Endocrine Abstracts

Metabolic dysfunction-associated steatotic liver disease (MASLD) results from excessive fat accumulation in the liver while metabolic dysfunction-associated steatohepatitis (MASH) is the progressive, inflammatory form that can lead to fibrosis, cirrhosis, and liver cancer. Patient heterogeneity, variable disease progression and diagnostic challenges complicate early MASLD detection. Novel biomarkers of disease may be revealed by spatial disease-specific lipidomic profiles through matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). Human liver biopsy samples (n=30, 32-83y) from the HepaT1ca study (ClinicalTrials.gov NCT03213314) were categorized by %fat content (low<5%, medium 5-33%, high>33%) based on histology, with 5 samples/sex/group. MALDI-MSI was applied for untargeted lipid profiling at 75-micron resolution on a SYNAPT G2-Si qToF-MS (Waters Corp.). LipidMaps database was used for lipid identification while data were processed using MassLynx^TM and Lipostar MSI^TM software. Statistical analyses, including sum normalization and Pareto scaling, were performed in MetaboAnalyst. Lipid markers distinguishing groups and sex were identified using partial least squares discriminant analysis (PLS-DA), orthogonal PLS-DA and variable importance for projection (VIP) scores. PLS-DA showed clear separation between the %fat groups, with components 1 and 2 explaining 12% and 16.8% variance, respectively. The high-fat group had a distinct lipid profile, while the mid and low-fat groups overlapped. Sex differences in lipid profiles were observed within each %fat group. Key lipid markers distinguishing high- from low-fat groups across sexes included triglycerides (e.g., TG 54:10, VIP score=1.75), diacylglycerols (e.g., DG 36:2, 1.74), and phosphatidylcholines (e.g., PC 32:0, 1.13). In the high-fat group, males had higher levels of phosphatidylcholines (e.g., PC 36:1, 2.2) and lysophosphatidylcholine (e.g., LPC 18:1, 1.8) while females had more phosphatidylcholines (e.g., PC 34:2, 1.0 and PC 38:5, 1.1). Thus, MSI can identify sex-specific biomarkers of liver pathology which may aid early MASH diagnosis or treatment if further explored as imaging tools, blood-based biomarkers, or therapeutic targets.