RECOVER Initiative
Research!America’s National Health Research Forum
Posted on by Lawrence Tabak, D.D.S., Ph.D.
RECOVER: What Clinical Research Comes Next for Helping People with Long COVID
“I connected with RECOVER to be a part of the answers that I was looking for when I was at my worst.” Long COVID patient and RECOVER representative, Nitza Rochez (Bronx, NY)
People, like Nitza Rochez, who are living with Long COVID—the wide-ranging health issues that can follow an infection with SARS-CoV-2, the coronavirus that causes COVID-19—experience disabling symptoms with significant physical, emotional and financial consequences.
The NIH has been engaging and listening to Nitza and others living with Long COVID even before the start of its Researching COVID to Enhance Recovery (RECOVER) Initiative. But now, with the launch of RECOVER, patients and those with affected family or community members have joined researchers, clinicians, and experts in their efforts to unlock the mysteries of Long COVID. All have come together to understand what causes the condition, identify who is most at risk, and determine how to prevent and treat it.
RECOVER is unprecedented in its size and scope as the most-diverse, deeply characterized cohort of Long COVID patients. We’ve enlisted the help of many patient volunteers, who have enrolled in observational studies designed to help researchers learn as much as possible about people who have Long COVID.
Indeed, thousands of research participants are now providing health information and undergoing in-depth medical evaluations and tests, enabling investigators to look for trends. Additionally, studies of millions of electronic medical records are providing insights about those who have received care during the pandemic. More than 40 studies are being conducted to identify the causes of disease, potential biomarkers of Long COVID, and new therapeutic targets.
In all, RECOVER’s research assets are voluminous. They involve invaluable contributions from many people and communities, including research volunteers, research investigators, and clinical specialists. In addition, millions of health records and numerous related tissues and specimens are being analyzed for possible leads.
At the center of it all is the National Community Engagement Group (NCEG). The NCEG is comprised of people living with Long COVID and those representing others living with the condition, and it is truly instrumental to the initiative’s progress in understanding how and why SARS-CoV-2 impacts people in different ways. It’s also helping researchers learn why some people recover while others do not.
So far, we’ve learned that people hospitalized with COVID-19 are twice as likely to have Long COVID than those who were not hospitalized for infection. We’ve also learned that members of racial and ethnic minority groups with Long COVID were more likely to have been hospitalized with COVID-19.
Similarly, disparities in Long COVID exist within those living in areas with particular environmental exposures [1], and those who were already burdened by other diseases and conditions—such as diabetes and chronic pulmonary disease [2]. We’ve also discovered that the certain types of symptoms of Long COVID are consistent among patients regardless of which SARS-CoV-2 variant caused their initial infection. Yet, people infected with the earlier variants have a higher number of symptoms than those infected with more recent variants.
Patient experiences have guided and will continue to guide the study designs and trajectory of RECOVER. Now, fueled by the knowledge that we have gained, RECOVER is preparing to advance to the next phase of discovery—testing interventions in clinical trials to see if they can help people with Long COVID.
To prepare, we are beginning to identify potential clinical trial sites. This important step will help us to find the right places with the right staff and capabilities for enrolling the appropriate patient populations needed to implement the studies. We’ll ensure that the public knows when these upcoming clinical trials are ready to enroll.
Of course, the design of these RECOVER clinical trials will be critical, and insights gained from patients have been key in this process. Results from RECOVER study questionnaires, surveys, and discussions with people experiencing Long COVID identified symptom clusters considered to be the most significant and burdensome to patients. These include sleep disorders, “brain fog” (trouble thinking clearly), exercise intolerance and fatigue, and nervous system dysfunction affecting people’s ability to regulate normal body functions like heart rate and body temperature.
These patient observations have effectively guided the design of the clinical trials that will evaluate whether certain interventions and therapies can help alleviate symptoms that are part of these specific clusters. We’re excited to be advancing toward this phase of the initiative and, again, are very grateful to patient representatives like Nitza, quoted above, for getting us to this phase.
Effective evaluation of those treatments will be important, too. Early in the pandemic, while many clinical trials were launching, most were not large enough or did not have the appropriate objectives to define effective treatments for acute COVID-19. This left clinicians with few clear options when faced with patients needing help.
