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.
The Women of RNA: Two Award-Winners Share Why They Spent Their Careers Studying DNA's Lesser-Known Cousin
When Lynne Maquat, who leads the Center for RNA Biology at the University of Rochester, became interested in the ribonucleic acid molecule in the 1970s, she was definitely in the minority. The same was true for Joan Steitz, now professor of molecular biophysics and biochemistry at Yale University, who began to study RNA a decade earlier in the 1960s.
"My first RNA experiment was a failure, because we didn't understand how things worked," Steitz recalls. In her first undergraduate experiment, she unwittingly used a lab preparation that destroyed the RNA. "Unknowingly, our preparation contained enzymes that degraded our RNA."
At the time, scientists pursuing genetic research tended to focus on DNA, or deoxyribonucleic acid — and for good reason. It was clear that the enigmatic double-helix ribbon held the answers to organisms' heredity, genetic traits, development, growth and aging. If scientists could decipher the secrets of DNA and understand how its genetic instructions translate into the body's functions in health and disease, they could develop treatments for all kinds of diseases. On the contrary, the prevailing dogma of the time viewed RNA as merely a helper that passively carried out DNA's genetic instructions for protein-making — so it received much less attention.
But Maquat and Steitz weren't interested in heredity. They studied biochemistry and biophysics, so they wanted to understand how RNA functioned on the molecular level — how it carried instructions, catalyzed reactions, and helped build protein bonds, among other things.
"I'm a mechanistic biochemist, so I like to know how things happen," Maquat says. "Once you understand the mechanism, you can think of how to solve problems." And so the quest to understand how RNA does its job became the focus of both women's careers.
"People can now appreciate why some of us studied RNA for such a long time."
Half a century later, in 2021, their RNA work has earned two prestigious recognitions only months from each other. In February, they received the Wolf Prize in Medicine, followed by the Warren Alpert Foundation Prize in May, awarded to scientists whose achievements led to prevention, cure or treatments of human diseases.
It was the development of the COVID-19 vaccines that made RNA a household name. Made by Moderna and Pfizer, the vaccines use the RNA molecule to deliver genetic instructions for making SARS-CoV-2's characteristic spike protein in our cells. The presence of this foreign-looking protein triggers the immune system to attack and remember the pathogen. As the vaccines reached the finish line, RNA took center stage, and it was Maquat's and Steitz's research that helped reveal how these molecular cogwheels drive many biological functions within cells.
If you think of a cell as a kingdom, the DNA plays the role of a queen. Like a monarch in a palace, DNA nestles inside the cell's nucleus issuing instructions needed for the cell to function. But no queen can successfully govern without her court, her messengers, and her soldiers, as well as other players that make her kingdom work. That's what RNAs do — they act as the DNA's vassals. They carry instructions for protein assembly, catalyze reactions and supervise many other processes to make sure the cellular kingdom performs as it should.
There are a myriad of these RNA vassals in our cells, and each type has its own specific task. There are messenger RNAs that deliver genetic instructions for protein synthesis from DNA to ribosomes, the cells' protein-making factories. There are ribosomal RNAs that help stitch together amino acids to make proteins. There are transfer RNAs that can bring amino acids to this protein synthesis machine, keeping it going. Then there are circular RNAs that act as sponges, absorbing proteins to help regulate the activity of genes. And that's only the tip of the iceberg when it comes to RNA diversity, researchers say.
"We know what the most abundant and important RNAs are doing," says Steitz. "But there are thousands of different ones, and we still don't have a full knowledge of them."
Critical to RNA's proper functioning is a process called splicing, in which a precursor mRNA is transformed into mature, fully-functional mRNA — a phenomenon that Steitz's work helped elucidate. The splicing process, which takes place in cellular assembly lines, involves removing extra RNA sequences and stringing the remaining RNA pieces together. Steitz found that tiny RNA particles called snRNPs are crucial to this process. They act as handy helpers, finding and removing errant genetic material from the mRNA molecules.
A dysfunctional RNA assembly line leads to diseases, including many cancers. For instance, Steitz found that people with Lupus — an autoimmune disorder — have antibodies that mistakenly attack the little snRNP helpers. She also discovered that when snRNPs don't do their job properly, they can cause what scientists call mis-splicing, producing defective mRNAs.
