Next year, a neurologist will test CRISPR base editing in a trial of five people with muscular dystrophy to see if their muscles accept corrected cells and whether they multiply and take over the function of damaged cells.
When Martin Weber climbs the steps to his apartment on the fifth floor in Munich, an attentive observer might notice that he walks a little unevenly. “That’s because my calf muscles were the first to lose strength,” Weber explains.
About three years ago, the now 19-year-old university student realized that he suddenly had trouble keeping up with his track team at school. At tennis tournaments, he seemed to lose stamina after the first hour. “But it was still within the norm,” he says. “So it took a while before I noticed something was seriously wrong.” A blood test showed highly elevated liver markers. His parents feared he had liver cancer until a week-long hospital visit and scores of tests led to a diagnosis: hereditary limb-girdle muscular dystrophy, an incurable genetic illness that causes muscles to deteriorate.
As you read this text, you will surely use several muscles without being aware of them: Your heart muscle pumps blood through your arteries, your eye muscles let you follow the words in this sentence, and your hand muscles hold the tablet or cell phone. Muscles make up 40 percent of your body weight; we usually have 656 of them. Now imagine they are slowly losing their strength. No training, no protein shake can rebuild their function.
This is the reality for most people in Simone Spuler’s outpatient clinic at the Charité Hospital in Berlin, Germany: Almost all of her 2,500 patients have muscular dystrophy, a progressive illness striking mostly young people. Muscle decline leads to a wheelchair and, eventually, an early death due to a heart attack or the inability to breathe. In Germany alone, 300,000 people live with this illness, the youngest barely a year old. The CDC estimates that its most common form, Duchenne, affects 1 in every 3,500 to 6,000 male births each year in the United States.
The devastating progression of the disease is what motivates Spuler and her team of 25 scientists to find a cure. In 2019, they made a spectacular breakthrough: For the first time, they successfully used mRNA to introduce the CRISPR-Cas9 tool into human muscle stem cells to repair the dystrophy. “It’s really just one tiny molecule that doesn’t work properly,” Spuler explains.
CRISPR-Cas9 is a technology that lets scientists select and alter parts of the genome. It’s still comparatively new but has advanced quickly since its discovery in the early 2010s. “We now have the possibility to repair certain mutations with genetic editing,” Spuler says. “It’s pure magic.”
She projects a warm, motherly air and a professional calm that inspires trust from her patients. She needs these qualities because the 60-year-old neurologist has one of the toughest jobs in the world: All day long, patients with the incurable diagnosis of muscular dystrophy come to her clinic, and she watches them decline over the years. “Apart from physiotherapy, there is nothing we can recommend right now,” she says. That motivated her early in her career, when she met her first patients at the Max Planck Institute for Neurobiology near Munich in the 1990s. “I knew I had 30, 40 years to find something.”
She learned from the luminaries of her profession with postdocs at the University of California San Diego, Harvard and Johns Hopkins, before serving as a clinical fellow at the Mayo Clinic. In 2005, the Charité offered her the opportunity to establish a specialized clinic for myasthenia, or muscular weakness. An important influence on Spuler, she says, has been the French microbiologist Emmanuelle Charpentier, who received the Nobel Prize in 2020 along with Jennifer Doudna for their CRISPR research, and has worked in Berlin since 2015.
When CRISPR was first introduced, it was mainly used to cut through DNA. However, the cut can lead to undesired side effects. For the muscle stem cells, Spuler now uses a base editor to repair the damaged molecule with super fine scissors or tweezers.
“Apart from physiotherapy, there is nothing we can recommend right now,” Spuler says about her patients with limb-girdle muscular dystrophy.
Pablo Castagnola
Last year, she proved that the method works in mice. Injecting repaired cells into the rodents led to new muscle fibers and, in 2021 and 2022, she passed the first safety meetings with the Paul-Ehrlich Institute, which is responsible for approving human gene editing trials in Germany. She raised the nearly four million Euros needed to test the new method in the first clinical trial in humans with limb-girdle muscular dystrophy, beginning with one muscle that can easily be measured, such as the biceps.
