老化は故障ではなくプログラムかもしれない

Home Why Aging May Be a Program, Not a Breakdown Comment Save Article Read Later Share Facebook Copied! Copy link Email Pocket Reddit Ycombinator Comment Comments Save Article Read Later Read Later Q&A Why Aging May Be a Program, Not a Breakdown By Ingrid Wickelgren August 14, 2026 By deciphering the molecular signatures of millions of mouse cells, Junyue Cao has found that aging is not haphazard wear and tear but rather a “remodeling of the cell society.” Comment Save Article Read Later Junyue Cao, a cell biologist at Rockefeller University in New York City, analyzed gene expression in millions of mouse cells from different life stages. He was surprised to find that “changes in aging are not universal across all the cells,” he said. Karen Dias for Quanta Magazine Introduction In some ways, we know aging when we see it, from the graying of hair to the wrinkling of skin to declines in motor, sensory, and cognitive capacities. Yet the underlying biology of aging remains a matter of uncertainty and debate. Many lines of research align with the theory that aging is a direct result of decay — the inevitable degradation of molecules (including proteins or DNA), organelles, cells, or whole organs — from external assault or inexorable breakdown. When the body’s repair mechanisms fail to keep pace with these changes, like a factory with deteriorating equipment and too few mechanics, it manifests as the known signs of aging and, eventually, death. The idea makes a lot of sense, but according to the cell biologist Junyue Cao, it’s inaccurate. Far from a random but linear process of wear and tear, he argues, aging is a stepwise, programmed, orderly affair. “The destruction of the system is programmed at a very early stage,” said Cao, who heads the Laboratory of Single-Cell Genomics and Population Dynamics at Rockefeller University. Using technology that offers a systemwide view of the aging process in mice, Cao has outlined discrete stages of aging, akin to those of embryonic development, that are defined by changes in molecular signals and specific cell populations. In humans, the process likely begins before age 30. Cao’s interest in aging began in high school in Hebei, China, when he became acutely aware that his grandparents and parents were not going to live forever. While many teenagers awakening to mortality might turn to poetry or self-destructive behavior, Cao turned to science. Finding a way to slow aging became his lifelong goal, and it’s why he chose biology as his major at Peking University in Beijing. Initially, Cao assumed that the deterioration of particular proteins and protein networks was responsible for aging, in line with the prevailing model. But then after college, when he was working in a lab trying to identify those proteins, he realized that a daunting number of them were associated with aging, and that their effects depended on the type of cell in which they were operating. It was a picture both more complex and more organized than he had thought. Cao decided he needed data — lots of it — on thousands of molecular changes across hundreds of cell types. As a graduate student, he developed a high-throughput technology that could quantify these dynamics in embryonic development. When he started his own lab at Rockefeller in 2020, he put this technology to work on aging. In graduate school, Cao developed tools to identify changes in gene expression during embryonic development in mice. Now his lab applies these tools across an animal’s entire lifespan. Karen Dias for Quanta Magazine In one series of experiments, Cao and his team processed 21 million cells, sampled from 14 tissues or organs in about 50 male and female mice at five life stages, and built a data set of gene expression for each cell. “It’s extremely large-scale data,” Cao said. “You know which organ it’s from and which age it’s from, and you also know extensive molecular information.” Each stage was marked by a dramatic decline in or expansion of specific cell types. Two of his landmark papers, published in 2025 and 2026 in Science, point to a radical redistribution of the cells that make up the body as mammals age, and describe some of the epigenomic instructions that guide this process. “There are molecular changes and maybe some other changes in aging,” Cao said, “but they all converge in the remodeling of the cell society.” Quanta spoke with Cao about evidence for the programmed theory of aging, what happens at each stage, and why aging mammals are like trees shedding leaves. The interview has been condensed and edited for clarity. You began studying aging as a college student. How has your approach to the topic evolved? Back in college, I thought the problem of aging that needed solving was the lack of a drug. I thought that we were going to develop some magic drug or chemical that we could use to increase the lifespan of animals. So I joined a lab working on computational drug design, trying to design peptides that target molecules related to aging. But the major challenge was that we didn’t know what molecules to target. Cao’s analysis required enormous volumes of data: tens of thousands of gene expression changes across 21 million cells, sampled from 14 tissues or organs in about 50 male and female mice at five life stages. Karen Dias for Quanta Magazine After I graduated, I moved to the U.S. and worked at the Jackson Laboratory [a Maine-based biomedical research nonprofit] as a research assistant studying molecular pathways associated with aging in mice. I thought that by studying pathways, we could identify a [drug] target and, from there, develop drugs to increase lifespan. But after a few years, I learned that aging cannot be explained by a single pathway or target. It involves many different pathways, and these pathways have very different effects on different cell types in the body. I wanted to understand how aging progresses on a molecular level across hundreds to thousands of cell types in different organs. How did you do that? A major challenge is that aging involves changes across many different levels — molecules, organelles, cells, organs, and the whole body. To measure changes at all these levels, we needed technology that was both high throughput, which means you can use it to scan not just one cell or cell type but millions of cells across an entire organism, and high resolution, so you can see very detailed changes at the cellular and molecular levels. I applied to graduate school, where I developed tools that could scan the entire mammalian organism, from the brain to the kidneys to the lungs, while detailing tens of thousands of gene expression changes within single cells across hundreds of different cell types. When I got to Rockefeller, we used this technology to understand the dynamics of the whole system in aging. During distinct time windows as an animal ages, different cell types undergo distinct dynamics, according to Cao’s lab’s experiments. Some expand, some decline, and others remain stable. Karen Dias for Quanta Magazine Can you describe those experiments and what you learned from them? In one set of studies, we extracted more than 20 million cells from various organs from mice of different ages: 3, 6, 12, 16, and 23 months — roughly equivalent to 20, 30, 50, 60, and 75 years in humans. We analyzed the expression of 20,000 genes per cell and used this information to define the cell types. Then we tracked their population dynamics. We found that not every cell type gets changed in aging. We identified 536 main cell types and 1,828 subtypes. Only about one-quarter of these subtypes show a strong shift in aging. Others remain stable across the lifespan. It is surprising to find that changes in aging are not universal across all the cells, that there are specific cell populations that are more vulnerable. When do these population changes occur? We found that aging can be separated into distinct time windows. In each window, specific groups of