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.
In different countries' national dietary guidelines, red meats (beef, pork, and lamb) are often confined to a very small corner. Swedish officials, for example, advise the population to "eat less red and processed meat". Experts in Greece recommend consuming no more than four servings of red meat — not per week, but per month.
"Humans 100% rely on the microbes to digest this food."
Yet somehow, the matter is far from settled. Quibbles over the scientific evidence emerge on a regular basis — as in a recent BMJ article titled, "No need to cut red meat, say new guidelines." News headlines lately have declared that limiting red meat may be "bad advice," while carnivore diet enthusiasts boast about the weight loss and good health they've achieved on an all-meat diet. The wildly successful plant-based burgers? To them, a gimmick. The burger wars are on.
Nutrition science would seem the best place to look for answers on the health effects of specific foods. And on one hand, the science is rather clear: in large populations, people who eat more red meat tend to have more health problems, including cardiovascular disease, colorectal cancer, and other conditions. But this sort of correlational evidence fails to settle the matter once and for all; many who look closely at these studies cite methodological shortcomings and a low certainty of evidence.
Some scientists, meanwhile, are trying to cut through the noise by increasing their focus on the mechanisms: exactly how red meat is digested and the step-by-step of how this affects human health. And curiously, as these lines of evidence emerge, several of them center around gut microbes as active participants in red meat's ultimate effects on human health.
Dr. Stanley Hazen, researcher and medical director of preventive cardiology at Cleveland Clinic, was one of the first to zero in on gut microorganisms as possible contributors to the health effects of red meat. In looking for chemical compounds in the blood that could predict the future development of cardiovascular disease, his lab identified a molecule called trimethylamine-N-oxide (TMAO). Little by little, he and his colleagues began to gather both human and animal evidence that TMAO played a role in causing heart disease.
Naturally, they tried to figure out where the TMAO came from. Hazen says, "We found that animal products, and especially red meat, were a dietary source that, [along with] gut microbes, would generate this product that leads to heart disease development." They observed that the gut microbes were essential for making TMAO out of dietary compounds (like red meat) that contained its precursor, trimethylamine (TMA).
So in linking red meat to cardiovascular disease through TMAO, the surprising conclusion, says Hazen, was that, "Without a doubt, [the microbes] are the most important aspect of the whole pathway."
"I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
Other researchers have taken an interest in different red-meat-associated health problems, like colorectal cancer and the inflammation that accompanies it. This was the mechanistic link tackled by the lab of professor Karsten Zengler of the UC San Diego Departments of Pediatrics and Bioengineering—and it also led straight back to the gut microbes.
Zengler and colleagues recently published a paper in Nature Microbiology that focused on the effects of a red meat carbohydrate (or sugar) called Neu5Gc.
He explains, "If you eat animal proteins in your diet… the bound sugars in your diet are cleaved off in your gut and they get recycled. Your own cells will not recognize between the foreign sugars and your own sugars, because they look almost identical." The unsuspecting human cells then take up these foreign sugars — spurring antibody production and creating inflammation.
Zengler showed, however, that gut bacteria use enzymes to cleave off the sugar during digestion, stopping the inflammation and rendering the sugar harmless. "There's no enzyme in the human body that can cleave this [sugar] off. Humans 100% rely on the microbes to digest this food," he says.
Both researchers are quick to caution that the health effects of diet are complex. Other work indicates, for example, that while intake of red meat can affect TMAO levels, so can intake of fish and seafood. But these new lines of evidence could help explain why some people, ironically, seem to be in perfect health despite eating a lot of red meat: their ideal frequency of meat consumption may depend on their existing community of gut microbes.
"It helps explain what accounts for inter-person variability," Hazen says.
These emerging mechanisms reinforce overall why it's prudent to limit red meat, just as the nutritional guidelines advised in the first place. But both Hazen and Zengler predict that interventions to buffer the effects of too many ribeyes may be just around the corner.
Zengler says, "Our idea is that you basically can help your own digestive system detoxify these inflammatory compounds in meat, if you continue eating red meat or you want to eat a high amount of red meat." A possibly strategy, he says, is to use specific pre- or probiotics to cultivate an inflammation-reducing gut microbial community.
