Hapmap Could Yield Genetic Clues to Many Diseases

A new way of looking at genes called the HapMap may speed up the search for causes and cures for diseases ranging from Alzheimer's, asthma, cancer and diabetes, to heart disease, hypertension and schizophrenia, new research suggests.

What the HapMap shows are the boundaries of so-called neighborhoods of genetic variation (haplotypes) across the human genome. By using data from HapMap, researchers can identify genetic variations in each neighborhood with a minimum amount of work.

Using HapMap, researchers can compare genetic patterns of people affected by a disease with those who are unaffected. This enables scientists to survey genetic variation across the whole genome, and to identify the genetic contributions to common diseases far more efficiently than was possible before.

The results of the first phase of the HapMap Project appear in the Oct. 27 issue of Nature.

"What the HapMap project did was to try and understand and catalog patterns of genetic variation in samples in populations for three different parts of the world," says principal HapMap investigator Peter Donnelly, a professor of statistics at the University of Oxford Wellcome Trust Center for Human Genetics in England.

The 269 DNA samples came from whites living in Utah, people from the Yoruba tribe in Nigeria, Japanese people in Tokyo and the Han Chinese in Beijing, Donnelly says. "The project looked at the genetic type at about 1 million different places in the human genome," he says. The next phase of the project will look at another 2 million positions.

The places at which the researchers looked are called SNPs (single nucleotide polymorphisms). DNA is a string of building blocks made up of four chemicals. The order in which the chemicals appear is called the genetic code.

"SNPs are places where some percent of the population have one of those building blocks, and some have another. These are positions where we know that different people vary in samples from the population we looked at," Donnelly explains.

Donnelly notes that the makeup of SNPs differed in each population they drew samples from. "The reason for doing these samples is that we know there are different genetic histories for those groups," he says.

"There are patterns that you might see in a Caucasian sample that you wouldn't see in a Japanese sample, and some in Yoruba that you wouldn't see in another population," Donnelly says. "But there are also similarities across the groups."

There are about 10 million SNPs that vary in humans, he says.

One way of identifying the genetic component of a disease is to look at all 10 million SNPs in people with the diseases and in those without the disease. But since SNPs vary with some regularity, it means that to find the genetic differences, one doesn't have to look at all 10 million gene positions, Donnelly explains.

Donnelly likened the HapMap process to five people who always take the same bus every day. To know which bus they are on, out of the many buses at the bus stop, you only need to know which bus one is on to know which bus they are all on.

"This means that we can now afford to do those studies," Donnelly says. Because instead of looking at 10 million SNPs in people with and without a disease, one needs to look at only about 500,000 SNPs.

The HapMap will help scientists learn about the genetic component of many common diseases, Donnelly says.

"For most of those diseases, we don't know very much about what causes them or what triggers them, so if we have the genetics it would give us a foothold in beginning to understand how the disease works," he says. "And that would give us a possibility of predicting it and trying to prevent it, but more importantly, of developing new drug therapies or treatment."

One expert thinks that more population groups need to be included to make the HapMap more useful.

"The HapMap will help a lot in finding genes involved in diseases," says Bernice Morrow, a professor of molecular genetics at Albert Einstein College of Medicine, in New York City. "It helps localize the causes of diseases more quickly."

However, the value of the HapMap depends on what populations you look at, Morrow says. "The HapMap is useless for the New York population," she says. "It is very useful for the populations for which the HapMap has been generated, but not very useful for every population."

For example, the HapMap has not been made for many other populations.

"We don't know if it's going to be useful for Hispanic populations, or African-Americans, or people from the Caribbean," Morrow says. "There are more differences among Africans than there are among African-Americans and Caucasians, because there is more genetic variation in Africa. We need HapMaps for those people, too."

Different ethnic groups have different susceptibilities to different diseases, Morrow points out. "Ethnicity is important. We are more similar than we thought, but there are still important differences," she says. "The HapMap is great, but it needs to be expanded."

(The HealthDay Web site is at http://www.HealthDay.com.)