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Clinical Trial Summary

This study aim to find out metabolic molecules in blood and urine which could identify high risk of advanced fibrosis in MAFLD patients via NMR-based metabolic profiling.


Clinical Trial Description

Metabolic dysfunction-associated fatty liver disease (MAFLD) is currently the most common liver disease in the world, with an incidence of 29.81% in China. Studies have shown that the severity of liver fibrosis is the most important predictor of disease progression in patients with MAFLD, and the more severe the degree of liver fibrosis, the worse the prognosis. Therefore, discovering non-invasive indicators that can predict the risk and identify people at high risk of MAFLD with advanced liver fibrosis is essential for early clinical intervention in order to improve their clinical prognosis. Some non-invasive tests like Vibration-controlled Transient Elastography (VCTE), Fibrosis-4 Index (FIB-4), and NAFLD fibrosis score (NFS) have been used to evaluate the liver fibrosis state in MAFLD patients, but lack of prospect in metabolic molecular level. Nuclear magnetic resonance(NMR)-based metabolomic profiling can identify and quantify significant biological molecules in tissue extracts, body fluids (blood, urine, cerebrospinal fluid, saliva, etc.), and secretions, and has wide applications in the study of cancer and other metabolic diseases. Therefore, this study intends to collect the demographic characteristics and serological indicators of MAFLD patients detected by liver VCTE, and use NMR profiling to perform metabolomic analysis on their peripheral blood and urine samples, in order to discover potential non-invasive biomarkers that can be used to predict and evaluate MAFLD advanced liver fibrosis, and further verify these MAFLD metabolomic indicators that may be associated with advanced liver fibrosis through multi-center clinical studies, in an attempt to provide ideal non-invasive biomarkers for MAFLD progression prediction and clinical intervention monitoring. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05734599
Study type Observational
Source Huazhong University of Science and Technology
Contact Bin Cheng, Doctor
Phone 027-83663334
Email bcheng@tjh.tjmu.edu.cn
Status Not yet recruiting
Phase
Start date March 1, 2023
Completion date May 1, 2024

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