Researchers Get Closer to Gene Editing Treatment for Cardiovascular Disease
Later this year, Verve Therapeutics of Cambridge, Ma., will initiate Phase 1 clinical trials to test VERVE-101, a new medication that, if successful, will employ gene editing to significantly reduce low-density lipoprotein cholesterol, or LDL.
LDL is sometimes referred to as the “bad” cholesterol because it collects in the walls of blood vessels, and high levels can increase chances of a heart attack, cardiovascular disease or stroke. There are approximately 600,000 heart attacks per year due to blood cholesterol damage in the United States, and heart disease is the number one cause of death in the world. According to the CDC, a 10 percent decrease in total blood cholesterol levels can reduce the incidence of heart disease by as much as 30 percent.
Verve’s Founder and CEO, Sekar Kathiresan, spent two decades studying the genetic basis for heart attacks while serving as a professor of medicine at Harvard Medical School. His research led to two critical insights.
“One is that there are some people that are naturally resistant to heart attack and have lifelong, low levels of LDL,” the cardiologist says. “Second, there are some genes that can be switched off that lead to very low LDL cholesterol, and individuals with those genes switched off are resistant to heart attacks.”
Kathiresan and his team formed a hypothesis in 2016 that if they could develop a medicine that mimics the natural protection that some people enjoy, then they might identify a powerful new way to treat and ultimately prevent heart attacks. They launched Verve in 2018 with the goal of creating a one-time therapy that would permanently lower LDL and eliminate heart attacks caused by high LDL.
"Imagine a future where somebody gets a one-time treatment at the time of their heart attack or before as a preventive measure," says Kathiresan.
The medication is targeted specifically for patients who have a genetic form of high cholesterol known as heterozygous familial hypercholesterolemia, or FH, caused by expression of a gene called PCSK9. Verve also plans to develop a program to silence a gene called ANGPTL3 for patients with FH and possibly those with or at risk of atherosclerotic cardiovascular disease.
FH causes cholesterol to be high from birth, reaching levels of 200 to 300 milligrams per deciliter. Suggested normal levels are around 100 to 129 mg/dl, and anything above 130 mg/dl is considered high. Patients with cardiovascular disease usually are asked to aim for under 70 mg/dl, but many still have unacceptably high LDL despite taking oral medications such as statins. They are more likely to have heart attacks in their 30s, 40s and 50s, and require lifelong LDL control.
The goal for drug treatments for high LDL, Kathiresan says, is to reduce LDL as low as possible for as long as possible. Physicians and researchers also know that a sizeable portion of these patients eventually start to lose their commitment to taking their statins and other LDL-controlling medications regularly.
“If you ask 100 patients one year after their heart attack what fraction are still taking their cholesterol-lowering medications, it’s less than half,” says Kathiresan. “So imagine a future where somebody gets a one-time treatment at the time of their heart attack or before as a preventive measure. It’s right in front of us, and it’s something that Verve is looking to do.”
In late 2020, Verve completed primate testing with monkeys that had genetically high cholesterol, using a one-time intravenous injection of VERVE-101. It reduced the monkeys’ LDL by 60 percent and, 18 months later, remains at that level. Kathiresan expects the LDL to stay low for the rest of their lives.
Verve’s gene editing medication is packaged in a lipid nanoparticle to serve as the delivery mechanism into the liver when infused intravenously. The drug is absorbed and makes its way into the nucleus of the liver cells.
Verve’s program targeting PCSK9 uses precise, single base, pair base editing, Kathiresan says, meaning it doesn't cut DNA like CRISPR gene editing systems do. Instead, it changes one base, or letter, in the genome to a different one without affecting the letters around it. Comparing it to a pencil and eraser, he explains that the medication erases out a letter A and makes it a letter G in the A, C, G and T code in DNA.
“We need to continue to advance our approach and tools to make sure that we have the absolute maximum ability to detect off-target effects,” says Euan Ashley, professor of medicine and genetics at Stanford University.
By making that simple change from A to G, the medication switches off the PCSK9 gene, automatically lowering LDL cholesterol.
