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.
Even before the pandemic created a need for more telehealth options, depression was a hot area of research for app developers. Given the high prevalence of depression and its connection to suicidality — especially among today’s teenagers and young adults who grew up with mobile devices, use them often, and experience these conditions with alarming frequency — apps for depression could be not only useful but lifesaving.
“For people who are not depressed, but have been depressed in the past, the apps can be helpful for maintaining positive thinking and behaviors,” said Andrea K. Wittenborn, PhD, director of the Couple and Family Therapy Doctoral Program and a professor in human development and family studies at Michigan State University. “For people who are mildly to severely depressed, apps can be a useful complement to working with a mental health professional.”
Health and fitness apps, in general, number in the hundreds of thousands. These are driving a market expected to reach $102.45 billion by next year. The mobile mental health app market is a small part of this but still sizable at $500 million, with revenues generated through user health insurance, employers, and direct payments from individuals.
Apps can provide data that health professionals cannot gather on their own. People’s constant interaction with smartphones and wearable devices yields data on many health conditions for millions of patients in their natural environments and while they go about their usual activities. Compared with the in-office measurements of weight and blood pressure and the brevity of doctor-patient interactions, the thousands of data points gathered unobtrusively over an extended time period provide a far better and more detailed picture of the person and their health.
At their most advanced level, apps for mental health, including depression, passively gather data on how the user touches and interacts with the mobile device through changes in digital biomarkers that relate to depressive symptoms and other conditions.
Building on three decades of research since early “apps” were used for delivering treatment manuals to health professionals, today’s more than 20,000 mental health apps have a wide range of functionalities and business models. Many of these apps can be useful for depression.
Some apps primarily provide a virtual connection to a group of mental health professionals employed or contracted by the app. Others have options for meditation, sleeping or, in the case of industry leaders Calm and Headspace, overall well-being. On the cutting edge are apps that detect changes in a person’s use of mobile devices and their interactions with them.
Apps such as AbleTo, Happify Health, and Woebot Health focus on cognitive behavioral therapy, a type of counseling with proven potential to change a person’s behaviors and feelings. “CBT has been demonstrated in innumerable studies over the last several decades to be effective in the treatment of behavioral health conditions such as depression and anxiety disorders,” said Dr. Reena Pande, chief medical officer at AbleTo. “CBT is intended to be delivered as a structured intervention incorporating key elements, including behavioral activation and adaptive thinking strategies.”
These CBT skills help break the negative self-talk (rumination) common in patients with depression. They are taught and reinforced by some self-guided apps, using either artificial intelligence or programmed interactions with users. Apps can address loneliness and isolation through connections with others, even when a symptomatic person doesn’t feel like leaving the house.
At their most advanced level, apps for mental health, including depression, passively gather data on how the user touches and interacts with the mobile device through changes in “digital biomarkers” that can be associated with onset or worsening of depressive symptoms and other cognitive conditions. In one study, Mindstrong Health gathered a year’s worth of data on how people use their smartphones, such as scrolling through articles, typing and clicking. Mindstrong, whose founders include former leaders of the National Institutes of Health, modeled the timing and order of these actions to make assessments that correlated closely with gold-standard tests of cognitive function.
National organizations of mental health professionals have been following the expanding number of available apps over the years with keen interest. App Advisor is an initiative of the American Psychiatric Association that helps psychiatrists and other mental health professionals navigate the issues raised by mobile health technology. App Advisor does not rate or recommend particular apps but rather provides guidance about why apps should be assessed and how health professionals can do this.
A website that does review mental health apps is One Mind Psyber Guide, an independent nonprofit that partners with several national organizations. One Mind users can select among numerous search terms for the condition and therapeutic approach of interest. Apps are rated on a five-point scale, with reviews written by professionals in the field.
Do mental health apps related to depression have the kind of safety and effectiveness data required for medications and other medical interventions? Not always — and not often. Yet the overall results have shown early promise, Wittenborn noted.
“Studies that have attempted to detect depression from smartphone and wearable sensors [during a single session] have ranged in accuracy from about 86 to 89 percent,” Wittenborn said. “Studies that tried to predict changes in depression over time have been less accurate, with accuracy ranging from 59 to 85 percent.”
