A Single Blood Test May Soon Replace Your Annual Physical
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
For all the excitement over "personalized medicine" in the last two decades, its promise has not fully come to pass. Consider your standard annual physical.
Scientists have measured thousands of proteins from a single blood test to assess many individualized health conditions at once.
Your doctor still does a blood test to check your cholesterol and gauge your risk for heart disease by considering traditional risk factors (like smoking, diabetes, blood pressure) — an evaluation that has not changed in decades.
But a high-risk number alone is not enough to tell accurately whether you will suffer from heart disease. It just reflects your risk compared to population-level averages. In other words, not every person with elevated "bad" cholesterol will have a heart attack, so how can doctors determine who truly needs to give up the cheeseburgers and who doesn't?
Now, an emerging area of research may unlock some real-time answers. For the first time, as reported in the journal Nature Medicine last week, scientists have measured thousands of proteins from a single blood test to assess many individualized health conditions at once, including liver and kidney function, diabetes risk, body fat, cardiopulmonary fitness, and even smoking and alcohol consumption. Proteins can give a clear snapshot of how your body is faring at any given moment, as well as a sneak preview at what diseases may be lurking under the surface.
"Years from now," says study co-author Peter Ganz of UCSF, "we will probably be looking back on this paper as a milestone in personalized medicine."
We spoke to Ganz about the significance of this milestone. Our interview has been edited and condensed.
Is this the first study of its kind?
Yes, it is. This is a study where we measured 5,000 proteins at once to look for patterns that could either predict the risk of future diseases or inform the current state of health. Previous to this, people have measured typically one protein at a time, and some of these individual proteins have made it into clinical practice.
An example would be a protein called C-reactive protein, which is a measure of inflammation and is used sometimes in cardiology to predict the risk of future heart attacks. But what's really new is this scale. We wanted to get away from just focusing on one problem that the patient may have at a time, whether it's heart disease or kidney disease, and by measuring a much greater number of proteins, the hope is that we could inform the health of ultimately just about every organ in the body or every tissue. It's a step forward for what I would call "a one-stop shop."
"I'm very excited about personalized medicine through proteins as opposed to genes because you get both the nature and nurture."
Three things get me excited about this. One is the convenience for the patient of a single test to determine many different diseases. The second thing is the healthcare cost savings. We estimated what the cost would be to get these 11 healthcare measures that we reported on using traditional testing and the cost was upwards of 3,000 British pounds. And even though I don't know for sure what the cost of the protein tests would ultimately be, [it could come down to about $50 to $100].
The last thing is that the measurement of proteins is part of what people have called personalized medicine or precision medicine. If you look at risk factors across the population, it may not apply to individuals. In contrast, proteins are downstream of risk factors. So proteins actually tell us whether the traditional risk factors have set in motion the necessary machinery to cause disease. Proteins are the worker bees that regulate what the human body does, and so if you can find some anomalies in the proteins, that may inform us if a disease is likely to be ongoing even in its earliest stages.
Does protein testing have advantages over genetic testing for predicting future health risks?
The problem with genomics is that genes usually don't take care of the environment. It's a blueprint, but your blueprint has no idea what you will be exposed to during your lifetime in terms of the environment and lifestyle that you may choose and medications that you may be on. These are things that proteins can account for. I'm very excited about personalized medicine through proteins as opposed to genes because you get both the nature and nurture as opposed to genomics, which only gives you nature but doesn't account for anything else.
Proteins can also be tracked over time and that's not something you can do with genes. So if your behavior improves, your genes won't change, but your proteins will.
Could this new test become a regular feature of your annual physical?
That's the idea. This would be basically almost a standalone test that you could have done every year. And hopefully you wouldn't need other tests to complement this. This could be your yearly physical.
How much more does it need to be validated before it can enter the clinic and patients can trust the results?
This was a proof-of concept study. To really make this useful, we need to expand from 11 measures of health to a hundred or more health insights, to cover the whole body. And we need to expand this to all racial groups. Three of the five centers in the study were European – all Caucasian – so it's one of our high priorities to find groups of patients with better representation of minorities.
When do you expect doctors to be routinely giving this test to patients?
Much closer to five years than 20 years. We're scaling up from 11 disease states to 100, and many of those studies are underway. Results should be done within three to five years.
Do you think insurance will cover it?
Good question. I have been approached by an insurance company that wanted to understand the product better – a major insurer, with the possibility that this could actually be cost saving.
I have to ask you a curveball -- do you think that the downfall of Theranos will make consumers hesitant to trust a new technology that relies on using a single blood sample to screen for multiple health risks?
[Laughs] You're not the first person to ask me that today. I actually got a call from Elizabeth Holmes [in 2008 when I was at Harvard]. I met with her for an afternoon and met her team two more times. I gave them advice that they completely disregarded.
In many ways, what we do is diametrically opposite to Theranos. They had a culture of secrecy, and what we do is about openness. We publish, like this paper in Nature Medicine, to show the scientific details. Our supplement is much longer than the typical academic paper. We reveal everything we know. A lot of the research we do is funded by [the National Institutes of Health], and they have strict expectations about data sharing. So we agree to make the data available on a public website. If there is something we haven't done with the data, others can do it.
So you're saying that this is not another Theranos.
No, God forbid. We hope to be the opposite.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
A new injection is helping stave off RSV this season
In November 2021, Mickayla Wininger’s then one-month-old son, Malcolm, endured a terrifying bout with RSV, the respiratory syncytial (sin-SISH-uhl) virus—a common ailment that affects all age groups. Most people recover from mild, cold-like symptoms in a week or two, but RSV can be life-threatening in others, particularly infants.
