On the steep slope of plummeting DNA sequencing costs rides the suggestion that whole-genome sequencing will soon be a part of the clinical experience for most patients. But researchers have now shown that deciphering the genetic code of most people would alert them to an increased risk for at least one of 24 common diseases, but fail to warn them about other diseases they will ultimately develop.
It’s not easy to predict the ultimate usefulness of medical genomics, in part because the field is so young and not widely adopted. The researchers estimated the potential of the technique to alter a patient’s lifestyle and medical treatment by studying disease rates from identical twins.
The result is not a big surprise, but experts disagree over the study’s implications. Some welcome a more skeptical look at the promise of the technology that deciphers the As, Ts, Gs, and Cs of a person’s genetic blueprint, and point out that it’s not easy to interpret that blueprint for medical information. Others complain that the new analysis only knocks down a straw man, since we already know that whole-genome sequencing has limits, and it hasn’t yet been applied to common diseases in a clinical setting.
Provoking these disparate reactions may be exactly the authors’ intentions. “We became interested in trying to start a debate about the utility and potential benefit of genome-wide sequencing for personal medicine,” says Nicholas Roberts, a graduate student at Johns Hopkins University, and the first author on the study. Roberts says whole-genome sequencing has proved useful for patients with diseases that have a strong link to genetics, but less useful for those with many common and complex diseases, such as cancer or heart disease, that are caused by both genetics and environmental or lifestyle factors.
To see how the technology could affect the broader population, Roberts and coauthors looked to identical twins. The researchers had no actual genome-sequence data for the twins, but instead had data on the long-term incidences of cancer, heart disease, obesity, and other common conditions among the more than 50,000 pairs. Although identical twins share (nearly) identical genome sequences, they do not always develop or die from the same diseases. Other effects, such as diet, exercise, and the varying strength of the effects of particular genetic sequences, can all play a role in whether or not a genetic predisposition leads to an actual malady. How often a disease developed in a person whose twin had the same disease illustrates how well genome sequencing might predict an individual’s disease risk, the authors say.
They calculate that for 23 of the 24 diseases examined, most people who have their genome sequenced will receive negative results—that is, their genome sequence will show no increased risk for a disease such as diabetes as compared to the general population. That negative answer, however, is not a free pass—it would simply mean that person had nearly the same chance of developing the disease as the rest of the population.
Nonetheless, for more than 90 percent of people who’ve had their genome sequenced, the information may alert them to an increased risk for at least one of the 24 diseases examined, and thus could make them more proactive about fighting it.
For some experts, the estimates bring a much-needed reality check. “Genomics is going to be very valuable, and it has already proven very valuable to some patients, but whole-genome sequencing and the like will not be a panacea or a magic bullet for everybody out there, especially with regard to common disease,” says James Evans, a clinical cancer geneticist at the University of North Carolina at Chapel Hill School of Medicine. “In the end, we all pay for each other’s medical care, either because we are in an insurance plan or we are in Medicare, so it’s in nobody’s interest to indiscriminately apply technology and new modalities to people who don’t need them and won’t benefit from them.”
Yet other experts say the study shows only what we already knew. No one trying to translate clinical genomics into clinical practice is using prediction of risk for common disease traits, because it doesn’t work, says James Lupski, clinical geneticist at Baylor College of Medicine. However, with less common syndromes with clear genetic causes, defining the genes involved and identifying them in diagnosis is extremely powerful, says Lupski. “I don’t want people throwing out the baby with the bathwater.”
George Church, a professor of genetics at Harvard Medical School and director of the Center for Computational Genetics, says we will save many more lives if whole-genome sequencing is done on the whole population. “Even if the majority of individuals will receive negative test results, you don’t know until you check,” said Church by e-mail. “It is analogous to fire insurance; you don’t know in advance if you are in the majority who will not lose their house.”
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
The Biggest Questions: What is death?
New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
How to fix the internet
If we want online discourse to improve, we need to move beyond the big platforms.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.