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Finding Antibodies that Neutralize SARS-CoV-2

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Neutralizing Antibodies
Caption: Model of three neutralizing antibodies (blue, purple and orange) bound to the spike protein, which allows SARS-CoV-2 attach to our cells. Credit: Christopher Barnes and Pamela Bjorkman, California Institute of Technology, Pasadena.

It’s now clear that nearly everyone who recovers from coronavirus disease 2019 (COVID-19) produces antibodies that specifically target SARS-CoV-2, the novel coronavirus that causes the infection. Yet many critical questions remain. A major one is: just how well do those particular antibodies neutralize the virus to fight off the infection and help someone recover from COVID-19? Fortunately, most people get better—but should the typical antibody response take the credit?

A new NIH-funded study of nearly 150 people who recovered from COVID-19 offers some essential insight. The study, published in the journal Nature, shows that most people, in fact, do produce antibodies that can effectively neutralize SARS-CoV-2. But there is a catch: 99 percent of the study’s participants didn’t make enough neutralizing antibodies to mount an ideal immune response.

The good news is that when researchers looked at individuals who mounted a strong immune response, they were able to identify three antibodies (depicted above) that were extremely effective at neutralizing SARS-CoV-2. By mass-producing copies of these antibodies as so-called monoclonal antibodies, the researchers can now better evaluate their potential as treatments to help people who don’t make strongly neutralizing antibodies, or not enough of them.

These findings come from a team led by Michel Nussenzweig, Paul Bieniasz, and Charles Rice at The Rockefeller University, New York, and Pamela Bjorkman at the California Institute of Technology, Pasadena. In the Nussenzweig lab, the team has spent years searching for broadly neutralizing antibodies against the human immunodeficiency virus (HIV). In response to the COVID-19 pandemic and its great urgency, Nussenzweig and team shifted their focus recently to look for promising antibodies against SARS-CoV-2.

Antibodies are blood proteins that the immune system makes to neutralize viruses or other foreign invaders. The immune system doesn’t make just one antibody to thwart an invader; it makes a whole family of antibodies. But not all antibodies in that family are created equal. They can vary widely in where they latch onto a virus like SARS-CoV-2, and that determines how effective each will be at blocking it from infecting human cells. That’s one reason why people respond differently to infections such as COVID-19.

In early April, Nussenzweig’s team began analyzing samples from volunteer survivors who visited The Rockefeller Hospital to donate plasma, which contains the antibodies. The volunteers had all recovered from mild-to-severe cases of COVID-19, showing their first signs of illness about 40 days prior to their first plasma collection.

Not surprisingly, all volunteers had produced antibodies in response to the virus. To test the strength of the antibodies, the researchers used a special assay that shows how effective each one is at blocking the virus from infecting human cells in lab dishes.

Overall, most of the plasma samples—118 of 149—showed at best poor to modest neutralizing activity. In about one-third of individuals, their plasma samples had below detectable levels of neutralizing activity. It’s possible those individuals just resolved the infection quickly, before more potent antibodies were produced.

More intriguing to the researchers were the results from two individuals that showed an unusually strong ability to neutralize SARS-CoV-2. Among these two “elite responders” and four other individuals, the researchers identified 40 different antibodies that could neutralize SARS-CoV-2. But again, not all antibodies are created equal. Three neutralized the virus even when present at extremely low levels, and they now will be studied further as possible monoclonal antibodies.

The team determined that those strongly neutralizing antibodies bind three distinct sites on the receptor-binding domain (RBD) of the coronavirus spike protein. This portion of the virus is important because it allows SARS-CoV-2 to bind and infect human cells. Importantly, when the researchers looked more closely at plasma samples with poor neutralizing ability, they found that they also contained those RBD-binding antibodies, just not in very large numbers.

These findings help not only to understand the immune response to COVID-19, they are also critical for vaccine design, revealing what a strong neutralizing antibody for SARS-CoV-2 should look like to help the immune system win. If a candidate vaccine can generate such strongly neutralizing antibodies, researchers will know that they are on the right track.

While this research showed that there’s a lot of variability in immune responses to SARS-CoV-2, it appears that most of us are inherently capable of producing antibodies to neutralize this devastating virus. That brings more reason for hope that the many vaccines now under study to elicit such neutralizing antibodies in sufficient numbers may afford us with much-needed immune protection.


