The Skinny on Fat and Covid-19
Obesity is a risk factor for worse outcomes for a variety of medical conditions ranging from cancer to Covid-19. Most experts attribute it simply to underlying low-grade inflammation and added weight that make breathing more difficult.
Now researchers have found a more direct reason: SARS-CoV-2, the virus that causes Covid-19, can infect adipocytes, more commonly known as fat cells, and macrophages, immune cells that are part of the broader matrix of cells that support fat tissue. Stanford University researchers Catherine Blish and Tracey McLaughlin are senior authors of the study.
Most of us think of fat as the spare tire that can accumulate around the middle as we age, but fat also is present closer to most internal organs. McLaughlin's research has focused on epicardial fat, “which sits right on top of the heart with no physical barrier at all,” she says. So if that fat got infected and inflamed, it might directly affect the heart.” That could help explain cardiovascular problems associated with Covid-19 infections.
Looking at tissue taken from autopsy, there was evidence of SARS-CoV-2 virus inside the fat cells as well as surrounding inflammation. In fat cells and immune cells harvested from health humans, infection in the laboratory drove "an inflammatory response, particularly in the macrophages…They secreted proteins that are typically seen in a cytokine storm” where the immune response runs amok with potential life-threatening consequences. This suggests to McLaughlin “that there could be a regional and even a systemic inflammatory response following infection in fat.”
It is easy to see how the airborne SARS-CoV-2 virus infects the nose and lungs, but how does it get into fat tissue? That is a mystery and the source of ample speculation.
The macrophages studied by McLaughlin and Blish were spewing out inflammatory proteins, While the the virus within them was replicating, the new viral particles were not able to replicate within those cells. It was a different story in the fat cells. “When [the virus] gets into the fat cells, it not only replicates, it's a productive infection, which means the resulting viral particles can infect another cell,” including microphages, McLaughlin explains. It seems to be a symbiotic tango of the virus between the two cell types that keeps the cycle going.
It is easy to see how the airborne SARS-CoV-2 virus infects the nose and lungs, but how does it get into fat tissue? That is a mystery and the source of ample speculation.
Macrophages are mobile; they engulf and carry invading pathogens to lymphoid tissue in the lymph nodes, tonsils and elsewhere in the body to alert T cells of the immune system to the pathogen. Perhaps some of them also carry the virus through the bloodstream to more distant tissue.
ACE2 receptors are the means by which SARS-CoV-2 latches on to and enters most cells. They are not thought to be common on fat cells, so initially most researchers thought it unlikely they would become infected.
However, while some cell receptors always sit on the surface of the cell, other receptors are expressed on the surface only under certain conditions. Philipp Scherer, a professor of internal medicine and director of the Touchstone Diabetes Center at the University of Texas Southwestern Medical Center, suggests that, in people who have obesity, “There might be higher levels of dysfunctional [fat cells] that facilitate entry of the virus,” either through transiently expressed ACE2 or other receptors. Inflammatory proteins generated by macrophages might contribute to this process.
Another hypothesis is that viral RNA might be smuggled into fat cells as cargo in small bits of material called extracellular vesicles, or EVs, that can travel between cells. Other researchers have shown that when EVs express ACE2 receptors, they can act as decoys for SARS-CoV-2, where the virus binds to them rather than a cell. These scientists are working to create drugs that mimic this decoy effect as an approach to therapy.
Do fat cells play a role in Long Covid? “Fat cells are a great place to hide. You have all the energy you need and fat cells turn over very slowly; they have a half-life of ten years,” says Scherer. Observational studies suggest that acute Covid-19 can trigger the onset of diabetes especially in people who are overweight, and that patients taking medicines to regulate their diabetes “were actually quite protective” against acute Covid-19. Scherer has funding to study the risks and benefits of those drugs in animal models of Long Covid.
McLaughlin says there are two areas of potential concern with fat tissue and Long Covid. One is that this tissue might serve as a “big reservoir where the virus continues to replicate and is sent out” to other parts of the body. The second is that inflammation due to infected fat cells and macrophages can result in fibrosis or scar tissue forming around organs, inhibiting their function. Once scar tissue forms, the tissue damage becomes more difficult to repair.
Current Covid-19 treatments work by stopping the virus from entering cells through the ACE2 receptor, so they likely would have no effect on virus that uses a different mechanism. That means another approach will have to be developed to complement the treatments we already have. So the best advice McLaughlin can offer today is to keep current on vaccinations and boosters and lose weight to reduce the risk associated with obesity.
Awash in a fluid finely calibrated to keep it alive, a human eye rests inside a transparent cubic device. This ECaBox, or Eyes in a Care Box, is a one-of-a-kind system built by scientists at Barcelona’s Centre for Genomic Regulation (CRG). Their goal is to preserve human eyes for transplantation and related research.
