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Searching for Ways to Prevent Life-Threatening Blood Clots in COVID-19

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At Home with Gary Gibbons

Six months into the coronavirus disease 2019 (COVID-19) pandemic, researchers still have much to learn about the many ways in which COVID-19 can wreak devastation on the human body. Among the many mysteries is exactly how SARS-CoV-2, which is the novel coronavirus that causes COVID-19, triggers the formation of blood clots that can lead to strokes and other life-threatening complications, even in younger people.

Recently, I had a chance to talk with Dr. Gary Gibbons, Director of NIH’s Heart, Lung, and Blood Institute (NHLBI) about what research is being done to tackle this baffling complication of COVID-19. Our conversation took place via videoconference, with him connecting from his home in Washington, D.C., and me linking in from my home just up the road in Maryland. Here’s a condensed transcript of our chat:

Collins: I’m going to start by asking about the SARS-CoV-2-induced blood clotting not only in the lungs, but in other parts of the body. What do we know about the virus that would explain this?

Gibbons: It seems like every few weeks another page gets turned on COVID-19, and we learn even more about how this virus affects the body. Blood clots are one of the startling and, unfortunately, devastating complications that emerged as patients were cared for, particularly in New York City. It became apparent that certain individuals had difficulty getting enough oxygen into their system. The difficulty couldn’t be explained entirely by the extent of the pneumonia affecting the lungs’ ability to exchange oxygen.

It turned out that, in addition to the pneumonia, blood clots in the lungs were compromising oxygenation. But some patients also had clotting, or thrombotic, complications in their veins and arteries in other parts of the body. Quite puzzling. There were episodes of relatively young individuals in their 30s and 40s presenting with strokes related to blood clots affecting the arterial circulation to the brain.

We’re still trying to understand what promotes the clotting. One clue involves the endothelial cells that form the inner lining of our blood vessels. These cells have on their surface a protein called the angiotensin-converting enzyme 2 (ACE2) receptor, and this clue is important for two reasons. One, the virus attaches to the ACE2 receptor, using it as an entry point to infect cells. Two, endothelial-lined blood vessels extend to every organ in the body. Taken together, it seems that some COVID-19 complications relate to the virus attaching to endothelial cells, not only in the lungs, but in the heart and multiple organs.

Collins: So, starting in the respiratory tree, the virus somehow breaks through into a blood vessel and then gets spread around the body. There have been strange reports of people with COVID-19 who may not get really sick, but their toes look frostbitten. Is “COVID toes,” as some people call it, also part of this same syndrome?

Gibbons: We’re still in the early days of learning about this virus. But I think this offers a further clue that the virus not only affects large vessels but small vessels. In fact, clots have been reported at the capillary level, and that’s fairly unusual. It’s suggestive that an interaction is taking place between the platelets and the endothelial surface.

Normally, there’s a tightly regulated balance in the bloodstream between pro-coagulant and anticoagulant proteins to prevent clotting and keep the blood flowing. But when you cut your finger, for example, you get activation for blood clots in the form of a protein mesh. It looks like a fishing net that can help seal the injury. In addition, platelets in the blood stream help to plug the holes in that fishing net and create a real seal of a blood vessel.

Well, imagine it happening in those small vessels, which usually have a non-stick endothelial surface, almost like Teflon, that prevents clotting. Then the virus comes along and tips the balance toward promoting clot formation. This disturbs the Teflon-like property of the endothelial lining and makes it sticky. It’s incredible the tricks this virus has learned by binding onto one of these molecules in the endothelial lining.

Collins: Who are the COVID-19 patients most at risk for this clotting problem?

Gibbons: Unfortunately, it appears right now that older adults are among the most vulnerable. They have a lot of the risks for the formation of these blood clots. What’s notable is these thrombotic complications are also happening to relatively young adults or middle-aged individuals who don’t have a lot of other chronic conditions, or comorbidities, to put them at higher risk for severe disease. Again, it’s suggestive that this virus is doing something that is particular to the coagulation system.

Collins: We’d love to have a way of identifying in advance the people who are most likely to get into trouble with blood clotting. They might be the ones you’d want to start on an intervention, even before you have evidence that things are getting out of control. Do you have any kind of biomarker to tell you which patients might benefit from early intervention?

Gibbons: Biomarkers are being actively studied. What we do know from some earlier observations is that you can assess the balance of clotting and anticlotting factors in the blood by measuring a biomarker called D-dimer. It’s basically a protein fragment, a degradation product, from a prior clot. It tells you a bit about the system’s activity in forming and dissolving clots.

If there’s a lot of D-dimer activity, it suggests a coagulation cascade is jazzed up. In those patients, it’s probably a clue that this is a big trigger in terms of coagulation and thrombosis. So, D-dimer levels could maybe tell us which patients need really aggressive full anticoagulation.

Collins: Have people tried empirically using blood thinners for people who seem to be getting into trouble with this clotting problem?

