The path to personalized medicine may run through social stereotyping

For a gene in which the effect depends on the environmental condition, what kinds of medical conditions would receive the necessary investment in pharmaceutical and sociological research, screening, and preventative treatment/monitoring to address the conjunction of genetic and environmental factors involved?

Recall the example of MAOA levels as a predictor of adult antisocial behavior, in which a misclassification problem arises:

Within each category [high or low MAOA level] people show a range of anti-social behaviors. It turns out that, among children who experienced probable or severe maltreatment, the ranges overlap, that is, some of the high MAOA individuals ended up with higher anti-social behavior scores than some of the low MAOA individuals.


once the resources are invested to screen children for MAOA levels, attention would be focused on all low MAOA children. Indeed, how could this stereotyping be avoided if we do not know from a childhood MAOA assessment whether any particular individual is one who would go on, after maltreatment, to be an antisocial adult? Additional research would be needed to identify other characteristics that differentiate among the low MAOA children (and perhaps help predict who among the high MAOA children are also vulnerable). If that research were successful, additional resources would have to be invested to customize the way that parents, teachers, doctors, social workers treated the different low and high MAOA children and to educate everyone not to treat children according to their MAOA group membership…

Now consider the original question about investment in research, screening, and preventative treatment/monitoring for some less charged condition, say, some specific adult disease.  Some well-organized parental advocacy groups may secure funding to address the prenatal diagnosis and post-natal treatment of rare debilitating genetic disorders (such as PKU). However, public and corporate policy would more likely focus on conditions for which the number of vulnerable people times the average benefit of ameliorating the effect of the genetic difference would be large. In such cases, if the MAOA case is any guide, if the effect of the genetic difference depends on identified social or environmental factors, and if variability within the groups that have on-average high and low vulnerability produces a problem of misclassification, pressure would arise for researchers to differentiate among individuals within the groups. Until distinguishing characteristics were found, parents, teachers, doctors, social workers, insurance companies, policy makers, friends, and the individuals themselves could do no better than treat individuals according to their group membership. If the additional research were not conducted or not successful, or if the cost of differentiating among individuals were too high, we might never get beyond treating individuals according to their group membership.

The scenario speaks to the prospect of personalized medicine. In its simplest form, this involves the use of genetic information to predict which patients with a given condition (e.g., heart arythmia) 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 to adjust their exposure and risky behaviors accordingly. If the MAOA analogy holds, the path to personalized medicine will, ironically, pass through a phase in which large numbers of people are treated according to their group membership. Moreover, this phase may not be a passing one: What social conditions—or assumptions about control—can ensure that the information and resources needed to move beyond it are forthcoming?

Adapted from P. Taylor, “Infrastructure and Scaffolding: Interpretation and Change of Research Involving Human Genetic Information,” Science as Culture, 18(4):435-459, 2009


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