Personalized medicine … in its simplest form, involves the use of genetic information to predict which patients with a given condition (e.g., heart arrhythmia) will benefit from a particular drug treatment (e.g., beta blockers). More ambitiously, personalized medicine promises to inform people of their heightened vulnerability (or resistance) to specific environmental, dietary, therapeutic, and other factors early enough that they can adjust their exposure and risky behaviors accordingly.
[T]he path to personalized medicine will involve a phase in which large numbers of people are treated according to their group membership. Moreover, this phase may not be a passing one.
To appreciate this point, consider an analogy to the MAOA case in the previous post:
[S]uppose the MAOA-maltreatment data concerned not antisocial behavior but a less charged trait, say, a specific adult disease. What kinds of medical diagnoses would receive the necessary investment in pharmaceutical and sociological research, screening, and preventative treatment or monitoring to address the conjunction of genetic and environmental factors involved? One answer is that, especially with the efforts of well-organized parental advocacy groups (Panofsky 2011), government funding might be secured to address the prenatal diagnosis or post-natal treatment of rare debilitating genetic disorders such as PKU… Another answer is that the most likely focus for public and corporate policy would be on diagnoses for which the net benefit, i.e., the number of vulnerable people times the average benefit of ameliorating the effect of the genetic difference, would be large. (More precisely: the focus would be on diagnoses for which the benefit minus the cost of research, screening, and treatment is largest.)
What would the MAOA case lead us to expect for medical diagnoses with large benefit/cost ratios? If the effect of some genetic difference depended on identified social or environmental factors, and if variability within the groups that have, on average, high and low vulnerability produced a problem of misclassification, pressure might arise to differentiate among individuals within the groups.
Until additional research succeeded in identifying distinguishing characteristics, we would expect that parents, teachers, doctors, social workers, insurance companies, policy makers, friends, and the individuals themselves would do the best that they could, which is to use the genetic information to treat individuals according to their group membership. If the additional research were not conducted or were not successful, we might never get beyond treatment according to group membership.
The quotes above are from pages 135ff in Taylor, Peter J. (2014) Nature-Nurture? No: Moving the Sciences of Variation and Heredity Beyond the Gaps.
Panofsky, A. (2011). “Generating sociability to drive science: Patient advocacy organizations and genetics research.” Social Studies of Science 41(1): 31–57.
(Introduction to this series of posts)