Metabolically Dysfunctional-associated Steatotic Liver Disease (MASLD) is a spectrum of diseases that starts with the accumulation of excessive fat within the hepatocytes of healthy individuals, leading to liver inflammation and can progress to advanced scarring (cirrhosis), Hepatocellular Carcinoma (HCC), and liver failure. Common radiologic tests and serum-based surrogate markers are used; however, operator dependence, radiological exposure, and affordability are major limitations. Furthermore, while liver biopsy is the gold standard for MASLD staging, it is significantly limited by its invasiveness, sampling variability, and potential interobserver variability. Thus, finding novel non-invasive markers for diagnosis and prognosis is necessary.
Lipids and metabolites play a significant role in the remodelling of MASL to its more severe forms. In this study, we performed comprehensive global plasma lipidomics profiling of non-MASLD healthy individuals, MASLD, and HCC patients. Plasma samples were subjected to liquid-liquid extraction using a cold methanol and dichloromethane (MeOH/DCM) protocol developed in laboratory with previous modifications. Profiling was performed utilising a Vanquish UHPLC system coupled to an Orbitrap mass spectrometer with an HSST3 column. The platform operated in positive and negative polarity with an Orbitrap resolution of 120,000 and a scan range of 70–1500. Analytical stability was monitored by injecting a quality control (QC) sample at the beginning of the batch and after every 10 experimental samples. Data processing and lipid identification were conducted using Compound Discoverer by employing strict screening criteria, including QC, high mass accuracy and MS2 scores.
We performed systematic comparisons of MASLD, Cirrhosis and HCC patients from healthy individuals to observe substantial alterations in lipid classes, such as Sphingolipids, glycerolipids and phospholipids, which were strongly associated with MASLD stage and disease severity to hold significant promise for development as non-invasive diagnostic and prognostic markers for predicting disease severity and establishing clinico-pathological correlations.