A Starting Point
These days, Charles Rotimi is frequently en route from his office in Washington, DC, to Nigeria to carry out delicate negotiations with community leaders and residents that will permit the HapMap project to begin gathering blood samples. The Yoruba people of western Nigeria are one of Africa’s largest and oldest ethnic groups, and a perfect starting point for the HapMap project.
Rotimi, a genetic epidemiologist at Howard University’s National Human Genome Center, is hoping the HapMap can provide genetic details that will greatly facilitate his research on how people with shared ancestry vary in their reactions to drugs and susceptibility to common diseases. Specifically, Rotimi is interested in pinning down why populations of the African diaspora in various parts of the world suffer from dramatically different rates of diseases like hypertension, diabetes, and obesity.
For example, in results gleaned from conventional epidemiological studies during the last few years, Rotimi has found that about 7 percent of blacks living in rural Africa and 14 percent of those living in urban Africa suffer from hypertension, while 34 percent of African Americans have the condition. “We see drastically different rates of disease in those that share common ancestry,” says Rotimi. “We’re seeing very clearly that the current environment is the most important factor.” But he believes the HapMap could shed new light on this result. “We’ve made assumptions about the underlying genetics” of the different populations, says Rotimi. It might turn out, he says, that the HapMap reveals previously unrecognized “subtle differences in genetic patterns” that could help him better interpret the disease findings. For example, he says, if the patterns of the haplotype blocks in the populations are sufficiently different, it could be a key clue to understanding genetic factors underlying disease risks.
It is just these types of studies that point to the ethical complexities raised by the HapMap and other new genomic methods. On one hand, looking for genetic variations among racial groups runs the danger of reinforcing old stereotypes. Yet genetic differences and similarities in populations with shared ancestry are frequently observed and can provide a powerful tool for understanding diseases; they may even help researchers pinpoint nongenetic factors, like diet and the environment, that influence who contracts a disease. At least according to some, the use of broad racial categories in genetic studies may actually help turn up social, environmental, and cultural reasons for health disparities among different groups.
Last summer, Neil Risch, a leading population geneticist at Stanford University, gained national attention by publishing a paper in an online journal called Genome Biology calling for the use of five racial categories in genetic studies. The paper attacked a growing consensus among researchers that racial classifications are neither genetically valid nor useful. Risch’s contrarian conclusion: differences in drug responses and disease risks need to be separately examined in each of the five racial groups. Otherwise, he warned, genetic research will tend to ignore issues peculiar to minority groups.
No sooner had Risch’s paper begun stirring up the race debate in the genetics community than a group of researchers headed by Marcus Feldman, a prominent population biologist at Stanford, published an article in Science that reported detailed data on gene samples from individuals from 52 populations. The research group sorted the samples using both an advanced genomic approach and self-reported ancestry. They found that the genetic samples fell generally into five geographic categories: Europe, Africa, East Asia, Oceania, and the Americas. They also found that how people categorized themselves-whether they called themselves black or white or Asian-correlated closely with the genetic categories.
Yale’s Kidd, one of the coauthors of the Science paper, notes that following its publication, some observers argued that the findings demonstrated the existence of races as biological entities, while others maintained that the data proved the opposite. “My opinion is closer to the latter,” says Kidd. The results, he explains, show that it is possible to detect very small genetic differences between different populations if you look closely enough. “There is a bit of history that is recoverable,” says Kidd. “But that doesn’t support the idea of race. It does support that when you look around there is some geographical structure that is present in the genome, though it’s extremely small.”
While the interpretation of the results might be in doubt, the paper, and today’s advancing genetic tools, clearly mark the reentry of mainstream genetics into the debate over race and how to best categorize populations.