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Re-examining the Gene in Personalized Genomics

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Abstract

Personalized genomics companies (PG; also called ‘direct-to-consumer genetics’) are businesses marketing genetic testing to consumers over the Internet. While much has been written about these new businesses, little attention has been given to their roles in science communication. This paper provides an analysis of the gene concept presented to customers and the relation between the information given and the science behind PG. Two quite different gene concepts are present in company rhetoric, but only one features in the science. To explain this, we must appreciate the delicate tension between PG, academic science, public expectation, and market forces.

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Notes

  1. It is interesting that PG companies use the number of SNPs included in their tests as marketing tools. Some boast of using 2 million where others used only 1.5. Since only a few thousand of those SNPs confer any information, the gross amount of SNPs tested is little indication of test quality.

  2. Some companies omit (2), requiring you to infer the subjective risk, or omit (3), requiring you to calculate adjusted risk.

  3. There are some interesting and important questions about the degree to which this is accomplished. Many ethnic groups are not represented in the GWAS studies on which PG results are based (see Mountain et al. 2007).

  4. Perhaps the most discussed of these is height, which is estimated to be 80–90 % heritable, but for which SNPs account for only 5 %. The issue of missing heritability is a complex one. The poor risk associations discussed here are but a symptom of this greater problem. On the problem of heritability estimates (see Sesardic 2005). On the problem of missing heritability (see Maher 2008).

  5. To be clear, we cannot access what the PG scientists really think genes are. To access scientists’ inner thoughts isn’t possible. The best we can do is to analyze the material they present to their customers and examine their scientific practices. How they actually conceive of and use the concept is beyond the scope of this sort of investigation. For more on the epistemic and psychological barriers to reconstructing scientific concepts (see Waters 2004).

  6. This likely owes, at least in part, to early linkage disequilibrium (DL) mapping, a technique for mapping polymorphisms, which evolved into contemporary GWAS. Early DL approaches, relying on restriction fragment length polymorphisms and familial transmission data, were predicated on the fact that polymorphisms shared by individuals related ancestrally are often surrounded by shared alleles at nearby loci. The polymorphism is thus treated as a marker for the ‘true’ source of the trait(s) in question. In contemporary studies, however, samples are not restricted to family lines, and thus researches ought not to assume so readily that a polymorphism is indicative of shared alleles. Yet this caveat may have been neglected and surrogate assumption adopted erroneously, in contemporary GWAS (see Kruglyak 2008).

  7. http://www.navigenics.com/visitor/for_physicians/physician_faqs/.

  8. http://www.navigenics.com/visitor/about_us/our_science/genetic_markers/.

  9. http://www.navigenics.com/visitor/genetics_and_health/terminology/.

  10. The difficulty in piecing together information about the science will only be compounded by the extremely high reading level required of PG users. Lachance et al. (2010) found that the reading level of PG websites was 15, at least 6 grades above the average reading comprehension of US citizens.

  11. http://www.deCODEme.com/genetic-code.

  12. http://www.deCODEme.com/genes-traits-diseases.

  13. http://www.deCODEme.com/genetic-code.

  14. http://www.deCODEme.com/genetic-variation.

  15. http://www.deCODEme.com/genetic-variation.

  16. http://www.navigenics.com/visitor/genetics_and_health/family_history/.

  17. Some recent work has shown just how fruitful (though difficult) it can be to include clinical metrics, like family history, into risk assessments relying on DNA (see Ashley et al. 2010).

  18. In the wake of criticism of GWAS, some EWAS (environmental-wide association studies) have been suggested. Yet these have not been funded or pursued with anything like the enthusiasm of GWAS (see Patel et al. 2010; Turkheimer 2012).

  19. This may be set to change, a new company, Personalis, promises to integrate whole-genome scans with clinical risk information (family history, behaviour, etc.). It will be interesting to watch whether, if successful, Personalis prompts other PG companies to follow suit, as I predict.

References

  • 23andMe. (2010a). http://www.23andme.com. Accessed December 9, 2010.

  • 23andMe. (2010b). Keywords for genetics. Retrieved from: https://www.23andme.com/gen101/graphics/genetics/. March 1, 2011.

  • 23andMe. (2011). 23andMe announces additional investment in series C financing [press release]. Retrieved from: https://www.23andme.com/about/press/20110107/.

  • Ashley, E. A., Butte, A. J., Wheeler, M. T., Chen, R., Klein, T. E., Dewey, F. E., et al. (2010). Clinical assessment incorporating a personal genome. The Lancet, 375(9725), 1525–1535. doi:10.1016/S0140-6736(10)60452-7.

