How Genetics Can Enrich the Way We Study Social Inequality

May 22, 2014

This feature is part of a new RSF blog series, Work in Progress, which highlights some of the ongoing research of our current class of Visiting Scholars.

Visiting Scholar Dalton Conley is well acquainted with working across disciplines: He currently holds multiple appointments at NYU, including in the Sociology Department, the School of Medicine, and the Wagner School of Public Service. In his time in residence at the Russell Sage Foundation, he is examining the impact of genetics on socioeconomic attainment. Using genetic markers—genes or DNA sequences that can be used to identify particular inherited characteristics—in nationally representative data sets, Conley will attempt to construct genetic risk scores and use them to deepen our understanding of the relationship between genetic endowment and socioeconomic status.

In a new interview with the Foundation, Conley discussed the history of merging genetics with the social sciences, and offered ways of using new genetics data to enrich the way we form policies to address social inequality.

Q. Your research examines the intersection of biology and the social sciences, and in particular, tries to understand how molecular genetics can help explain social stratification. Due to historical misuses of science to justify social inequality (as with the eugenics movement in the nineteenth century or, more recently, Herrnstein and Murray's The Bell Curve) this has been such a controversial area that many social scientists now steer clear of biological explanations altogether. How do you reconcile this fraught history with your own work, and what's new about your research?

The history of loose-and-fast research makes it even more important to have responsible scientists doing this kind of work. I think it's because of The Bell Curve—which was a sloppy piece of research in terms of the inferences that the authors were making, and their use of naïve regressions on variables that were poorly measured—that it's important to show that bridging biological science and social science can be done responsibly. I subscribe to the Enlightenment notion that the scientific method will lead us to truth, and that there shouldn't be taboo areas that are off-limits for research. Right now we’re seeing an onslaught of big data in many fields, including the humanities. As the data come in, many people, including myself, want to analyze them. The question with respect to genetic data then becomes: What is the right way to make conclusions? We could potentially upset some long-held beliefs in the social sciences, but that's just part of science—that we continually progress. The key is not to over-promise what we're delivering with genetic analysis, and to try to frame our findings ourselves so they don’t get misinterpreted in public discourse. I don't think there's anything special about genetics that makes it more open to misinterpretation than other fields of study.

Q. How can an understanding of genetics enrich the way we look at social inequality?

As we develop a better understanding of the role of genetic disposition as it affects one’s social and economic outcomes, I think we’re starting to see a few things. First, we’re finding that there's so much variability in genotype and given the unique combinations of genes that matter for say, education, that it's almost a random lottery at birth for each generation. In other words, the genetic differences within families are as great, if not greater, than they are between families. So the world of Herrnstein and Murray, in which the population is stratifying based on genetics, isn't really operant (which is a relief!) We're also finding that things like cognitive development—that is to say, educational attainment or IQ—are influenced by literally thousands of little effects across the whole genome. Finally, we’re developing a better understanding of gene-environment interaction. For example, genetic disposition is not going to explain why the kid growing up poor in West Baltimore is likely to be in the bottom of the income distribution as an adult while a rich kid who grows up in Westport, Connecticut is likely to be at the top. But within those communities, I think genetics can go a long way in explaining which kids are resilient and which kids are going to be more devastated by their social disadvantages.

Increasingly, researchers in this area are seeing that genes don’t necessarily affect the mean levels of outcomes, but rather, that they affect the range of outcomes. So in other words, if you’re measuring something like educational attainment or cognitive ability, you could have two populations where people in Population A have one allele (i.e. one version of a gene) and people in Population B have another allele. Even if there is no mean difference in cognitive ability between these two groups as an effect of these differing alleles, it is possible that Population A may have a wider spread of results than Population B. This means they could have a genotype that allows for more variation, particularly in response to the environment. We’d call those “orchids” in the Stress Diathesis Hypothesis—which means that if they have that genotype, and a really good social environment, they’ll flourish. But they’re very sensitive, so if they’re placed in a harsh environment, they don’t do well at all. The other kids are the “dandelions.” They’re more robust, or more indifferent to their environments. They’ll do better than “orchids” in a bad environment, but may not do as well as “orchids” in good environments.

Q. How can we use this information to help shape more effective policies regarding social and economic inequality?

Increasingly, as we notice these sorts of genotypes for sensitivity or responsiveness to the environment, they may tell us where to direct specific policy interventions. Typically, any social scientist who ran a experiment—say, for reading comprehension—and got a 20% improvement in scores thanks to the intervention, would be jumping for joy. 20% is a huge effect! But that 20% improvement is probably not because the 100 kids in the treatment group all improved their scores by a fifth. It’s more likely that 20 out of 100 kids doubled their reading scores—they really responded to the intervention, while it had little to no effect on the other kids. The idea is that this is where genetics come into play—with respect to heterogeneous treatment effects—that certain kids are “reading orchids” and other kids are “reading dandelions.”

Another example could be dyslexia, which normally doesn’t get diagnosed until a kid is already behind in reading in elementary school. But if we could identify a genotype that predicted dyslexia, and we knew a kid was at risk from birth because of this genotype, we could intervene to nip the dyslexia in the bud with treatments like phonics instruction well before the child falls behind in school.

Whether or not social scientists are involved in studying genetics, the personal genomics revolution (the website 23andMe is one example) is taking off. People are going to act on information, and genetics are going to be in the social world, influencing social behavior. I think it only behooves us to have social scientists researching it as well.


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