Serum identification of at-risk MASH: The metabolomics-advanced steatohepatitis fibrosis score (MASEF).

BACKGROUND: Early identification of those with NAFLD activity score ≥ 4 and significant fibrosis (≥F2) or at-risk metabolic dysfunction-associated steatohepatitis (MASH) is a priority as these patients are at increased risk for disease progression and may benefit from therapies. We developed and validated a highly specific metabolomics-driven score to identify at-risk MASH. METHODS: We included derivation (n = 790) and validation (n = 565) cohorts from international tertiary centers. Patients underwent laboratory assessment and liver biopsy for metabolic dysfunction-associated steatotic liver disease. Based on 12 lipids, body mass index, aspartate aminotransferase, and alanine aminotransferase, the MASEF score was developed to identify at-risk MASH and compared to the FibroScan-AST (FAST) score. We further compared the performance of a FIB-4 + MASEF algorithm to that of FIB-4 + liver stiffness measurements (LSM) by vibration-controlled transient elastography (VCTE). RESULTS: The diagnostic performance of the MASEF score showed an area under the receiver-operating characteristic curve, sensitivity, specificity, and positive and negative predictive values of 0.76 (95% CI 0.72-0.79), 0.69, 0.74, 0.53, and 0.85 in the derivation cohort, and 0.79 (95% CI 0.75-0.83), 0.78, 0.65, 0.48, and 0.88 in the validation cohort, while FibroScan-AST performance in the validation cohort was 0.74 (95% CI 0.68-0.79; p = 0.064), 0.58, 0.79, 0.67, and 0.73, respectively. FIB-4+MASEF showed similar overall performance compared with FIB-4 + LSM by VCTE ( p = 0.69) to identify at-risk MASH. CONCLUSION: MASEF is a promising diagnostic tool for the assessment of at-risk MASH. It could be used alternatively to LSM by VCTE in the algorithm that is currently recommended by several guidance publications.

Role of Intracellular Drug Disposition in the Response of Acute Myeloid Leukemia to Cytarabine and Idarubicin Induction Chemotherapy.

Despite its often low efficacy and high toxicity, the standard treatment for acute myeloid leukemia (AML) is induction chemotherapy with cytarabine and idarubicin. Here, we have investigated the role of transporters and drug-metabolizing enzymes in this poor outcome. The expression levels (RT-qPCR) of potentially responsible genes in blasts collected at diagnosis were related to the subsequent response to two-cycle induction chemotherapy. The high expression of uptake carriers (ENT2), export ATP-binding cassette (ABC) pumps (MDR1), and enzymes (DCK, 5-NT, and CDA) in the blasts was associated with a lower response. Moreover, the sensitivity to cytarabine in AML cell lines was associated with ENT2 expression, whereas the expression of ABC pumps and enzymes was reduced. No ability of any AML cell line to export idarubicin through the ABC pumps, MDR1 and MRP, was found. The exposure of AML cells to cytarabine or idarubicin upregulated the detoxifying enzymes (5-NT and DCK). In AML patients, 5-NT and DCK expression was associated with the lack of response to induction chemotherapy (high sensitivity and specificity). In conclusion, in the blasts of AML patients, the reduction of the intracellular concentration of the active metabolite of cytarabine, mainly due to the increased expression of inactivating enzymes, can determine the response to induction chemotherapy.

Metabolic subtypes of patients with NAFLD exhibit distinctive cardiovascular risk profiles.

BACKGROUND AND AIMS: We previously identified subsets of patients with NAFLD with different metabolic phenotypes. Here we align metabolomic signatures with cardiovascular disease (CVD) and genetic risk factors. APPROACH AND RESULTS: We analyzed serum metabolome from 1154 individuals with biopsy-proven NAFLD, and from four mouse models of NAFLD with impaired VLDL-triglyceride (TG) secretion, and one with normal VLDL-TG secretion. We identified three metabolic subtypes: A (47%), B (27%), and C (26%). Subtype A phenocopied the metabolome of mice with impaired VLDL-TG secretion; subtype C phenocopied the metabolome of mice with normal VLDL-TG; and subtype B showed an intermediate signature. The percent of patients with NASH and fibrosis was comparable among subtypes, although subtypes B and C exhibited higher liver enzymes. Serum VLDL-TG levels and secretion rate were lower among subtype A compared with subtypes B and C. Subtype A VLDL-TG and VLDL-apolipoprotein B concentrations were independent of steatosis, whereas subtypes B and C showed an association with these parameters. Serum TG, cholesterol, VLDL, small dense LDL5,6 , and remnant lipoprotein cholesterol were lower among subtype A compared with subtypes B and C. The 10-year high risk of CVD, measured with the Framingham risk score, and the frequency of patatin-like phospholipase domain-containing protein 3 NAFLD risk allele were lower in subtype A. CONCLUSIONS: Metabolomic signatures identify three NAFLD subgroups, independent of histological disease severity. These signatures align with known CVD and genetic risk factors, with subtype A exhibiting a lower CVD risk profile. This may account for the variation in hepatic versus cardiovascular outcomes, offering clinically relevant risk stratification.