    Article  Google Scholar 

  • Bates, B. R. (2005). Public culture and public understanding of genetics: A focus group study. Public Understanding of Science, 14(47), 47–65.

    Google Scholar 

  • Burian, R. M. (2004). Molecular epigenesis, molecular pleiotropy, and molecular gene definitions. History and Philosophy of the Life Sciences, 26, 59–80.

    Article  Google Scholar 

  • Cohen. (2008). Volleyball and the public perception of genetics. http://scienceblogs.com/worldsfair/2008/08/beach_volleyball_and_the_publi.php.

  • Condit, C. M. (2011). ‘When do people deploy genetic determinism? A review pointing to the need for multi-factorial theories of public utilization of scientific discourses. Sociology Compass, 5(7), 618–635.

    Article  Google Scholar 

  • Condit, C. M., Gronnvoll, M., Landau, J., Shen, L., Wright, L., & Harris, T. M. (2009). Believing in both genetic determinism and behavioral action: A materialist framework and implications. Public Understanding of Science, 18(6), 730–746.

    Article  Google Scholar 

  • deCODEme. (2010). http://www.decodeme.com/. Accessed December 9, 2010.

  • Eriksson, N., Macpherson, J. M., Tung, J. Y., Hon, L. S., Naughton, B., et al. (2010). Web-based, participant-driven studies yield novel genetic associations for common traits. PLoS Genetics, 6(6), e1000993.

    Article  Google Scholar 

  • Fogel, T. (2000). The dissolution of protein coding genes in molecular biology’. In P. Beurton, R. Falk, & H. J. Rheinberger (Eds.), The concept of the gene in development and evolution (pp. 3–25). Cambridge, UK: Cambridge University Press.

    Chapter  Google Scholar 

  • Fox Keller, E. (2000). The century of the gene. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Fox Keller, E. (2010). The mirage of a space between nature and nurture. NC: Duke University Press.

    Google Scholar 

  • Gibson, G., & Goldstein, D. B. (2007). Human genetics: The hidden text behind genome-wide associations. Current Biology, 17(21), 929–932.

    Article  Google Scholar 

  • Goldstein, D. B. (2009). Common genetic variation and human traits. The New England Journal of Medicine, 360(17), 1696.

    Google Scholar 

  • Grey, R. D. (1992). The gene is dead. In P. E. Griffiths (Ed.), Trees of life (pp. 165–210). Dordrecht: Kluwer.

    Chapter  Google Scholar 

  • Griffiths, P. E. (2006). The fearless vampire conservator: Philip Kitcher, genetic determinism and the informational gene. In C. Rehmann-Sutter & E. M. Neumann-Held (Eds.), Genes in development: Rethinking the molecular paradigm (pp. 175–198). NC: Duke University Press.

    Google Scholar 

  • Griffiths, P. E., & Stotz, K. (2007). Gene. In M. Ruse & D. Hull (Eds.), Cambridge companion to philosophy of biology (pp. 85–102). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Hawkes, C. H. (1997). Twin studies in medicine—What do they tell us? Quarterly Journal of Medicine, 90(5), 311–321.

    Article  Google Scholar 

  • Hindorff, L. A., Praveen, S., Heather, A. J., Erin, M. R., Jayashri, P. M., Francis, S. C., et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States, 106(23), 9362–9367.

    Article  Google Scholar 

  • Hudson, K. (2008). The health benefits of genomics: Out with the old, in with the new. Health Affairs, 27(6), 1612–1615.

    Article  Google Scholar 

  • Hunter, D. J., & Chanock, S. J. (2010). Genome wide association studies and ‘the art of the soluble’. Journal of the National Cancer Institute, 102(12), 1–2.

    Article  Google Scholar 

  • Hunter, D. J., Altshuler, D., & Rader, D. J. (2008a). From Darwin’s finches to canaries in the coal mine—Mining the genome for new biology. New England Journal of Medicine, 358(26), 2760–2763.

    Article  Google Scholar 

  • Hunter, D. J., Khoury, M., & Drazen, J. M. (2008b). Letting the genome out of the bottle—Will we get our wish? The New England Journal of Medicine, 358(2), 105–107.

    Article  Google Scholar 

  • Ioannidis, J. P. A. (2009). Personalized genetic prediction: Too limited, too expensive, or too soon? Annals of Internal Medicine, 150(2), 139–141.

    Article  Google Scholar 

  • Kruglyak, L. (2008). The road to genome-wide association studies. Nature Genetics, 9, 314–318.

    Google Scholar 

  • Kua, E., Reder, M., & Grossel, M. J. (2004). Science in the news: A study of reporting genomics. Public Understanding of Science, 13, 309–322.