Learning from this experience, the RECOVER trials will be harmonized to ensure coordinated and efficient evaluation of interventions—in other words, all potential therapies will be using the same protocols platforms and the same data elements. This consistency accelerates our understanding and strengthens the certainty of findings.
Given the widespread and diverse impact that the virus has on the body, it is highly likely that more than one treatment will be needed for each kind of patient experience. Finding solutions for everyone—people of all races, ethnicities, genders, ages, and geographic locations—is paramount.
RECOVER patient representative, Juan Lewis, of San Antonio shared with us, “In April 2020, I was fighting for my life, and today I fight for my quality of life. COVID impacted me physically, mentally, socially, and financially.”
For people like Juan who are experiencing debilitating Long COVID symptoms, we know that finding answers as quickly as possible is critical. As we look ahead to the next 12 months, we’ll continue the studies evaluating the underlying causes, risk factors, and outcomes of Long Covid, and we anticipate significant scientific progress on research leading to Long COVID treatments.
Keep an eye on the RECOVER website for updates on our progress, and published findings.
References:
[1] Identifying environmental risk factors for post-acute sequelae of SARS-CoV-2 infection: An EHR-based cohort study from the recover program. Zhang Y, Hu H, Fokaidis V, V CL, Xu J, Zang C, Xu Z, Wang F, Koropsak M, Bian J, Hall J, Rothman RL, Shenkman EA, Wei WQ, Weiner MG, Carton TW, Kaushal R. Environ Adv. 2023 Apr;11:100352.
[2] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 Jul;4(7):e532-e541.
Links:
RECOVER: Researching COVID to Enhance Recovery
Long COVID: Ask NIH Leader about Latest Research (YouTube)
NIH Builds Large Nationwide Study Population of Tens of Thousands to Support Research on Long-Term Effects of COVID-19, NIH News Release, September 15, 2021
Understanding Long-Term COVID-19 Symptoms and Enhancing Recovery, NIH Director’s Blog, October 4, 2022.
NIH RECOVER Research Identifies Potential Long COVID Disparities. NIH News Release, February 16, 2023.
NIH RECOVER Listening Session, June 2021 (NIH Videocast)
NIH RECOVER Listening Session: Understanding Long COVID Across Communities of Color and Those Hardest Hit by COVID, January 21, 2022 (NIH Videocast)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes, Centers, and Offices to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 25th in the series of NIH guest posts that will run until a new permanent NIH director is in place.
Understanding Long-Term COVID-19 Symptoms and Enhancing Recovery
Posted on by Walter J. Koroshetz, M.D., National Institute of Neurological Disorders and Stroke
We are in the third year of the COVID-19 pandemic, and across the world, most restrictions have lifted, and society is trying to get back to “normal.” But for many people—potentially millions globally—there is no getting back to normal just yet.
They are still living with the long-term effects of a COVID-19 infection, known as the post-acute sequelae of SARS-CoV-2 infection (PASC), including Long COVID. These people continue to experience debilitating fatigue, shortness of breath, pain, difficulty sleeping, racing heart rate, exercise intolerance, gastrointestinal and other symptoms, as well as cognitive problems that make it difficult to perform at work or school.
This is a public health issue that is in desperate need of answers. Research is essential to address the many puzzling aspects of Long COVID and guide us to effective responses that protect the nation’s long-term health.
For the past two years, NIH’s National Heart, Lung, and Blood Institute (NHLBI), the National Institute of Allergy and Infectious Diseases (NIAID), and my National Institute of Neurological Disorders and Stroke (NINDS) along with several other NIH institutes and the office of the NIH Director, have been leading NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, a national research program to understand PASC.
The initiative studies core questions such as why COVID-19 infections can have lingering effects, why new symptoms may develop, and what is the impact of SARS-CoV-2, the virus that causes COVID-19, on other diseases and conditions? Answering these fundamental questions will help to determine the underlying biologic basis of Long COVID. The answers will also help to tell us who is at risk for Long COVID and identify therapies to prevent or treat the condition.
The RECOVER initiative’s wide scope of research is also unprecedented. It is needed because Long COVID is so complex, and history indicates that similar post infectious conditions have defied definitive explanation or effective treatment. Indeed, those experiencing Long COVID report varying symptoms, making it highly unlikely that a single therapy will work for everyone, underscoring the need to pursue multiple therapeutic strategies.
