COVID Variants Are Like “a Thief Changing Clothes” – and Our Camera System Barely Exists
Whether it's "natural selection" as Darwin called it, or it's "mutating" as the X-Men called it, living organisms change over time, developing thumbs or more efficient protein spikes, depending on the organism and the demands of its environment. The coronavirus that causes COVID-19, SARS-CoV-2, is not an exception, and now, after the virus has infected millions of people around the globe for more than a year, scientists are beginning to see those changes.
The notorious variants that have popped up include B.1.1.7, sometimes called the UK variant, as well as P.1 and B.1.351, which seem to have emerged in Brazil and South Africa respectively. As vaccinations are picking up pace, officials are warning that now
is not the time to become complacent or relax restrictions because the variants aren't well understood.
Some appear to be more transmissible, and deadlier, while others can evade the immune system's defenses better than earlier versions of the virus, potentially undermining the effectiveness of vaccines to some degree. Genomic surveillance, the process of sequencing the genetic code of the virus widely to observe changes and patterns, is a critical way that scientists can keep track of its evolution and work to understand how the variants might affect humans.
"It's like a thief changing clothes"
It's important to note that viruses mutate all the time. If there were funding and personnel to sequence the genome of every sample of the virus, scientists would see thousands of mutations. Not every variant deserves our attention. The vast majority of mutations are not important at all, but recognizing those that are is a crucial tool in getting and staying ahead of the virus. The work of sequencing, analyzing, observing patterns, and using public health tools as necessary is complicated and confusing to those without years of specialized training.
Jeremy Kamil, associate professor of microbiology and immunology at LSU Health Shreveport, in Louisiana, says that the variants developing are like a thief changing clothes. The thief goes in your house, steals your stuff, then leaves and puts on a different shirt and a wig, in the hopes you won't recognize them. Genomic surveillance catches the "thief" even in those different clothes.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context.
Understanding variants, both the uninteresting ones and the potentially concerning ones, gives public health officials and researchers at different levels a useful set of tools. Locally, knowing which variants are circulating in the community helps leaders know whether mask mandates and similar measures should be implemented or discontinued, or whether businesses and schools can open relatively safely.
There's more to it than observing new variants
Analysis is complex, particularly when it comes to understanding which variants are of concern. "So the question is always if a mutation becomes common, is that a random occurrence?" says Phoebe Lostroh, associate professor of molecular biology at Colorado College. "Or is the variant the result of some kind of selection because the mutation changes some property about the virus that makes it reproduce more quickly than variants of the virus that don't have that mutation? For a virus, [mutations can affect outcomes like] how much it replicates inside a person's body, how much somebody breathes it out, whether the particles that somebody might breathe in get smaller and can lead to greater transmission."
Along with all of those factors, accurate and useful genomic surveillance requires an understanding of where variants are occurring, how they are related, and an examination of why they might be prevalent.
For example, if a potentially worrisome variant appears in a community and begins to spread very quickly, it's not time to raise a public health alarm until several important questions have been answered, such as whether the variant is spreading due to specific events, or if it's happening because the mutation has allowed the virus to infect people more efficiently. Kamil offered a hypothetical scenario to explain: Imagine that a member of a community became infected and the virus mutated. That person went to church and three more people were infected, but one of them went to a karaoke bar and while singing infected 100 other people. Examining the conditions under which the virus has spread is, therefore, an essential part of untangling whether a mutation itself made the virus more transmissible or if an infected person's behaviors contributed to a local outbreak.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context. Genomic sequencing can help with that, but only when it's coordinated. When the same mutation occurs frequently, but is localized to one region, it's a concern, but when the same mutation happens in different places at the same time, it's much more likely that the "virus is learning that's a good mutation," explains Kamil.
The process is called convergent evolution, and it was a fascinating topic long before COVID. Just as your heritage can be traced through DNA, so can that of viruses, and when separate lineages develop similar traits it's almost like scientists can see evolution happening in real time. A mutation to SARS-CoV-2 that happens in more than one place at once is a mutation that makes it easier in some way for the virus to survive and that is when it may become alarming. The widespread, documented variants P.1 and B.1.351 are examples of convergence because they share some of the same virulent mutations despite having developed thousands of miles apart.