A Novel Serum Metabolomic Profile for the Differential Diagnosis of Distal Cholangiocarcinoma and Pancreatic Ductal Adenocarcinoma.

The diagnosis of adenocarcinomas located in the pancreas head, i.e., distal cholangiocarcinoma (dCCA) and pancreatic ductal adenocarcinoma (PDAC), constitutes a clinical challenge because they share many symptoms, are not easily distinguishable using imaging techniques and accurate biomarkers are not available. Searching for biomarkers with potential usefulness in the differential diagnosis of these tumors, we have determined serum metabolomic profiles in healthy controls and patients with dCCA, PDAC or benign pancreatic diseases (BPD). Ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) analysis was performed in serum samples from dCCA (n = 34), PDAC (n = 38), BPD (n = 42) and control (n = 25) individuals, divided into discovery and validation cohorts. This approach permitted 484 metabolites to be determined, mainly lipids and amino acids. The analysis of the results led to the proposal of a logistic regression model able to discriminate patients with dCCA and PDAC (AUC value of 0.888) based on the combination of serum levels of nine metabolites (acylcarnitine AC(16:0), ceramide Cer(d18:1/24:0), phosphatidylcholines PC(20:0/0:0) and PC(O-16:0/20:3), lysophosphatidylcholines PC(20:0/0:0) and PC(0:0/20:0), lysophosphatidylethanolamine PE(P-18:2/0:0), and sphingomyelins SM(d18:2/22:0) and SM(d18:2/23:0)) and CA 19-9. In conclusion, we propose a novel specific panel of serum metabolites that can help in the differential diagnosis of dCCA and PDAC. Further validation of their clinical usefulness in prospective studies is required.

Agonist of RORA Attenuates Nonalcoholic Fatty Liver Progression in Mice via Up-regulation of MicroRNA 122.

BACKGROUND & AIMS: Development of nonalcoholic steatohepatitis (NASH) is associated with reductions in hepatic microRNA122 (MIR122); the RAR related orphan receptor A (RORA) promotes expression of MIR122. Increasing expression of RORA in livers of mice increases expression of MIR122 and reduces lipotoxicity. We investigated the effects of a RORA agonist in mouse models of NASH. METHODS: We screened a chemical library to identify agonists of RORA and tested their effects on a human hepatocellular carcinoma cell line (Huh7). C57BL/6 mice were fed a chow or high-fat diet (HFD) for 4 weeks to induce fatty liver. Mice were given hydrodynamic tail vein injections of a MIR122 antagonist (antagomiR-122) or a control antagomiR once each week for 3 weeks while still on the HFD or chow diet, or intraperitoneal injections of the RORA agonist RS-2982 or vehicle, twice each week for 3 weeks. Livers, gonad white adipose, and skeletal muscle were collected and analyzed by reverse-transcription polymerase chain reaction, histology, and immunohistochemistry. A separate group of mice were fed an atherogenic diet, with or without injections of RS-2982 for 3 weeks; livers were analyzed by immunohistochemistry, and plasma was analyzed for levels of aminotransferases. We analyzed data from liver tissues from patients with NASH included in the RNA-sequencing databases GSE33814 and GSE89632. RESULTS: Injection of mice with antagomiR-122 significantly reduced levels of MIR122 in plasma, liver, and white adipose tissue; in mice on an HFD, antagomiR-122 injections increased fat droplets and total triglyceride content in liver and reduced ß-oxidation and energy expenditure, resulting in significantly more weight gain than in mice given the control microRNA. We identified RS-2982 as an agonist of RORA and found it to increase expression of MIR122 promoter activity in Huh7 cells. In mice fed an HFD or atherogenic diet, injections of RS-2982 increased hepatic levels of MIR122 precursors and reduced hepatic synthesis of triglycerides by reducing expression of biosynthesis enzymes. In these mice, RS-2982 significantly reduced hepatic lipotoxicity, reduced liver fibrosis, increased insulin resistance, and reduced body weight compared with mice injected with vehicle. Patients who underwent cardiovascular surgery had increased levels of plasma MIR122 compared to its levels before surgery; increased expression of plasma MIR122 was associated with increased levels of plasma free fatty acids and levels of RORA. CONCLUSIONS: We identified the compound RS-2982 as an agonist of RORA that increases expression of MIR122 in cell lines and livers of mice. Mice fed an HFD or atherogenic diet given injections of RS-2982 had reduced hepatic lipotoxicity, liver fibrosis, and body weight compared with mice given the vehicle. Agonists of RORA might be developed for treatment of NASH.