“Once the DNA change is made, all the cells in the liver will have that single A to G change made,” Kathiresan says. “Then the liver cells divide and give rise to future liver cells, but every time the cell divides that change, the new G is carried forward.”
Additionally, Verve is pursuing its second gene editing program to eliminate ANGPTL3, a gene that raises both LDL and blood triglycerides. In 2010, Kathiresan's research team learned that people who had that gene completely switched off had LDL and triglyceride levels of about 20 and were very healthy with no heart attacks. The goal of Verve’s medication will be to switch off that gene, too, as an option for additional LDL or triglyceride lowering.
“Success with our first drug, VERVE-101, will give us more confidence to move forward with our second drug,” Kathiresan says. “And it opens up this general idea of making [genomic] spelling changes in the liver to treat other diseases.”
The approach is less ethically concerning than other gene editing technologies because it applies somatic editing that affects only the individual patient, whereas germline editing in the patient’s sperm or egg, or in an embryo, gets passed on to children. Additionally, gene editing therapies receive the same comprehensive amount of testing for side effects as any other medicine.
“We need to continue to advance our approach and tools to make sure that we have the absolute maximum ability to detect off-target effects,” says Euan Ashley, professor of medicine and genetics at Stanford University and founding director of its Center for Inherited Cardiovascular Disease. Ashley and his colleagues at Stanford’s Clinical Genomics Program and beyond are increasingly excited about the promise of gene editing.
“We can offer precision diagnostics, so increasingly we’re able to define the disease at a much deeper level using molecular tools and sequencing,” he continues. “We also have this immense power of reading the genome, but we’re really on the verge of taking advantage of the power that we now have to potentially correct some of the variants that we find on a genome that contribute to disease.”
He adds that while the gene editing medicines in development to correct genomes are ahead of the delivery mechanisms needed to get them into the body, particularly the heart and brain, he’s optimistic that those aren’t too far behind.
“It will probably take a few more years before those next generation tools start to get into clinical trials,” says Ashley, whose book, The Genome Odyssey, was published last year. “The medications might be the sexier part of the research, but if you can’t get it into the right place at the right time in the right dose and not get it to the places you don’t want it to go, then that tool is not of much use.”
Medical experts consider knocking out the PCSK9 gene in patients with the fairly common genetic disorder of familial hypercholesterolemia – roughly one in 250 people – a potentially safe approach to gene editing and an effective means of significantly lowering their LDL cholesterol.
Nurse Erin McGlennon has an Implantable Cardioverter Defibrillator and takes medications, but she is also hopeful that a gene editing medication will be developed in the near future.
Erin McGlennon
Mary McGowan, MD, chief medical officer for The Family Heart Foundation in Pasadena, CA, sees the tremendous potential for VERVE-101 and believes patients should be encouraged by the fact that this kind of research is occurring and how much Verve has accomplished in a relatively short time. However, she offers one caveat, since even a 60 percent reduction in LDL won’t completely eliminate the need to reduce the remaining amount of LDL.
“This technology is very exciting,” she said, “but we want to stress to our patients with familial hypercholesterolemia that we know from our published research that most people require several therapies to get their LDL down., whether that be in primary prevention less than 100 mg/dl or secondary prevention less than 70 mg/dl, So Verve’s medication would be an add-on therapy for most patients.”
Dr. Kathiresan concurs: “We expect our medicine to lower LDL cholesterol by about 60 percent and that our patients will be on background oral medications, including statins that lower LDL cholesterol.”
Several leading research centers are investigating gene editing treatments for other types of cardiovascular diseases. Elizabeth McNally, Elizabeth Ward Professor and Director at the Center for Genetic Medicine at Northwestern University’s Feinberg School of Medicine, pursues advanced genetic correction in neuromuscular diseases such as Duchenne muscular dystrophy and spinal muscular atrophy. A cardiologist, she and her colleagues know these diseases frequently have cardiac complications.
