mild COVID-19
Human Antibodies Target Many Parts of Coronavirus Spike Protein
Posted on by Dr. Francis Collins
For many people who’ve had COVID-19, the infections were thankfully mild and relatively brief. But these individuals’ immune systems still hold onto enduring clues about how best to neutralize SARS-CoV-2, the coronavirus that causes COVID-19. Discovering these clues could point the way for researchers to design highly targeted treatments that could help to save the lives of folks with more severe infections.
An NIH-funded study, published recently in the journal Science, offers the most-detailed picture yet of the array of antibodies against SARS-CoV-2 found in people who’ve fully recovered from mild cases of COVID-19. This picture suggests that an effective neutralizing immune response targets a wider swath of the virus’ now-infamous spike protein than previously recognized.
To date, most studies of natural antibodies that block SARS-CoV-2 have zeroed in on those that target a specific portion of the spike protein known as the receptor-binding domain (RBD)—and with good reason. The RBD is the portion of the spike that attaches directly to human cells. As a result, antibodies specifically targeting the RBD were an excellent place to begin the search for antibodies capable of fending off SARS-CoV-2.
The new study, led by Gregory Ippolito and Jason Lavinder, The University of Texas at Austin, took a different approach. Rather than narrowing the search, Ippolito, Lavinder, and colleagues analyzed the complete repertoire of antibodies against the spike protein from four people soon after their recoveries from mild COVID-19.
What the researchers found was a bit of a surprise: the vast majority of antibodies—about 84 percent—targeted other portions of the spike protein than the RBD. This suggests a successful immune response doesn’t concentrate on the RBD. It involves production of antibodies capable of covering areas across the entire spike.
The researchers liken the spike protein to an umbrella, with the RBD at the tip of the “canopy.” While some antibodies do bind RBD at the tip, many others apparently target the protein’s canopy, known as the N-terminal domain (NTD).
Further study in cell culture showed that NTD-directed antibodies do indeed neutralize the virus. They also prevented a lethal mouse-adapted version of the coronavirus from infecting mice.
One reason these findings are particularly noteworthy is that the NTD is one part of the viral spike protein that has mutated frequently, especially in several emerging variants of concern, including the B.1.1.7 “U.K. variant” and the B.1.351 “South African variant.” It suggests that one reason these variants are so effective at evading our immune systems to cause breakthrough infections, or re-infections, is that they’ve mutated their way around some of the human antibodies that had been most successful in combating the original coronavirus variant.
Also noteworthy, about 40 percent of the circulating antibodies target yet another portion of the spike called the S2 subunit. This finding is especially encouraging because this portion of SARS-CoV-2 does not seem as mutable as the NTD segment, suggesting that S2-directed antibodies might offer a layer of protection against a wider array of variants. What’s more, the S2 subunit may make an ideal target for a possible pan-coronavirus vaccine since this portion of the spike is widely conserved in SARS-CoV-2 and related coronaviruses.
Taken together, these findings will prove useful for designing COVID-19 vaccine booster shots or future vaccines tailored to combat SARS-COV-2 variants of concern. The findings also drive home the conclusion that the more we learn about SARS-CoV-2 and the immune system’s response to neutralize it, the better position we all will be in to thwart this novel coronavirus and any others that might emerge in the future.
Reference:
[1] Prevalent, protective, and convergent IgG recognition of SARS-CoV-2 non-RBD spike epitopes. Voss WN, Hou YJ, Johnson NV, Delidakis G, Kim JE, Javanmardi K, Horton AP, Bartzoka F, Paresi CJ, Tanno Y, Chou CW, Abbasi SA, Pickens W, George K, Boutz DR, Towers DM, McDaniel JR, Billick D, Goike J, Rowe L, Batra D, Pohl J, Lee J, Gangappa S, Sambhara S, Gadush M, Wang N, Person MD, Iverson BL, Gollihar JD, Dye J, Herbert A, Finkelstein IJ, Baric RS, McLellan JS, Georgiou G, Lavinder JJ, Ippolito GC. Science. 2021 May 4:eabg5268.