To understand Long COVID fully, hundreds of RECOVER investigators are recruiting more than 17,000 adults (including pregnant people) and more than 18,000 children to take part in cohort studies. Hundreds of enrolling sites have been set up across the country. An autopsy research cohort will also provide further insight into how COVID-19 affects the body’s organs and tissues.
In addition, researchers will analyze electronic health records from millions of people to understand how Long COVID and its symptoms change over time. The RECOVER initiative is also utilizing consistent research protocols across all the study sites. The protocols have been carefully developed with input from patients and advocates, and they are designed to allow for consistent data collection, improve data sharing, and help to accelerate the pace of research.
From the very beginning, people suffering from Long COVID have been our partners in RECOVER. Patients and advocates have contributed important perspectives and provided valuable input into the master protocols and research plans.
Now, with RECOVER underway, individuals with Long COVID, their caregivers, and community members continue to serve a critical role in the Initiative. The National Community Engagement Group (NCEG) has been established to make certain that RECOVER meets the needs of all people affected by Long COVID. The RECOVER Patient and Community Engagement Strategy outlines all the approaches that RECOVER is using to engage with and gather input from individuals impacted by Long COVID.
The NIH recently made more than 40 awards to improve understanding of the underlying biology and pathology of Long COVID. There have already been several important findings published by RECOVER scientists.
For example, in a recent study published in the journal Lancet Digital Health, RECOVER investigators used machine learning to comb through electronic health records to look for signals that may predict whether someone has Long COVID [1]. As new findings, tools, and technologies continue to emerge that help advance our knowledge of the condition, the RECOVER Research Review (R3) Seminar Series will provide a forum for researchers and our partners with up-to-date information about Long COVID research.
It is important to note that post-viral conditions are not a new concept. Many, but not all, of the symptoms reported in Long COVID, including fatigue, post-exertional malaise, chronic musculoskeletal pain, sleep disorders, postural orthostatic tachycardia (POTS), and cognitive issues, overlap with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).
ME/CFS is a serious disease that can occur following infection and make people profoundly sick for decades. Like Long COVID, ME/CFS is a heterogenous condition that does not affect everybody in the same way, and the knowledge gained through research on Long COVID may also positively impact the understanding, treatment, and prevention of POTS, ME/CFS, and other chronic diseases.
Unlike other post-viral conditions, people who experience Long COVID were all infected by the same virus—albeit different variants—at a similar point in time. This creates a unique opportunity for RECOVER researchers to study post-viral conditions in real-time.
The opportunity enables scientists to study many people simultaneously while they are still infected to monitor their progress and recovery, and to try to understand why some individuals develop ongoing symptoms. A better understanding of the transition from acute to chronic disease may offer an opportunity to intervene, identify who is at risk of the transition, and develop therapies for people who experience symptoms long after the acute infection has resolved.
The RECOVER initiative will soon announce clinical trials, leveraging data from clinicians and patients in which symptom clusters were identified and can be targeted by various interventions. These trials will investigate therapies that are indicated for other non-COVID conditions and novel treatments for Long COVID.
Through extensive collaboration across the multiple NIH institutes and offices that contribute to the RECOVER effort, our hope is critical answers will emerge soon. These answers will help us to recognize the full range of outcomes and needs resulting from PASC and, most important, enable many people to make a full recovery from COVID-19. We are indebted to the over 10,000 subjects who have already enrolled in RECOVER. Their contributions and the hard work of the RECOVER investigators offer hope for the future to the millions still suffering from the pandemic.
Reference:
[1] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 Jul;4(7):e532-e541.
Links:
COVID-19 Research (NIH)
Long COVID (NIH)
RECOVER: Researching COVID to Enhance Recovery (NIH)
“NIH builds large nationwide study population of tens of thousands to support research on long-term effects of COVID-19,” NIH News Release, September 15, 2021.
Director’s Messages (National Institute of Neurological Disorders and Stroke/NIH)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 18th in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.
Using AI to Advance Understanding of Long COVID Syndrome
Posted on by Lawrence Tabak, D.D.S., Ph.D.
