UC scientists map key protein interactions linked with profound autism

Scientists have now gotten closer to understanding how gene mutations may lead some people to develop profound autism.

The clues, they say, lie in the murky space between genes and disease — where key proteins come together and interact.

A team of researchers from UC San Francisco mapped more than a thousand interactions between many proteins that come from certain autism risk genes. This molecular atlas, published in the journal Science, could point researchers toward new and promising treatments.

"It's an unprecedented resource for the field," says Dr. Daniel Geschwind, a professor of human genetics, neurology, and psychiatry at UCLA who was not involved with the study. "A lot of people interested in understanding autism and drug development are going to be using this."

For families affected by profound autism, it offers hope for eventual drug therapies. "This is the kind of scientific advance we have been waiting for and praying for," says Alison Singer, president of the nonprofit Autism Science Foundation, who has a daughter with severe cognitive impairment. "There's still a lot of work ahead, [but] this paper makes the path from genetic discovery to treatment much clearer."

The work builds on progress made in recent years to identify single genes that harbor mutations found in a subset of individuals with profound autism.

Getting past the "wall"

People with profound autism often live with severe intellectual disability and require around-the-clock care. They're nonverbal or minimally verbal, and often have serious medical conditions like epilepsy.

Pinning down the biology behind profound autism has always been a complicated endeavor — while both genes and environmental factors play a role, those factors can vary widely from person to person.

In the past decade or so, some genetics researchers have had remarkable success in identifying high-impact genetic differences in a subset of people with profound autism.

"They've discovered several hundred genes and corresponding mutations that are prevalent in [these] individuals," says Nevan Krogan, director of the Quantitative Biosciences Institute at UC San Francisco.

"But they kind of hit a wall," he added — because scientists haven't been able to turn those gene discoveries into many promising drugs and treatments.

"There was this huge missing piece," says Dr. Matthew State, a clinical psychiatrist and geneticist at UCSF: The genes serve as blueprints for making proteins that drive brain development, but researchers lacked visibility into how those proteins do the work.

State has been a pioneer in identifying high-risk genes, and the mutations in those genes, that are associated with profound autism. Krogan has been at the forefront of using new technology to look into protein interactions.

More than a decade ago, the two researchers were introduced by their mutual boss, the chancellor at UCSF, who encouraged them to collaborate. "[State] had the genes and the mutations. I had the technologies to look at the corresponding proteins," Krogan says.

They focused on filling a knowledge gap. "What we've been missing is the mechanistic understanding of how these mutations [on the genes] are seemingly resulting in autism," Krogan says. "In order to understand that, you need to go to the proteins."

Proteins are the complex molecules that come together to build the body, based on instructions encoded in the genes. "What makes an eye cell an eye cell, and a muscle a muscle, are the proteins and how they work together," State says. "They are the machinery of life."

In this case, the researchers wanted to find the molecular machinery of profound autism — to understand which proteins came from those high-risk autism genes, and how those proteins worked together.

The research was slow at first, but more recent advances in technology — including artificial intelligence — have sped things up.

To start, the researchers went on a "fishing expedition" for protein interactions. They chose 100 proteins from these high-risk autism genes, injected them into lab-grown cells, and then pulled them out, along with the additional proteins that attached to them.

Then, they used an AI system called AlphaFold, developed by Google DeepMind, to help determine which proteins in the clumps were directly touching. "Where AI is playing an important role is being predictive about who's talking to who," says Krogan. "Sometimes they take years to figure out. Now, we can get these insights in an hour." While imperfect, the system has worked well enough to save significant time and money, Krogan says.

Then, they wanted to see what happened to the proteins when the genes got tweaked. They introduced mutations that appear in patients with profound autism, and assessed what changed. "We broke the proteins in the way that they're broken in autism," says State. "That allows us ultimately to answer the question of, when they're going wrong in autism, how are they going wrong?"

They conducted this research in frogs and in organoids, which are lab-grown tissues that model the human brain. In one example, the mutations weakened the connection between two proteins related to which genes turn on and off in a cell. Then, one went rogue, turning on other genes that led to neurodevelopmental defects in organoids.

Molecular convergence

There are hundreds of rare, high-risk autism genes, acting in more than a thousand different ways.

But in mapping more than 1,800 protein interactions, the researchers found that many of them moved along shared biological pathways — particularly those related to early brain development, such as how synapses get constructed, and which neurons develop and when.

The convergence found in this study aligns with other recent publications, adding to an emerging understanding in the field, says Dr. Geschwind of UCLA.

"If we look at multiple mutations and they converge on the same process, that's strong evidence that you're dealing with the things that you want to treat," State says.

Identifying this more limited set of protein complexes that likely contribute to the development of profound autism could change the approach to treatments, says Singer with the Autism Science Foundation. "We've been working gene-by-gene to correct mutations," she says.

And if future drugs could target these shared protein pathways, she adds, "we may not need that separate therapeutic strategy for every autism gene."

Setting sights on new drug-development targets

It takes years to go from a biological discovery like this to an approved drug that treats humans. The findings would need to be translated into drug candidates, then tested for safety and effectiveness.

"It takes time and a lot of persistence and focus," State says. "This [paper] is unlikely to lead to therapies tomorrow — but it lays an important foundation for them."

Most human drugs are made to target proteins, Geschwind at UCLA says, so the newly published map of protein interactions offers an accessible entry point for pharmaceutical development.

And researchers hope to combine recent technological advances in ways that accelerate that progress even more. "When you put together the ability to borrow from successes in other fields [such as cancer treatments], and the development of AI, we're at an inflection point that will hopefully shorten the time cycle," State says.

Last week, Krogan's Quantitative Biosciences Institute received a $46 million grant from the Aligning Research to Impact Autism initiative, funded by philanthropist and Google co-founder Sergey Brin. The researchers are already working on next steps.

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