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.
Your phone could show if a bridge is about to collapse
In summer 2017, Thomas Matarazzo, then a postdoctoral researcher at the Massachusetts Institute of Technology, landed in San Francisco with a colleague. They rented two cars, drove up to the Golden Gate bridge, timing it to the city’s rush hour, and rode over to the other side in heavy traffic. Once they reached the other end, they turned around and did it again. And again. And again.
“I drove over that bridge 100 times over five days, back and forth,” says Matarazzo, now an associate director of High-Performance Computing in the Center for Innovation in Engineering at the United States Military Academy, West Point. “It was surprisingly stressful, I never anticipated that. I had to maintain the speed of about 30 miles an hour when the speed limit is 45. I felt bad for everybody behind me.”
Matarazzo had to drive slowly because the quality of data they were collecting depended on it. The pair was designing and testing a new smartphone app that could gather data about the bridge’s structural integrity—a low-cost citizen-scientist alternative to the current industrial methods, which aren’t always possible, partly because they’re expensive and complex. In the era of aging infrastructure, when some bridges in the United States and other countries are structurally unsound to the point of collapsing, such an app could inform authorities about the need for urgent repairs, or at least prompt closing the most dangerous structures.
There are 619,588 bridges in the U.S., and some of them are very old. For example, the Benjamin Franklin Bridge connecting Philadelphia to Camden, N.J., is 96-years-old while the Brooklyn Bridge is 153. So it’s hardly surprising that many could use some upgrades. “In the U.S., a lot of them were built in the post-World War II period to accommodate the surge of motorization,” says Carlo Ratti, architect and engineer who directs the Senseable City Lab at Massachusetts Institute of Technology. “They are beginning to reach the end of their life.”
According to the 2022 American Road & Transportation Builders Association’s report, one in three U.S. bridges needs repair or replacement. The Department of Transportation (DOT) National Bridge Inventory (NBI) database reveals concerning numbers. Thirty-six percent of U.S. bridges need repair work and over 78,000 bridges should be replaced. More than 43,500 bridges are rated in poor condition and classified as “structurally deficient” – an alarming description. Yet, people drive over them 167.5 million times a day. The Pittsburgh bridge which collapsed in January this year—only hours before President Biden arrived to discuss the new infrastructure law—was on the “poor” rating list.
Assessing the structural integrity of a bridge is not an easy endeavor. Most of the time, these are visual inspections, Matarazzo explains. Engineers check cracks, rust and other signs of wear and tear. They also check for wildlife—birds which may build nests or even small animals that make homes inside the bridge structures, which can slowly chip at the structure. However, visual inspections may not tell the whole story. A more sophisticated and significantly more expensive inspection requires placing special sensors on the bridge that essentially listen to how the bridge vibrates.
“Some bridges can afford expensive sensors to do the job, but that comes at a very high cost—hundreds of thousands of dollars per bridge per year,” Ratti says.
We may think of bridges as immovable steel and concrete monoliths, but they naturally vibrate, oscillating slightly. That movement can be influenced by the traffic that passes over them, and even by wind. Bridges of different types vibrate differently—some have longer vibrational frequencies and others shorter ones. A good way to visualize this phenomenon is to place a ruler over the edge of a desk and flick it slightly. If the ruler protrudes far off the desk, it will vibrate slowly. But if you shorten the end that hangs off, it will vibrate much faster. It works similarly with bridges, except there are more factors at play, including not only the length, but also the design and the materials used.
The long suspension bridges such as the Golden Gate or Verrazano Narrows, which hang on a series of cables, are more flexible, and their vibration amplitudes are longer. The Golden Gate Bridge can vibrate at 0.106 Hertz, where one Hertz is one oscillation per second. “Think about standing on the bridge for about 10 seconds—that's how long it takes for it to move all the way up and all the way down in one oscillation,” Matarazzo says.
