Background & Aims Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are due to different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. Methods We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low level of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Results Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that was also present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. Conclusions In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be used to monitor disease progression and identify therapeutic targets for patients.

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.

Nonalcoholic fatty liver disease (NAFLD) is the most common type of chronic liver disease worldwide and includes a broad spectrum of histologic phenotypes, ranging from simple hepatic steatosis or nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH). While liver biopsy is the reference gold standard for NAFLD diagnosis and staging, it has limitations due to its sampling variability, invasive nature, and high cost. Thus, there is a need for noninvasive biomarkers that are robust, reliable, and cost effective. In this study, we measured 540 lipids and amino acids in serum samples from biopsy‐proven subjects with normal liver (NL), NAFL, and NASH. Using logistic regression analysis, we identified two panels of triglycerides that could first discriminate between NAFLD and NL and second between NASH and NAFL. These noninvasive tests were compared to blinded histology as a reference standard. We performed these tests in an original cohort of 467 patients with NAFLD (90 NL, 246 NAFL, and 131 NASH) that was subsequently validated in a separate cohort of 192 patients (7 NL, 109 NAFL, 76 NASH). The diagnostic performances of the validated tests showed an area under the receiver operating characteristic curve, sensitivity, and specificity of 0.88 ± 0.05, 0.94, and 0.57, respectively, for the discrimination between NAFLD and NL and 0.79 ± 0.04, 0.70, and 0.81, respectively, for the discrimination between NASH and NAFL. When the analysis was performed excluding patients with glucose levels >136 mg/dL, the area under the receiver operating characteristic curve for the discrimination between NASH and NAFL increased to 0.81 ± 0.04 with sensitivity and specificity of 0.73 and 0.80, respectively. Conclusion: The assessed noninvasive lipidomic serum tests distinguish between NAFLD and NL and between NASH and NAFL with high accuracy. (Hepatology Communications 2018;2:807‐820)

Early and differential diagnosis of intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) by noninvasive methods represents a current clinical challenge. The analysis of low‐molecular‐weight metabolites by new high‐throughput techniques is a strategy for identifying biomarkers. Here, we have investigated whether serum metabolome can provide useful biomarkers in the diagnosis of iCCA and HCC and could discriminate iCCA from HCC. Because primary sclerosing cholangitis (PSC) is a risk factor for CCA, serum metabolic profiles of PSC and CCA have also been compared. The analysis of the levels of lipids and amino acids in the serum of patients with iCCA, HCC, and PSC and healthy individuals (n = 20/group) showed differential profiles. Several metabolites presented high diagnostic value for iCCA versus control, HCC versus control, and PSC versus control, with areas under the receiver operating characteristic curve (AUC) greater than those found in serum for the nonspecific tumor markers carbohydrate antigen 19‐9 (CA 19‐9) and alpha‐fetoprotein (AFP), commonly used to help in the diagnosis of iCCA and HCC, respectively. The development of an algorithm combining glycine, aspartic acid, SM(42:3), and SM(43:2) permitted to accurately differentiate in the diagnosis of both types of tumors (biopsy‐proven). The proposed model yielded 0.890 AUC, 75% sensitivity, and 90% specificity. Another algorithm by combination of PC(34:3) and histidine accurately permitted to differentiate PSC from iCCA, with an AUC of 0.990, 100% sensitivity, and 70% specificity. These results were validated in independent cohorts of 14‐15 patients per group and compared with profiles found in patients with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Conclusion: Specific changes in serum concentrations of certain metabolites are useful to differentiate iCCA from HCC or PSC, and could help in the early diagnosis of these diseases.

Methionine adenosyltransferase 1A (MAT1A) and glycine N-methyltransferase (GNMT) are the primary genes involved in hepatic S-adenosylmethionine (SAMe) synthesis and degradation, respectively. Mat1a ablation in mice induces a decrease in hepatic SAMe, activation of lipogenesis, inhibition of triglyceride (TG) release, and steatosis. Gnmt deficient mice, despite showing a large increase in hepatic SAMe, also develop steatosis. We hypothesized that as an adaptive response to hepatic SAMe accumulation, phosphatidylcholine (PC) synthesis via the phosphatidylethanolamine (PE) N-methyltransferase (PEMT) pathway is stimulated in Gnmt−/− mice. We also propose that the excess PC thus generated is catabolized leading to TG synthesis and steatosis via diglyceride (DG) generation. We observed that Gnmt−/− mice present with normal hepatic lipogenesis and increased TG release. We also observed that the flux from PE to PC is stimulated in the liver of Gnmt−/− mice and that this results in a reduction in PE content and a marked increase in DG and TG. Conversely, reduction of hepatic SAMe following the administration of a methionine deficient diet reverted the flux from PE to PC of Gnmt−/− mice to that of wild type animals and normalized DG and TG content preventing the development of steatosis. Gnmt−/− mice with an additional deletion of perilipin2, the predominant lipid droplet protein, maintain high SAMe levels, with a concurrent increased flux from PE to PC, but do not develop liver steatosis. Conclusion These findings indicate that excess SAMe reroutes PE towards PC and TG synthesis, and lipid sequestration.