[1] Convergent antibody responses to SARS-CoV-2 in convalescent individuals. Robbiani DF, Gaebler C, Muecksch F, et al. Nature. 2020 Jun 18. [Published online ahead of print].


Coronavirus (COVID-19) (NIH)

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV)

Nussenzweig Lab (The Rockefeller University, New York)

Bjorkman Lab (California Institute of Technology, Pasadena)

NIH Support: National Institute of Allergy and Infectious Diseases

Public Health Policies Have Prevented Hundreds of Millions of Coronavirus Infections

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Touchless carryout
Credit: Stock photo/Juanmonino

The alarming spread of coronavirus disease 2019 (COVID-19) last winter presented a profound threat to nations around the world. Many government leaders responded by shutting down all non-essential activities, implementing policies that public health officials were hopeful could slow the highly infectious SARS-CoV-2, the novel coronavirus that causes COVID-19.

But the shutdown has come at a heavy cost for the U.S. and global economies. It’s also taken a heavy personal toll on many of us, disrupting our daily routines—getting children off to school, commuting to the office or lab, getting together with friends and family, meeting face to face to plan projects, eating out, going to the gym—and causing lots of uncertainty and frustration.

As difficult as the shutdowns have been, new research shows that without these public health measures, things would have been much, much worse. According to a study published recently in Nature [1], the implementation of containment and mitigation strategies across the globe prevented or delayed about 530 million coronavirus infections across six countries—China, South Korea, Iran, Italy, France, and the United States. Take a moment to absorb that number—530 million. Right now, there are 8.8 million cases documented across the globe.

Estimates of the benefits of anti-contagion policies have drawn from epidemiological models that simulate the spread of COVID-19 in various ways, depending on assumptions built into each model. But models are sophisticated ways of guessing. Back when decisions about staying at home had to be made, no one knew for sure if, or how well, such approaches to limit physical contact would work. What’s more, the only real historical precedent was the 1918 Spanish flu pandemic in a very different, much-less interconnected world.

That made it essential to evaluate the pros and cons of these public health strategies within a society. As many people have rightfully asked: are the health benefits really worth the pain?

Recognizing a pressing need to answer this question, an international team of scientists dropped everything that they were doing to find out. Led by Solomon Hsiang, director of the University of California, Berkeley’s Global Policy Laboratory and Chancellor’s Professor at the Goldman School of Public Policy, a research group of 15 researchers from China, France, South Korea, New Zealand, Singapore, and the United States evaluated 1,717 policies implemented in all six countries between January 2020, when the virus began its global rise, and April 6, 2020.

The team relied on econometric methods that use statistics and math to uncover meaningful patterns hiding in mountains of data. As the name implies, these techniques are used routinely by economists to understand, in a before-and-after way, how certain events affect economic growth.

In this look-back study, scientists compare observations before and after an event they couldn’t control, such as a natural disaster or disease outbreak. In the case of COVID-19, these researchers compared public health datasets in multiple localities (e.g., states or cities) within each of the six countries before and several weeks after lockdowns. For each data sample from a given locality, the time period right before a policy deployment was the experimental “control” for the same locality several weeks after it received one or more shutdown policy “treatments.”

Hsiang and his colleagues measured the effects of all the different policies put into place at local, regional, and national levels. These included travel restrictions, business and school closures, shelter-in-place orders, and other actions that didn’t involve any type of medical treatment for COVID-19.

Because SARS-CoV-2 is a new virus, the researchers knew that early in the pandemic, everyone was susceptible, and the outbreak would grow exponentially. The scientists could then use a statistical method designed to estimate how the daily growth rate of infections changed over time within a location after different combinations of large-scale policies were put into place.

The result? Early in the pandemic, coronavirus infection rates grew 38 percent each day, on average, across the six countries: translating to a two-day doubling time. Applying all policies at once slowed the daily COVID-19 infection rate by 31 percentage points! Policies having the clearest benefit were business closures and lockdowns, whereas travel restrictions and bans on social gatherings had mixed results. Without more data, the analysis can’t specify why, but the way different countries enacted those policies might be one reason.

As we continue to try to understand and thwart this new virus and its damage to so many aspects of our personal and professional lives, these new findings add context, comfort, and guidance about the present circumstances. They tell us that individual sacrifices from staying home and canceled events contributed collectively to a huge, positive impact on the world.

Now, as various communities start cautiously to open up, we should continue to practice social distancing, mask wearing, and handwashing. This is not the time to say that the risk has passed. We are all tired of the virus and its consequences for our personal lives, but the virus doesn’t care. It’s still out there. Stay safe, everyone!


