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.
Story by Big Think
For most of history, artificial intelligence (AI) has been relegated almost entirely to the realm of science fiction. Then, in late 2022, it burst into reality — seemingly out of nowhere — with the popular launch of ChatGPT, the generative AI chatbot that solves tricky problems, designs rockets, has deep conversations with users, and even aces the Bar exam.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
Opioid prescription policies may hurt those in chronic pain
Tinu Abayomi-Paul works as a writer and activist, plus one unwanted job: Trying to fill her opioid prescription. She says that some pharmacists laugh and tell her that no one needs the amount of pain medication that she is seeking. Another pharmacist near her home in Venus, Tex., refused to fill more than seven days of a 30-day prescription.
To get a new prescription—partially filled opioid prescriptions can’t be dispensed later—Abayomi-Paul needed to return to her doctor’s office. But without her medication, she was having too much pain to travel there, much less return to the pharmacy. She rationed out the pills over several weeks, an agonizing compromise that left her unable to work, interact with her children, sleep restfully, or leave the house. “Don’t I deserve to do more than survive?” she says.
Abayomi-Paul’s pain results from a degenerative spine disorder, chronic lymphocytic leukemia, and more than a dozen other diagnoses and disabilities. She is part of a growing group of people with chronic pain who have been negatively impacted by the fallout from efforts to prevent opioid overdose deaths.
Guidelines for dispensing these pills are complicated because many opioids, like codeine, oxycodone, and morphine, are prescribed legally for pain. Yet, deaths from opioids have increased rapidly since 1999 and become a national emergency. Many of them, such as heroin, are used illegally. The CDC identified three surges in opioid use: an increase in opioid prescriptions in the ‘90s, a surge of heroin around 2010, and an influx of fentanyl and other powerful synthetic opioids in 2013.
As overdose deaths grew, so did public calls to address them, prompting the CDC to change its prescription guidelines in 2016. The new guidelines suggested limiting medication for acute pain to a seven-day supply, capping daily doses of morphine, and other restrictions. Some statistics suggest that these policies have worked; from 2016 to 2019, prescriptions for opiates fell 44 percent. Physicians also started progressively lowering opioid doses for patients, a practice called tapering. A study tracking nearly 100,000 Medicare subscribers on opioids found that about 13 percent of patients were tapering in 2012, and that number increased to about 23 percent by 2017.
But some physicians may be too aggressive with this tapering strategy. About one in four people had doses reduced by more than 10 percent per week, a rate faster than the CDC recommends. The approach left people like Abayomi-Paul without the medication they needed. Every year, Abayomi-Paul says, her prescriptions are harder to fill. David Brushwood, a pharmacy professor who specializes in policy and outcomes at the University of Florida in Gainesville, says opioid dosing isn’t one-size-fits-all. “Patients need to be taken care of individually, not based on what some government agency says they need,” he says.
‘This is not survivable’
Health policy and disability rights attorney Erin Gilmer advocated for people with pain, using her own experience with chronic pain and a host of medical conditions as a guidepost. She launched an advocacy website, Healthcare as a Human Right, and shared her struggles on Twitter: “This pain is more than anything I've endured before and I've already been through too much. Yet because it's not simply identified no one believes it's as bad as it is. This is not survivable.”
When her pain dramatically worsened midway through 2021, Gilmer’s posts grew ominous: “I keep thinking it can't possibly get worse but somehow every day is worse than the last.”
The CDC revised its guidelines in 2022 after criticisms that people with chronic pain were being undertreated, enduring dangerous withdrawal symptoms, and suffering psychological distress. (Long-term opioid use can cause physical dependency, an adaptive reaction that is different than the compulsive misuse associated with a substance use disorder.) It was too late for Gilmer. On July 7, 2021, the 38-year-old died by suicide.
