Using Stem Cells to Predict Pediatric Liver Disease Before It Starts

What if we could identify a child’s risk for chronic liver disease years before they showed a single symptom?

Driven by the rise in obesity, metabolic dysfunction–associated steatotic liver disease (MASLD) now affects between 5-10% of children in the United States. While early-stage MASLD is often reversible with diet and lifestyle changes, it can lead to liver damage, heart disease, and diabetes if left undetected. However, current models can only identify the disease after it appears.

New research led by Marisa Medina, PhD, in the UCSF Division of Pediatric Cardiology, has found a route to predict who is likely to develop MASLD before the disease appears. By using patient-derived stem cells to model genetic predisposition, the team has developed a functional risk score that could revolutionize how we identify and protect at-risk children.

Stem Cells as a Genetic Mirror

To see how a child’s biology responds to their environment, the UCSF team turned to induced pluripotent stem cells (iPSCs). The study, published in Stem Cells Translational Medicine, demonstrates that these cells can serve as a powerful mirror for a patient's health.

Created from a patient’s own tissue, these stem cells carry the donor’s exact genetic "instruction manual." Traditionally, scientists believed these cells had to be painstakingly turned into liver cells to study liver disease.

The team’s discovery, however, found that undifferentiated stem cells are just as effective at revealing a patient’s genetic predisposition to store fat, which, when accumulated in the liver, causes MASLD.

“These stem cells can carry a child’s inherited biology and offer a scalable platform, making it feasible to screen large numbers of children and shift to prevention during childhood instead of reactive treatments later in life,” says Medina. “Using undifferentiated iPSCs represents a conceptual and practical shift in functional disease modeling.”

The "Fat Challenge": Defining the Risk Score

The research centered on a functional assessment: exposing these patient-derived cells to a special type of fat to assess their response. The team found that cells from patients with MASLD were genetically programmed to accumulate significantly higher levels of lipids than those from healthy controls.

Using data from three distinct cohorts, the researchers developed a MASLD risk score based solely on this cellular behavior. The findings demonstrate that this test can accurately distinguish between individuals with the disease and healthy controls, establishing these cellular patterns as a powerful predictor of future disease risk.

“Childhood is a uniquely powerful window for prevention,” says Medina. “While this is an early-stage study, the results are highly encouraging. With the most severe form of the disease, the test correctly identified 75% of affected individuals and did not misclassify any healthy controls. If we can identify high-risk children early, we have years — even decades — to intervene before irreversible damage occurs.”

A standard DNA test looks for known genetic variants, but we don’t yet know all the variants that influence MASLD. By measuring the cells' direct response to fat, the UCSF team can capture the combined impact of known and unknown genetic variation.

“For pediatricians, this could change how we monitor and counsel families,” Medina explains. “Instead of reacting to obesity or liver damage, we could proactively support children whose biology places them at higher risk.”

From Reactive Diagnosis to Proactive Prevention

For pediatricians, current MASLD models that only detect the disease after it appears means an uphill battle against a difficult-to-treat disease. The iPSC-based model offers a way to identify high-risk individuals, potentially years before clinical symptoms appear.

Identifying high-risk children early allows for:

• Targeted Surveillance: Justifying more frequent screenings for those with high risk.
• Personalized Intervention: Providing families with a clear, data-driven reason to prioritize intensive lifestyle changes — such as nutrition, exercise, and maintenance of healthy weight — which remain the first and most effective line of MASLD prevention.
• Preventive Excellence: Moving toward a future where we can estimate a child’s 5-to-10-year risk of liver dysfunction.

The Future of Personalized Liver Care

While the current model is a proof-of-concept, the team plans to expand the research to include larger, more diverse cohorts. By integrating this cellular risk assessment with other clinical data — such as obesity, diabetes, and cholesterol — this research opens the door to risk management strategies tailored to a child’s individual risk factors.

"Our goal is to identify high-risk children before the disease causes irreversible damage to their liver," Medina notes. At the UCSF Department of Pediatrics, this work is part of our mission to give every child the opportunity for a healthy, disease-free future.

Authors: Other authors from the UCSF Department of Pediatrics include: Yuanyuan Qin, PhD; Parth Chhetri; Elizabeth Theusch, PhD; Grace Lim; Sheila Teker; Yu-Lin Kuang, PhD; and Antonio Munoz-Howell.  

Funding: This work was supported by the California Institute for Regenerative Medicine, the National Institutes of Health (NIH) R01 DK130391, NIH R01 DK132129, and the Program for Breakthrough Biomedical Research, which is partially funded by the Sandler Foundation.