Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.
Leading XPRIZE Healthspan and Beating Negativity with Dr. Peter Diamandis
A new competition by the XPRIZE Foundation is offering $101 million to researchers who discover therapies that give a boost to people aged 65-80 so their bodies perform more like when they were middle-aged.
For today’s podcast episode, I talked with Dr. Peter Diamandis, XPRIZE’s founder and executive chairman. Under Peter’s leadership, XPRIZE has launched 27 previous competitions with over $300 million in prize purses. The latest contest aims to enhance healthspan, or the period of life when older people can play with their grandkids without any restriction, disability or disease. Such breakthroughs could help prevent chronic diseases that are closely linked to aging. These illnesses are costly to manage and threaten to overwhelm the healthcare system, as the number of Americans over age 65 is rising fast.
In this competition, called XPRIZE Healthspan, multiple awards are available, depending on what’s achieved, with support from the nonprofit Hevolution Foundation and Chip Wilson, the founder of Lululemon and nonprofit SOLVE FSHD. The biggest prize, $81 million, is for improvements in cognition, muscle and immunity by 20 years. An improvement of 15 years will net $71 million, and 10 years will net $61 million.
In our conversation for this episode, Peter talks about his plans for XPRIZE Healthspan and why exponential technologies make the current era - even with all of its challenges - the most exciting time in human history. We discuss the best mental outlook that supports a person in becoming truly innovative, as well as the downsides of too much risk aversion. We talk about how to overcome the negativity bias in ourselves and in mainstream media, how Peter has shifted his own mindset to become more positive over the years, how to inspire a culture of innovation, Peter’s personal recommendations for lifestyle strategies to live longer and healthier, the innovations we can expect in various fields by 2030, the future of education and the importance of democratizing tech and innovation.
In addition to Peter’s pioneering leadership of XPRIZE, he is also the Executive Founder of Singularity University. In 2014, he was named by Fortune as one of the “World’s 50 Greatest Leaders.” As an entrepreneur, he’s started over 25 companies in the areas of health-tech, space, venture capital and education. He’s Co-founder and Vice-Chairman of two public companies, Celularity and Vaxxinity, plus being Co-founder & Chairman of Fountain Life, a fully-integrated platform delivering predictive, preventative, personalized and data-driven health. He also serves as Co-founder of BOLD Capital Partners, a venture fund with a half-billion dollars under management being invested in exponential technologies and longevity companies. Peter is a New York Times Bestselling author of four books, noted during our conversation and in the show notes of this episode. He has degrees in molecular genetics and aerospace engineering from MIT and holds an M.D. from Harvard Medical School.
Show links
- Peter Diamandis bio
- New XPRIZE Healthspan
- Peter Diamandis books
- 27 XPRIZE competitions and counting
- Life Force by Peter Diamandis and Tony Robbins
- Peter Diamandis Twitter
- Longevity Insider newsletter – AI identifies the news
- Peter Diamandis Longevity Handbook
- Hevolution funding for longevity
XPRIZE Founder Peter Diamandis speaks with Mehmoud Khan, CEO of Hevolution Foundation, at the launch of XPRIZE Healthspan.
Hevolution Foundation
From infections with no symptoms to why men are more likely to be hospitalized in the ICU and die of COVID-19, new research shows that your genes play a significant role
Early in the pandemic, genetic research focused on the virus because it was readily available. Plus, the virus contains only 30,000 bases in a dozen functional genes, so it's relatively easy and affordable to sequence. Additionally, the rapid mutation of the virus and its ability to escape antibody control fueled waves of different variants and provided a reason to follow viral genetics.
In comparison, there are many more genes of the human immune system and cellular functions that affect viral replication, with about 3.2 billion base pairs. Human studies require samples from large numbers of people, the analysis of each sample is vastly more complex, and sophisticated computer analysis often is required to make sense of the raw data. All of this takes time and large amounts of money, but important findings are beginning to emerge.
Asymptomatics
About half the people exposed to SARS-CoV-2, the virus that causes the COVID-19 disease, never develop symptoms of this disease, or their symptoms are so mild they often go unnoticed. One piece of understanding the phenomena came when researchers showed that exposure to OC43, a common coronavirus that results in symptoms of a cold, generates immune system T cells that also help protect against SARS-CoV-2.
Jill Hollenbach, an immunologist at the University of California at San Francisco, sought to identify the gene behind that immune protection. Most COVID-19 genetic studies are done with the most seriously ill patients because they are hospitalized and thus available. “But 99 percent of people who get it will never see the inside of a hospital for COVID-19,” she says. “They are home, they are not interacting with the health care system.”
Early in the pandemic, when most labs were shut down, she tapped into the National Bone Marrow Donor Program database. It contains detailed information on donor human leukocyte antigens (HLAs), key genes in the immune system that must match up between donor and recipient for successful transplants of marrow or organs. Each HLA can contain alleles, slight molecular differences in the DNA of the HLA, which can affect its function. Potential HLA combinations can number in the tens of thousands across the world, says Hollenbach, but each person has a smaller number of those possible variants.
She teamed up with the COVID-19 Citizen Science Study a smartphone-based study to track COVID-19 symptoms and outcomes, to ask persons in the bone marrow donor registry about COVID-19. The study enlisted more than 30,000 volunteers. Those volunteers already had their HLAs annotated by the registry, and 1,428 tested positive for the virus.
Analyzing five key HLAs, she found an allele in the gene HLA-B*15:01 that was significantly overrepresented in people who didn’t have any symptoms. The effect was even stronger if a person had inherited the allele from both parents; these persons were “more than eight times more likely to remain asymptomatic than persons who did not carry the genetic variant,” she says. Altogether this HLA was present in about 10 percent of the general European population but double that percentage in the asymptomatic group. Hollenbach and her colleagues were able confirm this in other different groups of patients.
