IIT Home Page CNR Home Page

Altered Metabolic Profile and Adipocyte Insulin Resistance Mark Severe Liver Fibrosis in Patients with Chronic Liver Disease

Metabolomics/lipidomics are important tools to identify novel biomarkers associated with liver damage. Patients with chronic liver disease (CLD) and hepatitis C virus (HCV) infection often have alterations in glucose, lipid and protein metabolism. The aim of this study was to evaluate if dysfunctional lipid and amino acid metabolism was associated with fibrosis severity and insulin resistance in CLD/HCV patients. We analyzed the baseline sera of 75 subjects with CLD/HCV infection HCV genotype-1, with proven liver biopsy prior to antiviral treatment. We measured amino acid (AA) and lipid concentration by gas and liquid chromatography-mass spectrometry respectively. Alterations in peripheral glucose metabolism due to insulin resistance (IR) were assesed by HOMA-IR (Glucose x Insulin/22.5), while adipose tissue IR was estimated as (Adipo-IR = Free Fatty Acids x Insulin). Baseline HOMA-IR and Adipo-IR were related to the degree of liver fibrosis. Reduction in ceramides 18:1/22:0, 18:1/24:0, diacylglycerol 42:6 and increased phosphocholine 40:6 were associated with higher fibrosis. Adipo-IR was related to lower levels of lysophosphatidylcholine 14:0 and 18:2 and with higher levels of sphingomyelin 18:2/24:0 and 18:2/24:1. Almost all AA were positively associated with Adipo-IR but not with HOMA-IR. We further confirmed the potential use of metabolomics and lipidomics in CLD/HCV subjects finding novel biomarkers of hepatic fibrosis and show that the adipose tissue IR is associated with more severe liver disease and is an important marker not only of altered lipid but also AA metabolism.

Int. J. Mol. Sci, 2019

Autori esterni: Melania Gaggini (IFC-CNR), Fabrizia Carli (IFC-CNR), Chiara Rosso (UniTo), Rami Younes (UniTo), Elisabetta Bugianesi (UniTo), Amalia Gastaldelli (IFC-CNR)
Autori IIT:

Tipo: Contributo in rivista ISI
Area di disciplina: Mathematics

File: ijms-20-06333-v2.pdf

Attività: Biologia computazionale