Antibody Testing Alone is Not the Key to Re-Opening Society
[Editor's Note: We asked experts from different specialties to weigh in on a timely Big Question: "How should immunity testing play a role in re-opening society?" Below, a virologist offers her perspective.]
With the advent of serology testing and increased emphasis on "re-opening" America, public health officials have begun considering whether or not people who have recovered from COVID-19 can safely re-enter the workplace.
"Immunity certificates cannot certify what is not known."
Conventional wisdom holds that people who have developed antibodies in response to infection with SARS-CoV-2, the coronavirus that causes COVID-19, are likely to be immune to reinfection.
For most acute viral infections, this is generally true. However, SARS-CoV-2 is a new pathogen, and there are currently many unanswered questions about immunity. Can recovered patients be reinfected or transmit the virus? Does symptom severity determine how protective responses will be after recovery? How long will protection last? Understanding these basic features is essential to phased re-opening of the government and economy for people who have recovered from COVID-19.
One mechanism that has been considered is issuing "immunity certificates" to individuals with antibodies against SARS-CoV-2. These certificates would verify that individuals have already recovered from COVID-19, and thus have antibodies in their blood that will protect them against reinfection, enabling them to safely return to work and participate in society. Although this sounds reasonable in theory, there are many practical reasons why this is not a wise policy decision to ease off restrictive stay-home orders and distancing practices.
Too Many Scientific Unknowns
Serology tests measure antibodies in the serum—the liquid component of blood, which is where the antibodies are located. In this case, serology tests measure antibodies that specifically bind to SARS-CoV-2 virus particles. Usually when a person is infected with a virus, they develop antibodies that can "recognize" that virus, so the presence of SARS-CoV-2 antibodies indicates that a person has been previously exposed to the virus. Broad serology testing is critical to knowing how many people have been infected with SARS-CoV-2, since testing capacity for the virus itself has been so low.
Tests for the virus measure amounts of SARS-CoV-2 RNA—the virus's genetic material—directly, and thus will not detect the virus once a person has recovered. Thus, the majority of people who were not severely ill and did not require hospitalization, or did not have direct contact with a confirmed case, will not test positive for the virus weeks after they have recovered and can only determine if they had COVID-19 by testing for antibodies.
In most cases, for most pathogens, antibodies are also neutralizing, meaning they bind to the virus and render it incapable of infecting cells, and this protects against future infections. Immunity certificates are based on the assumption that people with antibodies specific for SARS-CoV-2 will be protected against reinfection. The problem is that we've only known that SARS-CoV-2 existed for a little over four months. Although studies so far indicate that most (but not all) patients with confirmed COVID-19 cases develop antibodies, we don't know the extent to which antibodies are protective against reinfection, or how long that protection will last. Immunity certificates cannot certify what is not known.
The limited data so far is encouraging with regard to protective immunity. Most of the patient sera tested for antibodies show reasonable titers of IgG, the type of antibodies most likely to be neutralizing. Furthermore, studies have shown that these IgG antibodies are capable of neutralizing surrogate viruses as well as infectious SARS-CoV-2 in laboratory tests. In addition, rhesus monkeys that were experimentally infected with SARS-CoV-2 and allowed to recover were protected from reinfection after a subsequent experimental challenge. These data tentatively suggest that most people are likely to develop neutralizing IgG, and protective immunity, after being infected by SARS-CoV-2.
However, not all COVID-19 patients do produce high levels of antibodies specific for SARS-CoV-2. A small number of patients in one study had no detectable neutralizing IgG. There have also been reports of patients in South Korea testing PCR positive after a prior negative test, indicating reinfection or reactivation. These cases may be explained by the sensitivity of the PCR test, and no data have been produced to indicate that these cases are genuine reinfection or recurrence of viral infection.
Complicating matters further, not all serology tests measure antibody titers. Some rapid serology tests are designed to be binary—the test can either detect antibodies or not, but does not give information about the amount of antibodies circulating. Based on our current knowledge, we cannot be certain that merely having any level of detectable antibodies alone guarantees protection from reinfection, or from a subclinical reinfection that might not cause a second case of COVID-19, but could still result in transmission to others. These unknowns remain problematic even with tests that accurately detect the presence of antibodies—which is not a given today, as many of the newly available tests are reportedly unreliable.
A Logistical and Ethical Quagmire
While most people are eager to cast off the isolation of physical distancing and resume their normal lives, mere desire to return to normality is not an indicator of whether those antibodies actually work, and no certificate can confer immune protection. Furthermore, immunity certificates could lead to some complicated logistical and ethical issues. If antibodies do not guarantee protective immunity, certifying that they do could give antibody-positive people a false sense of security, causing them to relax infection control practices such as distancing and hand hygiene.
"We should not, however, place our faith in assumptions and make return to normality contingent on an arbitrary and uninformative piece of paper."