However, even variants that are emerging in different places at the same time don't present the kind of threat SARS-CoV-2 did in 2019. "This is nature," says Kamil. "It just means that this virus will not easily be driven to extinction or complete elimination by vaccines." Although a person who has already had COVID-19 can be reinfected with a variant, "it is almost always much milder disease" than the original infection, Kamil adds. Rather than causing full-fledged disease, variants have the potiental to "penetrate herd immunity, spreading relatively quietly among people who have developed natural immunity or been vaccinated, until the virus finds someone who has no immunity yet, and that person would be at risk of hospitalization-grade severe disease or death."
Surveillance and predictions
According to Lostroh, genomic surveillance can help scientists predict what's going to happen. "With the British strain, for instance, that's more transmissible, you can measure how fast it's doubling in the population and you can sort of tell whether we should take more measures against this mutation. Should we shut things down a little longer because that mutation is present in the population? That could be really useful if you did enough sampling in the population that you knew where it was," says Lostroh. If, for example, the more transmissible strain was present in 50 percent of cases, but in another county or state it was barely present, it would allow for rolling lockdowns instead of sweeping measures.
Variants are also extremely important when it comes to the development, manufacture, and distribution of vaccines. "You're also looking at medical countermeasures, such as whether your vaccine is still effective, or if your antiviral needs to be updated," says Lane Warmbrod, a senior analyst and research associate at Johns Hopkins Center for Health Security.
Properly funded and extensive genomic surveillance could eventually help control endemic diseases, too, like the seasonal flu, or other common respiratory infections. Kamil says he envisions a future in which genomic surveillance allows for prediction of sickness just as the weather is predicted today. "It's a 51 for infection today at the San Francisco Airport. There's been detection of some respiratory viruses," he says, offering an example. He says that if you're a vulnerable person, if you're immune-suppressed for some reason, you may want to wear a mask based on the sickness report.
The U.S. has the ability, but lacks standards
The benefits of widespread genomic surveillance are clear, and the United States certainly has the necessary technology, equipment, and personnel to carry it out. But, it's not happening at the speed and extent it needs to for the country to gain the benefits.
"The numbers are improving," said Kamil. "We're probably still at less than half a percent of all the samples that have been taken have been sequenced since the beginning of the pandemic."
Although there's no consensus on how many sequences is ideal for a robust surveillance program, modeling performed by the company Illumina suggests about 5 percent of positive tests should be sequenced. The reasons the U.S. has lagged in implementing a sequencing program are complex and varied, but solvable.
Perhaps the most important element that is currently missing is leadership. In order to conduct an effective genomic surveillance program, there need to be standards. The Johns Hopkins Center for Health Security recently published a paper with recommendations as to what kinds of elements need to be standardized in order to make the best use of sequencing technology and analysis.
"Along with which bioinformatic pipelines you're going to use to do the analyses, which sequencing strategy protocol are you going to use, what's your sampling strategy going to be, how is the data is going to be reported, what data gets reported," says Warmbrod. Currently, there's no guidance from the CDC on any of those things. So, while scientists can collect and report information, they may be collecting and reporting different information that isn't comparable, making it less useful for public health measures and vaccine updates.
Globally, one of the most important tools in making the information from genomic surveillance useful is GISAID, a platform designed for scientists to share -- and, importantly, to be credited for -- their data regarding genetic sequences of influenza. Originally, it was launched as a database of bird flu sequences, but has evolved to become an essential tool used by the WHO to make flu vaccine virus recommendations each year. Scientists who share their credentials have free access to the database, and anyone who uses information from the database must credit the scientist who uploaded that information.
Safety, logistics, and funding matter
Scientists at university labs and other small organizations have been uploading sequences to GISAID almost from the beginning of the pandemic, but their funding is generally limited, and there are no standards regarding information collection or reporting. Private, for-profit labs haven't had motivation to set up sequencing programs, although many of them have the logistical capabilities and funding to do so. Public health departments are understaffed, underfunded, and overwhelmed.
University labs may also be limited by safety concerns. The SARS-CoV-2 virus is dangerous, and there's a question of how samples should be transported to labs for sequencing.
