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.
Hiking is one of Marci Flory's favorite activities, but her chronic Lyme disease sometimes renders her unable to walk. Biotech companies Pfizer and Valneva are testing a vaccine for Lyme disease in a Phase III clinical trial.
“Initially doctors thought I had ALS, or less likely, multiple sclerosis,” she says. “But after repeated MRI scans for a year, they concluded I had a rare neurological condition called acute transverse myelitis.”
But Flory was not convinced. After ordering a variety of private blood tests, she discovered she was infected with a range of bacteria in the genus Borrelia that live in the guts of ticks, the infectious agents responsible for Lyme disease.
“It made sense,” she says. “Looking back, I was bitten in high school and misdiagnosed with mononucleosis. This was probably the start, and my immune system kept it under wraps for a while. The Lyme bacteria can burrow into every tissue in the body, go into cyst form and become dormant before reactivating.”
The reason why cases of Lyme disease are increasing is down to changing weather patterns, triggered by climate change, meaning that ticks are now found across a much wider geographic range than ever before.
When these species of bacteria are transmitted to humans, they can attack the nervous system, joints and even internal organs which can lead to serious health complications such as arthritis, meningitis and even heart failure. While Lyme disease can sometimes be successfully treated with antibiotics if spotted early on, not everyone responds to these drugs, and for patients who have developed chronic symptoms, there is no known cure. Flory says she knows of fellow Lyme disease patients who have spent hundreds of thousands of dollars seeking treatments.
Concerningly, statistics show that Lyme and other tick-borne diseases are on the rise. Recently released estimates based on health insurance records suggest that at least 476,000 Americans are diagnosed with Lyme disease every year, and many experts believe the true figure is far higher.
The reason why the numbers are growing is down to changing weather patterns, triggered by climate change, meaning that ticks are now found across a much wider geographic range than ever before. Health insurance data shows that cases of Lyme disease have increased fourfold in rural parts of the U.S. over the last 15 years, and 65 percent in urban regions.
As a result, many scientists who have studied Lyme disease feel that it is paramount to bring some form of protective vaccine to market which can be offered to people living in the most at-risk areas.
“Even the increased awareness for Lyme disease has not stopped the cases,” says Eva Sapi, professor of cellular and molecular biology at the University of New Haven. “Some of these patients are looking for answers for years, running from one doctor to another, so that is obviously a very big cost for our society at so many levels.”
Emerging vaccines – and backlash
But with the rising case numbers, interest has grown among the pharmaceutical industry and research communities. Vienna-based biotech Valneva have partnered with Pfizer to take their vaccine – a seasonal jab which offers protection against the six most common strains of Lyme disease in the northern hemisphere – into a Phase III clinical trial which began in August. Involving 6,000 participants in a number of U.S. states and northern Europe where Lyme disease is endemic, it could lead to a licensed vaccine by 2025, if it proves successful.
“For many years Lyme was considered a small market vaccine,” explains Monica E. Embers, assistant professor of parasitology at Tulane University in New Orleans. “Now we know that this is a much bigger problem, Pfizer has stepped up to invest in preventing this disease and other pharmaceutical companies may as well.”
Despite innovations, patient communities and their representatives remain ambivalent about the idea of a vaccine. Some of this skepticism dates back to the failed LYMErix vaccine which was developed in the late 1990s before being withdrawn from the market.
At the same time, scientists at Yale University are developing a messenger RNA vaccine which aims to train the immune system to respond to tick bites by exposing it to 19 proteins found in tick saliva. Whereas the Valneva vaccine targets the bacteria within ticks, the Yale vaccine attempts to provoke an instant and aggressive immune response at the site of the bite. This causes the tick to fall off and limits the potential for transmitting dangerous infections.
But despite these innovations, patient communities and their representatives remain ambivalent about the idea of a vaccine. Some of this skepticism dates back to the failed LYMErix vaccine which was developed in the late 1990s before being withdrawn from the market in 2002 after concerns were raised that it might induce autoimmune reactions in humans.
While this theory was ultimately disproved, the lingering stigma attached to LYMErix meant that most vaccine manufacturers chose to stay away from the disease for many years, something which Gregory Poland, head of the Mayo Clinic’s Vaccine Research Group in Minnesota, describes as a tragedy.