Certificates could be forged, putting susceptible people at higher exposure risk. It's not clear who would issue them, what they would entitle the bearer to do or not do, or how certification would be verified or enforced. There are many ways in which such certificates could be used as a pretext to discriminate against people based on health status, in addition to disability, race, and socioeconomic status. Tracking people based on immune status raises further concerns about privacy and civil rights.
Rather than issuing documents confirming immune status, we should instead "re-open" society cautiously, with widespread virus and serology testing to accurately identify and isolate infected cases rapidly, with immediate contact tracing to safely quarantine and monitor those at exposure risk. Broad serosurveillance must be coupled with functional assays for neutralization activity to begin assessing how protective antibodies might actually be against SARS-CoV-2 infection. To understand how long immunity lasts, we should study antibodies, as well as the functional capabilities of other components of the larger immune system, such as T cells, in recovered COVID-19 patients over time.
We should not, however, place our faith in assumptions and make return to normality contingent on an arbitrary and uninformative piece of paper. Re-opening society, the government, and the economy depends not only on accurately determining how many people have antibodies to SARS-CoV-2, but on a deeper understanding of how those antibodies work to provide protection.
Small changes in how a person talks could reveal Alzheimer’s earlier
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”
Gene therapy helps restore teen’s vision for first time
Story by Freethink
For the first time, a topical gene therapy — designed to heal the wounds of people with “butterfly skin disease” — has been used to restore a person’s vision, suggesting a new way to treat genetic disorders of the eye.
The challenge: Up to 125,000 people worldwide are living with dystrophic epidermolysis bullosa (DEB), an incurable genetic disorder that prevents the body from making collagen 7, a protein that helps strengthen the skin and other connective tissues.Without collagen 7, the skin is incredibly fragile — the slightest friction can lead to the formation of blisters and scarring, most often in the hands and feet, but in severe cases, also the eyes, mouth, and throat.
This has earned DEB the nickname of “butterfly skin disease,” as people with it are said to have skin as delicate as a butterfly’s wings.
The gene therapy: In May 2023, the FDA approved Vyjuvek, the first gene therapy to treat DEB.
Vyjuvek uses an inactivated herpes simplex virus to deliver working copies of the gene for collagen 7 to the body’s cells. In small trials, 65 percent of DEB-caused wounds sprinkled with it healed completely, compared to just 26 percent of wounds treated with a placebo.
“It was like looking through thick fog.” -- Antonio Vento Carvajal.
The patient: Antonio Vento Carvajal, a 14 year old living in Florida, was one of the trial participants to benefit from Vyjuvek, which was developed by Pittsburgh-based pharmaceutical company Krystal Biotech.
While the topical gene therapy could help his skin, though, it couldn’t do anything to address the severe vision loss Antonio experienced due to his DEB. He’d undergone multiple surgeries to have scar tissue removed from his eyes, but due to his condition, the blisters keep coming back.
“It was like looking through thick fog,” said Antonio, noting how his impaired vision made it hard for him to play his favorite video games. “I had to stand up from my chair, walk over, and get closer to the screen to be able to see.”
The idea: Encouraged by how Antonio’s skin wounds were responding to the gene therapy, Alfonso Sabater, his doctor at the Bascom Palmer Eye Institute, reached out to Krystal Biotech to see if they thought an alternative formula could potentially help treat his patient’s eyes.
The company was eager to help, according to Sabater, and after about two years of safety and efficacy testing, he had permission, under the FDA’s compassionate use protocol, to treat Antonio’s eyes with a version of the topical gene therapy delivered as eye drops.
The results: In August 2022, Sabater once again removed scar tissue from Antonio’s right eye, but this time, he followed up the surgery by immediately applying eye drops containing the gene therapy.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy. Don’t be afraid.” -- Yunielkys “Yuni” Carvajal.
The vision in Antonio’s eye steadily improved. By about eight months after the treatment, it was just slightly below average (20/25) and stayed that way. In March 2023, Sabater performed the same procedure on his young patient’s other eye, and the vision in it has also steadily improved.
“I’ve seen the transformation in Antonio’s life,” said Sabater. “He’s always been a happy kid. Now he’s very happy. He can function pretty much normally. He can read, he can study, he can play video games.”
Looking ahead: The topical gene therapy isn’t a permanent fix — it doesn’t alter Antonio’s own genes, so he has to have the eye drops reapplied every month. Still, that’s far less invasive than having to undergo repeated surgeries.
Sabater is now working with Krystal Biotech to launch trials of the eye drops in other patients, and not just those with DEB. By changing the gene delivered by the therapy, he believes it could be used to treat other eye disorders that are far more common — Fuchs’ dystrophy, for example, affects the vision of an estimated 300 million people over the age of 30.
Antonio’s mother, Yunielkys “Yuni” Carvajal, meanwhile, has said that having her son be the first to receive the eye drops was “very scary,” but she’s hopeful others will take a chance on new gene therapies if given the opportunity.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy,” she said. “Don’t be afraid.”