While whole-genome sequencing has proven useful for studying disease, it is less likely to be useful in predicting whether a healthy individual will develop a disease, a study recently published in Science Translational Medicine suggests. At the annual meeting of the American Association for Cancer Research in Chicago last month, Johns Hopkins Kimmel Cancer Center's Bert Vogelstein described the study done by his team. "Many believe, I among them, that we stand on the verge of a revolution," Vogelstein said at an AACR press conference. "Advances in technology and sequencing have immense applications for many fields of science." However, he added, "you can't always predict the final outcomes of revolutions."
The team collated data on 53,666 twin pairs, using one twin as a control to see which diseases he or she developed, and then using the prevalence of the disease in the second twin to calculate the genetic risk of a given disease for that genome. The researchers analyzed data on 24 diseases, including several cancers, and using that data, determined the twins' risk for diseases. What they found was that the majority of the twins would have tested negative for risk for 23 of the 24 diseases — in other words, that their risk was somewhere below the risk of the general population. These negative results, as Vogelstein called them, are not informative since the risk of these twins developing 19 of the 24 diseases would be, at minimum, 50 percent to 80 percent that of the general population.
For example, Vogelstein said, with ovarian cancer, 2 percent of women in the general population being tested predictively will get a positive result, whereas the risk of developing the disease is 10 percent or more. But while the risk for the remaining 98 percent of women who received a negative result would be below the 1.4 percent risk for the general population, their risk would be 1.2 percent or 1.3 percent, not significantly lower. The un-informative nature of a negative result is particularly apparent in cancer, which is a "mixture of genetic and non-genetic effects," Vogelstein said. And non-genetic events aren't limited to environmental factors, but also include stochastic influences, which researchers don't fully understand. "A fortune teller with this crystal ball would soon go out of business," he added.
These limitations don't mean that whole-genome sequencing is useless, Vogelstein said. In people with a family history of disease, whole-genome sequencing is valuable for identifying the genetic basis of that disease and the person's risk for developing it. However, for diseases like cancer, he added, predictive whole-genome sequencing is not the ideal method for ensuring the public's health, and cannot substitute for conventional risk-management strategies like regular check-ups and a healthy lifestyle.
Vogelstein also referenced a recent review article by Colditz et al. in Science Translational Medicine, which suggested that US cancer deaths could be halved every year if people applied what was already known about cancer prevention and took steps like quitting smoking, losing weight, or getting vaccinated against HPV and hepatitis. "We have to make surveillance and early detection open to all, not just those that have a predisposition," Vogelstein said, adding that a widespread public health strategy of educating patients and convincing them to live healthy lifestyles would be more effective for the prevention of disease than widespread whole-genome sequencing of healthy individuals.