COVID-19 infections
How One Change to The Coronavirus Spike Influences Infectivity
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Since joining NIH, I’ve held a number of different leadership positions. But there is one position that thankfully has remained constant for me: lab chief. I run my own research laboratory at NIH’s National Institute of Dental and Craniofacial Research (NIDCR).
My lab studies a biochemical process called O-glycosylation. It’s fundamental to life and fascinating to study. Our cells are often adorned with a variety of carbohydrate sugars. O-glycosylation refers to the biochemical process through which these sugar molecules, either found at the cell surface or secreted, get added to proteins. The presence or absence of these sugars on certain proteins plays fundamental roles in normal tissue development and first-line human immunity. It also is associated with various diseases, including cancer.
Our lab recently joined a team of NIH scientists led by my NIDCR colleague Kelly Ten Hagen to demonstrate how O-glycosylation can influence SARS-CoV-2, the coronavirus that causes COVID-19, and its ability to fuse to cells, which is a key step in infecting them. In fact, our data, published in the journal Proceedings of the National Academy of Sciences, indicate that some variants, seem to have mutated to exploit the process to their advantage [1].
The work builds on the virus’s reliance on the spike proteins that crown its outer surface to attach to human cells. Once there, the spike protein must be activated to fuse and launch an infection. That happens when enzymes produced by our own cells make a series of cuts, or cleavages, to the spike protein.
The first cut comes from an enzyme called furin. We and others had earlier evidence that O-glycosylation can affect the way furin makes those cuts. That got us thinking: Could O-glycosylation influence the interaction between furin and the spike protein? The furin cleavage area of the viral spike was indeed adorned with sugars, and their presence or absence might influence spike activation by furin.
We also noticed the Alpha and Delta variants carry a mutation that removes the amino acid proline in a specific spot. That was intriguing because we knew from earlier work that enzymes called GALNTs, which are responsible for adding bulky sugar molecules to proteins, prefer prolines near O-glycosylation sites.
It also suggested that loss of proline in the new variants could mean decreased O-glycosylation, which might then influence the degree of furin cleavage and SARS-CoV-2’s ability to enter cells. I should note that the recent Omicron variant was not examined in the current study.
After detailed studies in fruit fly and mammalian cells, we demonstrated in the original SARS-CoV-2 virus that O-glycosylation of the spike protein decreases furin cleavage. Further experiments then showed that the GALNT1 enzyme adds sugars to the spike protein and this addition limits the ability of furin to make the needed cuts and activate the spike protein.
Importantly, the spike protein change found in the Alpha and Delta variants lowers GALNT1 activity, making it easier for furin to start its activating cuts. It suggests that glycosylation of the viral spike by GALNT1 may limit infection with the original virus, and that the Alpha and Delta variant mutation at least partially overcomes this effect, to potentially make the virus more infectious.
Building on these studies, our teams looked for evidence of GALNT1 in the respiratory tracts of healthy human volunteers. We found that the enzyme is indeed abundantly expressed in those cells. Interestingly, those same cells also express the ACE2 receptor, which SARS-CoV-2 depends on to infect human cells.
It’s also worth noting here that the Omicron variant carries the very same spike mutation that we studied in Alpha and Delta. Omicron also has another nearby change that might further alter O-glycosylation and cleavage of the spike protein by furin. The Ten Hagen lab is looking into these leads to learn how this region in Omicron affects spike glycosylation and, ultimately, the ability of this devastating virus to infect human cells and spread.
Reference:
[1] Furin cleavage of the SARS-CoV-2 spike is modulated by O-glycosylation. Zhang L, Mann M, Syed Z, Reynolds HM, Tian E, Samara NL, Zeldin DC, Tabak LA, Ten Hagen KG. PNAS. 2021 Nov 23;118(47).
