Extracellular vesicles and microRNAs in metabolic dysfunction-associated steatotic liver disease: from steatosis to...

Extracellular vesicles (EVs) and microRNAs, involved in intercellular communication, have emerged as potential biomarkers in liver diseases. This study aimed to evaluate EV characteristics and microRNA transport across the full spectrum of metabolic dysfunction-associated steatotic liver disease (MASLD). 168 patients with MASLD and 50 controls were recruited. Biochemical and clinical variables were evaluated. EVs were isolated from serum and characterized by nanoparticle tracking analysis, flow cytometry, and Western blotting. Using MiRWalk 3.0 and the TarPmiR algorithm, candidate EV-associated microRNAs related to MASLD were identified. The expression of miR-4758, miR-188, miR-1226, and miR-122, was evaluated in EVs and serum. EV size and concentration varied significantly across disease stages (p<0.001 and p<0.05, respectively), with early MASLD dominated by exosome, and later stages showing a shift toward microvesicles. In MASLD patients, interestingly, miR-122 was lower in EVs compared to serum (p<0.05). In steatosis, it was higher in serum than EVs (p<0.05), without significant differences in later stages. miR-122 in EVs increased in association with GGT and cholesterol, and decreased with elevated creatinine. Serum miR-122 was also elevated in patients with high cholesterol. In MASLD miR-4758 was higher in EVs than in serum (p<0.05), expressed in steatosis and cirrhosis (p<0.05), suggesting it is a good disease marker, and detected exclusively in serum in HCC (p<0.05). miR-4758-EVs increased with high glucose. MiR-188 and miR-1226 were exclusively expressed in serum (p<0.05), and miR-1226 was elevated in patients with high cholesterol. EV size was reduced in individuals with high triglycerides and albumin, suggesting interaction between EVs, biochemical parameters and disease stage. These findings suggest that microRNA expression and transport in EVs and serum vary across MASLD stages and associate with key biochemical parameters, supporting the clinical value of jointly assessing both compartments as potential biomarkers to distinguish early disease from advanced stages such as HCC. See also the graphical abstract(Fig. 1).