What made the allele so potent against SARS-CoV-2? Part of the answer came from x-ray crystallography. A key element was the molecular shape of parts of the cold virus OC43 and SARS-CoV-2. They were virtually identical, and the allele could bind very tightly to them, present their molecular antigens to T cells, and generate an extremely potent T cell response to the viruses. And “for whatever reasons that generated a lot of memory T cells that are going to stick around for a long time,” says Hollenbach. “This T cell response is very early in infection and ramps up very quickly, even before the antibody response.”
Understanding the genetics of the immune response to SARS-CoV-2 is important because it provides clues into the conditions of T cells and antigens that support a response without any symptoms, she says. “It gives us an opportunity to think about whether this might be a vaccine design strategy.”
Dead men
A researcher at the Leibniz Institute of Virology in Hamburg Germany, Guelsah Gabriel, was drawn to a question at the other end of the COVID-19 spectrum: why men more likely to be hospitalized and die from the infection. It wasn't that men were any more likely to be exposed to the virus but more likely, how their immune system reacted to it
Several studies had noted that testosterone levels were significantly lower in men hospitalized with COVID-19. And, in general, the lower the testosterone, the worse the prognosis. A year after recovery, about 30 percent of men still had lower than normal levels of testosterone, a condition known as hypogonadism. Most of the men also had elevated levels of estradiol, a female hormone (https://pubmed.ncbi.nlm.nih.gov/34402750/).
Every cell has a sex, expressing receptors for male and female hormones on their surface. Hormones docking with these receptors affect the cells' internal function and the signals they send to other cells. The number and role of these receptors varies from tissue to tissue.
Gabriel began her search by examining whole exome sequences, the protein-coding part of the genome, for key enzymes involved in the metabolism of sex hormones. The research team quickly zeroed in on CYP19A1, an enzyme that converts testosterone to estradiol. The gene that produces this enzyme has a number of different alleles, the molecular variants that affect the enzyme's rate of metabolizing the sex hormones. One genetic variant, CYP19A1 (Thr201Met), is typically found in 6.2 percent of all people, both men and women, but remarkably, they found it in 68.7 percent of men who were hospitalized with COVID-19.
Lung surprise
Lungs are the tissue most affected in COVID-19 disease. Gabriel wondered if the virus might be affecting expression of their target gene in the lung so that it produces more of the enzyme that converts testosterone to estradiol. Studying cells in a petri dish, they saw no change in gene expression when they infected cells of lung tissue with influenza and the original SARS-CoV viruses that caused the SARS outbreak in 2002. But exposure to SARS-CoV-2, the virus responsible for COVID-19, increased gene expression up to 40-fold, Gabriel says.
Did the same thing happen in humans? Autopsy examination of patients in three different cites found that “CYP19A1 was abundantly expressed in the lungs of COVID-19 males but not those who died of other respiratory infections,” says Gabriel. This increased enzyme production led likely to higher levels of estradiol in the lungs of men, which “is highly inflammatory, damages the tissue, and can result in fibrosis or scarring that inhibits lung function and repair long after the virus itself has disappeared.” Somehow the virus had acquired the capacity to upregulate expression of CYP19A1.
Only two COVID-19 positive females showed increased expression of this gene. The menopause status of these women, or whether they were on hormone replacement therapy was not known. That could be important because female hormones have a protective effect for cardiovascular disease, which women often lose after going through menopause, especially if they don’t start hormone replacement therapy. That sex-specific protection might also extend to COVID-19 and merits further study.
The team was able to confirm their findings in golden hamsters, the animal model of choice for studying COVID-19. Testosterone levels in male animals dropped 5-fold three days after infection and began to recover as viral levels declined. CYP19A1 transcription increased up to 15-fold in the lungs of the male but not the females. The study authors wrote, “Virus replication in the male lungs was negatively associated with testosterone levels.”
The medical community studying COVID-19 has slowly come to recognize the importance of adipose tissue, or fat cells. They are known to express abundant levels of CYP19A1 and play a significant role as metabolic tissue in COVID-19. Gabriel adds, “One of the key findings of our study is that upon SARS-CoV-2 infection, the lung suddenly turns into a metabolic organ by highly expressing” CYP19A1.
She also found evidence that SARS-CoV-2 can infect the gonads of hamsters, thereby likely depressing circulating levels of sex hormones. The researchers did not have autopsy samples to confirm this in humans, but others have shown that the virus can replicate in those tissues.
A possible treatment
Back in the lab, substituting low and high doses of testosterone in SARS-COV-2 infected male hamsters had opposite effects depending on testosterone dosage used. Gabriel says that hormone levels can vary so much, depending on health status and age and even may change throughout the day, that “it probably is much better to inhibit the enzyme” produced by CYP19A1 than try to balance the hormones.
Results were better with letrozole, a drug approved to treat hypogonadism in males, which reduces estradiol levels. The drug also showed benefit in male hamsters in terms of less severe disease and faster recovery. She says more details need to be worked out in using letrozole to treat COVID-19, but they are talking with hospitals about clinical trials of the drug.
Gabriel has proposed a four hit explanation of how COVID-19 can be so deadly for men: the metabolic quartet. First is the genetic risk factor of CYP19A1 (Thr201Met), then comes SARS-CoV-2 infection that induces even greater expression of this gene and the deleterious increase of estradiol in the lung. Age-related hypogonadism and the heightened inflammation of obesity, known to affect CYP19A1 activity, are contributing factors in this deadly perfect storm of events.
Studying host genetics, says Gabriel, can reveal new mechanisms that yield promising avenues for further study. It’s also uniting different fields of science into a new, collaborative approach they’re calling “infection endocrinology,” she says.