CA19-9 capability as predictor of pancreatic cancer resectability in a Spanish cohort.

CA19-9 serum has been suggested as a marker of unresectability but different cut-off levels have been published. A cut-off of 500 U/ml is currently considered in an international consensus as biological criteria of borderline resectable pancreatic adenocarcinoma. To evaluate whether serum CA19-9 threshold of 500 U/ml could be adequate predictor of resectability in pancreatic adenocarcinoma. Multicenter, observational, prospective study performed in Spain including 203 patients diagnosed with pancreatic adenocarcinoma. 43 (21.2%) cases were resectable and 160 (78.8%) unresectable. Among the 176 preoperative CA19-9 available values, 98 (58.3%) were ≤ 500 U/ml and 73 (42.7%) > 500 U/ml. Resectability rate in those patients with CA19-9 ≤ 500 U/ml was 60% while it was found to be 18% when CA19-9 > 500 U/ml. Statistical model to predict resectability based on CA19-9 provide an AUC of 0.6618 (95% CI 0.53-0.83) when only CA19-9 values > 500 U/ml are studied. Serum levels of CA19-9 higher than 500 U/ml are indicative of unresectable disease, however reduced sensitivity and specificity lead to a limited clinical applicability for resectability.

The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles.

OBJECTIVE: To characterize the most relevant changes in the lipidome of endometrial fluid aspirate (EFA) in non-implantative cycles. DESIGN: Lipidomics in a prospective cohort study. SETTINGS: Reproductive unit of a university hospital. PATIENTS: Twenty-nine women undergoing an IVF cycle. Fifteen achieved pregnancy and 14 did not. INTERVENTION: Endometrial fluid aspiration immediately before performing embryo transfer. MAIN OUTCOME MEASURES: Clinical pregnancy rate and lipidomic profiles obtained on an ultra-high performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC-ToF-MS)-based analytical platform. RESULTS: The comparative analysis of the lipidomic patterns of endometrial fluid in implantative and non-implantative IVF cycles revealed eight altered metabolites: seven glycerophospholipids and an omega-6 polyunsaturated fatty acid. Then, women with a non-implantative cycle were accurately classified with a support vector machine algorithm including these eight lipid metabolites. The diagnostic performances of the algorithm showed an area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy of 0.893 ± 0.07, 85.7%, 80.0%, and 82.8%, respectively. CONCLUSION: A predictive lipidomic signature linked to the implantative status of the endometrial fluid has been found.

Metabolomics Discloses a New Non-invasive Method for the Diagnosis and Prognosis of Patients with Alcoholic Hepatitis.

