Effects of Ellagic Acid on Glucose and Lipid Metabolism: A Systematic Review and Meta-Analysis

Abstract

Background. Abnormal glucose and lipid metabolism (GALM) serve as both a cause and an inducer for the development of the disease. Improvement and treatment of GALM are an important stage to prevent the occurrence and development of the disease. However, current clinical treatment for GALM is limited. Ellagic acid (EA), a common polyphenol present in foods, has been shown to improve abnormalities in GALM observed in patients suffering from metabolic diseases. Objective. This study used a meta-analysis method to systematically assess the effects of EA on GALM. Method. As of November 8, 2023, a comprehensive search was conducted across 5 databases, namely, PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar to identify randomized controlled trials (RCTs) in which EA served as the primary intervention for diseases related to GALM. The risk of bias within the included studies was assessed according to the Cochrane Handbook. All statistical analyzes were performed using RevMan 5.4 software. Results. In this study, a total of 482 articles were retrieved, resulting in the inclusion of 10 RCTs in the meta-analysis. The results showed that EA could reduce fasting blood glucose (FBG) (p=0.008), increase insulin secretion (p=0.01), improve insulin resistance index (HOMA-IR) (p=0.003), decrease triglyceride (TG) (p=0.004), and reduce cholesterol (Chol) (p=0.04) and low-density lipoprotein (LDL-c) (p=0.0004). EA had no significant effect on waist circumference (WC), body weight (BW), body mass index (BMI), 2 hours after prandial blood glucose (2 h-PG), total cholesterol (TC), and high-density lipoprotein (HDL-c). Conclusions. The effect of improvement in glucose and lipids of EA was closely related to the dose and the intervention time. EA can improve GALM caused by diseases. To corroborate the findings of this study and improve the reliability of the results, EA is imperative to refine the research methodology and increase the sample size in future investigations.