Gibbons: There’s a paper out of the Mount Sinai in New York City that looked at thousands of patients being treated for COVID-19 [1]. Based on clinical practice and judgments, one of the striking findings is that those who were fully anticoagulated had better survival than those who were not. Now, this was not a randomized, controlled clinical trial, where some were given full anticoagulation and others were not. It was just an observational study that showed an association. But this study indicated indirectly that by giving the blood thinners, changing that thrombotic risk, maybe it’s possible to reduce morbidity and mortality. That’s why we need to do a randomized, controlled clinical trial to see if it can be used to reduce these case fatality rates.

Collins: You and your colleagues got together and came up with a design for such a clinical trial. Tell us about that.

Gibbons: My institute studies the heart, lung, and blood. The virus attacks all three. So, our community has a compelling need to lean in and study COVID-19. Recently, NIH helped to launch a public-private partnership called Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV). As the name spells out, this initiative provides is a clinical platform to generate life-saving treatments as we wait for the development of a vaccine.

Through ACTIV, a protocol is now in the final stages of review for a clinical trial that will involve a network of hospitals and explore the question: is it sufficient to try a low-dose thrombo-prophylactic, or clot preventative, approach versus full anticoagulation? Some think patients ought to have full anticoagulation, but that’s not without risk. So, we want to put that question to the test. As part of that, we’ll also learn more about biomarkers and what could be predictive of individuals getting the greatest benefit.

If we find that fully anticoagulating patients prevents clots, then that’s great. But it begs the question: what happens when patients go home? Is it sufficient to just turn off the drip and let them go their merry way? Should they have a low dose thrombo-prophylactic regimen for a period of time? If so, how long? Or should they be fully anticoagulated with oral anticoagulation for a certain period of time? All these and other questions still remain.

Collins: This can make a huge difference. If you’re admitted to the hospital with COVID-19, that means you’re pretty sick and, based on the numbers that I’ve seen, your chance of dying is about 12 percent if nothing else happens. If we can find something like an anticoagulant that would reduce that risk substantially, we can have a huge impact on reducing deaths from COVID-19. How soon can we get this trial going, Gary?

Gibbons: We have a sense of urgency that clearly this pandemic is taking too many lives and time is of the essence. So, we’ve indeed had a very streamlined process. We’re leveraging the fact that we have clinical trial networks, where regardless of what they were planning to do, it’s all hands on deck. As a result, we’re able to move faster to align with that sense of urgency. We hope that we can be off to a quick launch within the next two to three weeks with the anticoagulation trials.

Collins: This is good because people are waiting on the vaccines, but realistically we won’t know whether the vaccines are working for several more months, and having them available for lots of people will be at the very end of this year or early 2021 at best. Meanwhile, people still are going to be getting sick with COVID-19. We want to be able to have as many therapeutic options as possible to offer to them. And this seems like a pretty exciting one to try and move forward as quickly as possible. You and your colleagues deserve a lot of credit for bringing this to everybody’s attention.

But before we sign off, I have to raise another issue of deep significance. Gary, I think both of us are struggling not only with the impact of COVID-19 on the world, but the profound sorrow, grief, frustration, and anger that surrounds the death of George Floyd. This brings into acute focus the far too numerous other circumstances where African Americans have been mistreated and subjected to tragic outcomes.

This troubling time also shines a light on the health disparities that affect our nation in so many ways. We can see what COVID-19 has done to certain underrepresented groups who have borne an undue share of the burden, and have suffered injustices at the hands of society. It’s been tough for many of us to admit that our country is far from treating everyone equally, but it’s a learning opportunity and a call to redouble our efforts to find solutions.

Gary, you’ve been a wonderful leader in that conversation for a long time. I want to thank you both for what you’re doing scientifically and for your willingness to speak the truth and stand up for what’s right and fair. It’s been great talking to you about all these issues.

Gibbons: Thank you. We appreciate this opportunity to fulfill NIH’s mission of turning scientific discovery into better health for all. If there’s any moment that our nation needs us, this is it.

Reference:

[1] Association of Treatment Dose Anticoagulation With In-Hospital Survival Among Hospitalized Patients With COVID-19. Paranjpe I, Fuster V, Lala A, Russak A, Glicksberg BS, Levin MA, Charney AW, Narula J, Fayad ZA, Bagiella E, Zhao S, Nadkarni GN. J Am Coll Cardiol. 2020 May 5;S0735-1097(20)35218-9.

Links:

Coronavirus (COVID-19) (NIH)

Rising to the Challenge of COVID-19: The NHLBI Community Response,” Director’s Messages, National Heart, Lung, and Blood Institute/NIH, April 29, 2020.

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) (NIH)


Using Artificial Intelligence to Detect Cervical Cancer

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Doctor reviewing cell phone
Credit: gettyimages/Dean Mitchell

My last post highlighted the use of artificial intelligence (AI) to create an algorithm capable of detecting 10 different kinds of irregular heart rhythms. But that’s just one of the many potential medical uses of AI. In this post, I’ll tell you how NIH researchers are pairing AI analysis with smartphone cameras to help more women avoid cervical cancer.

In work described in the Journal of the National Cancer Institute [1], researchers used a high-performance computer to analyze thousands of cervical photographs, obtained more than 20 years ago from volunteers in a cancer screening study. The computer learned to recognize specific patterns associated with pre-cancerous and cancerous changes of the cervix, and that information was used to develop an algorithm for reliably detecting such changes in the collection of images. In fact, the AI-generated algorithm outperformed human expert reviewers and all standard screening tests in detecting pre-cancerous changes.

