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Your Environment. Your Health.

Stool Microbiome Unlocks Advances in Diagnosing Liver Disease

Rohit Loomba, M.D.
University of California, San Diego

NIEHS grantees and collaborators developed a rapid, low-cost tool to accurately diagnose liver fibrosis and cirrhosis. The noninvasive method uses stool samples to characterize the gut microbiome, or the bacteria that live in gut, which has been linked to liver health. The method could lead to improved patient care and treatment outcomes for liver disease.

Fibrosis, or the formation of scar tissue in the liver, can be reversed if diagnosed early. Long-term, repeated scarring can lead to cirrhosis and permanent liver damage. Researchers studied stool samples from 163 patients with liver disease and their healthy family members. Using metabolic and genetic profiling and machine learning, they developed a gut microbiome signature for liver disease based on differences in the types and amounts of bacteria in patients compared to healthy individuals. A microbiome signature based on 19 bacterial species present only in the patient group accurately diagnosed cirrhosis in 94% of patients. To further validate the signature, they applied it to cirrhosis patient populations in China and Italy and correctly identified the disease in more than 90% of cases. Additionally, the signature distinguished early stage fibrosis from cirrhosis.

This universal gut microbiome signature can identify cirrhosis across geographically separated cohorts, independent of the effects of genetics and environment. According to the authors, the method has immense potential to improve liver disease diagnosis, especially in resource-limited settings where other screening options might not be available.

Citation: Oh TG, Kim SM, Caussy C, Fu T, Guo J, Bassirian S, Singh S, Madamba EV, Bettencourt R, Richards L, Raffatellu M, Dorrestein PC, Yu RT, Atkins AR, Huan T, Brenner DA, Sirlin CB, Knight R, Downes M, Evans RM, Loomba R. 2020. A universal gut-microbiome-derived signature predicts cirrhosis. Cell Metab. doi:10.1016/j.cmet.2020.06.005 [Online 30 June 2020].

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