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Omi and Winant (2014) “stress that race is a social construction, and not a fixed, static category rooted in some notion of innate biological differences.” Social, economic, and political forces, across time and place, have influenced racial meanings. Many scientists hoped that mapping our genome would provide definitive evidence that there is no such thing biologically as race. Humans share over 99% of the same genome.

However, some scientists have chosen to concentrate on the last partial percentage as potentially significant genetic variation due to racial or ethnic differences. In an ideal world, scientists envisioned that these studies would target diseases and treatments for particular populations. However, this has led some to argue that a biological basis for race really exists, which also might result in rather ugly social consequences, such as rationalizing racism.

An example of a widely available image online (below) shows a statistical summary of genetic data that clusters according to the countries in Europe. While the original scientific article does not mention race, the authors found a close correspondence between genes and geography. They believed that these results supported the accuracy of genetic ancestry testing based on a sample of 1,376 Europeans. This image reappears on science blogs and as evidence on popular forums about similarities between ethnic groups based on the distance shown on the map.

Shiao, Bode, Beyer, and Selvig (2012) presented a theoretical synthesis between recent genetic ancestry research and the social construction of race. The authors accepted that statistically identifiable clusters of genes seem homologous to certain racial and ethnic classifications. However, any identifiable biological basis for race and ethnicity cannot be separated from its complex social construction across time and place.

Duster (2015) urged social researchers to critically examine the social assumptions about race that have been transmogrified as science and trace their actual origins in social, historical, and folk categories of race. Some scientists have stated that genetics research studying differences between populations is scientifically appropriate, but assigning value such as genetic superiority to their findings is politics, not science. Instead, Duster argued that politics cannot be separated from science because the use of racial and ethnic categories originally come from political taxonomies. He also cautioned against ancestry testing and admixture research (a combination of genetic lineages) as fundamentally flawed science as well as depending on political history to define populations. Ancestry testing relies on “reference populations” of contemporary people along with assumptions about migrations, reproductive patterns, and historical events. The actual computer models determining an individual’s results tend to be a “black box” proprietary to the companies marketing a particular test. For example, a customer might receive results that provide the appearance of precision (example below). This “professional genetic genealogist and television consultant” provides a review of four consumer tests for determining admixture, which shows differing results across the companies.

In 2014, USA Today published an opinion piece about the genealogy “craze” as the second most popular hobby and second most visited category of website (after pornography). While the author refers to the digitization of databases as the popularizing factor, consumer genetic testing also appeals to these hobbyists.

Duster believed that these results should be qualified with more caveats. For example, for a person expecting certain results, the company’s sample might not include that population. There also is no guarantee that a match of genetic markers to a certain population or geographical area means that the individual has a close affinity to a racial or ethnic group.

Duster’s article sparked controversy in the social sciences and he published a response to seven of his commentators (2015). In particular, the intersection between science and society is visible in the question of when, rather than where, an individual might claim ancestry. For example, Italy became a unified nation state in 1858. Prior to these dates, ethnic categories would be based on regional admixtures including Milanese, Roman, and Neapolitan. How do scientists determine the appropriate admixture for a single ethnic category of Italian?

He also presented the Boers in South Africa in the mid-sixteenth century as another example requiring social context. A white person born in Africa with grandparents of this ancestry would be African. However, the observable appearance of whiteness would outweigh the “scientifically neutral” ancestry analysis. Other researchers have proven that the phenotype determines results more than genotype.

The Guardian recently published an article about the booming consumer genetic testing market, worth $70 million in 2015 and expected to rise to $340 million by 2022 (chart below by Credence Research cited in the article). In addition to ancestry, consumers hope to understand the relationship between their genes and health, which might include their response to a particular type of exercise and diet.

In addition, Duster warned against the potential problems in social scientists and geneticists collaborating on research. Social scientists may not understand the scientific details of the genetics research in order to question the assumptions, which lends multi-disciplinary legitimacy to the collaboration and normalizes the science. Genomic advocates also claim benefit in new medication targeting certain populations, but this helps rationalize racial hierarchies. Who should benefit from targeted research? Marmot (2005) attributed social factors as the root cause of health inequalities, such as significant differences in life expectancy and treatment of disease. Gravlee (2009) stated that “social inequalities shape the biology of racialized groups, and embodied inequalities perpetuate a racialized view of human biology.” House (2015) recently reiterated that social policies to improve socioeconomic determinants of health would be necessary to reverse worsening health outcomes and reduce health spending in the United States. For example, the following chart (below) shows poverty rates among senior citizens by race and ethnicity in a report looking at Medicare beneficiaries conducted by the Kaiser Family Foundation.

Yudell, Roberts, DeSalle, and Tishkoff (2016) called for a systematic effort to address issues concerning the use of race in genetic research. The authors distinguished between ancestry as “a process-based concept, a statement about an individual’s relationship to other individuals… a very personal understanding of one’s genomic heritage” versus race as “a pattern-based concept… which connect an individual to a larger preconceived geographically circumscribed or socially constructed group.”

Where does this leave a consumer curious about their ancestral heritage and health-related consequences of their genome? Scientists would be the first to admit that their research is based on limited opportunity samples (present-day volunteers) and statistical correlations, rather than absolute certainty. However, companies marketing their consumer genetic tests seem unlikely to mention the assumptions and potential inaccuracies in their product. These companies also profit from selling the data collected from their customers to pharmaceutical and biotech firms. In addition, sociologists should continue to discuss the social and historical basis for determining race and racism, which rejects a biological explanation as insufficient for the complexity in these issues. There also is room for further intersectional analysis of the socioeconomic determinants of health in determining future directions for genetic research to improve health in disadvantaged populations.

 

Bibliography
Duster, T. (2015a). A post-genomic surprise. The molecular reinscription of race in science, law and medicine. The British Journal of Sociology, 66(1), 1–27. https://doi.org/10.1111/1468-4446.12118
Duster, T. (2015b). Response to comments on ‘A post-genomic surprise.’ The British Journal of Sociology, 66(1), 83–92. https://doi.org/10.1111/1468-4446.12117_8
Gravlee, C. C. (2009). How race becomes biology: Embodiment of social inequality. American Journal of Physical Anthropology, 139(1), 47–57. https://doi.org/10.1002/ajpa.20983
House, J. S. (2016). Social Determinants and Disparities in Health: Their Crucifixion, Resurrection, and Ultimate Triumph(?) in Health Policy. Journal of Health Politics, Policy and Law, 41(4), 599–626. https://doi.org/10.1215/03616878-3620845
Marmot, M. (2005). Social determinants of health inequalities. The Lancet, 365(9464), 1099–1104. https://doi.org/10.1016/S0140-6736(05)71146-6
Novembre, J., Johnson, T., Bryc, K., Kutalik, Z., Boyko, A. R., Auton, A., … Bustamante, C. D. (2008). Genes mirror geography within Europe. Nature, 456(7218), 98–101. https://doi.org/10.1038/nature07331
Omi, M., & Winant, H. (2014) Racial Formation in the United States, 3rd edition. Routledge.
Shiao, J. L., Bode, T., Beyer, A., & Selvig, D. (2012). The Genomic Challenge to the Social Construction of Race. Sociological Theory, 30(2), 67–88.
Yudell, M., Roberts, D., DeSalle, R., & Tishkoff, S. (2016). Taking race out of human genetics. Science, 351(6273), 564–565. https://doi.org/10.1126/science.aac4951

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