Links:
COVID-19 Research (NIH)
Gregory Ippolito (University of Texas at Austin)
NIH Support: National Institute of Allergy and Infectious Diseases; National Cancer Institute; National Institute of General Medical Sciences; National Center for Advancing Translational Sciences
Study Finds 1 in 10 Healthcare Workers with Mild COVID Have Lasting Symptoms
Posted on by Dr. Francis Collins
It’s become increasingly clear that even healthy people with mild cases of COVID-19 can battle a constellation of symptoms that worsen over time—or which sometimes disappear only to come right back. These symptoms are part of what’s called “Long COVID Syndrome.”
Now, a new study of relatively young, healthy adult healthcare workers in Sweden adds needed information on the frequency of this Long COVID Syndrome. Published in the journal JAMA, the study found that just over 1 in 10 healthcare workers who had what at first seemed to be a relatively mild bout of COVID-19 were still coping with at least one moderate to severe symptom eight months later [1]. Those symptoms—most commonly including loss of smell and taste, fatigue, and breathing problems—also negatively affected the work and/or personal lives of these individuals.
These latest findings come from the COVID-19 Biomarker and Immunity (COMMUNITY) study, led by Charlotte Thålin, Danderyd Hospital and Karolinska Institutet, Stockholm. The study, launched a year ago, enlisted 2,149 hospital employees to learn more about immunity to SARS-CoV-2, the coronavirus that causes COVID-19.
After collecting blood samples from participants, the researchers found that about 20 percent already had antibodies to SARS-CoV-2, evidence of a past infection. Thålin and team continued collecting blood samples every four months from all participants, who also completed questionnaires about their wellbeing.
Intrigued by recent reports in the medical literature that many people hospitalized with COVID-19 can have persistent symptoms for months after their release, the researchers decided to take a closer look in their COMMUNITY cohort. They did so last January during their third round of follow up.
This group included 323 mostly female healthcare workers, median age of 43. The researchers compared symptoms in this group following mild COVID-19 to the 1,072 mostly female healthcare workers in the study (median age 47 years) who hadn’t had COVID-19. They wanted to find out if those with mild COVID-19 coped with more and longer-lasting symptoms of feeling unwell than would be expected in an otherwise relatively healthy group of people. These symptoms included familiar things such as fatigue, muscle pain, trouble sleeping, and problems breathing.
Their findings show that 26 percent of those who had mild COVID-19 reported at least one moderate to severe symptom that lasted more than two months. That’s compared to 9 percent of participants without COVID-19. What’s more, 11 percent of the individuals with mild COVID-19 had at least one debilitating symptom that lasted for at least eight months. In the group without COVID-19, any symptoms of feeling unwell resolved relatively quickly.
The most common symptoms in the COVID-19 group were loss of taste or smell, fatigue, and breathing problems. In this group, there was no apparent increase in other symptoms that have been associated with COVID-19, including “brain fog,” problems with memory or attention, heart palpitations, or muscle and joint pain.
The researchers have noted that the Swedish healthcare workers represent a relatively young and healthy group of working individuals. Yet, many of them continued to suffer from lasting symptoms related to mild COVID-19. It’s a reminder that COVID-19 can and, in fact, is having a devastating impact on the lives and livelihoods of adults who are at low risk for developing severe and life-threatening COVID-19. If we needed one more argument for getting young people vaccinated, this is it.
At NIH, efforts have been underway for some time to identify the causes of Long COVID. In fact, a virtual workshop was held last winter with more than 1,200 participants to discuss what’s known and to fill in key gaps in our knowledge of Long COVID syndrome, which is clinically known as post-acute sequelae of COVID-19 (PASC). Recently, a workshop summary was published [2]. As workshops and studies like this one from Sweden help to define the problem, the hope is to learn one day how to treat or prevent this terrible condition. The NIH is now investing more than $1 billion in seeking those answers.
