Genetically Sequencing Healthy Babies Yielded Surprising Results
Today in Melrose, Massachusetts, Cora Stetson is the picture of good health, a bubbly precocious 2-year-old. But Cora has two separate mutations in the gene that produces a critical enzyme called biotinidase and her body produces only 40 percent of the normal levels of that enzyme.
In the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach.
That's enough to pass conventional newborn (heelstick) screening, but may not be enough for normal brain development, putting baby Cora at risk for seizures and cognitive impairment. But thanks to an experimental study in which Cora's DNA was sequenced after birth, this condition was discovered and she is being treated with a safe and inexpensive vitamin supplement.
Stories like these are beginning to emerge from the BabySeq Project, the first clinical trial in the world to systematically sequence healthy newborn infants. This trial was led by my research group with funding from the National Institutes of Health. While still controversial, it is pointing the way to a future in which adults, or even newborns, can receive comprehensive genetic analysis in order to determine their risk of future disease and enable opportunities to prevent them.
Some believe that medicine is still not ready for genomic population screening, but others feel it is long overdue. After all, the sequencing of the Human Genome Project was completed in 2003, and with this milestone, it became feasible to sequence and interpret the genome of any human being. The costs have come down dramatically since then; an entire human genome can now be sequenced for about $800, although the costs of bioinformatic and medical interpretation can add another $200 to $2000 more, depending upon the number of genes interrogated and the sophistication of the interpretive effort.
Two-year-old Cora Stetson, whose DNA sequencing after birth identified a potentially dangerous genetic mutation in time for her to receive preventive treatment.
(Photo courtesy of Robert Green)
The ability to sequence the human genome yielded extraordinary benefits in scientific discovery, disease diagnosis, and targeted cancer treatment. But the ability of genomes to detect health risks in advance, to actually predict the medical future of an individual, has been mired in controversy and slow to manifest. In particular, the oft-cited vision that healthy infants could be genetically tested at birth in order to predict and prevent the diseases they would encounter, has proven to be far tougher to implement than anyone anticipated.
But in the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach. Why did it take so long? And what remains to be done?
Great Expectations
Part of the problem was the unrealistic expectations that had been building for years in advance of the genomic science itself. For example, the 1997 film Gattaca portrayed a near future in which the lifetime risk of disease was readily predicted the moment an infant is born. In the fanfare that accompanied the completion of the Human Genome Project, the notion of predicting and preventing future disease in an individual became a powerful meme that was used to inspire investment and public support for genomic research long before the tools were in place to make it happen.
Another part of the problem was the success of state-mandated newborn screening programs that began in the 1960's with biochemical tests of the "heel-stick" for babies with metabolic disorders. These programs have worked beautifully, costing only a few dollars per baby and saving thousands of infants from death and severe cognitive impairment. It seemed only logical that a new technology like genome sequencing would add power and promise to such programs. But instead of embracing the notion of newborn sequencing, newborn screening laboratories have thus far rejected the entire idea as too expensive, too ambiguous, and too threatening to the comfortable constituency that they had built within the public health framework.
"What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Creating the Evidence Base for Preventive Genomics
Despite a number of obstacles, there are researchers who are exploring how to achieve the original vision of genomic testing as a tool for disease prediction and prevention. For example, in our NIH-funded MedSeq Project, we were the first to ask the question: "What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Most people do not understand that genetic information comes in four separate categories: 1) dominant mutations putting the individual at risk for rare conditions like familial forms of heart disease or cancer, (2) recessive mutations putting the individual's children at risk for rare conditions like cystic fibrosis or PKU, (3) variants across the genome that can be tallied to construct polygenic risk scores for common conditions like heart disease or type 2 diabetes, and (4) variants that can influence drug metabolism or predict drug side effects such as the muscle pain that occasionally occurs with statin use.
The technological and analytical challenges of our study were formidable, because we decided to systematically interrogate over 5000 disease-associated genes and report results in all four categories of genetic information directly to the primary care physicians for each of our volunteers. We enrolled 200 adults and found that everyone who was sequenced had medically relevant polygenic and pharmacogenomic results, over 90 percent carried recessive mutations that could have been important to reproduction, and an extraordinary 14.5 percent carried dominant mutations for rare genetic conditions.
A few years later we launched the BabySeq Project. In this study, we restricted the number of genes to include only those with child/adolescent onset that could benefit medically from early warning, and even so, we found 9.4 percent carried dominant mutations for rare conditions.
