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Whole-Genome Sequencing of Healthy Individuals Provides Limited Risk Prediction for Common Diseases

NEW YORK (GenomeWeb News) – Whole-genome sequencing of healthy individuals will likely only provide limited information about the risk of developing common diseases, and will not become a substitute for traditional medicine, according to a new study published today in Science Translational Medicine.

Researchers from Johns Hopkins University developed an algorithm to assess the ability of whole-genome sequencing of healthy individuals to provide clinically relevant information on 24 common diseases including autoimmune diseases, cancer, cardiovascular diseases, genitourinary diseases, neurological disorders, and obesity.

They used data generated from previously published studies on twins to show that while many individuals could be alerted to a predisposition to at least one disease, for the majority, whole-genome sequencing would be uninformative for most diseases, and the risk of developing these diseases would be similar to that of the general population.

"For individuals with a strong family history of disease, whole-genome sequencing may become extremely valuable," assuming scientists understand the genetic variables, Bert Vogelstein, director of the Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins University and a senior author of the paper, said during a press briefing. "But, for the vast majority of individuals, whole-genome sequencing will never be a predictive tool."

The goal of the study was to quantitatively analyze the predictive power of whole-genome sequencing.

To do this, the Johns Hopkins researchers analyzed data from over 53,000 pairs of identical twins, and for a set of 24 diseases determined whether a twin's genome increased or decreased his or her risk for developing disease.

The key to the analysis was the concept of a "genometype." The researchers did not know the individual sequences of the twins that they analyzed, but did know that the twins shared nearly identical genomes, so should have the same risks for developing genetic diseases.

"We can use twin 1 as a control, see what disease twin 1 gets, and then the prevalence of the disease in the other twin yields the genetic risk for that genome," explained Vogelstein.

Doing this in many twins, gives a "good capacity of genome sequencing to determine risk, even though we don't know the genome sequence of any of these twins," he added.

One challenge in developing the model was determining what would constitute clinically useful information, said Vogelstein. For instance, a result might indicate that a person has a 5 percent increase in risk over the baseline risk, but that may not always be useful information. If the risk for disease was initially 1 percent, and sequencing indicated a 5 percent increase over that baseline risk, then the individual would have a 1.05 percent risk of developing the disease — "not a significant difference," he said.

So, the team defined a positive test result as being at least a 10 percent risk for developing disease from all factors.

When applying these criteria to ovarian cancer, the researchers found that at maximum, 2 percent of women would find that they were at an increased risk for ovarian cancer. The test would be useful for these women because it would suggest that they would be candidates for intense surveillance. However, 98 percent of women would get a negative result, which would not be very informative, said Vogelstein, and would only mean that their risk of developing ovarian cancer would be around 1.3 percent, compared to the general population, which has a risk of 1.4 percent.

When the model was applied to other diseases, the results were similar, he said.

Additionally, he said that the model assumes "that we understand the functional significance of every variation," so it will not improve as scientists better understand the genome.

There were however, some outliers. For Alzheimer's disease, thyroid autoimmunity, type 1 diabetes, and coronary heart disease-related deaths in males, whole-genome sequencing could have the potential to identify 75 percent of patients who ultimately develop the disease.

Additionally, whole-genome sequencing could provide important information for individuals with rare diseases, or with a strong family history of disease, said Vogelstein.

As sequencing becomes cheaper and more accessible, it will be important to make sure that patients and physicians understand the value of the test, and that patients who choose to have their genomes sequenced are adequately informed about the meaning of the results, Vogelstein said.

In particular, it would be important for individuals to realize that if whole-genome sequencing detected a slightly lower risk for lung cancer, for example, that does not give a patient free reign to start smoking.

"Genetic testing, at its best, will not be the dominant determinant of patient care and will not be a substitute for preventative medicine strategies incorporating routine checkups and risk management based on the history, physical status, and lifestyle of the patient," the authors concluded.

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