Last August, an Ohio district court ruling set forth a new requirement for Walgreens, Walmart, and CVS pharmacists in two counties. These pharmacists must now document opioid prescriptions that are turned down, even for customers who have no previous purchases at that pharmacy, and they’re required to share this information with other locations in the same chain. None of the three pharmacies responded to an interview request from Leaps.org.
In a practice called red flagging, pharmacists may label a prescription suspicious for a variety of reasons, such as if a pharmacist observes an unusually high dose, a long distance from the patient’s home to the pharmacy, or cash payment. Pharmacists may question patients or prescribers to resolve red flags but, regardless of the explanation, they’re free to refuse to fill a prescription.
As the risk of litigation has grown, so has finger-pointing, says Seth Whitelaw, a compliance consultant at Whitelaw Compliance Group in West Chester, PA, who advises drug, medical device, and biotech companies. Drugmakers accused in National Prescription Opioid Litigation (NPOL), a complex set of thousands of cases on opioid epidemic deaths, which includes the Ohio district case, have argued that they shouldn’t be responsible for the large supply of opiates and overdose deaths. Yet, prosecutors alleged that these pharmaceutical companies hid addiction and overdose risks when labeling opioids, while distributors and pharmacists failed to identify suspicious orders or scripts.
Patients and pharmacists fear red flags
The requirements that pharmacists document prescriptions they refuse to fill so far only apply to two counties in Ohio. But Brushwood fears they will spread because of this precedent, and because there’s no way for pharmacists to predict what new legislation is on the way. “There is no definition of a red flag, there are no lists of red flags. There is no instruction on what to do when a red flag is detected. There’s no guidance on how to document red flags. It is a standardless responsibility,” Brushwood says. This adds trepidation for pharmacists—and more hoops to jump through for patients.
“I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately,” Nicolson says.
“We now have about a dozen studies that show that actually ripping somebody off their medication increases their risk of overdose and suicide by three to five times, destabilizes their health and mental health, often requires some hospitalization or emergency care, and can cause heart attacks,” says Kate Nicolson, founder of the National Pain Advocacy Center based in Boulder, Colorado. “It can kill people.” Nicolson was in pain for decades due to a surgical injury to the nerves leading to her spinal cord before surgeries fixed the problem.
Another issue is that primary care offices may view opioid use as a reason to turn down new patients. In a 2021 study, secret shoppers called primary care clinics in nine states, identifying themselves as long-term opioid users. When callers said their opioids were discontinued because their former physician retired, as opposed to an unspecified reason, they were more likely to be offered an appointment. Even so, more than 40 percent were refused an appointment. The study authors say their findings suggest that some physicians may try to avoid treating people who use opioids.
Abayomi-Paul says red flagging has changed how she fills prescriptions. “Once I go to one place, I try to [continue] going to that same place because of the amount of records that I have and making sure my medications don’t conflict,” Abayomi-Paul says.
Nicolson moved to Colorado from Washington D.C. in 2015, before the CDC issued its 2016 guidelines. When the guidelines came out, she found the change to be shockingly abrupt. “I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately.’” Since then, she’s spoken with dozens of patients who have been red-flagged or simply haven’t been able to access pain medication.
Despite her expertise, Nicolson isn’t positive she could successfully fill an opioid prescription today even if she needed one. At this point, she’s not sure exactly what various pharmacies would view as a red flag. And she’s not confident that these red flags even work. “You can have very legitimate reasons for being 50 miles away or having to go to multiple pharmacies, given that there are drug shortages now, as well as someone refusing to fill [a prescription.] It doesn't mean that you’re necessarily ‘drug seeking.’”
While there’s no easy solution. Whitelaw says clarifying the role of pharmacists and physicians in patient access to opioids could help people get the medication they need. He is seeking policy changes that focus on the needs of people in pain more than the number of prescriptions filled. He also advocates standardizing the definition of red flags and procedures for resolving them. Still, there will never be a single policy that can be applied to all people, explains Brushwood, the University of Florida professor. “You have to make a decision about each individual prescription.”