The Food and Drug Administration encourages the development of apps and has approved a few of them—mostly ones used by health professionals—but it is generally “hands off,” according to the American Psychiatric Association. The FDA has published a list of examples of software (including programming of apps) that it does not plan to regulate because they pose low risk to the public. First on the list is software that helps patients with diagnosed psychiatric conditions, including depression, maintain their behavioral coping skills by providing a “Skill of the Day” technique or message.
On its App Advisor site, the American Psychiatric Association says mental health apps can be dangerous or cause harm in multiple ways, such as by providing false information, overstating the app’s therapeutic value, selling personal data without clearly notifying users, and collecting data that isn’t relevant to mental health.
Although there is currently reason for caution, patients may eventually come to expect mental health professionals to recommend apps, especially as their rating systems, features and capabilities expand. Through such apps, patients might experience more and higher quality interactions with their mental health professionals. “Apps will continue to be refined and become more effective through future research,” said Wittenborn. “They will become more integrated into practice over time.”
Podcast: Has the First 150-Year-Old Already Been Born
Steven Austad is a pioneer in the field of aging, with over 200 scientific papers and book chapters on pretty much every aspect of biological aging that you could think of. He’s also a strong believer in the potential for anti-aging therapies, and he puts his money where his mouth is. In 2001, he bet a billion dollars that the first person to reach 150-years-old had already been born. I had a chance to talk with Steven for today’s podcast and asked if he still thinks the bet was a good idea, since the oldest person so far (that we know of), Jeanne Calment, died back in 1997. A few days after our conversation, the oldest person in the world, Kane Tanaka, died at 119.
Steven is the Protective Life Endowed Chair in Health Aging Research, a Distinguished Professor and Chair of the Department of Biology at the University of Alabama Birmingham. He's also Senior Scientific Director of the American Federation for Aging Research, which is managing a groundbreaking longevity research trial that started this year. Steven is also a great science communicator with five books, including one that comes out later this year, Methuselah’s Zoo, and he publishes prolifically in national media outlets.
See the rest of his bio linked below in the show notes.
Listen to the Episode
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Steven Austad is featured in the latest episode of Making Sense of Science. He's a distinguished professor of biology at the University of Alabama Birmingham and has a new book due to be published in August, Methuselah's Zoo.
Photo by Steve Wood
Show notes:
2:36 - Steven explains why a particular opossum convinced him to dedicate his career to studying longevity.
6:48 - Steven's billion dollar bet that someone alive today will make it to 150-years-old.
9:15 - The most likely people to make it to 150 (Hint: not men).
10:38 - I ask Steven about Elon Musk’s comments this month that if people lived a really long time, “we’d be stuck with old ideas and society wouldn’t advance.” Steve isn’t so fond of that take.
13:34 - Why women are winning maybe the most important battle of sexes: staying alive. This is an area that Steven has led research on (see show notes).
18:20 - Why women, on average, actually have more morbidities earlier than men, even though they live longer.
23:10 - How the pandemic could affect sex differences in longevity.
24:55 - How often should people work out and get other physical activity to maximize longevity and health span?
29:09 - Steven gave me the latest update on the TAME trial on metformin, and how he and others longevity experts designed this groundbreaking research on longevity not in their offices, not on a zoom call, but in a castle in the Spanish countryside.
32:10 - Which anti-aging therapies are the most promising at this point for future research.
39:32 - The drug cocktail approach to address multiple hallmarks of aging.
41:00 - How to read health news like a scientist.
45:38 - Should we try a Manhattan project for aging?
48:47 - Can Jeff Bezos and Larry Ellison help us live to 150?
Show links:
Steven Austad's bio
Pre-order Steven's new book, Methuselah's Zoo - https://www.amazon.com/dp/B09M2QGRJR/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1
Steven's journal article on Sex Differences in Lifespan - https://pubmed.ncbi.nlm.nih.gov/27304504/
Elon Musk's comments on super longevity "asphyxiating" society - https://www.cnbc.com/2022/04/11/elon-musk-on-avoid...
Steven's article on how to read news articles about health like a pro - https://www.nextavenue.org/how-to-read-health-news...
AFAR's research on Targeting Aging with Metformin (TAME) - https://www.afar.org/tame-trial