A newborn and mother in the hospital - first touch. (© martin81/Shutterstock)
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.
Dr. David Fajgenbaum looking through a microscope at his lab.
They're running a publicly accessible database called the CORONA Project (COvid19 Registry of Off-label & New Agents) that to date tracks 400 different COVID-19 treatments that have been tried somewhere in the world, along with the frequency of their use, and the outcomes.
"There's so many drugs being used all over the place, in different ways, with different outcomes," says Fajgenbaum. "We're trying to add some order to the madness."
20,000 people have accessed the registry—other physicians and researchers, those in the pharmaceutical industry, and even curious lay people—and the data are now being shared with the U.S. Food and Drug Administration in the hopes of launching large-scale trials that would lead to approving a constellation of treatment options for COVID-19 faster than any new drugs could come online.
"What David's group has done with the CORONA Project is on a scale that I don't think has ever been seen before," says Heather Stone, a health science policy analyst at the FDA who specializes in drug repurposing. She was not involved in establishing the project, but is now working with its data. "To collect and collate that information and make it openly accessible is a massive feat, and a huge benefit to the medical community," she says.
On a Personal Mission
In the science and medical world, Fajgenbaum lives a dual existence: he is both researcher and subject, physician and patient. In July 2010, when he was a healthy and physically fit 25-year-old finishing medical school, he began living through what would become a recurring, unprovoked, and overzealous immune response that repeatedly almost killed him.
His lymph nodes were inflamed; his liver, kidneys, and bone marrow were faltering; and he was dead tired all the time. At first his doctors mistook his mysterious illness for lymphoma, but his inflamed lymph nodes were merely a red herring. A month after his initial hospitalization, pathologists at Mayo Clinic finally diagnosed him with idiopathic multicentric Castleman disease—a particularly ruthless form of a class of lymph node disorders that doesn't just attack one part of the body, but many, and has no known cause. It's a rare diagnosis within an already rare set of disorders. Only about 1,500 Americans a year receive the same diagnosis.
Without many options for treatment, Fajgenbaum underwent recurring rounds of chemotherapy. Each time, the treatment would offer temporary respite from Castleman symptoms, but bring the full spate of chemotherapy side effects. And it wasn't a sustainable treatment for the long haul. Regularly dousing a person's cells in unmitigated toxicity was about as elegant a solution to Fajgenbaum's disease as bulldozing a house in response to a toaster fire. The fire might go out (though not necessarily), but the house would be destroyed.
A swirl of exasperation and doggedness finally propelled Fajgenbaum to take on a crucial question himself: Among all of the already FDA-approved drugs on the market, was there something out there, labeled for another use, that could beat back Castleman disease and that he could tolerate long-term? After months of research, he discovered the answer: sirolimus, a drug normally prescribed to patients receiving a kidney transplant, could be used to suppress his overactive immune system with few known side effects to boot.
Fajgenbaum became hellbent on devoting his practice and research to making similar breakthroughs for others. He founded the Castleman Disease Collaborative Network, to coordinate the research of others studying this bewildering disease, and directs a laboratory consumed with studying cytokine storms—out-of-control immune responses characterized by the body's release of cytokines, proteins that the immune system secretes and uses to communicate with and direct other cells.
In the spring of 2020, when cytokine storms emerged as a hallmark of the most severe and deadly cases of COVID-19, Fajgenbaum's ears perked up. Although SARS-CoV-2 itself was novel, Fajgenbaum already had almost a decade of experience battling the most severe biological forces it brought. Only this time, he thought, it might actually be easier to pinpoint a treatment—unlike Castleman disease, which has no known cause, at least here a virus was clearly the instigator.
"Because [a drug] looks promising, we need to do a well-designed, large randomized controlled trial to really investigate whether this drug works or not ... We don't use that to say, 'You should take it.'"
Thinking Beyond COVID
The week of March 13, when the World Health Organization declared COVID-19 a pandemic, Fajgenbaum found himself hoping that someone would make the same connection and apply the research to COVID. "Then like a minute later I was like, 'Why am I hoping that someone, somewhere, either follows our footsteps, or has a similar background to us? Maybe we just need to do it," he says. And the CORONA Project was born—first as a 10-day exercise, and later as the robust, interactive tool it now is.
