“Time is the most precious commodity in Alzheimer’s research,” according to Junyue Cao, PhD. “Every year we wait is another year when millions of patients and families suffer.”
Dr. Cao is well-qualified to assess the scope of this problem—and what can be done about it. By the time he became the inaugural Fisher Center Foundation Associate Professor at The Rockefeller University, in 2024, he had received extensive training in biology, drug design, and technology development. He now heads the Laboratory of Single-Cell Genomics and Population Dynamics, where his team builds groundbreaking tools to map cell vulnerability across the brain with unprecedented precision.
This research is paving the way to an entirely new approach to neurodegenerative disease, revealing how different genetic risks converge across vulnerable cell types. In this conversation, Dr. Cao reflects on his journey to this exciting frontier, explains why making research faster and more open is at the core of his mission, and shares his hopes for how technology could revolutionize the landscape of Alzheimer’s treatment—and one day, lead to a cure.
IN SEARCH OF A TARGET
How did you first become interested in Alzheimer’s research?
I have always been fascinated by aging—the question of what happens to the body as we grow older. Alzheimer’s then entered the picture when my grandmother developed the disease. Watching her decline was very painful, and it made me realize how little we understood about what was happening inside her brain.
So, ever since I enrolled at Peking University for my undergraduate degree, my goal has been to get to the bottom of these two things. Age is the number one risk factor for Alzheimer’s disease, and I wanted to understand how aging-associated processes affect system functions, and how therapies could potentially remedy their effects.
My initial training was in computational chemistry and drug design. The idea was that once you have a therapeutic target, you can use computers to model the right drugs to treat it. But pretty soon I became aware of an obvious problem—in the case of Alzheimer’s disease, we often don’t know what the right target is in the first place.
So, the question became how to identify the best targets for therapy?
Yes, and it led me to specialize in a completely different field—biology—here in the U.S. I moved to the Jackson Laboratory in Bar Harbor, Maine, where I started investigating a cellular process called unfolded protein response (UPR), which is basically a quality control mechanism associated with the accumulation of protein damage and stress in the body.
That work gave me crucial background for my research, because protein damage and misfolding are strongly associated with aging and neurodegenerative diseases. Over time, however, I realized that this approach could not lead to scalable therapeutic innovation, because in complex diseases—like Alzheimer’s—you need to be able to look at what happens in many different cell types, rather than one at a time.
So, that made me think that the real bottleneck was not biology, after all—it was technology. We didn’t have the tools to see what was happening across the entire brain. That’s why I eventually decided to shift my focus toward neuroscience, with the goal of developing tools that could capture cellular changes associated with the disease at its earliest stages.
SOMETHING LIKE AN IPHONE CAMERA
How did you transition from biology to technology design?
After three years at the Jackson Lab I moved to Caltech for my PhD, and there I began working on large-scale imaging tools to study cellular dynamics. Over time, however, I found that basic imaging was quite limited for the purpose of measuring changes across multiple cell types. The brain is extraordinarily complex, with thousands of different cell populations working together. And traditional imaging tools only allow to scan brain tissue in bulk, blurring important details.
So I transferred to the University of Washington and joined the laboratory of Jay Shendure, PhD, who works at the intersection of biology and genomics. That’s where I started focusing on the development of single-cell sequencing, a new technology we helped pioneer, which made it possible to analyze the genetic information of thousands of individual cells at the same time. And that laid the groundwork for what we do today here at The Rockefeller University.
Can you tell us more about your current research?
In essence, my team and I develop technologies that take single-cell sequencing and single-cell screening to the next level—from being able to test thousands to millions of brain cells at the same time. You can think of these tools as something like an iPhone camera, but instead of faces they scan individual cells, profiling their gene expression, molecular changes, and specific patterns of vulnerability.
To give you an example, traditional spatial biology relies on microscopes and fluorescent probes to examine how cells and molecules are organized within tissues, a process that’s both slow and limited in scale. We have designed a new method, called IRIS, which uses DNA-barcoded beads to capture information about cells that are adjacent to one another, and then artificial intelligence to analyze their spatial disposition.
Would you describe this as a paradigm shift in how we are able to study the brain?
Absolutely! Think about it this way: There are a million people sitting around a table—these are the brain cells—and without being able to see them, you want to know where they all are. Traditional tools would allow you to scan the position of each person, one by one—imagine how long that would take. What IRIS allows you to do, instead, is ask everyone who their neighbors are, and then use that information to reconstruct where each person is relative to all the others.
Another technique we’ve created is called PerturbSci-Kinetics, which makes it possible to screen individual brain cells at unprecedented scale. Instead of scanning, this tool allows us to perturb thousands of individual cells at the same time. That way we can test which genes drive specific molecular changes associated with Alzheimer’s and other diseases, which could eventually point the way to new therapeutic targets.
UNDERSTANDING BRAIN VULNERABILITY
What have these tools revealed about Alzheimer’s disease so far?
Fundamentally, the technologies that we’re developing could help researchers achieve the goal I’ve been pursuing from the very beginning—identifying the best possible targets for effective Alzheimer’s treatment.
A good example of this is a study we published in Nature Genetics in 2023, which showed that different genetic mutations associated with Alzheimer’s tend to converge on the same types of brain cell. We compared mutations affecting neurons to mutations affecting glial cells in mice. And to our surprise, in both cases the downstream effect was an alteration of choroid plexus epithelial cells, a group of cells that help clear toxins and amyloid from the brain. That’s an exciting result, because it suggests that no matter how the disease begins, it follows the same developmental patterns—which in turn makes therapy design more practical, since you don’t need to come up with a different treatment for each genetic mutation.
In addition, we also found that similar cell-state changes occur in patients with COVID-related brain fog. This suggests that some pathways of brain dysfunction may be shared across very different conditions. We’re now exploring whether similar mechanisms might exist in other neurodegenerative disorders—and you can see where this goes: one step at a time, we are moving toward a more unified understanding of brain vulnerability as a whole.
What do you see as the most urgent next step for the field?
The ultimate goal, of course, is to make Alzheimer’s research less descriptive and more actionable. Over decades, we have acquired a very deep understanding of amyloid plaques, tau tangles, and symptoms associated with each stage of the disease. But all of that takes time. And time is the most precious commodity in Alzheimer’s research. Every year we wait is another year when millions of patients and families suffer.
Now we are beginning to identify precise targets, the way cancer research did with oncogenes. If we can do that, we could eventually start seeing Alzheimer’s therapies that don’t just slow decline but prevent or even reverse the disease. That’s what keeps me going—knowing that the tools my team and I build today could open the door to that future.