The COVID-19 pandemic continues to present considerable public health challenges in the United States and around the globe. One of the most puzzling is why many people who get over an initial and often relatively mild COVID illness later develop new and potentially debilitating symptoms. These symptoms run the gamut including fatigue, shortness of breath, brain fog, anxiety, and gastrointestinal trouble.
People understandably want answers to help them manage this complex condition referred to as Long COVID syndrome. But because Long COVID is so variable from person to person, it’s extremely difficult to work backwards and determine what these people had in common that might have made them susceptible to Long COVID. The variability also makes it difficult to identify all those who have Long COVID, whether they realize it or not. But a recent study, published in the journal Lancet Digital Health, shows that a well-trained computer and its artificial intelligence can help.
Researchers found that computers, after scanning thousands of electronic health records (EHRs) from people with Long COVID, could reliably make the call. The results, though still preliminary and in need of further validation, point the way to developing a fast, easy-to-use computer algorithm to help determine whether a person with a positive COVID test is likely to battle Long COVID.
In this groundbreaking study, NIH-supported researchers led by Emily Pfaff, University of North Carolina, Chapel Hill, and Melissa Haendel, the University of Colorado Anschutz Medical Campus, Aurora, relied on machine learning. In machine learning, a computer sifts through vast amounts of data to look for patterns. One reason machine learning is so powerful is that it doesn’t require humans to tell the computer which features it should look for. As such, machine learning can pick up on subtle patterns that people would otherwise miss.
In this case, Pfaff, Haendel, and team decided to “train” their computer on EHRs from people who had reported a COVID-19 infection. (The records are de-identified to protect patient privacy.) The researchers found just what they needed in the National COVID Cohort Collaborative (N3C), a national, publicly available data resource sponsored by NIH’s National Center for Advancing Translational Sciences. It is part of NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, which aims to improve understanding of Long COVID.
The researchers defined a group of more than 1.5 million adults in N3C who either had been diagnosed with COVID-19 or had a record of a positive COVID-19 test at least 90 days prior. Next, they examined common features, including any doctor visits, diagnoses, or medications, from the group’s roughly 100,000 adults.
They fed that EHR data into a computer, along with health information from almost 600 patients who’d been seen at a Long COVID clinic. They developed three machine learning models: one to identify potential long COVID patients across the whole dataset and two others that focused separately on people who had or hadn’t been hospitalized.
All three models proved effective for identifying people with potential Long-COVID. Each of the models had an 85 percent or better discrimination threshold, indicating they are highly accurate. That’s important because, once researchers can identify those with Long COVID in a large database of people such as N3C, they can begin to ask and answer many critical questions about any differences in an individual’s risk factors or treatment that might explain why some get Long COVID and others don’t.
This new study is also an excellent example of N3C’s goal to assemble data from EHRs that enable researchers around the world to get rapid answers and seek effective interventions for COVID-19, including its long-term health effects. It’s also made important progress toward the urgent goal of the RECOVER initiative to identify people with or at risk for Long COVID who may be eligible to participate in clinical trials of promising new treatment approaches.
Long COVID remains a puzzling public health challenge. Another recent NIH study published in the journal Annals of Internal Medicine set out to identify people with symptoms of Long COVID, most of whom had recovered from mild-to-moderate COVID-19 [2]. More than half had signs of Long COVID. But, despite extensive testing, the NIH researchers were unable to pinpoint any underlying cause of the Long COVID symptoms in most cases.
So if you’d like to help researchers solve this puzzle, RECOVER is now enrolling adults and kids—including those who have and have not had COVID—at more than 80 study sites around the country.
References:
[1] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 May 16:S2589-7500(22)00048-6.
[2] A longitudinal study of COVID-19 sequelae and immunity: baseline findings. Sneller MC, Liang CJ, Marques AR, Chung JY, Shanbhag SM, Fontana JR, Raza H, Okeke O, Dewar RL, Higgins BP, Tolstenko K, Kwan RW, Gittens KR, Seamon CA, McCormack G, Shaw JS, Okpali GM, Law M, Trihemasava K, Kennedy BD, Shi V, Justement JS, Buckner CM, Blazkova J, Moir S, Chun TW, Lane HC. Ann Intern Med. 2022 May 24:M21-4905.
