Epigenetic determinants of GLP-1 responsiveness: Integrating dietary modulation beyond genetics

초록

Glucagon-like peptide-1 receptor (GLP-1R) agonists have become major therapeutic agents for obesity and type 2 diabetes, yet clinical responses vary substantially among individuals. Although genetic variation contributes to this heterogeneity, it does not fully explain differences in glycemic control, body weight reduction, or broader metabolic outcomes. This narrative review discusses diet-driven epigenetic regulation as a potential framework linking modifiable nutritional exposures to GLP-1 physiology and variability in GLP-1R agonist responsiveness. Endogenous GLP-1 biology and the pharmacological targeting of incretin signaling are first summarized, followed by genetic determinants of GLP-1 responsiveness and their limitations. Major diet-sensitive regulatory mechanisms are then examined, including one-carbon metabolism and DNA methylation, histone modification and chromatin remodeling, microbiome-derived metabolites, and RNA-mediated or epitranscriptomic regulation. These mechanisms may influence endogenous GLP-1 secretion and degradation, GLP-1R expression, β-cell functional capacity, and the broader metabolic or inflammatory context in which incretin signaling occurs. However, direct clinical evidence linking diet-induced epigenetic changes to GLP-1R agonist therapeutic response remains limited. Therefore, diet–epigenome interactions should be interpreted as plausible modifiers of GLP-1-related metabolic biology rather than established determinants of pharmacological efficacy. Future studies integrating dietary assessment, gut hormone profiling, microbiome analysis, epigenomic markers, and multidimensional therapeutic outcomes are needed to determine whether diet-sensitive molecular signatures can support precision nutrition strategies alongside GLP-1-based therapy. © 2026 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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