Wininger, who lives in southern Illinois, was dressing Malcolm for bed when she noticed what seemed to be a minor irregularity with this breathing. She and her fiancé, Gavin McCullough, planned to take him to the hospital the next day. The matter became urgent when, in the morning, the boy’s breathing appeared to have stopped.
After they dialed 911, Malcolm started breathing again, but he ended up being hospitalized three times for RSV and defects in his heart. Eventually, he recovered fully from RSV, but “it was our worst nightmare coming to life,” Wininger recalled.
It’s a scenario that the federal government is taking steps to prevent. In July, the Food and Drug Administration approved a single-dose, long-acting injection to protect babies and toddlers. The injection, called Beyfortus, or nirsevimab, became available this October. It reduces the incidence of RSV in pre-term babies and other infants for their first RSV season. Children at highest risk for severe RSV are those who were born prematurely and have either chronic lung disease of prematurity or congenital heart disease. In those cases, RSV can progress to lower respiratory tract diseases such as pneumonia and bronchiolitis, or swelling of the lung’s small airway passages.
Each year, RSV is responsible for 2.1 million outpatient visits among children younger than five-years-old, 58,000 to 80,000 hospitalizations in this age group, and between 100 and 300 deaths, according to the Centers for Disease Control and Prevention. Transmitted through close contact with an infected person, the virus circulates on a seasonal basis in most regions of the country, typically emerging in the fall and peaking in the winter.
In August, however, the CDC issued a health advisory on a late-summer surge in severe cases of RSV among young children in Florida and Georgia. The agency predicts "increased RSV activity spreading north and west over the following two to three months.”
Infants are generally more susceptible to RSV than older people because their airways are very small, and their mechanisms to clear these passages are underdeveloped. RSV also causes mucus production and inflammation, which is more of a problem when the airway is smaller, said Jennifer Duchon, an associate professor of newborn medicine and pediatrics in the Icahn School of Medicine at Mount Sinai in New York.
In 2021 and 2022, RSV cases spiked, sending many to emergency departments. “RSV can cause serious disease in infants and some children and results in a large number of emergency department and physician office visits each year,” John Farley, director of the Office of Infectious Diseases in the FDA’s Center for Drug Evaluation and Research, said in a news release announcing the approval of the RSV drug. The decision “addresses the great need for products to help reduce the impact of RSV disease on children, families and the health care system.”
Sean O’Leary, chair of the committee on infectious diseases for the American Academy of Pediatrics, says that “we’ve never had a product like this for routine use in children, so this is very exciting news.” It is recommended for all kids under eight months old for their first RSV season. “I would encourage nirsevimab for all eligible children when it becomes available,” O’Leary said.
For those children at elevated risk of severe RSV and between the ages of 8 and 19 months, the CDC recommends one dose in their second RSV season.
The drug will be “really helpful to keep babies healthy and out of the hospital,” said O’Leary, a professor of pediatrics at the University of Colorado Anschutz Medical Campus/Children’s Hospital Colorado in Denver.
An antiviral drug called Synagis (palivizumab) has been an option to prevent serious RSV illness in high-risk infants since it was approved by the FDA in 1998. The injection must be given monthly during RSV season. However, its use is limited to “certain children considered at high risk for complications, does not help cure or treat children already suffering from serious RSV disease, and cannot prevent RSV infection,” according to the National Foundation for Infectious Diseases.
Until the approval this summer of the new monoclonal antibody, nirsevimab, there wasn’t a reliable method to prevent infection in most healthy infants.
Both nirsevimab and palivizumab are monoclonal antibodies that act against RSV. Monoclonal antibodies are lab-made proteins that mimic the immune system’s ability to fight off harmful pathogens such as viruses. A single intramuscular injection of nirsevimab preceding or during RSV season may provide protection.
The strategy with the new monoclonal antibody is “to extend protection to healthy infants who nonetheless are at risk because of their age, as well as infants with additional medical risk factors,” said Philippa Gordon, a pediatrician and infectious disease specialist in Brooklyn, New York, and medical adviser to Park Slope Parents, an online community support group.
No specific preventive measure is needed for older and healthier kids because they will develop active immunity, which is more durable. Meanwhile, older adults, who are also vulnerable to RSV, can receive one of two new vaccines. So can pregnant women, who pass on immunity to the fetus, Gordon said.
Until the approval this summer of the new monoclonal antibody, nirsevimab, there wasn’t a reliable method to prevent infection in most healthy infants, “nor is there any treatment other than giving oxygen or supportive care,” said Stanley Spinner, chief medical officer and vice president of Texas Children’s Pediatrics and Texas Children’s Urgent Care.
As with any virus, washing hands frequently and keeping infants and children away from sick people are the best defenses, Duchon said. This approach isn’t foolproof because viruses can run rampant in daycare centers, schools and parents’ workplaces, she added.
Mickayla Wininger, Malcolm’s mother, insists that family and friends wear masks, wash their hands and use hand sanitizer when they’re around her daughter and two sons. She doesn’t allow them to kiss or touch the children. Some people take it personally, but she would rather be safe than sorry.
Wininger recalls the severe anxiety caused by Malcolm's ordeal with RSV. After returning with her infant from his hospital stays, she was terrified to go to sleep. “My fiancé and I would trade shifts, so that someone was watching over our son 24 hours a day,” she said. “I was doing a night shift, so I would take caffeine pills to try and keep myself awake and would end up crashing early hours in the morning and wake up frantically thinking something happened to my son.”
Two years later, her anxiety has become more manageable, and Malcolm is doing well. “He is thriving now,” Wininger said. He recently had his second birthday and "is just the spunkiest boy you will ever meet. He looked death straight in the eyes and fought to be here today.”
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.