INTRODUCTION AND AIMS: Alcoholic hepatitis is the most severe manifestation of alcoholic liver disease. Unfortunately, there are still some unresolved issues in the diagnosis and management of this disease, such as the need of histological diagnosis, an accurate prognostic stratification, and the development of novel targeted therapies. The present study aimed at addressing these issues by means of metabolomics, a novel high-throughput approach useful in other liver diseases. MATERIAL AND METHODS: 64 patients with biopsy-proven alcoholic hepatitis were included and compared with 26 patients with decompensated alcoholic cirrhosis without superimposed alcoholic hepatitis, which was ruled out by liver biopsy. RESULTS: The comparison of the metabolic profiles of patients with alcoholic hepatitis and decompensated cirrhosis showed marked differences between both groups. Importantly, metabolic differences were found among alcoholic hepatitis patients when subjects were stratified according to 90-day survival. Based on these findings, two non-invasive signatures were developed. The first one allowed an accurate non-invasive diagnosis of alcoholic hepatitis (AUROC 0.932; 95% CI 0.901-0.963). The second signature showed a good performance in the prognostic stratification of patients with alcoholic hepatitis (AUROC 0.963; 95% CI 0.895-1.000). CONCLUSIONS: Signatures based on metabolomics allowed an accurate non-invasive diagnosis and prognostic stratification of alcoholic hepatitis. The differences observed in the metabolic profile of the patients according to the presence and severity of alcoholic hepatitis are related with different mechanisms involved in the pathophysiology of alcoholic hepatitis such as peroxisomal activity, synthesis of inflammatory mediators or oxidation. This information could be useful for the development of novel targeted therapies.

Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer.

OBJECTIVES: Specific microRNA (miRNA) signatures in biological fluids can facilitate earlier detection of the tumors being then minimally invasive diagnostic biomarkers. Circulating miRNAs have also emerged as promising diagnostic biomarkers for colorectal cancer (CRC) screening. In this study, we investigated the performance of a specific signature of miRNA in plasma samples to design a robust predictive model that can distinguish healthy individuals from those with CRC or advanced adenomas (AA) diseases. METHODS: Case control study of 297 patients from 8 Spanish centers including 100 healthy individuals, 101 diagnosed with AA, and 96 CRC cases. Quantitative real-time reverse transcription was used to quantify a signature of miRNA (miRNA19a, miRNA19b, miRNA15b, miRNA29a, miRNA335, and miRNA18a) in plasma samples. Binary classifiers (Support Vector Machine [SVM] linear, SVM radial, and SVM polynomial) were built for the best predictive model. RESULTS: Area under receiving operating characteristic curve of 0.92 (95% confidence interval 0.871-0.962) was obtained retrieving a model with a sensitivity of 0.85 and specificity of 0.90, positive predictive value of 0.94, and negative predictive value of 0.76 when advanced neoplasms (CRC and AA) were compared with healthy individuals. CONCLUSIONS: We identified and validated a signature of 6 miRNAs (miRNA19a, miRNA19b, miRNA15b, miRNA29a, miRNA335, and miRNA18a) as predictors that can differentiate significantly patients with CRC and AA from those who are healthy. However, large-scale validation studies in asymptomatic screening participants should be conducted.

Metabolomics discloses potential biomarkers to predict the acute HVPG response to propranolol in patients with cirrhosis.

BACKGROUND: In cirrhosis, a decrease in hepatic venous pressure gradient (HVPG) > 10% after acute iv propranolol (HVPG response) is associated with a lower risk of decompensation and death. Only a part of patients are HVPG responders and there are no accurate non-invasive markers to identify them. We aimed at discovering metabolomic biomarkers of HVPG responders to propranolol. METHODS: Sixty-six patients with cirrhosis and HVPG ≥ 10 mm Hg in whom the acute HVPG response to propranolol was assessed, were prospectively included. A targeted metabolomic serum analysis using ultrahigh-performance liquid chromatography coupled to mass spectrometry was performed. Different combinations of 2-3 metabolites identifying HVPG responders (HVPG reduction > 10%) were obtained by stepwise logistic regression. The best of these model (AUROC, Akaike criterion) underwent internal cross-validation and cut-offs to classify responders/non-responders was proposed. RESULTS: A total of 41/66 (62%) patients were HVPG responders. Three hundred and eighty-nine metabolites were detected and 177 were finally eligible. Eighteen metabolites were associated to the HVPG response at univariate analysis; at multivariable analysis, a model including a phosphatidylcholine (PC(P-16:0/22:6)) and a free fatty acid (20:2(n-6), eicosadienoic acid) performed well for HVPG response, with an AUROC of 0.801 (0.761 at internal validation). The cut-off 0.629 was the most efficient for overall classification (49/66 patients correctly classified). Two cut-off values allowed identifying responders (0.688, PPV 84%) and non-responders (0.384, NPV 82%) with undetermined values for 17/66 patients. Clinical variables did not add to the model. CONCLUSIONS: The combination of two metabolites helps at identifying HVPG responders to acute propranolol. It could be a useful non-invasive test to classify the HVPG response to propranolol.

