The technique, called expected mutual information (EMI), determines how a set of DNA markers is likely to show the ancestral origin of locations on each chromosome. The team constructed an algorithm for the technique that selects panels of DNA markers that render the best picture of ancestral origin of disease genes. They then tested the algorithm to show that it is more powerful and accurate than standard algorithms that currently select for markers.
The impact is on identifying inherited genes that cause diseases in people of mixed races, which researchers call population admixture. Nephrologists, for instance, have noted that African Americans are far more likely than Europeans to die rapidly of end-stage, progressive kidney failure. Many African Americans also have genes that originated in Europe due to ethnic mixing. The technique helps researchers isolate the genetic causes of disease by detecting from which continent the recurrent disease genes originated.
It is hoped, then, that through gene therapy or perhaps drugs the disease can be prevented or treated.
This technique will allow researchers to analyze which regions of the genome are associated with end-stage, progressive renal failure, said Alan R. Templeton, Ph.D., Washington University Charles Rebstock Professor of Biology, and co-author of a paper on the technique and the algorithm published in the current issue of Genome Research 18, 661-667. Once the regions are identified, then you look at the individual genes and ask: Are there genetic factors involved with this, and if so, what are the candidates"
It's a good bet, Templeton said, that the disease genes are highly likely to have emerged from Africa, as African “Americans have shown the tendency to die more quickly of the disease.
The technique and algorithm apply beyond this particular disease, Templeton added.
We can look at many different hybrid human populations with this algorithm and use it on a diversity of diseases, he said.
Our novel approach extends previous methods by incorporating knowledge on population admixture, drawing a more precise picture of the mosaic of ancestries along an individual's genome, said Sivan Bercovici, Templeton's colleague at Technion and primary author of the Genome Research paper.
The researchers analyzed DNA from 575 cases of African-Americans with end-stage progressive renal failure and compared them to controls that did not have the disease. They came up with a panel of approximately 2,000 genetic markers, enough, Templeton said, to cover the whole genome.
To tease out the origins of disease-causing genes, researchers use a technique called mapping by admixture linkage disequilibrium (MALD), a powerful approach to identify regions of the genome that have genes associated with disease. It takes advantage of differences in disease prevalence between populations to look for variation patterns that are over-represented in groups with high susceptibility to a certain disorder.
Both EMI and the algorithm make MALD more accurate and efficient.
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To see if these results could be generalized from the genetically isolated Hutterite population to a more diverse group, the researchers tested the same variations in the CHI3L1 gene in 178 Caucasian children enrolled in prospective birth cohort, known as COAST, a collaboration led by Robert Lemanske of the University of Wisconsin at Madison.
They also looked for correlations between asthma and SNP -131C/G in two clinical samples, one from the Children's University Hospital in Freiberg, Germany (344 children with asthma and 28, and 94 without), and one from the asthma clinics at the University of Chicago Medical Center (99 children and adults with asthma and 197 without).
In the two clinical samples, those with the CC configuration at position 131 were more likely to have asthma, with CG intermediate and GG the lowest risk of the disease. In the COAST cohort, many subject were still too young to have developed asthma, but the genetic patterns was closely associated with YKL-40 levels, and this association was already present at birth.
The authors suspect that the change from C to G at this site reduces expression of the gene, resulting in lower levels of YKL-40 and protection from asthma.
Although variation in CHI3L1 appears to be one of the most significant genetic triggers yet discovered for susceptibility to asthma, it is far from the sole cause of the disease, the researcher caution. In the Hutterites, it explains 9.4 percent of the variance in YKL-40 levels, suggesting that additional genetic variants also influence these levels. Finding those variations "could identify additional genes," they add, "with significant impact on asthma risk and lung function."
"This evolutionarily ancient pathway involving the innate immune system plays a surprisingly important role in asthma pathogenesis," said Ober, "and a single genetic variant in the CHI3L1 gene may account for most of this risk."
This could have a significant impact on drug development, she added. "For some people, if you block YKL-40 you might dramatically reduce the severity of the disease. Knowing the genotype at SNP -131C might identify those who most likely to benefit from such a treatment."
Asthma is a chronic, treatable disease that causes narrowing of the airways, making breathing difficult at times. More than 22 million people in the United States have asthma, including 6.5 million children under age 18, according to the Centers for Disease Control and Prevention (CDC). The disease generates annual health care costs estimated at $14 billion.
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