References:
[1] Symptoms and functional impairment assessed 8 Months after mild COVID-19 among health care workers. Havervall S, Rosell A, Phillipson M, Mangsbo SM, Nilsson P, Hober S, Thålin C. JAMA. 2021 Apr 7.
[2] Toward understanding COVID-19 recovery: National Institutes of Health workshop on postacute COVID-19. Lerner A, et al. Ann Intern Med, 2021 March 30.
Links:
COVID-19 Research (NIH)
Charlotte Thålin (Karolinska Institutet, Stockholm, Sweden)
First Molecular Profiles of Severe COVID-19 Infections
Posted on by Dr. Francis Collins
To ensure that people with coronavirus disease 2019 (COVID-19) get the care they need, it would help if a simple blood test could predict early on which patients are most likely to progress to severe and life-threatening illness—and which are more likely to recover without much need for medical intervention. Now, researchers have provided some of the first evidence that such a test might be possible.
This tantalizing possibility comes from a study reported recently in the journal Cell. In this study, researchers took blood samples from people with mild to severe COVID-19 and analyzed them for nearly 2,000 proteins and metabolites [1]. Their detailed analyses turned up hundreds of molecular changes in blood that differentiated milder COVID-19 symptoms from more severe illness. What’s more, they found that they could train a computer to use the most informative of the proteins and predict the disease severity with a high degree of accuracy.
The findings come from the lab of Tiannan Guo, Westlake University, Zhejiang Province, China. His team recognized that, while we’ve learned a lot about the clinical symptoms of COVID-19 and the spread of the illness around the world, much less is known about the condition’s underlying molecular features. It also remains mysterious what distinguishes the 80 percent of symptomatic infected people who recover with little to no need for medical care from the other 20 percent, who suffer from much more serious illness, including respiratory distress requiring oxygen or even more significant medical interventions.
In search of clues, Guo and colleagues analyzed hundreds of molecular changes in blood samples collected from 53 healthy people and 46 people with COVID-19, including 21 with severe disease involving respiratory distress and decreased blood-oxygen levels. Their studies turned up more than 470 proteins and metabolites that differed in people with COVID-19 compared to healthy people. Of those, levels of about 300 were associated with disease severity.
Further analysis revealed that the majority of proteins and metabolites on the list are associated with the suppression or dysregulation of one of three biological processes. Two processes are related to the immune system, including early immune responses and the function of particular scavenging immune cells called macrophages. The third relates to the function of platelets, which are sticky, disc-shaped cell fragments that play an essential role in blood clotting. Such biological insights might help pave the way for potentially effective new ways to treat COVID-19 down the road.
Next, the researchers turned to “machine learning” to explore the possibility that such molecular changes also might be used to predict mild versus severe COVID-19. Machine learning involves the use of computers to discern patterns, or molecular signatures, in large data sets that a human being couldn’t readily pick out. In this case, the question was whether the computer could “learn” to tell the difference between mild and severe COVID-19 based on molecular data alone.
Their analyses showed that a computer, once trained, could differentiate mild and severe COVID-19 based on just 22 proteins and 7 metabolites. Their model correctly classified all but one person in the original training set, for an accuracy of about 94 percent. And importantly, in further prospective validation tests, they confirmed that this model accurately identified mild versus severe COVID-19 in most cases.
While these findings are certainly encouraging, there’s much more work to do. It will be important to explore these molecular signatures in many more people. It also will be critical to find out how early in the course of the disease such telltale signatures arise. While we await those answers, I find encouragement in all that we’re learning—and will continue to learn—about COVID-19 each day.
Reference:
[1] Proteomic and metabolomic characterization of COVID-19 patient sera. Shen B et al. Cell. 28 May 2020. [Epub ahead of publication]
Links:
Coronavirus (COVID-19) (NIH)
Blood Tests (National Heart, Lung, and Blood Institute/NIH)
Tiannan Guo Lab (Westlake University, Zhejiang Province, China)
