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.

We report novel 5-HT1BR-induced behaviors and striatal activation that were alleviated only by clinically effective pharmacological OCD treatment. Studying the mechanisms underlying these effects could provide insight into OCD pathophysiology.

Background: Alterations in brain-gut-microbiome interactions have been implicated as an important factor in obesity. This study aimed to explore the relationship between food addiction (FA) and the brain-gutmicrobiome axis, using a multi-omics approach involving microbiome data, metabolomics, and brain imaging. Methods: Brain magnetic resonance imaging was obtained in 105 females. FA was defined by using the Yale Food Addiction Scale. Fecal samples were collected for sequencing and metabolomics. Statistical analysis was done by using multivariate analyses and machine learning algorithms. Results: Of the females with obesity, 33.3% exhibited FA as compared with 5.3% and 0.0% of females with overweight and normal BMI, respectively (P = 0.0001). Based on a multilevel sparse partial least square discriminant analysis, there was a difference in the gut microbiome of females with FA versus those without. Differential abundance testing showed Bacteroides, Megamonas, Eubacterium, and Akkermansia were statistically associated with FA (q < 0.05). Metabolomics showed that indolepropionic acid was inversely correlated with FA. FA was also correlated with increased connectivity within the brain's reward network, specifically between the intraparietal sulcus, brain stem, and putamen. Conclusions: This is the first study to examine FA along the braingut-microbiome axis and it supports the idea of targeting the braingut-microbiome axis for the treatment of FA and obesity.

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.

Pancreatic ductal adenocarcinoma (PDAC)’s growing incidence has been linked to the rise in obesity and type 2 diabetes mellitus. In previous work, we have shown that metformin can prevent the increased incidence of PDAC in a KrasG12D mouse model subjected to a diet high in fat and calories (HFCD). One potential way that metformin can affect the host is through alterations in the gut microbiome. Therefore, we investigated microbial associations with PDAC development and metformin use in the same mouse model. Lox-Stop-Lox Kras G12D/+ (LSL-Kras G12D/+); p48-Cre (KC) mice were given control diet, HFCD, or HFCD with 5 mg/mL metformin in drinking water for 3 mo. At the end of the 3 mo, 16S rRNA sequencing was performed to characterize microbiome composition of duodenal mucosal, duodenal luminal, and cecal luminal samples. KC mice on an HFCD demonstrated depletion of intact acini and formation of advanced pancreatic intraepithelial neoplasia. This effect was completely abrogated by metformin treatment. HFCD was associated with significant changes in microbial composition and diversity in the duodenal mucosa and lumen, much of which was prevented by metformin. In particular, Clostridium sensu stricto was negatively correlated with percent intact acini and seemed to be inhibited by the addition of metformin while on an HFCD. Administration of metformin eliminated PDAC formation in KC mice. This change was associated with significant microbial changes in both the mucosal and luminal microbiome of the duodenum. This suggests that the microbiome may be a potential mediator of the chemopreventive effects of metformin. NEW & NOTEWORTHY Pancreatic ductal adenocarcinoma (PDAC)’s growing incidence has been linked to the rise in obesity and type 2 diabetes mellitus. Administration of metformin eliminated PDAC formation in KC mice with diet-induced obesity. This change was associated with significant microbial changes in both the mucosal and luminal microbiome of the duodenum. This suggests that the microbiome may be a potential mediator of the chemopreventive effects of metformin.