The presence of advanced fibrosis is an important measure of the severity of chronic liver disease. Prior works that have examined the gut microbiome as a novel biomarker for advanced fibrosis have only examined patients with nonalcoholic fatty liver disease. Therefore, our goal was to examine the gut microbiome across varying etiologies of liver disease to create a predictive model for liver fibrosis based upon a microbial signature. Stool samples were obtained from patients with chronic liver disease (n = 50) undergoing FibroScan (ultrasound elastography) at the VA Greater Los Angeles Healthcare System. Healthy control patients (n = 25) were also recruited as a reference population. Fecal samples underwent 16S ribosomal RNA sequencing. Using differentially abundant microbes, a random forest classifier model was created to distinguish advanced fibrosis from mild/moderate fibrosis. The findings were then validated in a separate cohort of chronic liver disease patients (n = 37). Etiologies for liver disease included non-alcoholic liver disease (58.0%), hepatitis C (26.0%), hepatitis B (10.0%), and alcohol (6.0%). Microbiome composition was distinct in liver patients with advanced fibrosis compared to those with minimal fibrosis and healthy controls (p = 0.003). In multivariate negative binomial modeling, 26 bacterial taxa were differentially abundant in patients with advanced fibrosis as compared to those with minimal/moderate fibrosis (q-value < 0.05). A random forests classifier based on these taxa had an AUROC of 0.90 to predict advanced fibrosis. Prevotella copri, which was enriched in patients with advanced fibrosis, was the most strongly predictive microbe in the classifier. The classifier had an AUROC of 0.82 for advanced fibrosis in the validation cohort and Prevotella copri remained the strongest predictive microbe for advanced fibrosis. There is a distinct microbial signature for patients with advanced fibrosis independent of liver disease etiology and other comorbidities. These results suggest that microbial profiles can be used as a non-invasive marker for advanced fibrosis and support the hypothesis that microbes and their metabolites contribute to hepatic fibrosis.

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Background: High protein calorie restriction diets have shown clinical efficacy for obesity, but the mechanisms are not fully known. The intestinal microbiome is a mediator of obesity and preclinical data support an effect of high protein diet (HPD) on the gut microbiome of obesity, but there are few studies in humans. Methods: To address this, we conducted a dietary intervention trial of 80 overweight and obese subjects who were randomized to a calorie-restricted high protein diet (HPD) (30% calorie intake) or calorie-restricted normal protein diet (NPD) (15%) for 8 weeks. Baseline dietary intake patterns were assessed by the Diet History Questionnaire III. Longitudinal fecal sampling was performed at baseline, week 1, week 2, week 4, week 6, and week 8, for a total of 365 samples. Intestinal microbiome composition was assessed by 16S rRNA gene sequencing. Results: At baseline, microbial composition was associated with fiber and protein intake. Subjects on the HPD showed a significant increase in microbial diversity as measured by the Shannon index compared to those on the NPD. The HPD was also associated with significant differences in microbial composition after treatment compared to the NPD. Both diets induced taxonomic shifts compared to baseline, including enrichment of Akkermansia spp. and Bifidobacterium spp. and depletion of Prevotella spp. Conclusion: These findings provide evidence that weight loss diets alter the gut microbiome in obesity and suggest differential effects of HPDs compared to NPDs which may influence the clinical response to HPD.

Background: The microbiome has been shown in pre-clinical and epidemiological studies to be important in both the development and treatment of obesity and metabolic associated fatty liver disease (MAFLD). However, few studies have examined the role of the microbiome in the clinical response to calorie restriction. To explore this area, we performed a prospective study examining the association of the intestinal microbiome with weight loss and change in hepatic steatosis on a calorie-restricted diet.Methods: A prospective dietary intervention study of 80 overweight and obese participants was performed at the Greater West Los Angeles Veterans Affair Hospital. Patients were placed on a macronutrient standardized diet for 16 weeks, including 14 weeks of calorie restriction (500 calorie deficit). Body composition analysis by impedance, plasma lipid measurements, and ultrasound elastography to measure hepatic steatosis were performed at baseline and week 16. Intestinal microbiome composition was assessed using 16S rRNA gene sequencing. A per protocol analysis was performed on all subjects completing the trial (n = 46).Results: Study completers showed significant reduction in weight, body mass index, total cholesterol, low density lipoprotein, and triglyceride. Subjects who lost at least 5% of their body weight had significantly greater reduction in serum triglyceride and hepatic steatosis than those with &lt;5% body weight loss. Enterococcus and Klebsiella were reduced at the end of the trial while Coprococcus and Collinsella were increased. There were also significant baseline microbiome differences between patients who had at least 5% weight loss as compared to those that did not. Lachnoclostridium was positively associated with hepatic steatosis and Actinomyces was positively associated with hepatic steatosis and weight. Baseline microbiome profiles were able to predict which patients lost at least 5% of their body weight with an AUROC of 0.80.Conclusion: Calorie restriction alters the intestinal microbiome and improves hepatic steatosis in those who experience significant weight loss. Baseline microbiome differences predict weight loss on a calorie–restricted diet and are associated with improvement in hepatic steatosis, suggesting a role of the gut microbiome in mediating the clinical response to calorie restriction.