J Endocrinol Invest. 2026 Jul 23. doi: 10.1007/s40618-026-02989-y. Online ahead of print.
ABSTRACT
BACKGROUND: With the advancement of proteomics technologies, an increasing number of studies have begun to examine semaglutide-associated protein expression changes and pathway alterations across different biological contexts. However, existing evidence remains fragmented across different disease backgrounds, sample types, and research platforms, lacking systematic integration.
METHODS: This review searched PubMed, Embase, and Web of Science for relevant studies published as of April 2026, including population-based, animal, and in vitro model studies that implemented semaglutide interventions and reported proteomic results.
RESULTS: A total of 16 studies were ultimately included, comprising 4 population-based studies and 12 animal and in vitro model studies. The included studies examined both circulating samples and tissue-level specimens, including serum, plasma, adipose tissue, myocardium, aorta, lung, kidney, hippocampus, and skeletal muscle. Common proteomics platforms utilized included SomaScan, TMT-LC-MS/MS, DIA proteomics, phosphorylation proteomics, and mitochondrial proteomics. Multiple studies identified the PPAR signaling pathway, oxidative phosphorylation, and fatty acid metabolism as frequently occurring pathways, while ECM remodeling, complement/inflammatory pathways, and mTORC1 signaling were also observed in some studies. These results suggest that semaglutide is associated with proteomic changes across metabolic, cardiovascular, hepatic, pulmonary, renal, and nervous systems, with recurring signals involving fatty acid metabolism, mitochondrial function, inflammatory protein networks, and extracellular matrix-related pathways.
CONCLUSION: Overall, proteomic evidence provides a useful molecular framework for describing semaglutide-associated biological responses across multiple tissues. However, existing studies still have limitations such as small sample sizes, high subject heterogeneity, significant differences in proteomic platforms, and limited population studies. Therefore, future research will require larger sample sizes, standardized designs, and multi-omics integration studies to further determine which proteomic signatures are reproducible, biologically meaningful, and clinically translatable.
PMID:42489869 | DOI:10.1007/s40618-026-02989-y