Links:
COVID-19 Research (NIH)
National COVID Cohort Collaborative (N3C) (National Center for Advancing Translational Sciences/NIH)
Emily Pfaff (University of North Carolina, Chapel Hill)
Melissa Haendel (University of Colorado, Aurora)
NIH Support: National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases
Breakthrough Infections in Vaccinated People Less Likely to Cause ‘Long COVID’
Posted on by Dr. Francis Collins
There’s no question that vaccines are making a tremendous difference in protecting individuals and whole communities against infection and severe illness from SARS-CoV-2, the coronavirus that causes COVID-19. And now, there’s yet another reason to get the vaccine: in the event of a breakthrough infection, people who are fully vaccinated also are substantially less likely to develop Long COVID Syndrome, which causes brain fog, muscle pain, fatigue, and a constellation of other debilitating symptoms that can last for months after recovery from an initial infection.
These important findings published in The Lancet Infectious Diseases are the latest from the COVID Symptom Study [1]. This study allows everyday citizens in the United Kingdom to download a smartphone app and self-report data on their infection, symptoms, and vaccination status over a long period of time.
Previously, the study found that 1 in 20 people in the U.K. who got COVID-19 battled Long COVID symptoms for eight weeks or more. But this work was done before vaccines were widely available. What about the risk among those who got COVID-19 for the first time as a breakthrough infection after receiving a double dose of any of the three COVID-19 vaccines (Pfizer, Moderna, AstraZeneca) authorized for use in the U.K.?
To answer that question, Claire Steves, King’s College, London, and colleagues looked to frequent users of the COVID Symptom Study app on their smartphones. In its new work, Steves’ team was interested in analyzing data submitted by folks who’d logged their symptoms, test results, and vaccination status between December 9, 2020, and July 4, 2021. The team found there were more than 1.2 million adults who’d received a first dose of vaccine and nearly 1 million who were fully vaccinated during this period.
The data show that only 0.2 percent of those who were fully vaccinated later tested positive for COVID-19. While accounting for differences in age, sex, and other risk factors, the researchers found that fully vaccinated individuals who developed breakthrough infections were about half (49 percent) as likely as unvaccinated people to report symptoms of Long COVID Syndrome lasting at least four weeks after infection.
The most common symptoms were similar in vaccinated and unvaccinated adults with COVID-19, and included loss of smell, cough, fever, headaches, and fatigue. However, all of these symptoms were milder and less frequently reported among the vaccinated as compared to the unvaccinated.
Vaccinated people who became infected were also more likely than the unvaccinated to be asymptomatic. And, if they did develop symptoms, they were half as likely to report multiple symptoms in the first week of illness. Another vaccination benefit was that people with a breakthrough infection were about a third as likely to report any severe symptoms. They also were more than 70 percent less likely to require hospitalization.
We still have a lot to learn about Long COVID, and, to get the answers, NIH has launched the RECOVER Initiative. The initiative will study tens of thousands of COVID-19 survivors to understand why many individuals don’t recover as quickly as expected, and what might be the cause, prevention, and treatment for Long COVID.
In the meantime, these latest findings offer the encouraging news that help is already here in the form of vaccines, which provide a very effective way to protect against COVID-19 and greatly reduce the odds of Long COVID if you do get sick. So, if you haven’t done so already, make a plan to protect your own health and help end this pandemic by getting yourself fully vaccinated. Vaccines are free and available near to you—just go to vaccines.gov or text your zip code to 438829.
Reference:
[1] Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study. Antonelli M, Penfold RS, Merino J, Sudre CH, Molteni E, Berry S, Canas LS, Graham MS, Klaser K, Modat M, Murray B, Kerfoot E, Chen L, Deng J, Österdahl MF, Cheetham NJ, Drew DA, Nguyen LH, Pujol JC, Hu C, Selvachandran S, Polidori L, May A, Wolf J, Chan AT, Hammers A, Duncan EL, Spector TD, Ourselin S, Steves CJ. Lancet Infect Dis. 2021 Sep 1:S1473-3099(21)00460-6.
Links:
COVID-19 Research (NIH)
Claire Steves (King’s College London, United Kingdom)