At first, our interpretation around the high proportion of apparently healthy individuals with dominant mutations for rare genetic conditions was simple – that these conditions had lower "penetrance" than anticipated; in other words, only a small proportion of those who carried the dominant mutation would get the disease. If this interpretation were to hold, then genetic risk information might be far less useful than we had hoped.
Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
But then we circled back with each adult or infant in order to examine and test them for any possible features of the rare disease in question. When we did this, we were surprised to see that in over a quarter of those carrying such mutations, there were already subtle signs of the disease in question that had not even been suspected! Now our interpretation was different. We now believe that genetic risk may be responsible for subclinical disease in a much higher proportion of people than has ever been suspected!
Meanwhile, colleagues of ours have been demonstrating that detailed analysis of polygenic risk scores can identify individuals at high risk for common conditions like heart disease. So adding up the medically relevant results in any given genome, we start to see that you can learn your risks for a rare monogenic condition, a common polygenic condition, a bad effect from a drug you might take in the future, or for having a child with a devastating recessive condition. Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
Preventive Genomics Arrives in Clinical Medicine
There is still considerable evidence to gather before we can recommend genomic screening for the entire population. For example, it is important to make sure that families who learn about such risks do not suffer harms or waste resources from excessive medical attention. And many doctors don't yet have guidance on how to use such information with their patients. But our research is convincing many people that preventive genomics is coming and that it will save lives.
In fact, we recently launched a Preventive Genomics Clinic at Brigham and Women's Hospital where information-seeking adults can obtain predictive genomic testing with the highest quality interpretation and medical context, and be coached over time in light of their disease risks toward a healthier outcome. Insurance doesn't yet cover such testing, so patients must pay out of pocket for now, but they can choose from a menu of genetic screening tests, all of which are more comprehensive than consumer-facing products. Genetic counseling is available but optional. So far, this service is for adults only, but sequencing for children will surely follow soon.
As the costs of sequencing and other Omics technologies continue to decline, we will see both responsible and irresponsible marketing of genetic testing, and we will need to guard against unscientific claims. But at the same time, we must be far more imaginative and fast moving in mainstream medicine than we have been to date in order to claim the emerging benefits of preventive genomics where it is now clear that suffering can be averted, and lives can be saved. The future has arrived if we are bold enough to grasp it.
Funding and Disclosures:
Dr. Green's research is supported by the National Institutes of Health, the Department of Defense and through donations to The Franca Sozzani Fund for Preventive Genomics. Dr. Green receives compensation for advising the following companies: AIA, Applied Therapeutics, Helix, Ohana, OptraHealth, Prudential, Verily and Veritas; and is co-founder and advisor to Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers and care systems.
This Mom Is On a Mission to End Sickle Cell Disease
[Editor's Note: This video is the third of a five-part series titled "The Future Is Now: The Revolutionary Power of Stem Cell Research." Produced in partnership with the Regenerative Medicine Foundation, and filmed at the annual 2019 World Stem Cell Summit, this series illustrates how stem cell research will profoundly impact human life.]
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Dadbot, Wifebot, Friendbot: The Future of Memorializing Avatars
In 2016, when my family found out that my father was dying from cancer, I did something that at the time felt completely obvious: I started building a chatbot replica of him.
I simply wanted to create an interactive way to share key parts of his life story.
I was not under any delusion that the Dadbot, as I soon began calling it, would be a true avatar of him. From my research about the voice computing revolution—Siri, Alexa, the Google Assistant—I knew that fully humanlike AIs, like you see in the movies, were a vast ways from technological reality. Replicating my dad in any real sense was never the goal, anyway; that notion gave me the creeps.
Instead, I simply wanted to create an interactive way to share key parts of his life story: facts about his ancestors in Greece. Memories from growing up. Stories about his hobbies, family life, and career. And I wanted the Dadbot, which sent text messages and audio clips over Facebook Messenger, to remind me of his personality—warm, erudite, and funny. So I programmed it to use his distinctive phrasings; to tell a few of his signature jokes and sing his favorite songs.
While creating the Dadbot, a laborious undertaking that sprawled into 2017, I fixated on two things. The first was getting the programming right, which I did using a conversational agent authoring platform called PullString. The second, far more wrenching concern was my father's health. Failing to improve after chemotherapy and immunotherapy, and steadily losing energy, weight, and the animating sparkle of life, he died on February 9.
John Vlahos at a family reunion in the summer of 2016, a few months after his cancer diagnosis.
