Even as biomedical researchers generate and dig through mountains of gene sequence data, physicians proceed in the clinic as they always have. They design preventive care, plan treatments and select drugs by assessing patient type—frequently with race and ethnicity central. Molecular biologists often look to these categories, too, as a means to sort out the ways in which gene variants influence patient response to drugs and disease. And if they get federal funding, investigators must divide the groups they study by race.
Now evolutionary biologists are leading a shift in perspective. Lumping people by the social categories of race, they argue, can hide patterns of biological variation and lead to misinterpretation. And although ancestral population groups may be important, more comprehensive evolutionary thinking would help doctors and researchers predict patient response, design studies and interpret the associations seen between genes and disease susceptibility. Race isn’t meaningless, says Lynn Jorde, an evolutionary geneticist at the University of Utah, but “those categories are only marginally useful.”
Evolutionary medicine has long served to explain how some genes can be harmful in one context but beneficial in another. In one iconic example, having two copies of a mutated hemoglobin gene causes sickle-cell anemia, but having one copy protects against malaria. Now the field aims to offer insight that might lead to a true “personalized” medicine—one that takes into account not just population history but also the dynamic of human variation, environment and selection pressures that acts on each individual today.
Genetics researchers have begun to move in this direction by replacing “race” with “ancestry.” As early humans spread out from Africa, some variation arose in human DNA that remains today. By sampling enough groups from enough locations, investigators hope to identify adaptive changes that might differ by ancestral location and be important to health.
Even that approach, however, might oversimplify human variation and whatever functional meaning it has. Many population studies divide the world into three primary ancestral groups—usually sub-Saharan African, East Asian and European—roughly representing migrations out of Africa. But these categories not only can be hard to distinguish from “race,” they also ignore the overlap between groups and the continuous nature of the way people and genes spread today. “What we see is this wonderful, intertwined history,” Jorde remarks.
Evolutionary theory would predict that most genetic variants important to health are common, ancient and thus shared, whereas some rare variants may be quite population-specific. Even so, more recent “microevolution” caused by mutations, selection and genetic drift in each generation continues to shape our genes beyond the template set by ancient migrations. One example comes from Steven J. Mack of the Children’s Hospital & Research Center Oakland in California, who explores HLA, a cell-surface molecule that plays a role in self-nonself recognition and several kinds of disease. Mack and his collaborators studied 20 populations and found that the greatest diversity in the frequency of gene variants lay outside Africa. Surprisingly, populations in Africa, Europe and Southwest Asia looked similar to one another in terms of frequency of common polymorphisms; Oceania and the indigenous Americas had much more variation. Fresh diversification arose, Mack theorizes, as these smaller, isolated populations confronted new pathogens.
Diddahally Govindaraju, director of the Framingham Heart Study Genetics Laboratory in Boston, says a simple equation that attempts to trace high disease risk to susceptibility genes in a population grouped by ancestry will often fail. Without evolution as a framework, he contends, “the questions are off, the interpretations are off.” Gene action must be understood in the context of adaptive and sometimes haphazard trade-offs as well as developmental stages, the history of human colonization and the pace of environmental change.