Links:
COVID-19 Research (NIH)
Kelly Ten Hagen (National Institute of Dental and Craniofacial Research/NIH)
Lawrence Tabak (NIDCR)
NIH Support: National Institute of Dental and Craniofacial Research
Breakthrough Infections Occur in Those with Lower Antibody Levels, Israeli Study Shows
Posted on by Dr. Francis Collins
To see how COVID-19 vaccines are working in the real world, Israel has provided particularly compelling data. The fact that Israel is relatively small, keeps comprehensive medical records, and has a high vaccination rate with a single vaccine (Pfizer) has contributed to its robust data collection. Now, a new Israeli study offers some insight into those relatively uncommon breakthrough infections. It confirms that breakthrough cases, as might be expected, arise most often in individuals with lower levels of neutralizing antibodies.
The findings reported in The New England Journal of Medicine focused on nearly 1,500 of about 11,500 fully vaccinated health care workers at Sheba Medical Center, Ramat Gan, Israel [1]. All had received two doses of the Pfizer mRNA vaccine. But, from December 19, 2020 to April 28, 2021, they were tested for a breakthrough infection due to a known exposure to someone with COVID-19 or possible symptoms of the disease.
Just 39 confirmed breakthrough cases were found, indicating a breakthrough infection rate of just 0.4 percent. That’s consistent with rates reported in previous studies. Most in the Israeli study who tested positive for COVID-19 had mild or no symptoms and none required hospitalization.
In the new study, researchers led by Gili Regev-Yochay at Sheba Medical Center’s Infection Control and Prevention Unit, characterized as many breakthrough infections as possible among the health care workers. Almost half of the infections involved members of the hospital nursing staff. But breakthrough cases also were found in hospital administration, maintenance workers, doctors, and other health professionals.
The average age of someone with a breakthrough infection was 42, and it’s notable that only one person was known to have a weakened immune system. The most common symptoms were respiratory congestion, muscle aches (myalgia), and loss of smell or taste. Most didn’t develop a fever. At six weeks after diagnosis, 19 percent reported having symptoms of Long COVID syndrome, including prolonged loss of smell, persistent cough, weakness, and fatigue. About a quarter stayed home from work for longer than the required 10 days, and one had yet to return to work at six weeks.
For 22 of the 39 people with a breakthrough infection, the researchers had results of neutralizing antibody tests from the week leading up to their positive COVID-19 test result. To look for patterns in the antibody data, they matched those individuals to 104 uninfected people for whom they also had antibody test results. These data showed that those with a breakthrough infection had consistently lower levels of neutralizing antibodies circulating in their bloodstream to SARS-CoV-2, the coronavirus that causes COVID-19. In general, higher levels of neutralizing antibodies are associated with greater protection and lower infectivity—though other aspects of the immune system (memory B cells and cell-mediated immunity) also contribute.
Importantly, in all cases for which there were relevant data, the source of the breakthrough infection was thought to be an unvaccinated person. In fact, more than half of those who developed a breakthrough infection appeared to have become infected from an unvaccinated member of their own household.
Other cases were suspected to arise from exposure to an unvaccinated coworker or patient. Contact tracing found no evidence that any of the 39 health care workers with a breakthrough infection passed it on to anyone else.
The findings add to evidence that full vaccination and associated immunity offer good protection against SARS-CoV-2 infection and severe illness. Understanding how SARS-CoV-2 immunity changes over time is key for charting the course of this pandemic and making important decisions about COVID-19 vaccine boosters.
Many questions remain. For instance, it’s not clear from the study whether lower neutralizing antibodies in those with breakthrough cases reflect waning immunity or, for reasons we don’t yet understand, those individuals may have had a more limited immune response to the vaccine. Also, this study was conducted before the Delta variant became dominant in Israel (and now in the whole world).
Overall, these findings provide more reassurance that these vaccines are extremely effective. Breakthrough infections, while they can and do occur, are a relatively uncommon event. Here in the U.S., the Centers for Disease Control and Prevention (CDC) has recently estimated that infection is six times less likely for vaccinated than unvaccinated persons [2]. That those with immunity tend to have mild or no symptoms if they do develop a breakthrough case, however, is a reminder that these cases could easily be missed, and they could put vulnerable populations at greater risk. It’s yet another reason for all those who can to get themselves vaccinated as soon as possible or consider a booster shot when they become eligible.