Fortunately, cells have a built-in quality-control process that can spot and correct these mistakes, which is what Maquat studied in her work. In 1981, she discovered a molecular quality-control system that spots and destroys such incorrectly assembled mRNA. With the cryptic name "nonsense-mediated mRNA decay" or NMD, this process is vital to the health and wellbeing of a cellular kingdom in humans — because splicing mistakes happen far more often than one would imagine.
"We estimate that about a third of our mRNA are mistakes," Maquat says. "And nonsense-mediated mRNA decay cleans up these mistakes." When this quality-control system malfunctions, defective mRNA forge faulty proteins, which mess up the cellular machinery and cause disease, including various forms of cancer.
Scientists' newfound appreciation of RNA opens door to many novel treatments.
Now that the first RNA-based shots were approved, the same principle can be used for create vaccines for other diseases, the two RNA researchers say. Moreover, the molecule has an even greater potential — it can serve as a therapeutic target for other disorders. For example, Spinraza, a groundbreaking drug approved in 2016 for spinal muscular atrophy, uses small snippets of synthetic genetic material that bind to the RNA, helping fix splicing errors. "People can now appreciate why some of us studied RNA for such a long time," says Maquat.
Steitz is thrilled that the entire field of RNA research is enjoying the limelight. "I'm delighted because the prize is more of a recognition of the field than just our work," she says. "This is a more general acknowledgment of how basic research can have a remarkable impact on human health."
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
In 2010, a 67-year-old former executive assistant for a Fortune 500 company was diagnosed with mild cognitive impairment. By 2014, her doctors confirmed she had Alzheimer's disease.
As her disease progressed, she continued to live independently but wasn't able to drive anymore. Today, she can manage most of her everyday tasks, but her two daughters are considering a live-in caregiver. Despite her condition, the woman may represent a beacon of hope for the approximately 44 million people worldwide living with Alzheimer's disease. The now 74-year-old is among a small cadre of Alzheimer's patients who have undergone an experimental ultrasound procedure aimed at slowing cognitive decline.
In November 2020, Elisa Konofagou, a professor of biomedical engineering and director of the Ultrasound and Elasticity Imaging Laboratory at Columbia University, and her team used ultrasound to noninvasively open the woman's blood-brain barrier. This barrier is a highly selective membrane of cells that prevents toxins and pathogens from entering the brain while allowing vital nutrients to pass through. This regulatory function means the blood-brain barrier filters out most drugs, making treating Alzheimer's and other brain diseases a challenge.
Ultrasound uses high-frequency sound waves to produce live images from the inside of the human body. But scientists think it could also be used to boost the effectiveness of Alzheimer's drugs, or potentially even improve brain function in dementia patients without the use of drugs.
The procedure, which involves a portable ultrasound system, is the culmination of 17 years of lab work. As part of a small clinical trial, scientists positioned a sensor transmitting ultrasound waves on top of the woman's head while she sat in a chair. The sensor sends ultrasound pulses throughout the target region. Meanwhile, investigators intravenously infused microbubbles into the woman to boost the effects of the ultrasound. Three days after the procedure, scientists scanned her brain so that they could measure the effects of the treatments. Five months later, they took more images of her brain to see if the effects of the treatment lasted.
Promising Signs
After the first brain scan, Konofagou and her team found that amyloid-beta, the protein that clumps together in the brains of Alzheimer's patients and disrupts cell function, had declined by 14%. At the woman's second scan, amyloid levels were still lower than before the experimental treatment, but only by 10% this time. Konofagou thinks repeat ultrasound treatments given early on in the development of Alzheimer's may have the best chance at keeping amyloid plaques at bay.
This reduction in amyloid appeared to halt the woman's cognitive decline, at least temporarily. Following the ultrasound treatment, the woman took a 30-point test used to measure cognitive impairment in Alzheimer's. Her score — 22, indicating mild cognitive impairment — remained the same as before the intervention. Konofagou says this was actually a good sign.
"Typically, every six months an Alzheimer's patient scores two to three points lower, so this is highly encouraging," she says.
Konofagou speculates that the results might have been even more impressive had they applied the ultrasound on a larger section of the brain at a higher frequency. The selected site was just 4 cubic centimeters. Current safety protocols set by the U.S. Food and Drug Administration stipulate that investigators conducting such trials only treat one brain region with the lowest pressure possible.
