NMR-based Metabolic Profiling Identifies High Risk of MAFLD Patients With Advanced Fibrosis

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.

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.

Eligibility Criteria:
Inclusion Criteria:

* Patients with MAFLD

  * Meet the diagnostic criteria in the 2020 Asian Pacific Association for the Study of the Liver (APASL) Clinical Practice Guidelines for the Diagnosis and Management of Metabolism-Related Fatty Liver Disease
  * Liver Vibration-controlled Transient Elastography (FibroTouch) with evidence of hepatic steatosis (CAP value≥ 240db/m)
  * Age≥ 18 years

Healthy controls:

* Liver Vibration-controlled Transient Elastography (FibroTouch) showed no fatty liver and no liver fibrosis;
* No history of other chronic diseases, no use of appropriate prescription drugs;
* The amount of alcohol consumed was ≤8 g per day for women and ≤16g per day for men.

Exclusion Criteria:

* • Chronic viral hepatitis, alcoholic liver disease or excessive alcohol consumption (more than 30 g of alcohol per day for men and 20 g for women), decompensated cirrhosis;

  * Chronic liver disease due to other causes (e.g., autoimmune hepatitis, primary biliary cirrhosis, primary sclerosing cholangitis, hereditary hemochromatosis, Wilson disease, alpha-1 antitrypsin deficiency, celiac disease)
  * Imaging findings suggest a malignant mass of the liver;
  * Patients with other malignant tumors (excluding cured ones);
  * Have secondary obesity due to endocrine, genetic, metabolic, and central nervous system diseases. Judge by professional doctors whether it is hypothalamic obesity, pituitary obesity, hypothyroid obesity, obesity caused by Cushing's syndrome and hypogonadal obesity;
  * Have received or are currently receiving medical or surgical treatment for weight loss in the past three months or are currently being treated;
  * Weight fluctuations of ≥ 5 kg over the past two months;
  * Currently pregnant or nursing;
  * Severe cardiovascular and cerebrovascular disease or stage III hypertension;
  * Hepatitis B, active tuberculosis, AIDS and other infectious diseases;
  * Those who are unable to sign the informed consent form (such as mental illness and drug addiction, etc.).