This is Part 2 of a two-part story on the science and promise of the International HapMap Project. Part 1 was published on November 7.

Sequencing a single human genome took an international team comprising hundreds of researchers 13 years. Now, in just three years, another global consortium has begun to identify the genetic differences among hundreds of individuals from four countries – and fashion them into a powerful new tool for understanding how these differences affect human health.

The International HapMap Project, launched in October 2002, has catalogued more than three million single-nucleotide polymorphisms (SNPs), or single-point differences in the sequence of the human genome, based on samples from four different populations around the world. More than 200 scientists in Canada, China, Japan, Nigeria, the United Kingdom, and the United States participated in the project. The team published an analysis of the project’s first phase, examining about one million of those variations, in the October 27 issue of Nature.

The study reported on genetic differences identified in 269 individuals: 90 from the Yoruba in Ibadan, Nigeria; 90 from Utah, representing people of northern European ancestry; 45 Han Chinese from Beijing, China; and 44 Japanese from Tokyo, Japan. These differences are inherited in large blocks, called haplotypes. The data analysis was led by Peter Donnelly of the University of Oxford in England and David Altshuler, director of the program in Medical and Population Genetics of the Broad Institute of Harvard and MIT in Cambridge, MA.

The HapMap Consortium undertook the project in an effort to speed the identification of genes involved in common diseases, such as cancer and diabetes. “The goal in this project is a medical one: we want to advance medical genetic studies of disease, and we want to do this in a way that would benefit people throughout the world,” says Mark J. Daly, who led the Broad Institute’s analysis efforts for the HapMap.

Different populations have haplotype blocks of different lengths, and may also inherit different patterns of variation, making the decision to study diverse populations inevitable. With a full catalog of haplotype patterns, researchers can speed up their hunts for disease-related genes by selecting “tag SNPs,” individual variations that depict the full pattern of differences in each block.

Previous genetic studies had suggested the group could capture a great deal of the world’s genetic diversity by sampling populations of recent European, African, and Asian descent. Still, researchers have begun studies to examine additional populations to see how useful data from the HapMap will be in studying these groups. “The reports I’ve heard are pretty encouraging,” says Donnelly. “For example, the European sample was individuals taken from Utah; but, given the data I’ve seen, it seems that if you’re doing a study in a German population or a British population or a French population, they extrapolate pretty well.”

Charles N. Rotimi, who coordinated sample collection for the project among the Yoruba people in Nigeria, emphasizes the importance of studying populations beyond the original four. “We want to make sure that the genetic variations we now have at a very detailed level actually apply to all human populations,” says Rotimi, who is director of genetic epidemiology at the National Human Center at Howard University. “The best way to test that is enroll other populations.”

Indeed, the U.S. National Human Genome Research Institute has already funded studies of seven other population samples: African ancestry from the southwestern United States; Chinese-Americans from Denver, CO; Gujarati Indian ancestry from Houston, TX; Luhya from Eldoret, Kenya; Maasai from Webuye, Kenya; Mexican origin from Los Angeles, CA; and Tuscans from Sesto, Italy.

By taking advantage of all this data, and then using patients from around the world, geneticists can improve the power of studies to uncover links between gene variations and common diseases, such as cancer, diabetes, and asthma, says Rotimi. The key to uncovering many such links will be international collaborations, researchers say. One simple advantage will be statistical: “By bringing together multiple groups, you immediately increase your power to find these things because you’re studying much larger cohorts,” says Rotimi.

Geneticists might use studies of multiple populations in other ways, as well, Rotimi notes. One possibility is to begin a gene hunt by studying European populations, which tend to have longer and fewer haplotype blocks, which are easier to test. Then researchers could refine the location by examining older, African groups, which inherit shorter haplotypes, to narrow down the location and perhaps even identify and locate a specific gene.

In addition, Rotimi notes, the HapMap enables researchers to tackle questions about gene/environment interactions for the first time. “You now have people coming from different parts of the world, and you have the opportunity to study different environmental factors,” along with the individuals’ genetic variations, he says.

Tom Hudson, who has been engaged in the HapMap from its inception as former assistant director of the Whitehead Institute/MIT Center for Genome Research, agrees. Now director of the Montreal Genome Centre and Génome Québec Innovation Centre at McGill University, Hudson has launched one of several international studies that are applying HapMap data to human disease research.

The Montreal center is starting with a study of colon cancer that will examine the entire genomes of 1,200 people with and 1,200 without the disease, for genetic differences. The best leads from this phase will then be checked in 5,000 additional patients in the state of Washington, Newfoundland, Ontario, and France. “Many groups in disease areas are forming consortia, just like HapMap,” says Hudson. “[We] need large numbers of families or individuals in these studies, usually more than any single group has.”

Hudson has also undertaken more focused studies examining variations in 150 candidate genes for childhood asthma among 5,000 individuals and 200 genes in 15,000 heart attacks patients. The goal is to develop a deeper understanding of the links between genes and environment in the origins of these diseases. Another group at the Montreal Genome Centre has embarked on a whole genome study to find genes associated with type II diabetes.

Other research groups have started similar large studies: Donnelly is leading a U.K.-based consortium looking for genes related to a host of diseases: type I and type II diabetes, hypertension, cardiovascular disease, bipolar disorder, Crohn’s disease, rheumatoid arthritis, and susceptibility to tuberculosis. Meanwhile, researchers in Japan plan to screen 300,000 people in a search for genes related to 47 different diseases.

David Altshuler, for one, expects the progress to be rapid. For the first time, he points out, researchers can look broadly across the genome, around the world for genes linked to the most common diseases. And while it will take years before diagnostic tests and treatments based on such studies reach patients, the results could transform public health worldwide. “I do think this is an inflection point,” Altshuler says.