Nonalcoholic steatohepatitis (NASH) is the advanced form of nonalcoholic fatty liver disease (NAFLD) which sets the stage for further liver damage. The mechanism for the progression of NASH involves multiple parallel hits including oxidative stress, mitochondrial dysfunction, inflammation and others. Manipulation of any of these pathways may be an approach to prevent NASH development and progression. Aramchol (arachidyl-amido cholanoic acid) is presently in a phase IIb NASH study. The aim of this study was to investigate Aramchol’s mechanism of action and its effect on fibrosis using the methionine- and choline-deficient (MCD) diet model of NASH. We collected liver and serum from mice fed a MCD diet containing 0.1% methionine (0.1MCD) for four weeks, which developed steatohepatitis and fibrosis, as well as mice receiving a control diet; the metabolomes and proteomes were determined. 0.1MCD fed mice were given Aramchol (5mg/kg/day for the last 2 weeks); liver samples were analyzed histologically. Aramchol administration reduced features of steatohepatitis and fibrosis in 0.1MCD fed mice. Aramchol downregulated stearoyl-CoA desaturase 1 (SCD1), a key enzyme involved in triglyceride biosynthesis whose loss enhances fatty acid β-oxidation. Aramchol increased the flux through the transsulfuration pathway, leading to a rise in glutathione (GSH) and GSH/GSSG ratio, the main cellular antioxidant that maintains intracellular redox status. Comparison of serum metabolomic pattern between 0.1MCD fed mice and NAFLD patients showed a substantial overlap. Conclusions Aramchol treatment improved steatohepatitis and fibrosis by 1) decreasing SCD1, and 2) increasing the flux through the transsulfuration pathway maintaining cellular redox homeostasis. We also demonstrated that the 0.1MCD model resembles the metabolic phenotype observed in about 50% of NAFLD patients, which supports the potential use of Aramchol in NASH treatment.

Concerns have been raised about whether preclinical models sufficiently mimic molecular disease processes observed in nonalcoholic steatohepatitis (NASH) patients, bringing into question their translational value in studies of therapeutic interventions in the process of NASH/fibrosis. We investigated the representation of molecular disease patterns characteristic for human NASH in high‐fat diet (HFD)‐fed Ldlr‐/‐.Leiden mice and studied the effects of obeticholic acid (OCA) on these disease profiles. Multiplatform serum metabolomic profiles and genome‐wide liver transcriptome from HFD‐fed Ldlr‐/‐.Leiden mice were compared with those of NASH patients. Mice were profiled at the stage of mild (24 weeks HFD) and severe (34 weeks HFD) fibrosis, and after OCA intervention (24‐34 weeks; 10 mg/kg/day). Effects of OCA were analyzed histologically, biochemically, by immunohistochemistry, using deuterated water technology (de novo collagen formation), and by its effect on the human‐based transcriptomics and metabolomics signatures. The transcriptomics and metabolomics profile of Ldlr‐/‐.Leiden mice largely reflected the molecular signature of NASH patients. OCA modulated the expression of these molecular profiles and quenched specific proinflammatory‐profibrotic pathways. OCA attenuated specific facets of cellular inflammation in liver (F4/80‐positive cells) and reduced crown‐like structures in adipose tissue. OCA reduced de novo collagen formation and attenuated further progression of liver fibrosis, but did not reduce fibrosis below the level before intervention. Conclusion: HFD‐fed Ldlr‐/‐.Leiden mice recapitulate molecular transcriptomic and metabolomic profiles of NASH patients, and these signatures are modulated by OCA. Intervention with OCA in developing fibrosis reduces collagen deposition and de novo synthesis but does not resolve already manifest fibrosis in the period studied. These data show that human molecular signatures can be used to evaluate the translational character of preclinical models for NASH.

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