Nearly all cervical cancers are caused by the human papillomavirus (HPV). Cervical cancer screening—first with Pap smears and now also using HPV testing—have greatly reduced deaths from cervical cancer. But this cancer still claims the lives of more than 4,000 U.S. women each year, with higher frequency among women who are black or older [2]. Around the world, more than a quarter-million women die of this preventable disease, mostly in poor and remote areas [3].

These troubling numbers have kept researchers on the lookout for low cost, but easy-to-use, tools that could be highly effective at detecting HPV infections most likely to advance to cervical cancer. Such tools would also need to work well in areas with limited resources for sample preparation and lab analysis. That’s what led to this collaboration involving researchers from NIH’s National Cancer Institute (NCI) and Global Good, Bellevue, WA, which is an Intellectual Ventures collaboration with Bill Gates to invent life-changing technologies for the developing world.

Global Good researchers contacted NCI experts hoping to apply AI to a large dataset of cervical images. The NCI experts suggested an 18-year cervical cancer screening study in Costa Rica. The NCI-supported project, completed in the 1990s, generated nearly 60,000 cervical images, later digitized by NIH’s National Library of Medicine and stored away safely.

The researchers agreed that all these images, obtained in a highly standardized way, would serve as perfect training material for a computer to develop a detection algorithm for cervical cancer. This type of AI, called machine learning, involves feeding tens of thousands of images into a computer equipped with one or more high-powered graphics processing units (GPUs), similar to something you’d find in an Xbox or PlayStation. The GPUs allow the computer to crunch large sets of visual data in the images and devise a set of rules, or algorithms, that allow it to learn to “see” physical features.

Here’s how they did it. First, the researchers got the computer to create a convolutional neural network. That’s a fancy way of saying that they trained it to read images, filter out the millions of non-essential bytes, and retain the few hundred bytes in the photo that make it uniquely identifiable. They fed 1.28 million color images covering hundreds of common objects into the computer to create layers of processing ability that, like the human visual system, can distinguish objects and their qualities.

Once the convolutional neural network was formed, the researchers took the next big step: training the system to see the physical properties of a healthy cervix, a cervix with worrisome cellular changes, or a cervix with pre-cancer. That’s where the thousands of cervical images from the Costa Rican screening trial literally entered the picture.

When all these layers of processing ability were formed, the researchers had created the “automated visual evaluation” algorithm. It went on to identify with remarkable accuracy the images associated with the Costa Rican study’s 241 known precancers and 38 known cancers. The algorithm’s few minor hiccups came mainly from suboptimal images with faded colors or slightly blurred focus.

These minor glitches have the researchers now working hard to optimize the process, including determining how health workers can capture good quality photos of the cervix with a smartphone during a routine pelvic exam and how to outfit smartphones with the necessary software to analyze cervical photos quickly in real-world settings. The goal is to enable health workers to use a smartphone or similar device to provide women with cervical screening and treatment during a single visit.

In fact, the researchers are already field testing their AI-inspired approach on smartphones in the United States and abroad. If all goes well, this low-cost, mobile approach could provide a valuable new tool to help reduce the burden of cervical cancer among underserved populations.

The day that cervical cancer no longer steals the lives of hundreds of thousands of women a year worldwide will be a joyful moment for cancer researchers, as well as a major victory for women’s health.

References:

[1] An observational study of Deep Learning and automated evaluation of cervical images for cancer screening. Hu L, Bell D, Antani S, Xue Z, Yu K, Horning MP, Gachuhi N, Wilson B, Jaiswal MS, Befano B, Long LR, Herrero R, Einstein MH, Burk RD, Demarco M, Gage JC, Rodriguez AC, Wentzensen N, Schiffman M. J Natl Cancer Inst. 2019 Jan 10. [Epub ahead of print]

[2] “Study: Death Rate from Cervical Cancer Higher Than Thought,” American Cancer Society, Jan. 25, 2017.

[3] “World Cancer Day,” World Health Organization, Feb. 2, 2017.

Links:

Cervical Cancer (National Cancer Institute/NIH)

Global Good (Intellectual Ventures, Bellevue, WA)

NIH Support: National Cancer Institute; National Library of Medicine


LabTV: Curious About Drug Resistance of Hepatitis C Virus

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Ashley Matthew

As long as she can remember, Ashley Matthew wanted to be a medical doctor. She took every opportunity to pursue her dream, including shadowing physicians to learn more about what a career in health care is really like. But, as Matthew explains in today’s LabTV video, she also became attracted to the idea of doing research because of her affinity for solving problems and “figuring things out.”

So, Matthew decided to give biomedical research a try, landing a spot in an undergraduate summer program sponsored by the University of Massachusetts. Ten weeks later, she was convinced that her future in medicine just had to include a research component. That’s why Matthew is now well on her way as an M.D./Ph.D. student at the University of Massachusetts Medical School, Worcester, where she works in the lab of Celia Schiffer.


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