“Since 2002, we have not had a human Lyme vaccine in the U.S. despite the increasing number of cases,” says Poland. “Pretty much everyone in the field thinks they’re ten times higher than the official numbers, so you’re probably talking at least 400,000 each year. It’s an incredible burden but because of concerns about anti-vax protestors, until very recently, no manufacturer has wanted to touch this.”
Such was the backlash surrounding the failed LYMErix program that scientists have even explored the most creative of workarounds for protecting people in tick-populated regions, without needing to actually vaccinate them. One research program at the University of Tennessee came up with the idea of leaving food pellets containing a vaccine in woodland areas with the idea that rodents would eat the pellets, and the vaccine would then kill Borrelia bacteria within any ticks which subsequently fed on the animals.
Even the Pfizer-Valneva vaccine has been cautiously designed to try and allay any lingering concerns, two decades after LYMErix. “The concept is the same as the original LYMErix vaccine, but it has been made safer by removing regions that had the potential to induce autoimmunity,” says Embers. “There will always be individuals who oppose vaccines, Lyme or otherwise, but it will be a tremendous boost to public health to have the option.”
Vaccine alternatives
Researchers are also considering alternative immunization approaches in case sufficiently large numbers of people choose to reject any Lyme vaccine which gets approved. Researchers at UMass Chan Medical School have developed an artificially generated antibody, administered via an annual injection, which is capable of killing Borrelia bacteria in the guts of ticks before they can get into the human host.
So far animal studies have shown it to be 100 percent effective, while the scientists have completed a Phase I trial in which they tested it for safety on 48 volunteers in Nebraska. Because this approach provides the antibody directly, rather than triggering the human immune system to produce the antibody like a vaccine would, Embers predicts that it could be a viable alternative for the vaccine hesitant as well as providing an option for immunocompromised individuals who cannot produce enough of their own antibodies.
At the same time, many patient groups still raise concerns over the fact that numerous diagnostic tests for Lyme disease have been reported to have a poor accuracy. Without this, they argue that it is difficult to prove whether vaccines or any other form of immunization actually work. “If the disease is not understood enough to create a more accurate test and a universally accepted treatment protocol, particularly for those who weren’t treated promptly, how can we be sure about the efficacy of a vaccine?” says Natasha Metcalf, co-founder of the organization Lyme Disease UK.
Flory points out that there are so many different types of Borrelia bacteria which cause Lyme disease, that the immunizations being developed may only stop a proportion of cases. In addition, she says that chronic Lyme patients often report a whole myriad of co-infections which remain poorly understood and are likely to also be involved in the disease process.
Marci Flory undergoes an infusion in an attempt to treat her Lyme disease symptoms.
Marci Flory
“I would love to see an effective Lyme vaccine but I have my reservations,” she says. “I am infected with four types of Borrelia bacteria, plus many co-infections – Babesia, Bartonella, Erlichiosis, Rickettsia, and Mycoplasma – all from a single Douglas County Kansas tick bite. Lyme never travels alone and the vaccine won’t protect against all the many strains of Borrelia and co-infections.”
Valneva CEO Thomas Lingelbach admits that the Pfizer-Valneva vaccine is not perfect, but predicts that it will still have significant impact if approved.
“We expect the vaccine to have 75 percent plus efficacy,” he says. “There is this legacy around the old Lyme vaccines, but the world is very, very different today. The number of clinical manifestations known to be caused by infection with Lyme Borreliosis has significantly increased, and the understanding around severity has certainly increased.”
Embers agrees that while it will still be important for doctors to monitor for other tick-borne infections which are not necessarily covered by the vaccine, having any clinically approved jab would still represent a major step forward in the fight against the disease.
“I think that any vaccine must be properly vetted, and these companies are performing extensive clinical trials to do just that,” she says. “Lyme is the most common tick-borne disease in the U.S. so the public health impact could be significant. However, clinicians and the general public must remain aware of all of the other tick-borne diseases such as Babesia and Anaplasma, and continue to screen for those when a tick bite is suspected.”
A mosquito under the microscope.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.