The Columbia trial is aided by microbubble technology. During the procedure, investigators infused tiny, gas-filled spheres into the woman's veins to enhance the ultrasound reflection of the sound waves.
The big promise of ultrasound is that it could eventually make drugs for Alzheimer's obsolete.
"Ultrasound with microbubbles wakes up immune cells that go on to discard amyloid-beta," Konofagou says. "In this way, we can recover the function of brain neurons, which are destroyed by Alzheimer's in a sort of domino effect." What's more, a drug delivered alongside ultrasound can penetrate the brain at a dose up to 10 times higher.
Costas Arvanitis, an assistant professor at Georgia Institute of Technology who studies ultrasonic biophysics and isn't involved in the Columbia trial, is excited about the research. "First, by applying ultrasound you can make larger drugs — picture an antibody — available to the brain," he says. Then, you can use ultrasound to improve the therapeutic index, or the ratio of the effectiveness of a drug versus the ratio of adverse effects. "Some drugs might be effective but because we have to provide them in high doses to see significant responses they tend to come with side effects. By improving locally the concentration of a drug, you open up the possibility to reduce the dose."
The Columbia trial will enroll just six patients and is designed to test the feasibility and safety of the approach, not its efficacy. Still, Arvantis is hopeful about the potential benefits of the technique. "The technology has already been demonstrated to be safe, its components are now tuned to the needs of this specific application, and it's safe to say it's only a matter of time before we are able to develop personalized treatments," he says.
Konofagou and her colleagues recently presented their findings at the 20th Annual International Symposium for Therapeutic Ultrasound and intend to publish them in a scientific journal later this year. They plan to recruit more participants for larger trials, which will determine how effective the therapy is at improving memory and brain function in Alzheimer's patients. They're also in talks with pharmaceutical companies about ways to use their therapeutic approach to improve current drugs or even "create new drugs," says Konofagou.
A New Treatment Approach
On June 7, the FDA approved the first Alzheimer's disease drug in nearly two decades. Aducanumab, a drug developed by Biogen, is an antibody designed to target and reduce amyloid plaques. The drug has already sparked immense enthusiasm — and controversy. Proponents say the drug is a much-needed start in the fight against the disease, but others argue that the drug doesn't substantially improve cognition. They say the approval could open the door to the FDA greenlighting more Alzheimer's drugs that don't have a clear benefit, giving false hope to both patients and their families.
Konofagou's ultrasound approach could potentially boost the effects of drugs like aducanumab. "Our technique can be seamlessly combined with aducanumab in early Alzheimer's, where it has shown the most promise, to further enhance both its amyloid load reduction and further reduce cognitive deficits while using exactly the same drug regimen otherwise," she says. For the Columbia team, the goal is to use ultrasound to maximize the effects of aducanumab, as they've done with other drugs in animal studies.
But Konofagou's approach could transcend drug controversies, and even drugs altogether. The big promise of ultrasound is that it could eventually make drugs for Alzheimer's obsolete.
"There are already indications that the immune system is alerted each time ultrasound is exerted on the brain or when the brain barrier is being penetrated and gets activated, which on its own may have sufficient therapeutic effects," says Konofagou. Her team is now working with psychiatrists in hopes of using brain stimulation to treat patients with depression.
The potential to modulate the brain without drugs is huge and untapped, says Kim Butts Pauly, a professor of radiology, electrical engineering and bioengineering at Stanford University, who's not involved in the Columbia study. But she admits that scientists don't know how to fully control ultrasound in the brain yet. "We're only at the starting point of getting the tools to understand and harness how ultrasound microbubbles stimulate an immune response in the brain."
Meanwhile, the 74-year-old woman who received the ultrasound treatment last year, goes on about her life, having "both good days and bad days," her youngest daughter says. COVID-19's isolation took a toll on her, but both she and her daughters remain grateful for the opportunity to participate in the ultrasound trial.
"My mother wants to help, if not for herself, then for those who will follow her," the daughter says. She hopes her mother will be able to join the next phase of the trial, which will involve a drug in conjunction with the ultrasound treatment. "This may be the combination where the magic will happen," her daughter says.