image: (a) Visualisation of inter-individual differences in microbiota profiles (genus level composition) using principal component analysis (PCoA). Enterotypes (Bact2, Bact1, Rum, Prev) are represented by color. Vectors represent the post-hoc fit of the microbiota variation associated with the significant, independent determinants of genus-level variation in the microbiota community, steatosis severity and metformin intake (online supplemental table S2). Boxplots surrounding the PCoA represent the enterotype distribution data points along each PCo axis. The body of the box plot represents the first and third quartiles of the distribution, the line represents the median and the whiskers extend from the quartiles to the last data point within 1.5×interquartile range, with outliers beyond. (b) Enterotype distribution in the microDHNA cohort and compared with lean and overweight or obese participants in the Western population, Flemish Gut Flora Project (FGFP) data set. The microDHNA cohort showed greater prevalence of the dysbiotic Bact2 enterotype than lean and overweight/obese participants of the general Western population (n=2345, Chi-squared tests, online supplemental table S4). (c) Prevalence switch of enterotypes with steatosis severity in all participants and restricted to metformin users, showing the increase in Bact2 prevalence in patients with more severe steatosis (logistic regression (Logit), odds ratio=1.01, adjP=0.077, n=49, online supplemental table S5). Coloured areas represent the stacked enterotype prevalence along the steatosis gradient, with lines provided by multinomial Logit of enterotypes by steatosis severity, and data points (light grey) jittered at the corresponding steatosis severity level. (d) Genera proportions associated with steatosis severity and metformin intake (online supplemental table S5). Heatmap representation of the effect size of the associations (colour) (Spearman’s rank correlation ρ for steatosis severity and Wilcoxon rank-sum test rank biserial for metformin). Adjustment for multiple testing was performed using the Benjamini-Hochberg method (adjP). The asterisks represent the significance level (adjP<0.1*). (e) Scatter plot representation highlighting genera proportions significantly correlated with steatosis severity (Spearman rank correlation test; adjP<0.1, online supplemental table S5).
Credit: By Marta Borges-Canha, Javier Centelles-Lodeiro, Sara Vieira-Silva, et al.
A new study in eGastroenterology links gut dysbiosis with severe steatosis in metabolic dysfunction–associated steatotic liver disease (MASLD). In a 61-patient cohort, those with the inflammation-linked Bact2 enterotype developed severe steatosis at lower thresholds. Adding microbiota status to standard clinical tools improved diagnostic accuracy from 80% to 90%, suggesting a path toward earlier detection and personalized care.
MASLD: A Growing Global Burden
Metabolic dysfunction–associated steatotic liver disease (MASLD), formerly termed non-alcoholic fatty liver disease (NAFLD), is now the most common chronic liver disorder worldwide. Affecting nearly 38% of the global population, its prevalence parallels the epidemic of metabolic syndrome (MetS), a cluster of conditions including obesity, insulin resistance, and dyslipidaemia. Excessive fat accumulation in the liver, known as hepatic steatosis, drives disease progression, increases the risk of fibrosis, cirrhosis, and liver cancer.
Early identification of patients at risk of severe steatosis is crucial, yet current clinical tools such as the Fatty Liver Index (FLI) are imperfect. Mounting evidence points to the gut microbiota—disrupted in both MASLD and MetS—as a potential player in improving diagnosis.
Study Design and Key Findings
The new study, led by Professor Sara Vieira-Silva, analysed data from the microDHNA cohort, a cross-sectional study of 61 patients with MetS across different stages of MASLD. Participants underwent liver imaging, clinical evaluation, and gut microbiota profiling.
- Linking Gut Dysbiosis to Severe Steatosis. The study revealed a distinct microbial signature associated with steatosis severity. Patients with more advanced steatosis had: (1) Reduced beneficial commensals, including Akkermansia, known for maintaining gut barrier integrity. (2) Increased opportunistic bacteria, such as Streptococcus. (3) Higher prevalence of the Bacteroides 2 (Bact2) enterotype, a microbial community type previously linked to inflammation and reduced butyrate-producing capacity. Strikingly, Bact2 carriers reached the threshold for severe steatosis at much lower FLI scores than non-carriers (74 vs 101), suggesting that dysbiosis accelerates disease progression.
- Enhancing Diagnosis with Microbiota Profiling. To test whether microbial features could improve clinical diagnosis, the researchers built predictive models incorporating different variables.
- FLI alone: classified severe steatosis with 80% accuracy and an area under the ROC curve (AUC) of 92%.
- Bact2 status alone: showed similar accuracy (80%) but added independent predictive value.
- FLI + Bact2 combined: produced the best model, with 90% accuracy and AUC of 96%—a 10% increase in accuracy compared to FLI alone.
This finding demonstrates that simple microbial community typing can substantially strengthen non-invasive diagnostic tools.
Biological Implications of the Bact2 Enterotype
Beyond diagnostics, the study highlights the biological significance of dysbiosis. The Bact2 enterotype is characterised by reduced butyrate producers, depletion of metabolic diversity, and increased inflammatory potential. Prior research shows that this enterotype impairs glucose metabolism, increases bile acid production, and weakens gut barrier function. Together, these changes may promote systemic inflammation and exacerbate liver fat accumulation. Thus, dysbiosis is not just a biomarker—it may be an active driver of steatosis progression.
Clinical Relevance and Next Steps
The study suggests that profiling a patient’s gut microbiota could:
- Enable earlier detection of high-risk MASLD patients
- Support more precise risk stratification
- Open possibilities for microbiota-based therapies, such as dietary interventions or probiotics
The authors caution that larger, longitudinal studies are needed to confirm whether restoring gut microbial balance can slow MASLD progression.
In conclusion, this study provides compelling evidence that gut dysbiosis, particularly the inflammation-linked Bact2 enterotype, is strongly associated with severe hepatic steatosis in MASLD. Incorporating microbiota profiling with established clinical predictors significantly improves diagnostic accuracy.
Journal
eGastroenterology
Article Title
Gut dysbiosis is linked to severe steatosis and enhances its diagnostic performance in MASLD