All of the 400 treatments in the CORONA database are examples of repurposed drugs, or off-label uses: physicians are prescribing drugs to treat COVID that have been approved for a different disease. There are no bonafide COVID treatments, only inferences. The goal for people like Fajgenbaum and Stone is to identify potential treatments for further study and eventual official approval, so that physicians can treat the disease with a playbook in hand. When it works, drug repurposing opens up a way to move quickly: A range of treatments could be available to patients within just a few years of a totally new virus entering our reality compared with the 12 - 19 years new drug development takes.
"Companies for many decades have explored the use of their products for not just a single indication but often for many indications," says Stone. "'Supplemental approvals' are all essentially examples of drug repurposing, we just didn't call it that. The challenge, I think, is to explore those opportunities more comprehensively and systematically to really try to understand the full breadth of potential activity of any drug or molecule."
The left column shows the path of a repurposed drug, and on the right is the path of a newly discovered and developed drug.
Cures Within Reach
In Fajgenbaum's primary work, promising drugs stand out easily. For a disease like Castleman, where improvement almost never occurs on its own, any improvement that follows a treatment can pretty clearly be attributed to that treatment. But Fajgenbaum says tracking COVID outcomes is less straightforward since "the vast majority of people will get better, whether they take steroids or they take Skittles." That's why the intent of the database is to identify promising treatments only to generate hypotheses and fruitful clinical trials, not to offer full-throated treatment recommendations. Within the registry, Fajgenbaum considers a drug promising if it's being used in humans, not just in lab animals, and a significant proportion of cases report patient improvement.
"It's that sort of combination of rock-solid randomized controlled trial data, plus anecdotal retrospective data, that we combine to say, 'Wow, this drug looks more promising than another,'" says Fajgenbaum. "Because it looks promising, we need to do a well-designed, large randomized controlled trial to really investigate whether this drug works or not ... We don't use that to say, 'You should take it.'"
Experts say that the search for repurposed drugs to treat COVID could have implications for rare diseases in general. Rare diseases, of which Castleman is one, affect 400 million people around the world. 95% of them don't have a tailor-made, FDA-approved drug treatment. Developing one is a lengthy and often prohibitively expensive process. If only a dozen people will benefit from and buy a drug, it's not often worth it to pharmaceutical companies to spend millions of dollars making them. On occasion when they do, however, that overhead shows up in the price tag: the top 10 most expensive drugs in the world are all for rare diseases, often making them inaccessible to patients. Identifying new clinical uses for drugs that already exist is critical for opening a trap door out of a cycle that prioritizes profits over health outcomes.
"COVID is an interesting case where it's demonstrated that when the scientific and medical community really focuses all of its efforts and talents on a single problem, a solution can be identified and in a much faster time period than has ever historically been the case," says Stone. "I certainly wish it hadn't taken a pandemic to do that, but I think it does have lessons for the future in terms of our ability to accomplish things that we might have previously not thought were possible"—for example, mainstreaming the idea of drug repurposing as a treatment tool, even long after the pandemic subsides.
A Confounding Virus
The FDA declined to comment on what drugs it was fast-tracking for trials, but Fajgenbaum says that based on the CORONA Project's data, which includes data from smaller trials that have already taken place, he feels there are three drugs that seem the most clearly and broadly promising for large-scale studies. Among them are dexamethasone, which is a steroid with anti-inflammatory effects, and baricitinib, a rheumatoid arthritis drug, both of which have enabled the sickest COVID-19 patients to bounce back by suppressing their immune systems. The third most clearly promising drug is heparin, a blood thinner, which a recent trial showed to be most helpful when administered at a full dose, more so than at a small, preventative dose. (On the flipside, Fajgenbaum says "it's a little sad" that in the database you can see hydroxychloroquine is still the most-prescribed drug being tried as a COVID treatment around the world, despite over the summer being debunked widely as an effective treatment, and continuously since then.)
