Metabolic Profiling of Type 2 Diabetes Patients Reveals Metformin-Associated Alterations in Metabolic Pathways

Abstract

Type 2 diabetes mellitus (T2D) is emerging as a serious health problem worldwide, requiring attentive consideration of treatment strategies to optimize patient outcomes. Metformin is widely used as a first-line treatment drug for T2D. However, it is reported that the drug effect is not sufficiently exhibited in about 15% of patients. This is presumed to be due to the fact that the mechanism of metformin has not been fully identified, and there are differences in drug response according to the metabolic characteristics of individual patients. Therefore, there is an urgent need for an in-depth understanding of the metabolic effects of metformin and development of an individual drug response prediction model.Therefore, this study aims to closely analyze metabolic changes following metformin treatment to better understand the metabolic effects and mechanisms underlying the variability in metformin response.Large-scale metabolite profiling was performed on 530 T2D patient samples, and the metabolite profiles between metformin-administered and non-administrative groups were compared. The purpose of this study was to identify the metabolic pathways that change significantly depending on whether metformin is administered or not, and to understand the mechanism of action of metformin at the metabolite level.This study aims to identify the metabolic pathways that change significantly depending on metformin administration and understand the mechanisms underlying metformin response heterogeneity at the metabolite level. In conclusion, the results of this study are expected to provide novel insights regarding differences in metformin response, contributing to personalized treatment strategies through an integrated analysis of metabolite and clinical information. Future studies will evaluate the clinical utility of identified pathways and create a more refined understanding by integrating various omics data, such as genome and lifestyle information.