[1] The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Hsiang S, Allen D, Annan-Phan S, et al. Nature. 2020 June 8 [published online ahead of print].


Coronavirus (NIH)

Global Policy Lab: Effect of Anti-Contagion Policies (University of California, Berkeley)

Video: How much have policies to slow COVID-19 worked? (UC Berkeley)

Hsiang Lab (UC Berkeley)

Global Policy Lab Rallies for COVID-19 Research,” COVID-19 News, Goldman School of Public Policy, June 5, 2020.

Genes, Blood Type Tied to Risk of Severe COVID-19

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SARS-CoV-2 virus particles
Caption: Micrograph of SARS-CoV-2 virus particles isolated from a patient.
Credit: National Institute of Allergy and Infectious Diseases, NIH

Many people who contract COVID-19 have only a mild illness, or sometimes no symptoms at all. But others develop respiratory failure that requires oxygen support or even a ventilator to help them recover [1]. It’s clear that this happens more often in men than in women, as well as in people who are older or who have chronic health conditions. But why does respiratory failure also sometimes occur in people who are young and seemingly healthy?

A new study suggests that part of the answer to this question may be found in the genes that each one of us carries [2]. While more research is needed to pinpoint the precise underlying genes and mechanisms responsible, a recent genome-wide association (GWAS) study, just published in the New England Journal of Medicine, finds that gene variants in two regions of the human genome are associated with severe COVID-19 and correspondingly carry a greater risk of COVID-19-related death.

The two stretches of DNA implicated as harboring risks for severe COVID-19 are known to carry some intriguing genes, including one that determines blood type and others that play various roles in the immune system. In fact, the findings suggest that people with blood type A face a 50 percent greater risk of needing oxygen support or a ventilator should they become infected with the novel coronavirus. In contrast, people with blood type O appear to have about a 50 percent reduced risk of severe COVID-19.

These new findings—the first to identify statistically significant susceptibility genes for the severity of COVID-19—come from a large research effort led by Andre Franke, a scientist at Christian-Albrecht-University, Kiel, Germany, along with Tom Karlsen, Oslo University Hospital Rikshospitalet, Norway. Their study included 1,980 people undergoing treatment for severe COVID-19 and respiratory failure at seven medical centers in Italy and Spain.

In search of gene variants that might play a role in the severe illness, the team analyzed patient genome data for more than 8.5 million so-called single-nucleotide polymorphisms, or SNPs. The vast majority of these single “letter” nucleotide substitutions found all across the genome are of no health significance, but they can help to pinpoint the locations of gene variants that turn up more often in association with particular traits or conditions—in this case, COVID-19-related respiratory failure. To find them, the researchers compared SNPs in people with severe COVID-19 to those in more than 1,200 healthy blood donors from the same population groups.

The analysis identified two places that turned up significantly more often in the individuals with severe COVID-19 than in the healthy folks. One of them is found on chromosome 3 and covers a cluster of six genes with potentially relevant functions. For instance, this portion of the genome encodes a transporter protein known to interact with angiotensin converting enzyme 2 (ACE2), the surface receptor that allows the novel coronavirus that causes COVID-19, SARS-CoV-2, to bind to and infect human cells. It also encodes a collection of chemokine receptors, which play a role in the immune response in the airways of our lungs.

The other association signal popped up on chromosome 9, right over the area of the genome that determines blood type. Whether you are classified as an A, B, AB, or O blood type, depends on how your genes instruct your blood cells to produce (or not produce) a certain set of proteins. The researchers did find evidence suggesting a relationship between blood type and COVID-19 risk. They noted that this area also includes a genetic variant associated with increased levels of interleukin-6, which plays a role in inflammation and may have implications for COVID-19 as well.

These findings, completed in two months under very difficult clinical conditions, clearly warrant further study to understand the implications more fully. Indeed, Franke, Karlsen, and many of their colleagues are part of the COVID-19 Host Genetics Initiative, an ongoing international collaborative effort to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. Some NIH research groups are taking part in the initiative, and they recently launched a study to look for informative gene variants in 5,000 COVID-19 patients in the United States and Canada.

The hope is that these and other findings yet to come will point the way to a more thorough understanding of the biology of COVID-19. They also suggest that a genetic test and a person’s blood type might provide useful tools for identifying those who may be at greater risk of serious illness.