(Courtesy James Vlahos)
After a magazine article that I wrote about the Dadbot came out in the summer of 2017, messages poured in from readers. While most people simply expressed sympathy, some conveyed a more urgent message: They wanted their own memorializing chatbots. One man implored me to make a bot for him; he had been diagnosed with cancer and wanted his six-month-old daughter to have a way to remember him. A technology entrepreneur needed advice on replicating what I did for her father, who had stage IV cancer. And a teacher in India asked me to engineer a conversational replica of her son, who had recently been struck and killed by a bus.
Journalists from around the world also got in touch for interviews, and they inevitably came around to the same question. Will virtual immortality, they asked, ever become a business?
The prospect of this happening had never crossed my mind. I was consumed by my father's struggle and my own grief. But the notion has since become head-slappingly obvious. I am not the only person to confront the loss of a loved one; the experience is universal. And I am not alone in craving a way to keep memories alive. Of course people like the ones who wrote me will get Dadbots, Mombots, and Childbots of their own. If a moonlighting writer like me can create a minimum viable product, then a company employing actual computer scientists could do much more.
But this prospect raises unanswered and unsettling questions. For businesses, profit, and not some deeply personal mission, will be the motivation. This shift will raise issues that I didn't have to confront. To make money, a virtual immortality company could follow the lucrative but controversial business model that has worked so well for Google and Facebook. To wit, a company could provide the memorializing chatbot for free and then find ways to monetize the attention and data of whoever communicated with it. Given the copious amount of personal information flowing back and forth in conversations with replica bots, this would be a data gold mine for the company—and a massive privacy risk for users.
Virtual immortality as commercial product will doubtless become more sophisticated.
Alternately, a company could charge for memorializing avatars, perhaps with an annual subscription fee. This would put the business in a powerful position. Imagine the fee getting hiked each year. A customer like me would find himself facing a terrible decision—grit my teeth and keep paying, or be forced to pull the plug on the best, closest reminder of a loved one that I have. The same person would effectively wind up dying twice.
Another way that a beloved digital avatar could die is if the company that creates it ceases to exist. This is no mere academic concern for me: Earlier this year, PullString was swallowed up by Apple. I'm still able to access the Dadbot on my own computer, fortunately, but the acquisition means that other friends and family members can no longer chat with him remotely.
Startups like PullString, of course, are characterized by impermanence; they tend to get snapped up by bigger companies or run out of venture capital and fold. But even if big players like, say, Facebook or Google get into the virtual immortality game, we can't count on them existing even a few decades from now, which means that the avatars enabled by their technology would die, too.
The permanence problem is the biggest hurdle faced by the fledgling enterprise of virtual immortality. So some entrepreneurs are attempting to enable avatars whose existence isn't reliant upon any one company or set of computer servers. "By leveraging the power of blockchain and decentralized software to replicate information, we help users create avatars that live on forever," says Alex Roy, the founder and CEO of the startup Everlife.ai. But until this type of solution exists, give props to conventional technology for preserving memories: printed photos and words on paper can last for centuries.
The fidelity of avatars—just how lifelike they are—also raises serious concerns. Before I started creating the Dadbot, I worried that the tech might be just good enough to remind my family of the man it emulated, but so far off from my real father that it gave us all the creeps. But because the Dadbot was a simple chatbot and not some all-knowing AI, and because the interface was a messaging app, there was no danger of him encroaching on the reality of my actual dad.
But virtual immortality as commercial product will doubtless become more sophisticated. Avatars will have brains built by teams of computer scientists employing the latest techniques in conversational AI. The replicas will not just text but also speak, using synthetic voices that emulate the ones of the people being memorialized. They may even come to life as animated clones on computer screens or in 3D with the help of virtual reality headsets.
What fascinates me is how technology can help to preserve the past—genuine facts and memories from peoples' lives.
These are all lines that I don't personally want to cross; replicating my dad was never the goal. I also never aspired to have some synthetic version of him that continued to exist in the present, capable of acquiring knowledge about the world or my life and of reacting to it in real time.
Instead, what fascinates me is how technology can help to preserve the past—genuine facts and memories from people's lives—and their actual voices so that their stories can be shared interactively after they have gone. I'm working on ideas for doing this via voice computing platforms like Alexa and Assistant, and while I don't have all of the answers yet, I'm excited to figure out what might be possible.
[Adapted from Talk to Me: How Voice Computing Will Transform the Way We Live, Work, and Think (Houghton Mifflin Harcourt, March 26, 2019).]