Scientists Discover Fatty Liver Disease May Consist of Five Distinct Conditions - Video

Could fatty liver disease have different hidden forms that determine a person's risk of liver failure, cancer and heart disease? A new study suggests that metabolic dysfunction-associated steatotic liver disease (MASLD) comprises five biologically distinct subtypes, each associated with different health risks and patterns of disease progression.

Published in Nature Communications, the study conducted by researchers at Mayo Clinic and Virginia Tech identified five subtypes of fatty liver disease by analysing genetic and clinical information from more than 4,600 patients.

MASLD, previously known as nonalcoholic fatty liver disease, affects nearly 30% of adults worldwide. The condition develops when excess fat accumulates in the liver and can progress to inflammation, fibrosis, cirrhosis and liver cancer.

Researchers combined genetic sequencing data with clinical measurements, including liver enzyme levels, body mass index, blood lipid profiles and metabolic health indicators.

Using advanced computational analysis, they identified five distinct patient groups characterised by different biological mechanisms and associated complications.

The findings revealed that some MASLD subtypes were predominantly associated with obesity, diabetes and metabolic dysfunction, while others appeared to be influenced more strongly by inherited genetic variations.

Importantly, genetically driven subtypes were associated with a greater likelihood of developing advanced liver complications, even among individuals without conventional metabolic risk factors.

Researchers also identified previously unrecognised associations between certain MASLD subtypes and conditions including depression, sleep apnea and migraine, suggesting that the disease may involve biological processes extending beyond the liver.

The findings indicate that patients diagnosed with the same liver condition may face substantially different risks of cirrhosis, liver cancer and other complications.

Researchers suggested that integrating genetic information with clinical assessments could eventually help identify high-risk patients earlier and guide personalised screening and treatment strategies.

However, further studies involving larger and more diverse populations are needed to validate these subtypes and determine whether they respond differently to available therapies.

REFERENCE: Tahmina Sultana Priya, et al.; Subtyping metabolic dysfunction-associated steatotic liver disease using electronic health record-linked genomic cohorts reveals diverse etiologies and progression. Nature Communications, 2026; 17 (1) DOI: 10.1038/s41467-026-77410-6