In recent years, scientists have learned to transplant delicate organs such as the liver, lungs or pancreas, but eyes are another story. Even when preserved at the average transplant temperature of 4 Centigrade, they last for 48 hours max. That's one explanation for why transplanting the whole eye isn’t possible—only the cornea, the dome-shaped, outer layer of the eye, can withstand the procedure. The retina, the layer at the back of the eyeball that turns light into electrical signals, which the brain converts into images, is extremely difficult to transplant because it's packed with nerve tissue and blood vessels.
These challenges also make it tough to research transplantation. “This greatly limits their use for experiments, particularly when it comes to the effectiveness of new drugs and treatments,” said Maria Pia Cosma, a biologist at Barcelona’s Centre for Genomic Regulation (CRG), whose team is working on the ECaBox.
Eye transplants are desperately needed, but they're nowhere in sight. About 12.7 million people worldwide need a corneal transplant, which means that only one in 70 people who require them, get them. The gaps are international. Eye banks in the United Kingdom are around 20 percent below the level needed to supply hospitals, while Indian eye banks, which need at least 250,000 corneas per year, collect only around 45 to 50 thousand donor corneas (and of those 60 to 70 percent are successfully transplanted).
As for retinas, it's impossible currently to put one into the eye of another person. Artificial devices can be implanted to restore the sight of patients suffering from severe retinal diseases, but the number of people around the world with such “bionic eyes” is less than 600, while in America alone 11 million people have some type of retinal disease leading to severe vision loss. Add to this an increasingly aging population, commonly facing various vision impairments, and you have a recipe for heavy burdens on individuals, the economy and society. In the U.S. alone, the total annual economic impact of vision problems was $51.4 billion in 2017.
Even if you try growing tissues in the petri dish route into organoids mimicking the function of the human eye, you will not get the physiological complexity of the structure and metabolism of the real thing, according to Cosma. She is a member of a scientific consortium that includes researchers from major institutions from Spain, the U.K., Portugal, Italy and Israel. The consortium has received about $3.8 million from the European Union to pursue innovative eye research. Her team’s goal is to give hope to at least 2.2 billion people across the world afflicted with a vision impairment and 33 million who go through life with avoidable blindness.
Their method? Resuscitating cadaveric eyes for at least a month.
If we succeed, it will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo. -- Maria Pia Cosma.
“We proposed to resuscitate eyes, that is to restore the global physiology and function of human explanted tissues,” Cosma said, referring to living tissues extracted from the eye and placed in a medium for culture. Their ECaBox is an ex vivo biological system, in which eyes taken from dead donors are placed in an artificial environment, designed to preserve the eye’s temperature and pH levels, deter blood clots, and remove the metabolic waste and toxins that would otherwise spell their demise.
Scientists work on resuscitating eyes in the lab of Maria Pia Cosma.
Courtesy of Maria Pia Cosma.
“One of the great challenges is the passage of the blood in the capillary branches of the eye, what we call long-term perfusion,” Cosma said. Capillaries are an intricate network of very thin blood vessels that transport blood, nutrients and oxygen to cells in the body’s organs and systems. To maintain the garland-shaped structure of this network, sufficient amounts of oxygen and nutrients must be provided through the eye circulation and microcirculation. “Our ambition is to combine perfusion of the vessels with artificial blood," along with using a synthetic form of vitreous, or the gel-like fluid that lets in light and supports the the eye's round shape, Cosma said.
The scientists use this novel setup with the eye submersed in its medium to keep the organ viable, so they can test retinal function. “If we succeed, we will ensure full functionality of a human organ ex vivo. It will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo,” Cosma added.
A rapidly developing field of regenerative medicine aims to stimulate the body's natural healing processes and restore or replace damaged tissues and organs. But for people with retinal diseases, regenerative medicine progress has been painfully slow. “Experiments on rodents show progress, but the risks for humans are unacceptable,” Cosma said.
The ECaBox could boost progress with regenerative medicine for people with retinal diseases, which has been painfully slow because human experiments involving their eyes are too risky. “We will test emerging treatments while reducing animal research, and greatly accelerate the discovery and preclinical research phase of new possible treatments for vision loss at significantly reduced costs,” Cosma explained. Much less time and money would be wasted during the drug discovery process. Their work may even make it possible to transplant the entire eyeball for those who need it.
“It is a very exciting project,” said Sanjay Sharma, a professor of ophthalmology and epidemiology at Queen's University, in Kingston, Canada. “The ability to explore and monitor regenerative interventions will increasingly be of importance as we develop therapies that can regenerate ocular tissues, including the retina.”
