Metabolomics in Traditional Chinese Medicine for Diabetes Mellitus: Mechanistic Insights, Biomarker Discovery, and Clinical Application Prospects

Objective This review provides a comprehensive summary of recent advancements in metabolomic analysis within traditional Chinese medicine (TCM) for the treatment of diabetes mellitus. It focuses on the standardized profiling of syndrome‐specific metabolites, the identification of bioactive compounds using high‐throughput techniques, and the elucidation of mechanisms based on metabolic pathways. The review aims to establish a reproducible analytical framework for TCM metabolomics, which includes identifying active compounds, clarifying mechanisms of action, and assessing therapeutic efficacy. By synthesizing the current body of evidence, this work seeks to provide a scientific foundation for future research, enhance the integration of metabolomics with TCM theory, and support the modernization and global acceptance of TCM in diabetes care. Ultimately, it addresses key challenges, such as the subjective nature of syndrome diagnosis and the complexity of multicomponent interactions. Subjects and Methods A systematic review of the peer‐reviewed literature was conducted using PubMed, Web of Science, CNKI, and Wanfang Data for studies published up to 2025. The review included original research, reviews, and clinical trials that utilized metabolomic techniques (LC‐MS/MS, GC‐MS, and 600 MHz NMR) and standardized workflows (sample preparation, derivatization, instrument analysis, and data processing) in diabetic models. The qualitative synthesis focused on high‐throughput analytics, multivariate statistics (principal component analysis/partial least squares‐discriminant analysis PCA/PLS‐DA with 7‐fold cross‐validation and CV‐ANOVA, p 1, p < 0.05) and arachidonic acid (limit of detection LOD = 0.01–0.1 ng/mL), as well as the accumulation of turbid toxins involving pantothenate and CoA biosynthesis. Key hypoglycemic bioactive compounds, such as epicatechin and berberine, were identified using ultraperformance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry (UPLC‐QTOF‐MS), with a mass error of < 5 ppm. Mechanistic studies have shown that TCM works through multiple pathways, including improving insulin resistance (e.g., mulberry leaves modulating amino acid/lipid metabolism); protecting β‐cells (e.g., timosaponin BII restoring phosphatidylserine levels); regulating glycolipid metabolism (e.g., Huanglian decoction influencing energy‐related metabolites); modulating gut microbiota (e.g., Gegen Qinlian decoction altering bile acids and short‐chain fatty acids); and preventing complications (e.g., Sophora flavescens affecting oxidative stress through glycerophospholipid metabolism). Furthermore, metabolomics enabled efficacy comparisons, highlighting improved outcomes with nanoformulations or exercise‐TCM combinations. Conclusions Metabolomics provides a powerful approach to objectively assess TCM syndromes, clarify multitarget mechanisms, and comprehensively evaluate efficacy in diabetes treatment, which aligns well with TCM’s holistic principles. Despite existing challenges, such as the lack of standardized TCM syndrome classification and the complexity of metabolomic data (e.g., overlapping metabolite signals and multipathway crosstalk), future studies should focus on rigorous experimental designs, standardized protocols, and multiomics integration to promote biomarker discovery, personalized TCM, and its global integration into diabetes management.