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1. A thread on the relationship between race and genetics. Is race a reliable proxy for genetic diversity? Do racial, ethnic, and/or population groups correspond to identifiable genetic clusters? What does modern genomics research tell us?
2. An emerging orthodoxy holds that race is a social construct and thus a poor proxy for genetic diversity. This view holds that since genetic differences between racial groups are trivial, research on genetic contributions to racial disparities will be fruitless.
3. This line of thought can be traced directly to Richard Lewontin’s 1972 study “The apportionment of human diversity”, which showed that the majority of genetic variation is found within (85%) rather than between (15%) human races and populations. https://link.springer.com/chapter/10.1007/978-1-4684-9063-3_14
4. Clearly, much has changed since 1972: the advent of DNA sequencing, the human genome project, next-generation sequencing and population-scale genomics research. So what does modern genomics research have to say about the relationship between human genetic diversity and race?
5. As early as 1977, Jeffry Mitton showed that, in contrast to Lewontin’s findings, simultaneous analysis of multiple blood group loci allowed for clear differentiation between races. https://www.journals.uchicago.edu/doi/abs/10.1086/283155
6. In 2003, AWF Edwards attributed “Lewontin’s Fallacy” to a reliance on univariate analysis of single loci. Edwards showed that is was theoretically possible to classify racial groups with ~100% accuracy using multivariate analysis of multiple loci. https://pubmed.ncbi.nlm.nih.gov/12879450/
7. Edwards result was empirically validated by Tang et al. two years later. Multivariate analysis of 326 loci yielded 99.86% correspondence between genetic clusters and race/ethnicity for a cohort of 3,636 White, Black, Asian, and Hispanic subjects. https://pubmed.ncbi.nlm.nih.gov/15625622/
8. Witherspoon et al. evaluated genetic similarity among European, African, and East Asian populations in 2007. With thousands of loci, individuals from different populations are never more closely related than individuals from the same population. https://pubmed.ncbi.nlm.nih.gov/17339205/
9. Analysis of 650,000 variants by Paschou et al. in 2010 yielded perfect correspondence between self-reported origins and 51 global populations characterized as part of the Human Genome Diversity Project. https://pubmed.ncbi.nlm.nih.gov/20921023/
10. In 2018, Yuan et al. used a machine learning classifier to show 95.6% correspondence between genetic ancestry and self-identified race/ethnicity for ~11,000 cancer patients from the US National Cancer Institute’s Cancer Genome Atlas. https://pubmed.ncbi.nlm.nih.gov/30300578/
11. In 2019, Scientists from the US National Center for Biotechnology Information used their geometric method GRAF-pop to classify individuals into global “super-populations”, including admixed individuals from the US, with >99% accuracy. https://pubmed.ncbi.nlm.nih.gov/31151998/
12. Later that year, Fang et al. analyzed a cohort of ~202,000 US military veterans, reporting 99.47% correspondence between genetic ancestry clusters revealed by principle components analysis and self-identified race/ethnicity. https://pubmed.ncbi.nlm.nih.gov/31564439/
13. This year, Nagar et al. showed that continental ancestry percentages alone – % African, European, and Native American – predict self-identified race/ethnicity for the three major US groups – Black, White, and Hispanic – with >96% accuracy. https://pubmed.ncbi.nlm.nih.gov/33050895/
14. In summary, when individual loci are considered, there is more variation within groups (race, ethnicity, or population) than between groups. However, when multiple loci are analyzed together, clear and reproducible genetic differences between groups are undeniable.
15. Given that the vast majority of human traits, including health and disease related traits, are influenced by multiple loci, these findings have important implications for genetic contributions to racial differences of all kinds.