One of the confounding attributes of SARS-CoV-2 is its ability to cause such a huge spectrum of outcomes. It's unlikely a silver bullet treatment will emerge under that reality, so the database also helps surface drugs that seem most promising for a specific population. Fluvoxamine, a selective serotonin reuptake inhibitor used to treat obsessive compulsive disorder, showed promise in the recovery of outpatients—those who were sick, but not severely enough to be hospitalized. Tocilizumab, which was actually developed for Castleman disease, the disease Fajgenbaum is managing, was initially written off as a COVID treatment because it failed to benefit large portions of hospitalized patients, but now seems to be effective if used on intensive care unit patients within 24 hours of admission—these are some of the sickest patients with the highest risk of dying.
Other than fluvoxamine, most of the drugs labeled as promising do skew toward targeting hospitalized patients, more than outpatients. One reason, Fajgenbaum says, is that "if you're in a hospital it's very easy to give you a drug and to track you, and there are very objective measurements as to whether you die, you progress to a ventilator, etc." Tracking outpatients is far more difficult, especially when folks have been routinely asked to stay home, quarantine, and free up hospital resources if they're experiencing only mild symptoms.
But the other reason for the skew is because COVID is very unlike most other diseases in terms of the human immune response the virus triggers. For example, if oncology treatments show some benefit to people with the highest risk of dying, then they usually work extremely well if administered in the earlier stages of a cancer diagnosis. Across many diseases, this dialing backward is a standard approach to identifying promising treatments. With COVID, all of that reasoning has proven moot.
As we've seen over the last year, COVID cases often start as asymptomatic, and remain that way for days, indicating the body is mounting an incredibly weak immune response initially. Then, between days five and 14, as if trying to make up for lost time, the immune system overcompensates by launching a major inflammatory response, which in the sickest patient can lead to the type of cytokine storms that helped Fajgenbaum realize his years of Castleman research might be useful during this public health crisis. Because of this phased response, you can't apply the same treatment logic to all cases.
"In COVID, drugs that work late tend to not work if given early, and drugs that work early tend to not work if given late," says Fajgenbaum. "Generally this … is not a commonplace thing for a virus."
"There are drugs that are literally sitting in every single hospital pharmacy in the country that, if a study shows it's effective, can be deployed that evening to patients on a massive scale."
This see-sawing necessitates tracking a constellation of drugs that might work for different stages of the disease as a patient moves from the weak immune response stage into the overzealous immune response.
"COVID is difficult, compared to other diseases, because there are so many different levels of disease severity, and recovery at different rates," says Stone, the FDA researcher. "That makes it hard to see the patterns or signals and it makes it very important to collect very, very large numbers of cases in order to really reliably identify signals."
This particular moment in the pandemic feels like a massive tipping point, or the instant a tiny pinprick of light finally appeared at the end of the tunnel: several vaccines are already here, with more on the way imminently. In the U.S., more than 65 million doses of the vaccine have been administered, and positive COVID cases are finally falling back to levels not seen since October. On the hopeful surface, it might seem a strange moment to be preparing to launch trials that will validate treatments for a virus it seems the U.S. may finally be beating back. But at best, Americans are still months away from reaching herd immunity through vaccination, and new circulating variants may threaten to upend our fragile progress.
"In the meantime, there are drugs that are literally sitting in every single hospital pharmacy in the country that, if a study shows it's effective, can be deployed that evening to patients on a massive scale. It wouldn't have to be newly produced, it wouldn't have to be shipped, it's literally there already," says Fajgenbaum. "The idea that you can save a lot of lives by finding things that are just already there I think is really compelling, given how many people are going to die over these next few months."
Even after that, not everyone can or will be vaccinated, and, as the Wall Street Journal recently reported, "The pathogen will circulate for years, or even decades, leaving society to coexist with Covid-19 much as it does with other endemic diseases like flu, measles, and HIV." Neither vaccines, personal behavior, or treatments alone is a panacea against the virus, but together they might be.
"It's important to explore all avenues in this public health emergency, and drug repurposing can continue to play a role as the pandemic continues and evolves," says Stone. "I think COVID variants in particular are a big concern at the moment, and therefore continuing to investigate new therapeutics, even as the vaccines roll out, will continue to be a priority."
