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.
Coronavirus Risk Calculators: What You Need to Know
People in my family seem to develop every ailment in the world, including feline distemper and Dutch elm disease, so I naturally put fingers to keyboard when I discovered that COVID-19 risk calculators now exist.
"It's best to look at your risk band. This will give you a more useful insight into your personal risk."
But the results – based on my answers to questions -- are bewildering.
A British risk calculator developed by the Nexoid software company declared I have a 5 percent, or 1 in 20, chance of developing COVID-19 and less than 1 percent risk of dying if I get it. Um, great, I think? Meanwhile, 19 and Me, a risk calculator created by data scientists, says my risk of infection is 0.01 percent per week, or 1 in 10,000, and it gave me a risk score of 44 out of 100.
Confused? Join the club. But it's actually possible to interpret numbers like these and put them to use. Here are five tips about using coronavirus risk calculators:
1. Make Sure the Calculator Is Designed For You
Not every COVID-19 risk calculator is designed to be used by the general public. Cleveland Clinic's risk calculator, for example, is only a tool for medical professionals, not sick people or the "worried well," said Dr. Lara Jehi, Cleveland Clinic's chief research information officer.
Unfortunately, the risk calculator's web page fails to explicitly identify its target audience. But there are hints that it's not for lay people such as its references to "platelets" and "chlorides."
The 19 and Me or the Nexoid risk calculators, in contrast, are both designed for use by everyone, as is a risk calculator developed by Emory University.
2. Take a Look at the Calculator's Privacy Policy
COVID-19 risk calculators ask for a lot of personal information. The Nexoid calculator, for example, wanted to know my age, weight, drug and alcohol history, pre-existing conditions, blood type and more. It even asked me about the prescription drugs I take.
It's wise to check the privacy policy and be cautious about providing an email address or other personal information. Nexoid's policy says it provides the information it gathers to researchers but it doesn't release IP addresses, which can reveal your location in certain circumstances.
John-Arne Skolbekken, a professor and risk specialist at Norwegian University of Science and Technology, entered his own data in the Nexoid calculator after being contacted by LeapsMag for comment. He noted that the calculator, among other things, asks for information about use of recreational drugs that could be illegal in some places. "I have given away some of my personal data to a company that I can hope will not misuse them," he said. "Let's hope they are trustworthy."
The 19 and Me calculator, by contrast, doesn't gather any data from users, said Cindy Hu, data scientist at Mathematica, which created it. "As soon as the window is closed, that data is gone and not captured."
The Emory University risk calculator, meanwhile, has a long privacy policy that states "the information we collect during your assessment will not be correlated with contact information if you provide it." However, it says personal information can be shared with third parties.
3. Keep an Eye on Time Horizons
Let's say a risk calculator says you have a 1 percent risk of infection. That's fairly low if we're talking about this year as a whole, but it's quite worrisome if the risk percentage refers to today and jumps by 1 percent each day going forward. That's why it's helpful to know exactly what the numbers mean in terms of time.
Unfortunately, this information isn't always readily available. You may have to dig around for it or contact a risk calculator's developers for more information. The 19 and Me calculator's risk percentages refer to this current week based on your behavior this week, Hu said. The Nexoid calculator, by contrast, has an "infinite timeline" that assumes no vaccine is developed, said Jonathon Grantham, the company's managing director. But your results will vary over time since the calculator's developers adjust it to reflect new data.
When you use a risk calculator, focus on this question: "How does your risk compare to the risk of an 'average' person?"
4. Focus on the Big Picture
The Nexoid calculator gave me numbers of 5 percent (getting COVID-19) and 99.309 percent (surviving it). It even provided betting odds for gambling types: The odds are in favor of me not getting infected (19-to-1) and not dying if I get infected (144-to-1).
However, Grantham told me that these numbers "are not the whole story." Instead, he said, "it's best to look at your risk band. This will give you a more useful insight into your personal risk." Risk bands refer to a segmentation of people into five categories, from lowest to highest risk, according to how a person's result sits relative to the whole dataset.
The Nexoid calculator says I'm in the "lowest risk band" for getting COVID-19, and a "high risk band" for dying of it if I get it. That suggests I'd better stay in the lowest-risk category because my pre-existing risk factors could spell trouble for my survival if I get infected.