Larger, for-profit organizations often have the tools and distribution capabilities to safely collect and sequence samples, but there hasn't been a profit motive. Genomic sequencing is less expensive now than ever before, but even at $100 per sample, the cost adds up -- not to mention the cost of employing a scientist with the proper credentials to analyze the sequence.
The path forward
The recently passed COVID-19 relief bill does have some funding to address genomic sequencing. Specifically, the American Rescue Plan Act includes $1.75 billion in funding for the Centers for Disease Control and Prevention's Advanced Molecular Detection (AMD) program. In an interview last month, CDC Director Rochelle Walensky said that the additional funding will be "a dial. And we're going to need to dial it up." AMD has already announced a collaboration called the Sequencing for Public Health Emergency Response, Epidemiology, and Surveillance (SPHERES) Initiative that will bring together scientists from public health, academic, clinical, and non-profit laboratories across the country with the goal of accelerating sequencing.
Such a collaboration is a step toward following the recommendations in the paper Warmbrod coauthored. Building capacity now, creating a network of labs, and standardizing procedures will mean improved health in the future. "I want to be optimistic," she says. "The good news is there are a lot of passionate, smart, capable people who are continuing to work with government and work with different stakeholders." She cautions, however, that without a national strategy we won't succeed.
"If we maximize the potential and create that framework now, we can also use it for endemic diseases," she says. "It's a very helpful system for more than COVID if we're smart in how we plan it."
Researchers Are Discovering How to Predict – and Maybe Treat — Pregnancy Complications Early On.
Katie Love wishes there was some way she could have been prepared. But there was no way to know, early in 2020, that her pregnancy would lead to terrifyingly high blood pressure and multiple hospital visits, ending in induced labor and a 56-hour-long, “nightmare” delivery at 37 weeks. Love, a social media strategist in Pittsburgh, had preeclampsia, a poorly understood and potentially deadly pregnancy complication that affects 1 in 25 pregnant women in the United States. But there was no blood test, no easy diagnostic marker to warn Love that this might happen. Even on her first visit to the emergency room, with sky-high blood pressure, doctors could not be certain preeclampsia was the cause.
In fact, the primary but imperfect indicators for preeclampsia — high blood pressure and protein in the urine — haven’t changed in decades. The Preeclampsia Foundation calls a simple, rapid test to predict or diagnose the condition “a key component needed in the fight.”
Another common pregnancy complication is preterm birth, which affects 1 in 10 U.S. pregnancies, but there are few options to predict that might happen, either.
“The best tool that obstetricians have at the moment is still a tape measure and a blood pressure cuff to diagnose whatever’s happening in your pregnancy,” says Fiona Kaper, a vice president at the DNA-sequencing company Illumina in San Diego.
The hunt for such specific biomarkers is now taking off, at Illumina and elsewhere, as scientists probe maternal blood for signs that could herald pregnancy problems. These same molecules offer clues that might lead to more specific treatments. So far, it’s clear that many complications start with the placenta, the temporary organ that transfers nutrients, oxygen and waste between mother and fetus, and that these problems often start well before symptoms arise. Researchers are using the latest stem-cell technology to better understand the causes of complications and test treatments.
Pressing Need
Obstetricians aren’t flying completely blind; medical history can point to high or low risk for pregnancy complications. But ultimately, “everybody who’s pregnant is at risk for preeclampsia,” says Sarosh Rana, chief of maternal-fetal medicine at University of Chicago Medicine and an advisor to the Preeclampsia Foundation. And the symptoms of the condition include problems like headache and swollen feet that overlap with those of pregnancy in general, complicating diagnoses.
The “holy grail" would be early, first-trimester biomarkers. If obstetricians and expecting parents could know, in the first few months of pregnancy, that preeclampsia is a risk, a pregnant woman could monitor her blood pressure at home and take-low dose aspirin that might stave it off.
There are a couple more direct tests physicians can turn to, but these are imperfect. For preterm labor, fetal fibronectin makes up a sort of glue that keeps the amniotic sac, which cushions the unborn baby, attached to the uterus. If it’s not present near a woman’s cervix, that’s a good indicator that she’s not in labor, and can be safely sent home, says Lauren Demosthenes, an obstetrician and senior medical director of the digital health company Babyscripts in Washington, D.C. But if fibronectin appears, it might or might not indicate preterm labor.