References:
[1] Covid-19 breakthrough infections in vaccinated health care workers. Bergwerk M, Gonen T, Lustig Y, Amit S, Lipsitch M, Cohen C, Mandelboim M, Levin EG, Rubin C, Indenbaum V, Tal I, Zavitan M, Zuckerman N, Bar-Chaim A, Kreiss Y, Regev-Yochay G. N Engl J Med. 2021 Oct 14;385(16):1474-1484.
[2] Rates of COVID-19 cases and deaths by vaccination status, COVID Data Tracker, Centers for Disease and Prevention. Accessed October 25, 2021.
Links:
COVID-19 Research (NIH)
Sheba Medical Center (Ramat Gan, Israel)
COVID-19 Vaccines Protect the Family, Too
Posted on by Dr. Francis Collins
Any of the available COVID-19 vaccines offer remarkable personal protection against the coronavirus SARS-CoV-2. So, it also stands to reason that folks who are vaccinated will reduce the risk of spreading the virus to family members within their households. That protection is particularly important when not all family members can be immunized—as when there are children under age 12 or adults with immunosuppression in the home. But just how much can vaccines help to protect families from COVID-19 when only some, not all, in the household have immunity?
A Swedish study, published recently in the journal JAMA Internal Medicine, offers some of the first hard figures on this topic, and the findings are quite encouraging [1]. The data show that people without any immunity against COVID-19 were at considerably lower risk of infection and hospitalization when other members of their family had immunity, either from a natural infection or vaccination. In fact, the protective effect on family members went up as the number of immune family members increased.
The findings come from a team led by Peter Nordström, Umeå University, Sweden. Like in the United States, vaccinations in Sweden initially were prioritized for high-risk groups and people with certain preexisting conditions. As a result, Swedish families have functioned, often in close contact, as a mix of immune and susceptible individuals over the course of the pandemic.
To explore these family dynamics in greater detail, the researchers relied on nationwide registries to identify all Swedes who had immunity to SARS-COV-2 from either a confirmed infection or vaccination by May 26, 2021. The researchers identified more than 5 million individuals who’d been either diagnosed with COVID-19 or vaccinated and then matched them to a control group without immunity. They also limited the analysis to individuals in families with two to five members of mixed immune status.
This left them with about 1.8 million people from more than 800,000 families. The situation in Sweden is also a little unique from most Western nations. Somewhat controversially, the Swedish government didn’t order a mandatory citizen quarantine to slow the spread of the virus.
The researchers found in the data a rising protective effect for those in the household without immunity as the number of immune family members increased. Families with one immune family member had a 45 to 61 percent lower risk of a COVID-19 infection in the home than those who had none. Those with two immune family members enjoyed more protection, with a 75 to 86 percent reduction in risk of COVID-19. For those with three or four immune family members, the protection went up to more than 90 percent, topping out at 97 percent protection. The results were similar when the researchers limited the analysis to COVID-19 illnesses serious enough to warrant a hospital stay.
The findings confirm that vaccination is incredibly important not only for individual protection, but also for reducing transmission, especially within families and those with whom we’re in close physical contact. It’s also important to note that the findings apply to the original SARS-CoV-2 variant, which was dominant when the study was conducted. But we know that the vaccines offer good protection against Delta and other variants of concern.
These results show quite clearly that vaccines offer protection for individuals who lack immunity, with important implications for finally ending this pandemic. This doesn’t change the fact that all those who can and still need to get fully vaccinated should do so as soon as possible. If you are eligible for a booster shot, that’s something to consider, too. But, if for whatever reason you haven’t gotten vaccinated just yet, perhaps these new findings will encourage you to do it now for the sake of those other people you care about. This is a chance to love your family—and love your neighbor.
Reference:
[1] Association between risk of COVID-19 infection in nonimmune individuals and COVID-19 immunity in their family members. Nordström P, Ballin M, Nordström A. JAMA Intern Med. 2021 Oct 11.
