educating healthcare professionals about the implications of the lack of representation in sequencing studies is an important step for ensuring that healthcare professionals are aware of variation in disease risk among ancestry groups. Emphasizing the clinical significance of this variation is crucial for improving screening panels to make them more inclusive of all ancestral backgrounds. The information gained from studying clinically significant variation among Asian ancestries is extremely useful for extending the benefits of precision medicine to Asian populations and encouraging a shift towards greater overall inclusion in genomics.
Works Cited
Borrell, L. N. et al. Race and genetic ancestry in medicine — a time for reckoning with racism. New England Journal of Medicine 384, 474–480 (2021). https://pubmed.ncbi.nlm.nih.gov/33406325/
Chan, S. H. et al. Analysis of clinically relevant variants from ancestrally diverse Asian genomes. Nature Communications 13, (2022). https://pubmed.ncbi.nlm.nih.gov/36335097/
Precision Medicine needs an equity agenda. Nature Medicine 27, 737–737 (2021). https://pubmed.ncbi.nlm.nih.gov/33990803/
SG10K Health: Reference Genome Database. PRECISE Available at: https://www.npm.sg/partners/sg10k/.
Singapore Map. Maps of India (2023). https://www.mapsofindia.com/world-map/singapore/
Wall, J. D. et al. The GenomeAsia 100K project enables genetic discoveries across Asia. Nature 576, 106–111 (2019). https://pubmed.ncbi.nlm.nih.gov/31802016/
Written by Kelley Paris. Contact the author at keparis@davidson.edu
Read more about the author here.
© Copyright 2022 Department of Biology, Davidson College, Davidson, NC 28036
Interesting article! I agree that there’s more representation of European individuals in genomic studies. I’m curious to know why East and Southern Asians are usually targeted for sequencing (possibly because of these areas’ high funding and recognition). You mentioned admixture and how it can affect genetic disease risk, so I wonder about the extent to which interbreeding will be encouraged in society. This can be a considerable debate. For example, admixture can lead to increased disease resistance and create genetic variation, but it can also complicate mapping genetic ancestry because of the overlap of genetic similarity among different populations. Also, I hadn’t heard of precision medicine until taking this Genomics class, and I’m excited to see how advances in technology using precision medicine can impact the medical field (e.g., its impact on drug prescription to target specific genetic variants in individuals associated with diseases).