“Even though the field is driven by neuromuscular specialists, it’s the first therapies in patients with neuromuscular diseases that are also expected to make genetic corrections in the heart,” she says. “It’s almost like an afterthought that we’re potentially fixing the heart, too.”
Another limitation McGowan sees is that too many healthcare providers are not yet familiar with how to test patients to determine whether or not they carry genetic mutations that need to be corrected. “We need to get more genetic testing done,” she says. “For example, that’s the case with hypertrophic cardiomyopathy, where a lot of the people who probably carry that diagnosis and have never been genetically identified at a time when genetic testing has never been easier.”
One patient who has been diagnosed with hypertrophic cardiomyopathy also happens to be a nurse working in research at Genentech Pharmaceutical, now a member of the Roche Group, in South San Francisco. To treat the disease, Erin McGlennon, RN, has an Implantable Cardioverter Defibrillator and takes medications, but she is also hopeful that a gene editing medication will be developed in the near future.
“With my condition, the septum muscles are just growing thicker, so I’m on medicine to keep my heart from having dangerous rhythms,” says McGlennon of the disease that carries a low risk of sudden cardiac death. “So, the possibility of having a treatment option that can significantly improve my day-to-day functioning would be a major breakthrough.”
McGlennon has some control over cardiovascular destiny through at least one currently available technology: in vitro fertilization. She’s going through it to ensure that her children won't express the gene for hypertrophic cardiomyopathy.
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Podcast: Wellness chatbots and meditation pods with Deepak Chopra
Over the last few decades, perhaps no one has impacted healthy lifestyles more than Deepak Chopra. While several of his theories and recommendations have been criticized by prominent members of the scientific community, he has helped bring meditation, yoga and other practices for well-being into the mainstream in ways that benefit the health of vast numbers of people every day. His work has led many to accept new ways of thinking about alternative medicine, the power of mind over body, and the malleability of the aging process.
His impact is such that it's been observed our culture no longer recognizes him as a human being but as a pervasive symbol of new-agey personal health and spiritual growth. Last week, I had a chance to confirm that Chopra is, in fact, a human being – and deserving of his icon status – when I talked with him for the Leaps.org podcast. He relayed ideas that were wise and ancient, yet highly relevant to our world today, with the fluidity and ease of someone discussing the weather. Showing no signs of slowing down at age 76, he described his prolific work, including the publication of two books in the past year and a range of technologies he’s developing, including a meditation app, meditation pods for the workplace, and a chatbot for mental health called Piwi.
Take a listen and get inspired to do some meditation and deep thinking on the future of health. As Chopra told me, “If you don’t have time to meditate once per day, you probably need to meditate twice per day.”
Highlights:
2:10: Chopra talks about meditation broadly and meditation pods, including the ones made by OpenSeed for meditation in the workplace.
6:10: The drawbacks of quick fixes like drugs for mental health.
10:30: The benefits of group meditation versus individual meditation.
14:35: What is a "metahuman" and how to become one.
19:40: The difference between the conditioned mind and the mind that's infinitely creative.
22:48: How Chopra's views of free will differ from the views of many neuroscientists.
28:04: Thinking Fast and Slow, and the role of intuition.
31:20: Athletic and creative geniuses.
32:43: The nature of fundamental truth.
34:00: Meditation for kids.
37:12: Never alone.Love and how AI chatbots can support mental health.
42:30: Extending lifespan, gene editing and lifestyle.
46:05: Chopra's mentor in living a long good life (and my mentor).
47:45: The power of yoga.
Links:
- OpenSeed meditation pods for people to meditate at work (Chopra is an advisor to OpenSeed).
- Chopra's book from 2021, Metahuman: Unleash Your Infinite Potential
- Chopra's book from 2022, Abundance: The Inner Path to Wealth
- NeverAlone.Love, Chopra's collaboration of businesses, policy makers, mental health professionals and others to raise awareness about mental health, advance scientific research and "create a global technology platform to democratize access to resources."
- The Piwi chatbot for mental health
- The Chopra Meditation & Well-Being App for people of all ages
- Only 1.6 percent of U.S. children meditate, according to the National Center for Complementary and Integrative Health