Walk into your primary care physician’s office with the results of a genetic test, and you’re likely to be met with confusion, apprehension or even disdain. Most doctors aren’t equipped to deal with even the simplest genetics test, and they are highly unlikely to order them. But as the number of genetic tests grows, thanks largely to the availability of cheap DNA sequencing, a few pioneering physicians, scientists and entrepreneurs are trying to change that, looking for better ways to integrate genetics into routine medical practice.
These efforts are challenging, limited, and in some cases, controversial. Despite the growing number of disease-linked genes identified to date, little is known about how variations in these genes affect individuals, especially in combination with other genetic variations and environmental factors. A deep tension exists between those who want to move forward quickly, incorporating genetic testing into clinical practice as much as possible, and those who want to hold back until there is better evidence that this information can truly help individuals make better choices about their medical care and improve their overall health.
Speakers at the Consumer Genomics Conference in Boston last week outlined three very different attempts to integrate genomics in routine care. Steven Murphy, who writes “The Gene Sherpa” blog, runs a medical practice, called the Personalized Medicine Group, with about 3,000 patients in the New York City area. Physicians there perform what Murphy calls personalized risk assessment, incorporating family history and genetic testing, such as pharmacogenomic testing, preconception testing, and screens for risk of hereditary cancers and other disorders.
Murphy illustrated just how difficult it is to bring genomic testing into primary care, and how limited the testing is, with a case study from his practice: testing revealed that a 39 year old woman with incredibly low good cholesterol (high density lipoprotein or HDL) and a family history of heart disease had a variant in a gene that had previously been linked to heart disease. But the effect of her particular variant is not yet known. (A single gene can have hundreds of different variants, some harmless.) “I spent six to seven hours on the analysis to try to figure out what to do,” said Murphy. “And all of that is unpaid.”
Murphy operates out of the well-heeled New York suburb of Greenwich, CT, so his clientele certainly aren’t typical. (New York, after all, is the home to boutique or concierge medicine, where patients pay large fees for highly personalized care.) Insurance companies are unlikely to cover many of the genetic tests he uses, and most patients would be unable to pay the thousands of dollars such tests can cost out of pocket. El Camino Hospital, a public hospital in the heart of Silicon Valley, aims to incorporate genetic testing into medical care in a less rarefied atmosphere. The hospital created the Genomic Medicine Institute about a year ago to help physicians and patients access and understand genetic testing. The institute has worked with DNA Direct, a genetic testing company recently acquired by Medco, to create a web portal with information on testing for both doctors and patients. The institute also facilitates both ordering and insurance billing and has developed educational courses for physicians. According to Paul Billings, the institute’s chief science officer, uptake by hospital physicians has been “incredibly uneven.” Some surgeons have adopted it wholeheartedly, sending patients with cancer concerns for testing, while most internists and primary care physicians have not.
Brandon Colby aims to broaden the genomics testing market much further. Colby is a physician and founder of Existence Genetics, a startup based in Los Angeles that is developing a specialized genetic testing chip along with software to help doctors translate results from the test into personalized advice for patients. (Colby also serves as medical director of a private medical practice in Los Angeles that takes a similar approach.) The chip detects a number of disease-linked variations, including those linked to both rare and more common disorders. Specialized algorithms then convert this information into risk predictions, as well as recommendations for prevention strategies and the treatments most likely to work in that individual.
But some say this type of analysis is premature; it’s not yet clear how different mutations or environmental factors interact to create risk for a disease, or how well specific interventions will work in genetically-defined individuals. For example, during his talk at the conference, Colby described the case of a young girl found to have an increased risk of breast cancer thanks to a mutation in one of her DNA repair genes. She might want to avoid radiation, such as that from X-rays and CT scans, which could harm her DNA. But Robert Green, a neurologist at Boston University who studies genetic testing, points out that its unclear if this type of testing and the resulting recommendations will truly result in decreased risk of cancer, or whether it might increase her risk of dying from something like pneumonia, if she avoided a chest x-ray that might have diagnosed the disease.
The tension between implementing genetic testing and not was a common thread at the conference. Given that it will be impossible to rigorously test all the combinations of genetic variations, treatments, and other factors, it’s an issue that will be difficult to resolve.
Meta has built a massive new language AI—and it’s giving it away for free
Facebook’s parent company is inviting researchers to pore over and pick apart the flaws in its version of GPT-3
The gene-edited pig heart given to a dying patient was infected with a pig virus
The first transplant of a genetically-modified pig heart into a human may have ended prematurely because of a well-known—and avoidable—risk.
Saudi Arabia plans to spend $1 billion a year discovering treatments to slow aging
The oil kingdom fears that its population is aging at an accelerated rate and hopes to test drugs to reverse the problem. First up might be the diabetes drug metformin.
Yann LeCun has a bold new vision for the future of AI
One of the godfathers of deep learning pulls together old ideas to sketch out a fresh path for AI, but raises as many questions as he answers.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.