Michael Seldin, University of California, Davis—Health System (Press Release), September 14, 2006
Contact: Michael Seldin
University of California, Davis – Health System
Results promise to improve genetic studies of human disease
Sacramento, Calif. — An international team of scientists lead by researchers at UC Davis Health System has found that, with respect to genetics, modern Europeans fall into two groups: a Northern group and a Southern, or Mediterranean one. The findings, published in the Sept. 14 edition of Public Library of Science Genetics (www.plos.org), are important because they provide a method for scientists to take into account European ancestry when looking for genes involved in diseases.
“Until now, little has been known about the distribution of genetic variation in European populations and how much that distribution matters in terms of doing genetic studies,” said Michael Seldin, chair of the Rowe Program in Genetics (https://roweprogram.ucdavis.edu/) at UC Davis Health System. “Now we will be able to control for these differences in European populations in our efforts to find genes that cause common diseases.”
Seldin, who is also a professor of biochemistry and professor of medicine at UC Davis, worked with his colleagues to compare genetic data for 928 individuals. They looked at 5,700 single nucleotide polymorphisms, called SNPs or “snips.” SNPs are changes in which a single base in the DNA differs from the usual base at that position. Millions of SNP’s have been cataloged in the human genome. Some SNPs cause disease, like the one responsible for sickle cell anemia. Other SNPs are normal variations in the genome. People who share ancestry will have many SNPs in common.
Seldin and his group set out to discover which SNPs among Europeans could account for shared common ancestry. “We saw a clustering of individuals that come from either southern Europe or derived from populations that left southern Europe, or the Mediterranean, in the last 2,000 years,” Seldin said. This allowed the group to identify a set of 400 informative SNP markers that scientists could now use to control for European ancestry when conducting genetic studies of disease, response to drug treatment, or side effects from therapy.
In addition to future medical applications, the data are also of interest to anthropologists who study historical human migrations. The Southern grouping included individuals from Greece, Italy, Portugal and Spain, as well as Ashkenazi and Sephardic Jews. The Northern group included people with English, Irish, German, Swedish and Ukranian ancestry. These groups correspond to those historically divided by the Pyrenees and Alps mountain ranges.
With respect to population genetics, previous studies have shown that SNPs correlate broadly with continental ancestry, dividing modern humans into four large groups: Asia, Africa, Oceana, America and continental Europe. The new study gives scientists the evidence they need to further subdivide people with European ancestry into the Northern and Southern groups when looking for SNPs that may be involved in disease.
To prove this point, the researchers analyzed two sets of data. They looked at SNPs associated with rheumatoid arthritis and found that, when they corrected for ancestry, several of the genes that were previously believed to be good candidates for being involved in the disease were no longer candidates at all. They also corrected for ancestry in a data set looking at lactose intolerance. “When we did not control for differences in population structure, we got a lot of false associations,” Seldin explained.
Seldin and his colleagues will soon be expanding the current European study by looking at 500,000 SNPs. They also have plans for similar studies of other continental populations and for further defining different subpopulations. Seldin said studies of other continents and ethnic groups are necessary if science is to get the most out of the advances made by the Human Genome Project. “The ultimate aim of these studies is to be able to better define subgroups and use this information to eliminate false associations, giving us a better chance of finding true associations for disease genes,” Seldin said.