Intestinal Virome Signature Associated With Severity of Nonalcoholic Fatty Liver Disease

Background & Aims Alterations in the gut microbiome have been associated with the severity of nonalcoholic fatty liver disease (NAFLD). Previous studies focused exclusively on the bacteria in the microbiome; we investigated changes in the viral microbiome (virome) in patients with NAFLD. Methods In a prospective, cross-sectional, observational study, we extracted RNA and DNA virus-like particles from fecal samples from 73 patients with NAFLD: 29 patients had an NAFLD Activity Score (NAS) of 0–4, 44 patients had an NAS of 5–8 or liver cirrhosis (LCI), 37 patients had F0–F1 fibrosis, and 36 patients had F2–F4 fibrosis. As controls, 9 individuals without liver disease and 13 patients with mild primary biliary cholangitis were included in the analysis. We performed shotgun metagenomic sequencing of virus-like particles. Results Patients with NAFLD and NAS 5–8/LCI had a significant decrease in intestinal viral diversity compared with patients with NAFLD and NAS 0–4 or control individuals. The presence of more advanced NAFLD was associated with a significant reduction in the proportion of bacteriophages compared with other intestinal viruses. Using multivariate logistic regression analysis with leave-1-out cross validation, we developed a model, including a viral diversity index and simple clinical variables, that identified patients with NAS 5–8/LCI with an area under the curve of 0.95 (95% confidence interval, 0.91–0.99) and F2–F4 fibrosis with an area under the curve of 0.88 (95% confidence interval, 0.80–0.95). Addition of data on viral diversity significantly improved multivariate models, including those based on only clinical parameters or bacterial diversity. Conclusions In a study of fecal viromes from patients with NAFLD and control individuals, we associated histologic markers of NAFLD severity with significant decreases in viral diversity and proportion of bacteriophages. We developed a model based on fecal viral diversity and clinical data that identifies patients with severe NAFLD and fibrosis more accurately than models based only on clinical or bacterial data.