“What we want is a test that gives us a positive predictive [signal],” says Demosthenes. “I want to know, if I get it, is it really going to predict preterm birth, or is it just going to make us worry more and order more tests?” In fact, the fetal fibronectin test hasn’t been shown to improve pregnancy outcomes, and Demosthenes says it’s fallen out of favor in many clinics.
Similarly, there’s a blood test, based on the ratio of the amounts of two different proteins, that can rule out preeclampsia but not confirm it’s happening. It’s approved in many countries, though not the U.S.; studies are still ongoing. A positive test, which means “maybe preeclampsia,” still leaves doctors and parents-to-be facing excruciating decisions: If the mother’s life is in danger, delivering the baby can save her, but even a few more days in the uterus can promote the baby’s health. In Ireland, where the test is available, it’s not getting much use, says Patricia Maguire, director of the University College Dublin Institute for Discovery.
Maguire has identified proteins released by platelets that indicate pregnancy — the “most expensive pregnancy test in the world,” she jokes. She is now testing those markers in women with suspected preeclampsia.
The “holy grail,” says Maguire, would be early, first-trimester biomarkers. If obstetricians and expecting parents could know, in the first few months of pregnancy, that preeclampsia is a risk, a pregnant woman could monitor her blood pressure at home and take-low dose aspirin that might stave it off. Similarly, if a quick blood test indicated that preterm labor could happen, doctors could take further steps such as measuring the cervix and prescribing progesterone if it’s on the short side.
Biomarkers in Blood
It was fatherhood that drew Stephen Quake, a biophysicist at Stanford University in California, to the study of pregnancy biomarkers. His wife, pregnant with their first child in 2001, had a test called amniocentesis. That involves extracting a sample from within the uterus, using a 3–8-inch-long needle, for genetic testing. The test can identify genetic differences, such as Down syndrome, but also carries risks including miscarriage or infection. In this case, mom and baby were fine (Quake’s daughter is now a college student), but he found the diagnostic danger unacceptable.
Seeking a less invasive test, Quake in 2008 reported that there’s enough fetal DNA in the maternal bloodstream to diagnose Down syndrome and other genetic conditions. “Use of amniocentesis has plunged,” he says.
Then, recalling that his daughter was born three and a half weeks before her due date — and that Quake’s own mom claims he was a month late, which makes him think the due date must have been off — he started researching markers that could accurately assess a fetus’ age and predict the timing of labor. In this case, Quake was interested in RNA, not DNA, because it’s a signal of which genes the fetus’, placenta’s, and mother’s tissues are using to create proteins. Specifically, these are RNAs that have exited the cells that made them. Tissues can use such free RNAs as messages, wrapping them in membranous envelopes to travel the bloodstream to other body parts. Dying cells also release fragments containing RNAs. “A lot of information is in there,” says Kaper.
In a small study of 31 healthy pregnant women, published in 2018, Quake and collaborators discovered nine RNAs that could predict gestational age, which indicates due date, just as well as ultrasound. With another set of 38 women, including 13 who delivered early, the researchers discovered seven RNAs that predicted preterm labor up to two months in advance.
Quake notes that an RNA-based blood test is cheaper and more portable than ultrasound, so it might be useful in the developing world. A company he cofounded, Mirvie, Inc., is now analyzing RNA’s predictive value further, in thousands of diverse women. CEO and cofounder Maneesh Jain says that since preterm labor is so poorly understood, they’re sequencing RNAs that represent about 20,000 genes — essentially all the genes humans have — to find the very best biomarkers. “We don’t know enough about this field to guess what it might be,” he says. “We feel we’ve got to cast the net wide.”
Quake, and Mirvie, are now working on biomarkers for preeclampsia. In a recent preprint study, not yet reviewed by other experts, Quake’s Stanford team reported 18 RNAs that, measured before 16 weeks, correctly predicted preeclampsia 56–100% of the time.