Michael J. Pencina, a professor and biostatistician at Duke University School of Medicine, agreed that focusing on your general risk level is better than focusing on numbers. When you use a risk calculator, he said, focus on this question: "How does your risk compare to the risk of an 'average' person?"
The 19 and Me calculator, meanwhile, put my risk at 44 out of 100. Hu said that a score of 50 represents the typical person's risk of developing serious consequences from another disease – the flu.
5. Remember to Take Action
Hu, who helped develop the 19 and Me risk calculator, said it's best to use it to "understand the relative impact of different behaviors." As she noted, the calculator is designed to allow users to plug in different answers about their behavior and immediately see how their risk levels change.
This information can help us figure out if we should change the way we approach the world by, say, washing our hands more or avoiding more personal encounters.
"Estimation of risk is only one part of prevention," Pencina said. "The other is risk factors and our ability to reduce them." In other words, odds, percentages and risk bands can be revealing, but it's what we do to change them that matters.
Pseudoscience Is Rampant: How Not to Fall for It
Whom to believe?
The relentless and often unpredictable coronavirus (SARS-CoV-2) has, among its many quirky terrors, dredged up once again the issue that will not die: science versus pseudoscience.
How does one learn to spot the con without getting a Ph.D. and spending years in a laboratory?
The scientists, experts who would be the first to admit they are not infallible, are now in danger of being drowned out by the growing chorus of pseudoscientists, conspiracy theorists, and just plain troublemakers that seem to be as symptomatic of the virus as fever and weakness.
How is the average citizen to filter this cacophony of information and misinformation posing as science alongside real science? While all that noise makes it difficult to separate the real stuff from the fakes, there is at least one positive aspect to it all.
A famous aphorism by one Charles Caleb Colton, a popular 19th-century English cleric and writer, says that "imitation is the sincerest form of flattery."
The frauds and the paranoid conspiracy mongers who would perpetrate false science on a susceptible public are at least recognizing the value of science—they imitate it. They imitate the ways in which science works and make claims as if they were scientists, because even they recognize the power of a scientific approach. They are inadvertently showing us how much we value science. Unfortunately they are just shabby counterfeits.
Separating real science from pseudoscience is not a new problem. Philosophers, politicians, scientists, and others have been worrying about this perhaps since science as we know it, a science based entirely on experiment and not opinion, arrived in the 1600s. The original charter of the British Royal Society, the first organized scientific society, stated that at their formal meetings there would be no discussion of politics, religion, or perpetual motion machines.
The first two of those for the obvious purpose of keeping the peace. But the third is interesting because at that time perpetual motion machines were one of the main offerings of the imitators, the bogus scientists who were sure that you could find ways around the universal laws of energy and make a buck on it. The motto adopted by the society was, and remains, Nullius in verba, Latin for "take nobody's word for it." Kind of an early version of Missouri's venerable state motto: "Show me."
You might think that telling phony science from the real thing wouldn't be so difficult, but events, historical and current, tell a very different story—often with tragic outcomes. Just one terrible example is the estimated 350,000 additional HIV deaths in South Africa directly caused by the now-infamous conspiracy theories of their own elected President no less (sound familiar?). It's surprisingly easy to dress up phony science as the real thing by simply adopting, or appearing to adopt, the trappings of science.
Thus, the anti-vaccine movement claims to be based on suspicion of authority, beginning with medical authority in this case, stemming from the fraudulent data published by the now-disgraced Andrew Wakefield, an English gastroenterologist. And it's true that much of science is based on suspicion of authority. Science got its start when the likes of Galileo and Copernicus claimed that the Church, the State, even Aristotle, could no longer be trusted as authoritative sources of knowledge.
But Galileo and those who followed him produced alternative explanations, and those alternatives were based on data that arose independently from many sources and generated a great deal of debate and, most importantly, could be tested by experiments that could prove them wrong. The anti-vaccine movement imitates science, still citing the discredited Wakefield report, but really offers nothing but suspicion—and that is paranoia, not science.
Similarly, there are those who try to cloak their nefarious motives in the trappings of science by claiming that they are taking the scientific posture of doubt. Science after all depends on doubt—every scientist doubts every finding they make. Every scientist knows that they can't possibly foresee all possible instances or situations in which they could be proven wrong, no matter how strong their data. Einstein was doubted for two decades, and cosmologists are still searching for experimental proofs of relativity. Science indeed progresses by doubt. In science revision is a victory.
