Obesity-Dependent Metabolic Signatures Associated with Nonalcoholic Fatty Liver Disease Progression

Abstract

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.

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

“…This BMI‐dependent serum lipidomic test measures the probability of a certain sample to belong to one of these three groups: NL, NAFL, and NASH. In that previous work, a total of 467 biopsy‐proven samples, classified as NL, NAFL, or NASH, were analyzed using three different metabolic UPLC‐MS platforms that measured 540 different lipids and amino acids 19. Taking this work as a reference point, the next steps were conducted to reduce the complexity of the test by means of reducing the number of metabolites that needed to be measured as well as the required analytical platforms.…”

“…MS lipidomics is a high‐throughput technology that can measure simultaneously hundreds of different lipid classes and molecular species in a small volume of serum 37, 38, 39, 40. We first demonstrated this concept by showing that a panel of 540 lipids could differentiate NAFLD from NL and NASH from NAFL 19. We also observed that categorizing patients by their BMI improved the power of the classification algorithm 41.…”

“…Lipidomic profiles of the serum samples were obtained as described 19. Serum extracts were mixed with sodium chloride (50 mM) and chloroform/methanol (2:1) in 1.5 mL microtubes on ice.…”

Metabolic alterations in urine extracellular vesicles are associated to prostate cancer pathogenesis and progression

“…Metabolic profiles of urinary EVs were semi-quantified using four UHPLC-MS based analytical platforms as previously described [17,18]. Methanol was first added to urinary EV preparations, and after brief vortex, chloroform was added.…”

“…Chromatographic separation and mass spectrometric detection conditions employed were previously described [17,18]. The overall quality of the analysis procedure was monitored using six repeat injections of a pooled sample, considered as the quality control sample.…”