Other researchers are taking a similar tack. Kaper’s team at Illumina was able to classify preeclampsia from bloodstream RNAs with 85 to 89% accuracy, though they didn’t attempt to predict it. And Louise Laurent, a maternal-fetal medicine specialist and researcher at the University of California, San Diego (UCSD), has defined several pairs of microRNAs — pint-sized RNAs that regulate other ones — in second-trimester blood samples that predict preeclampsia later on.
Placentas in a Dish
The RNAs that show up in these studies often come from genes used by the placenta. But they’re only signals that something’s wrong, not necessarily the root cause. “There still is not much known about what really causes major complications of pregnancy,” says Laurent.
The challenge is that placental problems likely occur early on, as the organ forms in the first trimester. For example, if the placenta did a poor job of building blood vessels through the uterine lining, it might cause preeclampsia later as the growing fetus tries to access more and more blood through insufficient vessels, leading to high blood pressure in the mother. “Everyone has kind of suspected that that is probably what goes wrong,” says Mana Parast, a pathologist and researcher at UCSD.
To see how a placenta first faltered, “you want to go back in time,” says Parast. It’s only recently become possible to do something akin to that: She and Laurent take cells from the umbilical cord (which is a genetic match for the placenta) at the end of pregnancy, and turn them into stem cells, which can become any kind of cell. They then nudge those stem cells to make new placenta cells in lab dishes. But when the researchers start with cells from an umbilical cord after preeclampsia, they find the stem cells struggle to even form proper placenta cells, or they develop abnormally. So yes, something seems to go wrong right at the beginning. Now, the team plans to use these cell cultures to study the microRNAs that indicate preeclampsia risk, and to look for medications that might reverse the problems, Parast says.
Biomarkers could lead to treatments. For example, one of the proteins that commercial preeclampsia diagnostic kits test for is called soluble Flt-1. It’s a sort of anti-growth factor, explains Rana, that can cause problems with blood vessels and thus high blood pressure. Getting rid of the extra Flt-1, then, might alleviate symptoms and keep the mother safe, giving the baby more time to develop. Indeed, a small trial that filtered this protein from the blood did lower blood pressure, allowing participants to keep their babies inside for a couple of weeks longer, researchers reported in 2011.
For pregnant women like Love, even advance warning would have been beneficial. Laurent and others envision a first-trimester blood test that would use different kinds of biomolecules — RNAs, proteins, whatever works best — to indicate whether a pregnancy is at low, medium, or high risk for common complications.
“I prefer to be prepared,” says Love, now the mother of a healthy little girl. “I just wouldn’t have been so thrown off by the whole thing.”
Dec. 17th Event: The Latest on Omicron, Boosters, and Immunity
This virtual event will convene leading scientific and medical experts to discuss the most pressing questions around the new Omicron variant, including what we know so far about its ability to evade COVID-19 vaccines, the role of boosters in eliciting heightened immunity, and the science behind variants and vaccines. A public Q&A will follow the expert discussion.
EVENT INFORMATION:
Date: Friday Dec 17, 2021
2:00pm - 3:30pm EST
Dr. Céline Gounder, MD, ScM, is the CEO/President/Founder of Just Human Productions, a non-profit multimedia organization. She is also the host and producer of American Diagnosis, a podcast on health and social justice, and Epidemic, a podcast about infectious disease epidemics and pandemics. She served on the Biden-Harris Transition COVID-19 Advisory Board.
Dr. Theodora Hatziioannou, Ph.D., is a Research Associate Professor in the Laboratory of Retrovirology at The Rockefeller University. Her research includes identifying plasma samples from recovered COVID-19 patients that contain antibodies capable of neutralizing the SARS-CoV-2 coronavirus.
Dr. Onyema Ogbuagu, MBBCh, is an Associate Professor at Yale School of Medicine and an infectious disease specialist who treats COVID-19 patients and leads Yale’s clinical studies around COVID-19. He ran Yale’s trial of the Pfizer/BioNTech vaccine.
Dr. Eric Topol, M.D., is a cardiologist, scientist, professor of molecular medicine, and the director and founder of Scripps Research Translational Institute. He has led clinical trials in over 40 countries with over 200,000 patients and pioneered the development of many routinely used medications.
This event is the fourth of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.