Links:
COVID-19 Research (NIH)
Peter Nordström (Umeå University, Sweden)
COVID-19 Infected Many More Americans in 2020 than Official Tallies Show
Posted on by Dr. Francis Collins
At the end of last year, you may recall hearing news reports that the number of COVID-19 cases in the United States had topped 20 million. While that number came as truly sobering news, it also likely was an underestimate. Many cases went undetected due to limited testing early in the year and a large number of infections that produced mild or no symptoms.
Now, a recent article published in Nature offers a more-comprehensive estimate that puts the true number of infections by the end of 2020 at more than 100 million [1]. That’s equal to just under a third of the U.S. population of 328 million. This revised number shows just how rapidly this novel coronavirus spread through the country last year. It also brings home just how timely the vaccines have been—and continue to be in 2021—to protect our nation’s health in this time of pandemic.
The work comes from NIH grantee Jeffrey Shaman, Sen Pei, and colleagues, Columbia University, New York. As shown above in the map, the researchers estimated the percentage of people who had been infected with SARS-CoV-2, the novel coronavirus that causes COVID-19, in communities across the country through December 2020.
To generate this map, they started with existing national data on the number of coronavirus cases (both detected and undetected) in 3,142 U.S. counties and major metropolitan areas. They then factored in data from the Centers for Disease Control and Prevention (CDC) on the number of people who tested positive for antibodies against SARS-CoV-2. These CDC data are useful for picking up on past infections, including those that went undetected.
From these data, the researchers calculated that only about 11 percent of all COVID-19 cases were confirmed by a positive test result in March 2020. By the end of the year, with testing improvements and heightened public awareness of COVID-19, the ascertainment rate (the number of infections that were known versus unknown) rose to about 25 percent on average. This measure also varied a lot across the country. For instance, the ascertainment rates in Miami and Phoenix were higher than the national average, while rates in New York City, Los Angeles, and Chicago were lower than average.
How many people were potentially walking around with a contagious SARS-CoV-2 infection? The model helps to answer this, too. On December 31, 2020, the researchers estimate that 0.77 percent of the U.S. population had a contagious infection. That’s about 1 in every 130 people on average. In some places, it was much higher. In Los Angeles, for example, nearly 1 in 40 (or 2.42 percent) had a SARS-CoV-2 infection as they rang in the New Year.
Over the course of the year, the fatality rate associated with COVID-19 dropped, at least in part due to earlier diagnosis and advances in treatment. The fatality rate went from 0.77 percent in April to 0.31 percent in December. While this is great news, it still shows that COVID-19 remains much more dangerous than seasonal influenza (which has a fatality rate of 0.08 percent).
Today, the landscape has changed considerably. Vaccines are now widely available, giving many more people immune protection without ever having to get infected. And yet, the rise of the Delta and other variants means that breakthrough infections and reinfections—which the researchers didn’t account for in their model—have become a much bigger concern.
Looking ahead to the end of 2021, Americans must continue to do everything they can to protect their communities from the spread of this terrible virus. That means getting vaccinated if you haven’t already, staying home and getting tested if you’ve got symptoms or know of an exposure, and taking other measures to keep yourself and your loved ones safe and well. These measures we take now will influence the infection rates and susceptibility to SARS-CoV-2 in our communities going forward. That will determine what the map of SARS-CoV-2 infections will look like in 2021 and beyond and, ultimately, how soon we can finally put this pandemic behind us.
Reference:
[1] Burden and characteristics of COVID-19 in the United States during 2020. Pei S, Yamana TK, Kandula S, Galanti M, Shaman J. Nature. 2021 Aug 26.
Links:
COVID-19 Research (NIH)
Sen Pei (Columbia University, New York)
Jeffrey Shaman (Columbia University, New York)
New Metric Identifies Coronavirus Hotspots in Real Time
Posted on by Dr. Francis Collins
During the pandemic, it’s been critical to track in real time where the coronavirus is spreading at home and abroad. But it’s often hard for public health officials to know whether changes in the reported number of COVID-19 cases over time truly reflect the spread of the virus or whether they are confounded by changes in testing levels or lags in the reporting of results.