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation.
But is the world ready for eye transplants? “People are a bit weird or very emotional about donating their eyes as compared to other organs,” Cosma said. And much can be said about the problem of eye donor shortage. Concerns include disfigurement and healthcare professionals’ fear that the conversation about eye donation will upset the departed person’s relatives because of cultural or religious considerations. As just one example, Sharma noted the paucity of eye donations in his home country, Canada.
Yet, experts like Sharma stress the importance of these donations for both the recipients and their family members. “It allows them some psychological benefit in a very difficult time,” he said. So why are global eye banks suffering? Is it because the eyes are the windows to the soul?
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation. In fact, most major religions of the world permit and support organ transplantation and donation, and by extension eye donation, because they unequivocally see it as an “act of neighborly love and charity.” In Hinduism, the concept of eye donation aligns with the Hindu principle of daan or selfless giving, where individuals donate their organs or body after death to benefit others and contribute to society. In Islam, eye donation is a form of sadaqah jariyah, a perpetual charity, as it can continue to benefit others even after the donor's death.
Meanwhile, Buddhist masters teach that donating an organ gives another person the chance to live longer and practice dharma, the universal law and order, more meaningfully; they also dismiss misunderstandings of the type “if you donate an eye, you’ll be born without an eye in the next birth.” And Christian teachings emphasize the values of love, compassion, and selflessness, all compatible with organ donation, eye donation notwithstanding; besides, those that will have a house in heaven, will get a whole new body without imperfections and limitations.
The explanation for people’s resistance may lie in what Deepak Sarma, a professor of Indian religions and philosophy at Case Western Reserve University in Cleveland, calls “street interpretation” of religious or spiritual dogmas. Consider the mechanism of karma, which is about the causal relation between previous and current actions. “Maybe some Hindus believe there is karma in the eyes and, if the eye gets transplanted into another person, they will have to have that karmic card from now on,” Sarma said. “Even if there is peculiar karma due to an untimely death–which might be interpreted by some as bad karma–then you have the karma of the recipient, which is tremendously good karma, because they have access to these body parts, a tremendous gift,” Sarma said. The overall accumulation is that of good karma: “It’s a beautiful kind of balance,” Sarma said.
For the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the already existing body is sacred since it will be the basis of a new refashioned body in an afterlife.---Omar Sultan Haque.
With that said, Sarma believes it is a fallacy to personify or anthropomorphize the eye, which doesn’t have a soul, and stresses that the karma attaches itself to the soul and not the body parts. But for scholars like Omar Sultan Haque—a psychiatrist and social scientist at Harvard Medical School, investigating questions across global health, anthropology, social psychology, and bioethics—the hierarchy of sacredness of body parts is entrenched in human psychology. You cannot equate the pinky toe with the face, he explained.
“The eyes are the window to the soul,” Haque said. “People have a hierarchy of body parts that are considered more sacred or essential to the self or soul, such as the eyes, face, and brain.” In his view, the techno-utopian transhumanist communities (especially those in Silicon Valley) have reduced the totality of a person to a mere material object, a “wet robot” that knows no sacredness or hierarchy of human body parts. “But for the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the [already existing] body is sacred since it will be the basis of a new refashioned body in an afterlife,” Haque said. “You cannot treat the body like any old material artifact, or old chair or ragged cloth, just because materialistic, secular ideologies want so,” he continued.
For Cosma and her peers, however, the very definition of what is alive or not is a bit semantic. “As soon as we die, the electrophysiological activity in the eye stops,” she said. “The goal of the project is to restore this activity as soon as possible before the highly complex tissue of the eye starts degrading.” Cosma’s group doesn’t yet know when they will be able to keep the eyes alive and well in the ECaBox, but the consensus is that the sooner the better. Hopefully, the taboos and fears around the eye donations will dissipate around the same time.
As Our AI Systems Get Better, So Must We
As the power and capability of our AI systems increase by the day, the essential question we now face is what constitutes peak human. If we stay where we are while the AI systems we are unleashing continually get better, they will meet and then exceed our capabilities in an ever-growing number of domains. But while some technology visionaries like Elon Musk call for us to slow down the development of AI systems to buy time, this approach alone will simply not work in our hyper-competitive world, particularly when the potential benefits of AI are so great and our frameworks for global governance are so weak. In order to build the future we want, we must also become ever better humans.
The list of activities we once saw as uniquely human where AIs have now surpassed us is long and growing. First, AI systems could beat our best chess players, then our best Go players, then our best champions of multi-player poker. They can see patterns far better than we can, generate medical and other hypotheses most human specialists miss, predict and map out new cellular structures, and even generate beautiful, and, yes, creative, art.
