Today's biomedical researchers are relentlessly searching for genes that drive disease, with the goal of creating therapies that target those genes to restore health.
When a single gene is the culprit, the approach can be rather straightforward. But for the majority of diseases, in which multiple genes—sometimes thousands of them—are implicated, the task of pinpointing the connections becomes far more difficult.
But a new genomic mapping technique may change that. In a study published in Nature, researchers from Gladstone Institutes and Stanford University leveraged a comprehensive method of probing every gene in a cell to connect diseases and other traits with their underlying genetic machinery. These maps could clarify confusing biology and pinpoint disease-causing genes that are ripe for intervention.
"We can now look across every gene in the genome and get a sense of how each one affects a particular cell type," says Gladstone Senior Investigator Alex Marson, MD, PhD, the Connie and Bob Lurie Director of the Gladstone-UCSF Institute of Genomic Immunology, who co-led the study. "Our goal is to use this information as a map to gain new insights into how certain genes influence specific traits."
Finding the 'Why'
For decades, researchers have leaned on "genome-wide association studies," which analyze genomes from thousands of people to statistically link DNA anomalies with diseases and other traits. These projects have provided a wealth of data, but the information isn't always actionable—particularly when it comes to complex traits that are rooted in many genes.
"Even with these studies, there remains a huge gap in understanding disease biology on a genetic level," says first author Mineto Ota, MD, PhD. Ota is a postdoctoral scholar in Marson's Gladstone lab, as well as in the lab of Stanford scientist Jonathan Pritchard, PhD. "We understand that many variants are associated with disease; we just don't understand why."
In some ways, it's like having a map that shows a starting point and a destination but none of the roads in between, Mineto says.
"To understand complex traits, we really need to focus on the network," says Pritchard, a professor of Biology and Genetics at Stanford, who co-led the study with Marson. "How do we think about biology when thousands and thousands of genes, with many different functions, are all affecting a trait?"
To answer that question, the team queried two separate databases.
The first was derived from a human leukemia cell line often used to model red blood cell traits. An MIT researcher with no role in the current study had previously disabled every gene in the cell line, one by one, mapping how each loss affected genetic activity.
Marson and his team combined those findings with data from the UK Biobank, which contains genomic sequences of more than 500,000 people. Ota mined the data for people who had genetic mutations that reduced function in a way that altered their red blood cells.
By combining these datasets, the team was able to comprehensively map the gene networks that affect red blood cell traits, illuminating an incredibly complex genomic landscape. Now they had a starting point, a destination, and the web of roads in between.
They found that some genes act on multiple mechanisms, diminishing some biological activities while boosting others. A good example is SUPT5H, a gene linked to beta thalassemia, a blood disorder that affects hemoglobin production and can cause moderate to severe anemia. The researchers linked SUPT5H to three essential blood-cells programs: hemoglobin production, cell cycle, and autophagy. Importantly, they also highlighted how the gene affects those programs—by either boosting or minimizing gene activity.
"SUPT5H regulates all three main pathways that affect hemoglobin," Pritchard says. "It activates hemoglobin synthesis, slows down the cell cycle, and slows down autophagy, which together have a synergistic effect."
Applications for Immunology
The ability to reveal the detailed genetic mechanisms that control cells could have a profound impact on biological discovery and drug development.
While the study uncovered a number of ways gene networks influence blood cell function, those findings are secondary to the method itself. The research team—and possibly many others in the life science community—can now conduct similar research in a variety of human cells to tease out the molecular signatures that drive disease.
For the Marson lab, which seeks to better understand T cells and other immune mechanisms, this new method could be the wish that grants more wishes.
"The genetic burden associated with many autoimmune diseases, immune deficiencies, and allergies are overwhelmingly linked to T cells," Marson says. "We look forward to developing additional detailed maps that will help us really understand the genetic architecture behind these immune-mediated diseases."
About the Study
The study, "Causal modeling of gene effects from regulators to programs to traits," appears in the December 10, 2025 issue of Nature. Authors include: Mineto Ota, Jeffrey Spence, Tony Zeng, Emma Dann, Nikhil Milind, Alexander Marson, and Jonathan Pritchard. This research was funded by the National Institutes of Health, the Simons Foundation, the Lloyd J. Old STAR Award, the Parker Institute for Cancer Immunotherapy, the Innovative Genomics Institute, the Larry L. Hillblom Foundation, the Northern California JDRF Center of Excellence, the Byers family, K. Jordan, the CRISPR Cures for Cancer Initiative, the Astellas Foundation for Research on Metabolic Disorders, the Chugai Foundation for Innovative Drug Discovery Science, and the EMBO Postdoctoral Fellowship.
About Gladstone Institutes
Gladstone Institutes is an independent, nonprofit life science research organization that uses visionary science and technology to overcome disease. Established in 1979, it is located in the epicenter of biomedical and technological innovation, in the Mission Bay neighborhood of San Francisco. Gladstone has created a research model that disrupts how science is done, funds big ideas, and attracts the brightest minds.
