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.
Did Anton the AI find a new treatment for a deadly cancer?
Bile duct cancer is a rare and aggressive form of cancer that is often difficult to diagnose. Patients with advanced forms of the disease have an average life expectancy of less than two years.
Many patients who get cancer in their bile ducts – the tubes that carry digestive fluid from the liver to the small intestine – have mutations in the protein FGFR2, which leads cells to grow uncontrollably. One treatment option is chemotherapy, but it’s toxic to both cancer cells and healthy cells, failing to distinguish between the two. Increasingly, cancer researchers are focusing on biomarker directed therapy, or making drugs that target a particular molecule that causes the disease – FGFR2, in the case of bile duct cancer.
A problem is that in targeting FGFR2, these drugs inadvertently inhibit the FGFR1 protein, which looks almost identical. This causes elevated phosphate levels, which is a sign of kidney damage, so doses are often limited to prevent complications.
In recent years, though, a company called Relay has taken a unique approach to picking out FGFR2, using a powerful supercomputer to simulate how proteins move and change shape. The team, leveraging this AI capability, discovered that FGFR2 and FGFR1 move differently, which enabled them to create a more precise drug.
Preliminary studies have shown robust activity of this drug, called RLY-4008, in FGFR2 altered tumors, especially in bile duct cancer. The drug did not inhibit FGFR1 or cause significant side effects. “RLY-4008 is a prime example of a precision oncology therapeutic with its highly selective and potent targeting of FGFR2 genetic alterations and resistance mutations,” says Lipika Goyal, assistant professor of medicine at Harvard Medical School. She is a principal investigator of Relay’s phase 1-2 clinical trial.
Boosts from AI and a billionaire
Traditional drug design has been very much a case of trial and error, as scientists investigate many molecules to see which ones bind to the intended target and bind less to other targets.
“It’s being done almost blindly, without really being guided by structure, so it fails very often,” says Olivier Elemento, associate director of the Institute for Computational Biomedicine at Cornell. “The issue is that they are not sampling enough molecules to cover some of the chemical space that would be specific to the target of interest and not specific to others.”
Relay’s unique hardware and software allow simulations that could never be achieved through traditional experiments, Elemento says.
Some scientists have tried to use X-rays of crystallized proteins to look at the structure of proteins and design better drugs. But they have failed to account for an important factor: proteins are moving and constantly folding into different shapes.
David Shaw, a hedge fund billionaire, wanted to help improve drug discovery and understood that a key obstacle was that computer models of molecular dynamics were limited; they simulated motion for less than 10 millionths of a second.
In 2001, Shaw set up his own research facility, D.E. Shaw Research, to create a supercomputer that would be specifically designed to simulate protein motion. Seven years later, he succeeded in firing up a supercomputer that can now conduct high speed simulations roughly 100 times faster than others. Called Anton, it has special computer chips to enable this speed, and its software is powered by AI to conduct many simulations.
After creating the supercomputer, Shaw teamed up with leading scientists who were interested in molecular motion, and they founded Relay Therapeutics.
Elemento believes that Relay’s approach is highly beneficial in designing a better drug for bile duct cancer. “Relay Therapeutics has a cutting-edge approach for molecular dynamics that I don’t believe any other companies have, at least not as advanced.” Relay’s unique hardware and software allow simulations that could never be achieved through traditional experiments, Elemento says.
How it works
Relay used both experimental and computational approaches to design RLY-4008. The team started out by taking X-rays of crystallized versions of both their intended target, FGFR2, and the almost identical FGFR1. This enabled them to get a 3D snapshot of each of their structures. They then fed the X-rays into the Anton supercomputer to simulate how the proteins were likely to move.
Anton’s simulations showed that the FGFR1 protein had a flap that moved more frequently than FGFR2. Based on this distinct motion, the team tried to design a compound that would recognize this flap shifting around and bind to FGFR2 while steering away from its more active lookalike.
For that, they went back Anton, using the supercomputer to simulate the behavior of thousands of potential molecules for over a year, looking at what made a particular molecule selective to the target versus another molecule that wasn’t. These insights led them to determine the best compounds to make and test in the lab and, ultimately, they found that RLY-4008 was the most effective.
Promising results so far
Relay began phase 1-2 trials in 2020 and will continue until 2024. Preliminary results showed that, in the 17 patients taking a 70 mg dose of RLY-4008, the drug worked to shrink tumors in 88 percent of patients. This was a significant increase compared to other FGFR inhibitors. For instance, Futibatinib, which recently got FDA approval, had a response rate of only 42 percent.
Across all dose levels, RLY-4008 shrank tumors by 63 percent in 38 patients. In more good news, the drug didn’t elevate their phosphate levels, which suggests that it could be taken without increasing patients’ risk for kidney disease.
“Objectively, this is pretty remarkable,” says Elemento. “In a small patient study, you have a molecule that is able to shrink tumors in such a high fraction of patients. It is unusual to see such good results in a phase 1-2 trial.”
A simulated future
The research team is continuing to use molecular dynamic simulations to develop other new drug, such as one that is being studied in patients with solid tumors and breast cancer.
As for their bile duct cancer drug, RLY-4008, Relay plans by 2024 to have tested it in around 440 patients. “The mature results of the phase 1-2 trial are highly anticipated,” says Goyal, the principal investigator of the trial.
Sameek Roychowdhury, an oncologist and associate professor of internal medicine at Ohio State University, highlights the need for caution. “This has early signs of benefit, but we will look forward to seeing longer term results for benefit and side effect profiles. We need to think a few more steps ahead - these treatments are like the ’Whack-a-Mole game’ where cancer finds a way to become resistant to each subsequent drug.”
“I think the issue is going to be how durable are the responses to the drug and what are the mechanisms of resistance,” says Raymond Wadlow, an oncologist at the Inova Medical Group who specializes in gastrointestinal and haematological cancer. “But the results look promising. It is a much more selective inhibitor of the FGFR protein and less toxic. It’s been an exciting development.”
The Friday Five: How to exercise for cancer prevention
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:
- How to exercise for cancer prevention
- A device that brings relief to back pain
- Ingredients for reducing Alzheimer's risk
- Is the world's oldest disease the fountain of youth?
- Scared of crossing bridges? Your phone can help