People and their physicians live and work in a new era of personalized medicine. As part of this new reality, physicians hope to provide earlier diagnoses and improve treatment by evaluating an individual’s genetic blueprint. However, the first step must be to correctly decipher the deluge of information locked in a person’s DNA and determine its impact on human health.
Sudhir Kumar is an expert on bioinformatics, the computerized analysis of biological data. He led a team of researchers at Arizona State University’s Biodesign Institute to examine DNA mutations from both healthy and diseased patients. They evaluated the reliability of computer models aimed at predicting the eventual effect of such mutations. The results of the study appear in the September 2009 issue of Genome Research.
Kumar directs the Biodesign Institute’s Center for Evolutionary Functional Genomics. As part of their study, his team focused on single DNA mutations. Such changes to a person’s genome can sometimes make the difference between robust health and debilitating illness.
The ASU scientists focused on one specific type of DNA mutation. They zeroed in on single changes that take place at a given location along the length of DNA. These single changes can alter the resulting protein.
So how important are such protein changes? It turns out they are very important. These single changes are the source of much of our individuality. They code for differences such as eye and hair color. Scientists have discovered that each person’s genome contains thousands of such protein changes. Other single mutations, however, are linked with severe illnesses such as cystic fibrosis.
Experimentation on the enormous number of mutations across human populations is impractical. The cost would be excessive. However, Kumar says that Mother Nature has already done an experiment for us, presenting scientists with a set of benign mutations for each protein. Researchers working in the branch of science known as comparative genomics can take advantage of the genetic information collected from the diversity of life on Earth.
“Comparative genomics provides the first clues as to what a mutation might mean,” Kumar says. “This is an area that is going to become center stage in personal genomics and medicine.”
Scientists now know that humans display a striking degree of genetic similarity with many other species, particularly non-human primates like chimpanzees, gibbons, gorillas and orangutans. In fact, humans share more than 98 percent of our genetic code with these creatures.
Researchers in this field can use GenBank and other giant Web databases. GenBank contains more than 100 billion DNA and protein sequence elements collected from all walks of life.
“These databases already contain the outcomes of nature’s experiment. We can harness the results by using bioinformatics,” says Kumar.
Physicians who practice DNA medicine typically use a suite of computer tools. They need to assess whether a newly discovered protein change is potentially disease-causing or benign. Kumar’s study tested the reliability of two of the most widely-used tests, known as SIFT and PolyPhen. The ASU team examined more than 20,000 mutations from both diagnosed patients and healthy individuals. Their results showed that these tests make false predictions of risk up to 40 percent of the time. That is a rate of reliability that renders the tests impractical for clinical use.
Kumar and his colleagues wanted to identify where SIFT and PolyPhen tend to fail. They also wanted to know where the test’s predictions appear to be more reliable. To get answers, the ASU team examined the proteins in 44 species, from frogs to fish to chimps and gorillas.
They discovered that benign mutations tend to occur in regions of the genome that allow variation over evolutionary time across species. Kumar says that it is easier to make accurate predictions of benign mutations in these regions.
In contrast, DNA information that is essential for life is persistent from species to species. Many DNA positions permit no change over evolutionary time in order to preserve proper function. As a result, mutations in these positions would likely be damaging.
Kumar says that reinforcement of this theory was found in the subset of mutations discovered in disease-associated genes. Such mutations are clustered in positions of the genome that are conserved over evolutionary time. They also appear in mutant protein sequences that are rarely seen. Amazingly, less than 10 percent of known single gene disease mutations are ever found in other species.
Evolution has provided researchers with a storehouse of genetic mutations, Kumar says. Many of these mutations will prove benign for human health.
“Suppose you had a mutation at a certain position,” he explains. “And what if your dog has the same change as you have? It’s most likely that that change is not harmful.”
But if no other species contains the mutation found in one’s genome, it’s a clue that calls for further investigation, he adds.
Kumar says that it will take a combination of additional DNA sequencing data and improved understanding of protein function to refine the power of computer analyses. In the meantime, his bioinformatics evaluations of current computer tools suggest where such tests may be appropriately used for diagnosis with higher confidence. They also show and where the results are more likely to be unreliable.
The cost for running rapid DNA sequencing tests is plummeting. As a result, individual genetic profiling is becoming more and more popular. Such profiling offers every patient access to an enormous treasure trove of medically-relevant information.
According to Kumar, the ultimate challenge will be sorting out what all this genetic information implies for each individual’s prognosis. Only then will the promise of personalized medicine be fully realized.
In addition to Sudhir Kumar, other ASU researchers who worked on the study and appear as co-authors include Michael P. Suleski, Glenn J. Markov, Simon Lawrence, Antonio Marco and Alan J. Filipski.
For media inquiries contact:
Joe Caspermeyer, The Biodesign Institute, Joseph.caspermeyer@asu.edu, 480.727.0369