A recent paper by Microsoft researchers analyzing the significant leap in capabilities in OpenAI’s latest AI bot, ChatGPT-4, asserted that the algorithm can “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.” Calling this functionality “strikingly close to human-level performance,” the authors conclude it “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.”
The concept of AGI has been around for decades. In its common use, the term suggests a time when individual machines can do many different things at a human level, not just one thing like playing Go or analyzing radiological images. Debating when AGI might arrive, a favorite pastime of computer scientists for years, now has become outdated.
We already have AI algorithms and chatbots that can do lots of different things. Based on the generalist definition, in other words, AGI is essentially already here.
Unfettered by the evolved capacity and storage constraints of our brains, AI algorithms can access nearly all of the digitized cultural inheritance of humanity since the dawn of recorded history and have increasing access to growing pools of digitized biological data from across the spectrum of life.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
With these ever-larger datasets, rapidly increasing computing and memory power, and new and better algorithms, our AI systems will keep getting better faster than most of us can today imagine. These capabilities have the potential to help us radically improve our healthcare, agriculture, and manufacturing, make our economies more productive and our development more sustainable, and do many important things better.
Soon, they will learn how to write their own code. Like human children, in other words, AI systems will grow up. But even that doesn’t mean our human goose is cooked.
Just like dolphins and dogs, these alternate forms of intelligence will be uniquely theirs, not a lesser or greater version of ours. There are lots of things AI systems can't do and will never be able to do because our AI algorithms, for better and for worse, will never be human. Our embodied human intelligence is its own thing.
Our human intelligence is uniquely ours based on the capacities we have developed in our 3.8-billion-year journey from single cell organisms to us. Our brains and bodies represent continuous adaptations on earlier models, which is why our skeletal systems look like those of lizards and our brains like most other mammals with some extra cerebral cortex mixed in. Human intelligence isn’t just some type of disembodied function but the inextricable manifestation of our evolved physical reality. It includes our sensory analytical skills and all of our animal instincts, intuitions, drives, and perceptions. Disembodied machine intelligence is something different than what we have evolved and possess.
Because of this, some linguists including Noam Chomsky have recently argued that AI systems will never be intelligent as long as they are just manipulating symbols and mathematical tokens without any inherent understanding. Nothing could be further from the truth. Anyone interacting with even first-generation AI chatbots quickly realizes that while these systems are far from perfect or omniscient and can sometimes be stupendously oblivious, they are surprisingly smart and versatile and will get more so… forever. We have little idea even how our own minds work, so judging AI systems based on their output is relatively close to how we evaluate ourselves.
Anyone not awed by the potential of these AI systems is missing the point. AI’s newfound capacities demand that we work urgently to establish norms, standards, and regulations at all levels from local to global to manage the very real risks. Pausing our development of AI systems now doesn’t make sense, however, even if it were possible, because we have no sufficient ways of uniformly enacting such a pause, no plan for how we would use the time, and no common framework for addressing global collective challenges like this.
But if all we feel is a passive awe for these new capabilities, we will also be missing the point.
Human evolution, biology, and cultural history are not just some kind of accidental legacy, disability, or parlor trick, but our inherent superpower. Our ancestors outcompeted rivals for billions of years to make us so well suited to the world we inhabit and helped build. Our social organization at scale has made it possible for us to forge civilizations of immense complexity, engineer biology and novel intelligence, and extend our reach to the stars. Our messy, embodied, intuitive, social human intelligence is roughly mimicable by AI systems but, by definition, never fully replicable by them.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. We still don't know. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
As we do, we'll learn that many of our ideas and actions are made up of parts, some of which will prove essentially human and some of which can be better achieved by AI systems. Those in every walk of work and life who most successfully identify the optimal contributions of humans, AIs, and the two together, and who build systems and workflows empowering humans to do human things, machines to do machine things, and humans and machines to work together in ways maximizing the respective strengths of each, will be the champions of the 21st century across all fields.
The dawn of the age of machine intelligence is upon us. It’s a quantum leap equivalent to the domestication of plants and animals, industrialization, electrification, and computing. Each of these revolutions forced us to rethink what it means to be human, how we live, and how we organize ourselves. The AI revolution will happen more suddenly than these earlier transformations but will follow the same general trajectory. Now is the time to aggressively prepare for what is fast heading our way, including by active public engagement, governance, and regulation.
AI systems will not replace us, but, like these earlier technology-driven revolutions, they will force us to become different humans as we co-evolve with our technology. We will never reach peak human in our ongoing evolutionary journey, but we’ve got to manage this transition wisely to build the type of future we’d like to inhabit.
Alongside our ascending AIs, we humans still have a lot of climbing to do.