[1] Characteristics of and important lessons from the Coronavirus Disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. Wu Z, McGoogan JM, et. al. 2020 Feb 24. [published online ahead of print]

[2] Genomewide association study of severe Covid-19 with respiratory failure. Ellinghaus D, Degenhardt F, et. a. NEJM. June 17, 2020.


The COVID-19 Host Genetics Initiative

Andre Franke (Christian-Albrechts-University of Kiel, Germany)

Tom Karlsen (Oslo University Hospital Rikshospitalet, Norway)

NIH’s All of Us Program Joins Fight Against COVID-19

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We’ve learned so much about coronavirus disease 2019 (COVID-19), but there’s still much more that we need to learn in order to defeat this devastating pandemic. Among the critical questions: why do some young people who appear healthy and have no history of chronic disease get very sick from the virus? And why do some people in their 80s or 90s seemingly just shrug off the infection? There’s something going on biologically, but we don’t yet have the answers.

We do, however, have some resources that will enable us to examine lots of data in search of biological clues. One of them is NIH’s All of Us Research Program, which is seeking the help of 1 million people to build one of the most diverse health databases in our nation’s history. Two years after its national launch, the program already has enrolled nearly 350,000 diverse participants from across the United States.

As its name suggests, All of Us is open to all people over age 18 in communities all around the country. An important strength of the effort has been welcoming participants from all backgrounds. Indeed, about 75 percent of people who have volunteered for the program come from groups that have traditionally been underrepresented in medical research. That includes people from many racial and ethnic minority groups, as well as those of many different ages, socioeconomic backgrounds, and geographic locations, including remote and rural areas.

Because of COVID-19 and the need for physical distancing to curb the spread of the potentially deadly virus, All of Us has been forced to halt temporarily all in-person appointments. But program leaders, including Josh Denny, chief executive officer of All of Us, and Kelly Gebo, the program’s chief medical and scientific officer, saw an opportunity to roll up their sleeves and help during this unprecedented public health challenge. In fact, Gebo reports that they’d already been hearing from many of their participant partners that they wanted to be a part of the solution to the COVID-19 pandemic.

To rise to this challenge, the All of Us Research Program has just announced three initiatives to assist the scientific community in seeking new insights into COVID-19. The program will:

• Test blood samples from 10,000 or more participants for the presence of SARS-CoV-2 antibodies, indicating prior infection. The testing will start on samples collected in March 2020 and work backward until positive tests are no longer found. This will show the prevalence of novel coronavirus exposure among All of Us participants from across the country, allowing researchers to sift through the data and assess the varying rates and timing of infections across regions and communities.

• Rapidly collect relevant information from more than 200,000 participants who have shared their electronic health records. A number of those participants have already either been diagnosed with COVID-19 or sought health care for related symptoms. The program is working to standardize this information. It will help researchers look for patterns and learn more about COVID-19 symptoms and associated health problems, as well as the effects of different medicines and treatments.

• Deploy a new online survey to understand better the effects of the COVID-19 pandemic on participants’ physical and mental health. This 20- to 30-minute survey is designed both for participants who have been ill with COVID-19 and those who have not knowingly been infected. Questions will be included on COVID-19 symptoms, stress, social distancing and the economic impacts of the pandemic. Participants are invited to take the survey each month until the pandemic ends, so researchers can study the effects of COVID-19 over time and begin to better understand how and why COVID-19 affects people differently.

As this data becomes available, researchers will look for new leads to inform our efforts to bring greater precision to the diagnosis, treatment, and prevention of COVID-19, including for those communities that have been hit the hardest. Another hope is that what is learned about COVID-19 through All of Us and other NIH-supported research will provide us with the knowledge and tools we need to avert future pandemics,

In case you’re wondering, I happen to be among the thousands of people who’ve already volunteered to take part in All of Us. If you’d like to get involved too, new participants are always welcome to join.


Coronavirus (COVID-19) (NIH)

All of Us Research Program (NIH)

Join All of Us (NIH)

First Molecular Profiles of Severe COVID-19 Infections

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COVID-19 Severity Test
Credit: NIH

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.


[1] Proteomic and metabolomic characterization of COVID-19 patient sera. Shen B et al. Cell. 28 May 2020. [Epub ahead of publication]


Coronavirus (COVID-19) (NIH)

Blood Tests (National Heart, Lung, and Blood Institute/NIH)

Tiannan Guo Lab (Westlake University, Zhejiang Province, China)

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