Now, NIH-funded researchers have discovered a clever workaround to detect more accurately where COVID-19 hotspots are emerging. As published in the journal Science, the new approach focuses on the actual amount of virus present in a positive COVID diagnostic test [1], not just whether the test is positive or negative. What’s even better is these data on a person’s “viral load” are readily available from polymerase chain reaction, or PCR, tests that are the “gold standard” for detecting SARS-CoV-2, the virus responsible for COVID-19. In fact, if you’ve been tested for COVID-19, there’s a good chance you’ve had a PCR-based test.
Here’s how a PCR test for COVID-19 works. After a person provides a nasal swab or saliva sample, any genetic material in the sample is extracted and prepared for the PCR machine. It uses special nucleic acid primers that, if any genetic material from SARS-CoV-2 is present, will make millions more copies of them and result in a positive test result. PCR is an enzymatic reaction that works by running many cycles of heating and cooling; each cycle results in doubling of the genetic material present in the original sample.
But it turns out that PCR can go beyond a simple “yes” or “no” test result. It’s also possible to get some sense of how much coronavirus is present in a positive sample based on the number of cycles required to make enough copies of its genetic material to get the “yes” result. This measure is known as the “cycle threshold,” or Ct, value.
When a sample is run with lots of virus in it, the PCR machine doesn’t need to make so many cycles to reach detectable levels—and the Ct value is considered low. But, when the virus is barely present in a sample, the machine needs to run more cycles before it will reach the threshold for detection. In this case, the Ct value is high. This makes the Ct metric a bit counterintuitive: low Ct means a high level of infection, and high Ct means a low level of infection.
In the new study, researchers in Michael Mina’s lab, Harvard T. H. Chan School of Public Health, Boston, including James Hay and Lee Kennedy-Shaffer, wanted to use Ct values to understand better the overall trajectory of the spread of SARS-CoV-2. Their idea was a little out of the box, since Ct values weren’t being factored into a diagnostic testing process that was set up to give people a yes-or-no answer about COVID-19 status. In fact, Ct values were often discarded.
The team members had a hunch that the amount of virus in patient samples would vary based on whether an outbreak is increasing or declining. Their reasoning was that during an outbreak, when SARS-CoV-2 is spreading rapidly through a community, a larger proportion of infected individuals will have recently contracted the virus than when it is spreading more slowly. The researchers also knew that the virus reaches its peak level in humans soon after infection (generally a couple of days before symptoms begin), and then falls to very low but still detectable levels over the course of weeks or sometimes even months. So, when viral load within samples is highest—and Ct values are lowest—it suggests an outbreak of SARS-CoV-2 is underway. As an outbreak slows and cases fall, viral loads should fall and Ct values rise.
The researchers found that just 30 positive PCR test results on a single day were enough to give an accurate real-time estimate of the growth rate of SARS-CoV-2 infections based on Ct values. With Ct values from multiple time points, it was possible to reconstruct the epidemic curve and estimate the true number of people infected. They found that even Ct values collected from a single location at a single point in time could provide extremely valuable information about the growth or decline of an outbreak.
The findings suggest that these data can now be captured and put to good use as a key metric for decision-making and gauging the success of the pandemic response going forward. It’s also important to note that the value of these data are not unique to COVID-19 and the ongoing pandemic. It appears this can be extremely useful new way to monitor the course of other viral outbreaks, now and in the future, in a way that’s less susceptible to the vagaries of testing. The hope is that this will mean even greater success in capturing viral outbreaks and mobilizing resources in real time to the places where they are most needed.
Reference:
[1] Estimating epidemiologic dynamics from cross-sectional viral load distributions. Hay JA, Kennedy-Shaffer L, Kanjilal S, Lennon NJ, Gabriel SB, Lipsitch M, Mina MJ. Science. 2021 Jun 3.
Links:
COVID-19 Research (NIH)
Michael Mina (Harvard T. H. Chan School of Public Health, Boston)
NIH Support: Common Fund, National Institute of General Medical Sciences; National Cancer Institute
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