On the contrary, the concrete span bridges that rest on multiple columns like Brooklyn Bridge or Manhattan Bridge, are “stiffer” and have greater vibrational frequencies. A concrete bridge can have a frequency of 10 Hertz, moving 10 times in one second—like that shorter stretch of a ruler.
The special devices that can pick up and record these vibrations over time are called accelerometers. A network of these devices for each bridge can cost $20,000 to $50,000, and more—and require trained personnel to place them. The sensors also must stay on the bridge for some time to establish what’s a healthy vibrational baseline for a given bridge. Maintaining them adds to the cost. “Some bridges can afford expensive sensors to do the job, but that comes at a very high cost—hundreds of thousands of dollars per bridge per year,” Ratti says.
Making sense of the readouts they gather is another challenge, which requires a high level of technical expertise. “You generally need somebody, some type of expert capable of doing the analysis to translate that data into information,” says Matarazzo, which ticks up the price, so doing visual inspections often proves to be a more economical choice for state-level DOTs with tight budgets. “The existing systems work well, but have downsides,” Ratti says. The team thought the old method could use some modernizing.
Smartphones, which are carried by millions of people, contain dozens of sensors, including the accelerometers capable of picking up the bridges’ vibrations. That’s why Matarazzo and his colleague drove over the bridge 100 times—they were trying to pick up enough data. Timing it to rush hour supported that goal because traffic caused more “excitation,” Matarazzo explains. “Excitation is a big word we use when we talk about what drives the vibration,” he says. “When there's a lot of traffic, there's more excitation and more vibration.” They also collaborated with Uber, whose drivers made 72 trips across the bridge to gather data in different cars.
The next step was to clean the data from “noise”—various vibrations that weren’t relevant to the bridge but came from the cars themselves. “It could be jumps in speed, it could be potholes, it could be a bunch of other things," Matarazzo says. But as the team gathered more data, it became easier to tell the bridge vibrational frequencies from all others because the noises generated by cars, traffic and other things tend to “cancel out.”
The team specifically picked the Golden Gate bridge because the civil structural engineering community had studied it extensively over the years and collected a host of vibrational data, using traditional sensors. When the researchers compared their app-collected frequencies with those gathered by 240 accelerometers formerly placed on the Golden Gate, the results were the same—the data from the phones converged with that from the bridge’s sensors. The smartphone-collected data were just as good as those from industry devices.
The study authors estimate that officials could use crowdsourced data to make key improvements that would help new bridges to last about 14 years longer.
The team also tested their method on a different type of bridge—not a suspension one like the Golden Gate, but a concrete span bridge in Ciampino, Italy. There they compared 280 car trips over the bridge to the six sensors that had been placed on the bridge for seven months. The results were slightly less matching, but a larger volume of trips would fix the divergence, the researchers wrote in their study, titled Crowdsourcing bridge dynamic monitoring with smartphone vehicle trips, published last month in Nature Communications Engineering.
Although the smartphones proved effective, the app is not quite ready to be rolled out commercially for people to start using. “It is still a pilot version,” so there’s room for improvement, says Ratti, who co-authored the study. “But on a more optimistic note, it has really low barriers to entry—all you need is smartphones on cars—so that makes the system easy to reach a global audience.” And the study authors estimate that the use of crowdsourced data would result in a new bridge lasting about 14 years longer.
Matarazzo hopes that the app could be eventually accessible for your average citizen scientist to collect the data and supply it to their local transportation authorities. “I hope that this idea can spark a different type of relationship with infrastructure where people think about the data they're collecting as some type of contribution or investment into their communities,” he says. “So that they can help their own department of transportation, their own municipality to support that bridge and keep it maintained better, longer and safer.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
The Friday Five: Sugar could help catch cancer early
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
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Here are the promising studies covered in this week's Friday Five:
- Catching cancer early could depend on sugar
- How to boost memory in a flash
- This is your brain on books
- A tiny sandwich cake could help the heart
- Meet the top banana for fighting Covid variants