Our understanding of the mechanisms by which nonalcoholic fatty liver disease (NAFLD) progresses from simple steatosis to steatohepatitis (NASH) is still very limited. Despite the growing number of studies linking the disease with altered serum metabolite levels, an obstacle to the development of metabolome-based NAFLD predictors has been the lack of large cohort data from biopsy-proven patients matched for key metabolic features such as obesity. We studied 467 biopsied individuals with normal liver histology (n=90) or diagnosed with NAFLD (steatosis, n=246; NASH, n=131), randomly divided into estimation (80% of all patients) and validation (20% of all patients) groups. Qualitative determinations of 540 serum metabolite variables were performed using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS). The metabolic profile was dependent on patient body-mass index (BMI), suggesting that the NAFLD pathogenesis mechanism may be quite different depending on an individual’s level of obesity. A BMI-stratified multivariate model based on the NAFLD serum metabolic profile was used to separate patients with and without NASH. The area under the receiver operating characteristic curve was 0.87 in the estimation and 0.85 in the validation group. The cutoff (0.54) corresponding to maximum average diagnostic accuracy (0.82) predicted NASH with a sensitivity of 0.71 and a specificity of 0.92 (negative/positive predictive values = 0.82/0.84). The present data, indicating that a BMI-dependent serum metabolic profile may be able to reliably distinguish NASH from steatosis patients, have significant implications for the development of NASH biomarkers and potential novel targets for therapeutic intervention.

BackgroundObesity modulates inflammation and activation of immune pathways which can lead to liver complications. We aimed at identifying expression patterns of inflammatory and immune response genes specifically associated with obesity and NASH in the liver of morbidly obese patients.Methodology/Principal FindingsExpression of 222 genes was evaluated by quantitative RT-PCR in the liver of morbidly obese patients with histologically normal liver (n = 6), or with severe steatosis without (n = 6) or with NASH (n = 6), and in lean controls (n = 5). Hepatic expression of 58 out of 222 inflammatory and immune response genes was upregulated in NASH patients. The most notable changes occurred in genes encoding chemokines and chemokine receptors involved in leukocyte recruitment, CD and cytokines involved in the T cell activation towards a Th1 phenotype, and immune semaphorins. This regulation seems to be specific for the liver since visceral adipose tissue expression and serum levels of MCP1, IP10, TNFα and IL6 were not modified. Importantly, 47 other genes were already upregulated in histologically normal liver (e.g. CRP, Toll-like receptor (TLR) pathway). Interestingly, serum palmitate, known to activate the TLR pathway, was increased with steatosis.Conclusion/SignificanceThe liver of obese patients without histological abnormalities already displayed a low-grade inflammation and could be more responsive to activators of the TLR pathway. NASH was then characterized by a specific gene signature. These findings help to identify new potential actors of the pathogenesis of NAFLD.

Background: Metronidazole has a substantial impact on the gut microbiome. However, the recovery of the microbiome after discontinuation of administration, and the metabolic consequences of such alterations have not been investigated to date. Objectives: To describe the impact of 14-day metronidazole administration, alone or in combination with a hydrolyzed protein diet, on fecal microbiome, metabolome, bile acids (BAs), and lactate production, and on serum metabolome in healthy dogs. Animals: Twenty-four healthy pet dogs. Methods: Prospective, nonrandomized controlled study. Dogs fed various commercial diets were divided in 3 groups: control group (no intervention, G1); group receiving hydrolyzed protein diet, followed by metronidazole administration (G2); and group receiving metronidazole only (G3). Microbiome composition was evaluated with sequencing of 16S rRNA genes and quantitative polymerase chain reaction (qPCR)-based dysbiosis index. Untargeted metabolomics analysis of fecal and serum samples was performed, followed by targeted assays for fecal BAs and lactate. Results: No changes were observed in G1, or G2 during diet change. Metronidazole significantly changed microbiome composition in G2 and G3, including decreases in richness (P < .001) and in key bacteria such as Fusobacteria (q < 0.001) that did not fully resolve 4 weeks after metronidazole discontinuation. Fecal dysbiosis index was significantly increased (P < .001). Those changes were accompanied by increased fecal total lactate (P < .001), and decreased secondary BAs deoxycholic acid and lithocholic acid (P < .001).

Limited information is available regarding the metabolic consequences of intestinal dysbiosis in dogs with acute onset of diarrhea. The aim of this study was to evaluate the fecal microbiome, fecal concentrations of short-chain fatty acids (SCFAs), as well as serum and urine metabolites in healthy dogs (n=13) and dogs with acute diarrhea (n=13). The fecal microbiome, SCFAs, and serum/urine metabolite profiles were characterized by 454-pyrosequencing of the 16S rRNA genes, GC/MS, and untargeted and targeted metabolomics approach using UPLC/MS and HPLC/MS, respectively. Significantly lower bacterial diversity was observed in dogs with acute diarrhea in regards to species richness, chao1, and Shannon index (p=0.0218, 0.0176, and 0.0033; respectively). Dogs with acute diarrhea had significantly different microbial communities compared to healthy dogs (unweighted Unifrac distances, ANOSIM p=0.0040). While Bacteroidetes, Faecalibacterium, and an unclassified genus within Ruminococcaceae were underrepresented, the genus Clostridium was overrepresented in dogs with acute diarrhea. Concentrations of fecal propionic acid were significantly decreased in acute diarrhea (p=0.0033), and were correlated to a decrease in Faecalibacterium (ρ=0.6725, p=0.0332). The predicted functional gene content of the microbiome (PICRUSt) revealed overrepresentations of genes for transposase enzymes as well as methyl accepting chemotaxis proteins in acute diarrhea. Serum concentrations of kynurenic acid and urine concentrations of 2-methyl-1H-indole and 5-Methoxy-1H-indole-3-carbaldehyde were significantly decreased in acute diarrhea (p=0.0048, 0.0185, and 0.0330, respectively). These results demonstrate that the fecal dysbiosis present in acute diarrhea is associated with altered systemic metabolic states.

Non-alcoholic fatty liver disease (NAFLD), is the most common form of chronic liver disease in most western countries. Current NAFLD diagnosis methods (e.g. liver biopsy analysis or imaging techniques) are poorly suited as tests for such a prevalent condition, from both a clinical and financial point of view. The present work aims to demonstrate the potential utility of serum NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript metabolic profiling in defining phenotypic biomarkers that could be useful in NAFLD management. A parallel animal model / human NAFLD exploratory metabolomics approach was employed, using ultra performance liquid chromatography-mass spectrometry (UPLC ® -MS) to analyze 42 serum samples collected from non-diabetic, morbidly obese, biopsy-proven NAFLD patients, and 17 animals belonging to the glycine N-methyltransferase knockout (GNMT-KO) NAFLD mouse model. Multivariate statistical analysis of the data revealed a series of common biomarkers that were significantly altered in the NAFLD (GNMT-KO) subjects in comparison to their normal liver counterparts (WT). Many of the compounds observed could be associated with biochemical perturbations associated with liver dysfunction (e.g. reduced Creatine) and inflammation (e.g. eicosanoid signaling). This differential metabolic phenotyping approach may have a future role as a supplement for clinical decision making in NAFLD and in the adaption to more individualized treatment protocols.