New blood test aims to spot liver scarring when it’s still reversible and before it paves the way to cancer
A new blood test may detect a precursor to liver disease, which in turn may be a warning sign of cancer. The hope is that the test could help prevent liver cancer before it occurs.
The test uses a machine learning model for analyzing free-floating genetic material circulating in the blood. In the new study, researchers used it to detect pieces of DNA indicating early-stage liver scarring, or fibrosis. These early scars, if left untreated, can progress to severe liver scarring, called cirrhosis, and eventually cancer.
“The best way to intervene in liver cancer is not to detect liver cancer early, but to detect liver disease early,” Velculescu told Live Science.
Once detected, fibrosis can be reversed with antifibrotic medications, lifestyle changes and other treatments, he added. Cirrhosis, on the other hand, is largely irreversible.
Signs of illness written in the blood
Millions of Americans suffer from liver fibrosis but I don’t know. Risk factors for developing these scars include inflammation of the liver (hepatitis), diabetes, high blood pressure and obesity. When detected early, liver fibrosis is reversible.
But currently, traditional clinical assessments — such as the fibrosis-4 (FIB-4) blood test that uses age, liver enzymes and platelet counts to estimate levels of liver scarring — fail to detect liver disease at an early stage, Velculescu said.
We’re trying to detect changes that might occur in diseases that might occur across the genome.
Akshaya Annapragada, MD/PhD student at Johns Hopkins Kimmel Cancer Center.
In the new study, published March 4 in the journal Scientific translational medicineVelculescu and his colleagues first examined blood samples from 423 people with and without liver disease. By analyzing tens of millions of cell-free DNA fragments in blood, they discovered markers that could distinguish patients with early liver scarring from those without any degree of liver disease.
Also called free-floating DNA, cell-free DNA includes small snippets of genetic material that are released into the bloodstream when cells regenerate and die. Instead of looking for specific mutations or changes in DNA letters, the team used a computer model that looked for broader genome-wide patterns throughout the free-floating DNA released by cells.
“We are trying to detect changes that could occur in the context of a disease that can occur across the entire genome,” explains the first author of the study. Akshaya Annapragadaan MD/PhD student in Velculescu’s lab, told Live Science. “So you have more opportunities to find something.”
They identified several factors collectively linked to early liver disease. These included the length of DNA fragments and the frequency with which cells shed repetitive DNA sequences. They also spotted key epigenetic changes, or marks on the genome that alter gene activity without altering the underlying DNA code.
With these factors in hand, they developed a test to look for these patterns in the blood.
To then assess the effectiveness of the blood test, the team evaluated it in 221 other participants: 30 with early liver disease, 85 with advanced liver disease and 106 without liver disease. The test detected 50% of early cases of liver disease and about 78% of advanced cases.
It correctly identified people without disease 83 percent of the time, meaning it falsely reported liver disease 17 times out of 100.
By using machine learning to spot patterns across the entire genome, the new research allows the team to analyze billions of fragments at a time, said Alain-Thierryprofessor and research director at INSERM, who did not participate in the study.
This is an advantage over previous blood tests that looked only for specific mutations or disease markers and had to sequence the genome thousands of times to get enough DNA to interpret, Annapragada said. On the other hand, “this test only sequences the genome once or twice, so it is much cheaper and more effective”.
The next steps are larger clinical trials to validate machine learning models that can detect liver fibrosis, Velculescu said
Researchers said they hope tests like theirs will eventually pave the way for non-invasive methods of screening for many diseases from a single blood test, which would allow for earlier diagnosis and treatment of diseases before they become chronic and irreversible.
This article is for informational purposes only and is not intended to offer medical advice.
Akshaya V. Annapragada et al., Cell-free DNA fragmentomes for non-invasive detection of liver cirrhosis and other diseases. Scientific translational medicine.18, eadw2603 (2026). DOÏ:10.1126/scitranslmed.adw2603
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