But the imitators merely use doubt to suggest that science is not dependable and should not be used for informing policy or altering our behavior. They claim to be taking the legitimate scientific stance of doubt. Of course, they don't doubt everything, only what is problematic for their individual enterprises. They don't doubt the value of blood pressure medicine to control their hypertension. But they should, because every medicine has side effects and we don't completely understand how blood pressure is regulated and whether there may not be still better ways of controlling it.
But we use the pills we have because the science is sound even when it is not completely settled. Ask a hypertensive oil executive who would like you to believe that climate science should be ignored because there are too many uncertainties in the data, if he is willing to forgo his blood pressure medicine—because it, too, has its share of uncertainties and unwanted side effects.
The apparent success of pseudoscience is not due to gullibility on the part of the public. The problem is that science is recognized as valuable and that the imitators are unfortunately good at what they do. They take a scientific pose to gain your confidence and then distort the facts to their own purposes. How does one learn to spot the con without getting a Ph.D. and spending years in a laboratory?
"If someone claims to have the ultimate answer or that they know something for certain, the only thing for sure is that they are trying to fool you."
What can be done to make the distinction clearer? Several solutions have been tried—and seem to have failed. Radio and television shows about the latest scientific breakthroughs are a noble attempt to give the public a taste of good science, but they do nothing to help you distinguish between them and the pseudoscience being purveyed on the neighboring channel and its "scientific investigations" of haunted houses.
Similarly, attempts to inculcate what are called "scientific habits of mind" are of little practical help. These habits of mind are not so easy to adopt. They invariably require some amount of statistics and probability and much of that is counterintuitive—one of the great values of science is to help us to counter our normal biases and expectations by showing that the actual measurements may not bear them out.
Additionally, there is math—no matter how much you try to hide it, much of the language of science is math (Galileo said that). And half the audience is gone with each equation (Stephen Hawking said that). It's hard to imagine a successful program of making a non-scientifically trained public interested in adopting the rigors of scientific habits of mind. Indeed, I suspect there are some people, artists for example, who would be rightfully suspicious of changing their thinking to being habitually scientific. Many scientists are frustrated by the public's inability to think like a scientist, but in fact it is neither easy nor always desirable to do so. And it is certainly not practical.
There is a more intuitive and simpler way to tell the difference between the real thing and the cheap knock-off. In fact, it is not so much intuitive as it is counterintuitive, so it takes a little bit of mental work. But the good thing is it works almost all the time by following a simple, if as I say, counterintuitive, rule.
True science, you see, is mostly concerned with the unknown and the uncertain. If someone claims to have the ultimate answer or that they know something for certain, the only thing for sure is that they are trying to fool you. Mystery and uncertainty may not strike you right off as desirable or strong traits, but that is precisely where one finds the creative solutions that science has historically arrived at. Yes, science accumulates factual knowledge, but it is at its best when it generates new and better questions. Uncertainty is not a place of worry, but of opportunity. Progress lives at the border of the unknown.
How much would it take to alter the public perception of science to appreciate unknowns and uncertainties along with facts and conclusions? Less than you might think. In fact, we make decisions based on uncertainty every day—what to wear in case of 60 percent chance of rain—so it should not be so difficult to extend that to science, in spite of what you were taught in school about all the hard facts in those giant textbooks.
You can believe science that says there is clear evidence that takes us this far… and then we have to speculate a bit and it could go one of two or three ways—or maybe even some way we don't see yet. But like your blood pressure medicine, the stuff we know is reliable even if incomplete. It will lower your blood pressure, no matter that better treatments with fewer side effects may await us in the future.
Unsettled science is not unsound science. The honesty and humility of someone who is willing to tell you that they don't have all the answers, but they do have some thoughtful questions to pursue, are easy to distinguish from the charlatans who have ready answers or claim that nothing should be done until we are an impossible 100-percent sure.
Imitation may be the sincerest form of flattery.
The problem, as we all know, is that flattery will get you nowhere.
[Editor's Note: This article was originally published on June 8th, 2020 as part of a standalone magazine called GOOD10: The Pandemic Issue. Produced as a partnership among LeapsMag, The Aspen Institute, and GOOD, the magazine is available for free online.]