This spring, Weber and his parents drove the 400 miles from Munich to Berlin. At Spuler’s lab, her team took a biopsy from muscles in his left arm. The first two steps – extraction and repair in a culture dish – went according to plan; Spuler was able to repair the mutation in Weber’s cells outside his body.
Next year, Weber will be the youngest participant when Spuler starts to test the method in a trial of five people “in vivo,” inside their bodies. This will be the real moment of truth: Will the participants’ muscles accept the corrected cells? Will the cells multiply and take over the function of damaged cells, just like Spuler was able to do in her lab with the rodents?
The effort is costly and complex. “The biggest challenge is to make absolutely sure that we don’t harm the patient,” Spuler says. This means scanning their entire genomes, “so we don’t accidentally damage or knock out an important gene.”
Weber, who asked not to be identified by his real name, is looking forward to the trial and he feels confident that “the risks are comparatively small because the method will only be applied to one muscle. The worst that can happen is that it doesn’t work. But in the best case, the muscle function will improve.”
He was so impressed with the Charité scientists that he decided to study biology at his university. He’s read extensively about CRISPR, so he understands why he has three healthy siblings. “That’s the statistics,” the biologist in training explains. “You get two sets of genes from each parent, and you have to get two faulty mutations to have muscular dystrophy. So we fit the statistics exactly: One of us four kids inherited the mutation.”
It was his mother, a college teacher, and father, a physicist by training, who heard about Spuler’s research. Even though Weber does not live at home anymore, having a chronically ill son is nearly a full-time job for his mother, Annette. The Berlin visit and the trial are financed separately through private sponsors, but the fights with Weber’s health insurance are frustrating and time-consuming. “Physiotherapy is the only thing that helps a bit,” Weber says, “and yet, they fought us on approving it every step of the way.”
Spuler does not want to evoke unrealistic expectations. “Patients who are wheelchair-bound won’t suddenly get up and walk."
Her son continues to exercise as much as possible. Riding his bicycle to the university has become too difficult, so he got an e-scooter. He had to give up competitive tennis because he does not have the stamina for a two-hour match, but he can still play with his dad or his buddies for an hour. His closest friends know about the diagnosis. “They help me, for instance, to lift something heavy because I can’t do that anymore,” Weber says.
The family was elated to find medical support at the Munich Muscle Center by the German Alliance for Muscular Patients and then at Spuler’s clinic in Berlin. “When you hear that this is a progressive illness with no chance of improvement, your world collapses as a parent,” Annette Weber says. “And then all of a sudden, there is this woman who sees scientific progress as an opportunity. Even just to be able to participate in the study is fantastic.”
Spuler does not want to evoke unrealistic expectations. “Patients who are wheelchair-bound won’t suddenly get up and walk,” she says. After all, she will start by applying the gene editor to only one muscle, “but it would be a big step if even a small muscle that is essential to grip something, or to swallow, regains function.”
Weber agrees. “I understand that I won’t regain 100 percent of my muscle function but even a small improvement or at least halting the deterioration is the goal.”
And yet, Spuler and others are ultimately searching for a true solution. In a separate effort, Massachusetts-based biotech company Sarepta announced this month it will seek expedited regulators’ approval to treat Duchenne patients with its investigational gene therapy. Unlike Spuler’s methods, Sarepta focuses specifically on the Duchenne form of muscular dystrophy, and it uses an adeno-assisted virus to deliver the therapy.
Spuler’s vision is to eventually apply gene editing to the entire body of her patients. To speed up the research, she and a colleague founded a private research company, Myopax. If she is able to prove that the body accepts the edited cells, the technique could be used for other monogenetic illnesses as well. “When we speak of genetic editing, many are scared and say, oh no, this is God’s work,” says Spuler. But she sees herself as a mechanic, not a divine being. “We really just exchange a molecule, that’s it.”
If everything goes well, Weber hopes that ten years from now, he will be the one taking biopsies from the next generation of patients and repairing their genes.
Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
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.”