    Article  Google Scholar 

  • Kaufman, D.J., Bollinger J.M., Dvoskin, R. L., & Scott, J. A. (2012). Risky business: Risk perception and the use of medical services among customers of DTC personal genetic testing. Journal of Genetic Counseling, 21(3), 413–422.

    Google Scholar 

  • Lachance, C. R., Erby, L. A. H., Ford, B. M., Allen, V. C., & Kaphingst, K. A. (2010). Informational content, literacy demands, and usability of websites offering health-related genetic tests directly to consumers. Genetics Medicine, 12(5), 304–312.

    Article  Google Scholar 

  • Lakhman, K. (2010). First Walgreens, now house calls: The increasingly bizarre predicament of DTC genetic testing. The Sample. Retrieved from: http://www.genomeweb.com/blog/first-walgreens-now-house-calls-increasingly-bizarre-predicament-dtc-genetic-tes.

  • Leighton, J. W., Valverde, K., Bernhardt, B. A. (2012). The general public’s understanding and perception of direct-to-consumer genetic test results. Public Health Genomics, 15, 11–21.

    Google Scholar 

  • Maher, B. (2008). The case of the missing heritability. Nature, 456, 18–21. doi:10.1038/456018a.

    Article  Google Scholar 

  • Maston, G. A., Evans, S. K., & Green, M. R. (2006). Transcriptional regulatory elements in the human genome. Annual Review of Genomics and Human Genetics, 7, 29–59.

    Article  Google Scholar 

  • McGuire, A. L., & Burke, W. (2008). An unwelcome side effect of direct-to-consumer personal genome testing: Raiding the medical commons. The Journal of the American Medical Association, 300(22), 2669–2671.

    Article  Google Scholar 

  • McGuire, A. L., Diaz, C. M., Wang, T., & Hilsenbeck, S. G. (2009). Social networkers attitudes’ toward direct-to-consumer personal genome testing. American Journal of Bioethics, 9(6–7), 3–10.

    Google Scholar 

  • Mountain, J., Hsu, A., Macpherson, M., & Naughton, B. (2007). White paper 23-02: Estimating genotype-specific incidence in the context of ethnic variation [white paper]. Retrieved from: https://23andme.https.internapcdn.net/res/6295/pdf/23-02_Incidence_And_Ethnicity.pdf.

  • Navigenics. (2010a). http://www.navigenics.com/.

  • Navigenics. (2010b). An open letter to the surgeon general [press release]. Retrieved from: http://www.navigenics.com/visitor/about_us/press/releases/surgeon_general_112310/.

  • Navigenics. (2010c). Navigenics raises $18 million in series C financing [press release]. Retrieved from: http://www.navigenics.com/visitor/about_us/press/releases/financing_020310/.

  • Neumann-Held, E. (1999). The gene is dead—Long live the gene! Conceptualizing genes the constructionist way. In P. Koslowski (Ed.), Sociobiology and bio-economics: The theory of evolution in biological and economic theory (pp. 105–137). NY: Springer.

    Google Scholar 

  • O’Neill, S. C., McBride, C. M., Alford, S. H., & Kaphingst, K. A. (2010). Preferences for genetic and behavioral health information: The impact of risk factors and disease attributions. Annals of Behavioral Medicine, 40(2), 127–137.

    Article  Google Scholar 

  • Patel, C. J., Bhattacharya, J., & Butte, A. J. (2010). An environment-wide association study (EWAS) on type 2 diabetes mellitus’. PLoS One, 5(5), e10746. doi:10.1371/journal.pone.0010746.

    Article  Google Scholar 

  • Sesardic, N. (2005). Making sense of heritability. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Turkheimer, E. (2012). Genome wide association studies of behavior are social science. In K. S. Plaisance & T. A. C. Reydon (Eds.), Philosophy of behavioral biology (pp. 43–64). NY: Springer.

    Chapter  Google Scholar 

  • Waters, K. (1994). Genes made molecular. Philosophy of Science, 61, 163–185.

    Article  Google Scholar 

  • Waters, K. (2004). What concept analysis in philosophy of science should be (and why competing philosophical analyses cannot be tested by polling scientists)’. History and Philosophy of the Life Sciences, 26(1), 29–58.

    Article  Google Scholar 

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Acknowledgments

I would like to thank Stefan Linquist, T. Ryan Gregory, Greg Radick, and audiences in Windsor, Guelph, Toronto, and Exeter for feedback on this paper. Part of this research was supported by the Social Sciences and Humanities Research Council of Canada.

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    Jordan Bartol

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Bartol, J. Re-examining the Gene in Personalized Genomics. Sci & Educ 22, 2529–2546 (2013). https://doi.org/10.1007/s11191-012-9484-2

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