Hazen foresees the emergence of drugs that act not on the human, but on the human's gut microorganisms. "I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
He adds, "It's a matter of 'stay tuned', I think."
New Device Can Detect Peanut Allergens on a Plate in 30 Seconds
People with life-threatening allergies live in constant fear of coming into contact with deadly allergens. Researchers estimate that about 32 million Americans have food allergies, with the most severe being milk, egg, peanut, tree nuts, wheat, soy, fish, and shellfish.
"It is important to understand that just several years ago, this would not have been possible."
Every three minutes, a food allergy reaction sends someone to the emergency room, and 200,000 people in the U.S. require emergency medical care each year for allergic reactions, according to Food Allergy Research and Education.
But what if there was a way you could easily detect if something you were about to eat contains any harmful allergens? Thanks to Israeli scientists, this will soon be the case — at least for peanuts. The team has been working to develop a handheld device called Allerguard, which analyzes the vapors in your meal and can detect allergens in 30 seconds.
Leapsmag spoke with the founder and CTO of Allerguard, Guy Ayal, about the groundbreaking technology, how it works, and when it will be available to purchase.
What prompted you to create this device? Do you have a personal connection with severe food allergies?
Guy Ayal: My eldest daughter's best friend suffers from a severe food allergy, and I experienced first-hand the effect it has on the person and their immediate surroundings. Most notable for me was the effect on the quality of life – the experience of living in constant fear. Everything we do at Allerguard is basically to alleviate some of that fear.
How exactly does the device work?
The device is built on two main pillars. The first is the nano-chemical stage, in which we developed specially attuned nanoparticles that selectively adhere only to the specific molecules that we are looking for. Those molecules, once bound to the nanoparticles, induce a change in their electrical behavior, which is measured and analyzed by the second main pillar -- highly advanced machine learning algorithms, which can surmise which molecules were collected, and thus whether or not peanuts (or in the future, other allergens) were detected.
It is important to understand that just several years ago, this would not have been possible, because both the nano-chemistry, and especially the entire world of machine learning, big data, and what is commonly known as AI only started to exist in the '90s, and reached applicability for handheld devices only in the past few years.
Where are you at in the development process and when will the device be available to consumers?
We have concluded the proof of concept and proof of capability phase, when we demonstrated successful detection of the minimal known clinical amount that may cause the slightest effect in the most severely allergic person – less than 1 mg of peanut (actually it is 0.7 mg). Over the next 18 months will be productization, qualification, and validation of our device, which should be ready to market in the latter half of 2021. The sensor will be available in the U.S., and after a year in Europe and Canada.
The Allerguard was made possible through recent advances in machine learning, big data, and AI.
(Courtesy)
How much will it cost?
Our target price is about $200 for the device, with a disposable SenseCard that will run for at least a full day and cost about $1. That card is for a specific allergen and will work for multiple scans in a day, not just one time.
[At a later stage, the company will have sensors for other allergens like tree nuts, eggs, and milk, and they'll develop a multi-SenseCard that works for a few allergens at once.]
Are there any other devices on the market that do something similar to Allerguard?
No other devices are even close to supplying the level of service that we promise. All known methods for allergen detection rely on sampling of the food, which is a viable solution for homogenous foodstuffs, such as a factory testing their raw ingredients, but not for something as heterogenous as an actual dish – especially not for solid allergens such as peanuts, treenuts, or sesame.
If there is a single peanut in your plate, and you sample from anywhere on that plate which is not where that peanut is located, you will find that your sample is perfectly clean – because it is. But the dish is not. That dish is a death trap for an allergic person. Allerguard is the only suggested solution that could indeed detect that peanut, no matter where in that plate it is hiding.
Anything else readers should know?
Our first-generation product will be for peanuts only. You have to understand, we are still a start-up company, and if we don't concentrate our limited resources to one specific goal, we will not be able to achieve anything at all. Once we are ready to market our first device, the peanut detector, we will be able to start the R&D for the 2nd product, which will be for another allergen – most likely tree nuts and/or sesame, but that will probably be in debate until we actually start it.