Serum Metabolites as Diagnostic Biomarkers for Cholangiocarcinoma, Hepatocellular Carcinoma, and Primary Sclerosing Cholangitis.

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.

Obeticholic Acid Modulates Serum Metabolites and Gene Signatures Characteristic of Human NASH and Attenuates Inflammation and Fibrosis Progression in Ldlr-/-.Leiden Mice.

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.

Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer.

Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression.

Metabolomic-based noninvasive serum test to diagnose nonalcoholic steatohepatitis: Results from discovery and validation cohorts.

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).

Use of a metabolomic approach to non-invasively diagnose non-alcoholic fatty liver disease in patients with type 2 diabetes mellitus.

AIMS: To assess the utility of existing metabolomics scores to classify liver disease in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: A total of 220 patients with T2DM were recruited. Patients underwent routine laboratory tests, liver proton magnetic resonance spectroscopy (1 H-MRS), a 75-g oral glucose tolerance test, and liver biopsy if 1 H-MRS findings indicated non-alcoholic fatty liver disease. A serum sample was blindly provided to OWL Metabolomics on which to run the OWLiver Care and OWLiver tests. RESULTS: When compared with liver biopsy, the OWLiver Care and OWLiver tests had a suboptimal performance in patients with T2DM (areas under the receiver-operating characteristic [AUROC] curve both <0.70). Given the discordance of these results in this heterogeneous, multiethnic cohort compared with those of a previous report in predominantly white patients without diabetes, we examined the influence of age, ethnicity and other variables on test performance. A specific subset of patients was selected to mirror the characteristics of the population used for the development of this model (ie, white patients without T2DM). Among white patients with good glycaemic control (glycated haemoglobin <53mmol/mol [or <7%]) and without cirrhosis, the AUROC curve was significantly improved (0.79 [CI 95%: 0.68-0.90]). Among white patients with lower insulin resistance (homeostatic model assessment of insulin resistance <3) and without cirrhosis, the AUROC was even higher: 0.87 (CI 95%: 0.76-0.97). CONCLUSIONS: There is a great need to develop non-invasive approaches to diagnose non-alcoholic steatohepatitis in patients with T2DM; models originally developed for patients without diabetes cannot be directly applied to patients with T2DM.

Role of Aramchol in steatohepatitis and fibrosis in mice.

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 ß-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.

A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients.

Liver fibrosis must be evaluated in patients with hepatitis C virus (HCV) after liver transplantation because its severity affects their prognosis and the recurrence of HCV. Since invasive biopsy is still the gold standard to identify patients at risk of graft loss from rapid fibrosis progression, it becomes crucial the development of new accurate, non-invasive methods that allow repetitive examination of the patients. Therefore, we have developed a non-invasive, accurate model to distinguish those patients with different liver fibrosis stages. Two hundred and three patients with HCV were histologically classified (METAVIR) into five categories of fibrosis one year after liver transplantation. In this cross-sectional study, patients at fibrosis stages F0-F1 (n = 134) were categorised as "slow fibrosers" and F2-F4 (n = 69) as "rapid fibrosers". Chloroform/methanol serum extracts were analysed by reverse ultra-high performance liquid chromatography coupled to mass spectrometry. A diagnostic model was built through linear discriminant analyses. An algorithm consisting of two sphingomyelins and two phosphatidylcholines accurately classifies rapid and slow fibrosers after transplantation. The proposed model yielded an AUROC of 0.92, 71% sensitivity, 85% specificity, and 84% accuracy. Moreover, specific bile acids and sphingomyelins increased notably along with liver fibrosis severity, differentiating between rapid and slow fibrosers.

Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

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 caused by 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 levels 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 also was 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.

Data in support of enhancing metabolomics research through data mining.

Metabolomics research has evolved considerably, particularly during the last decade. Over the course of this evolution, the interest in this 'omic' discipline is now more evident than ever. However, the future of metabolomics will depend on its capability to find biomarkers. For that reason, data mining constitutes a challenging task in metabolomics workflow. This work has been designed in support of the research article entitled "Enhancing metabolomics research through data mining", which proposed a methodological data handling guideline. An aging research in healthy population was used as a guiding thread to illustrate this process. Here we provide a further interpretation of the obtained statistical results. We also focused on the importance of graphical visualization tools as a clue to understand the most common univariate and multivariate data analyses applied in metabolomics.