Jai-Sing Yang, Hong-Yi Chiu, Syun-Rong Jhan, Yao-An Liu, Chao-Jung Chen, Shih-Chang Tsai
Journal: International journal of molecular sciences 2026;27(15):
PMID: 42589269
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide and is characterized by excessive hepatic lipid accumulation and metabolic dysfunction. Although microRNA-34a (miR-34a) has been implicated in hepatic lipid metabolism, the molecular mechanisms underlying its contribution to MASLD remain incompletely understood. Here, we investigated the role of miR-34a in FFA-induced hepatic steatosis using HepG2 cells and explored RXR-associated signaling as a potential therapeutic strategy. RT-qPCR quantified miR-34a expression; direct target interactions were validated using dual-luciferase reporter assays; proteomic alterations were characterized by iTRAQ-based proteomics followed by Ingenuity Pathway Analysis (IPA); and transcriptomic responses to 9-cis-retinoic acid (9-cis-RA) were analyzed by RNA sequencing. FFA treatment significantly increased miR-34a expression, and dual-luciferase assays confirmed that miR-34a directly targets the 3'-UTRs of RXRα, PPARα, and SIRT1. Integrated proteomic and transcriptomic analyses consistently identified LXR/RXR signaling as one of the principal pathways associated with miR-34a dysregulation and 9-cis-RA treatment. Pharmacological activation of RXR-associated signaling with the pan-RXR agonist 9-cis-RA attenuated intracellular lipid accumulation and reduced the expression of key regulators of lipogenesis and fatty acid uptake, including FASN, SCD1, FABP4, and CD36. Collectively, these findings support the miR-34a-RXRα axis as one regulatory component within a broader nuclear receptor network associated with hepatic lipid homeostasis and support further investigation of RXR-associated signaling as a potential therapeutic strategy for MASLD. Nevertheless, confirmation of receptor-specific mechanisms and validation in more physiologically relevant experimental models will be required.
© Copyright 2026, Nutrition Evidence
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