SERUM GAMMA-GLUTAMYL TRANSFERASE AS A METABOLIC BIOMARKER OF GLYCAEMIC DYSREGULATION IN DIABETES MELLITUS: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract

Background: Diabetes mellitus is a major global metabolic disorder associated with increasing morbidity and mortality. Identification of inexpensive and accessible biomarkers for early glycaemic dysregulation remains clinically important. Serum gamma-glutamyl transferase (GGT), traditionally considered a hepatic enzyme marker, has recently been linked with oxidative stress, insulin resistance, and metabolic dysfunction. Objective: To systematically evaluate and analyse the association between serum GGT levels and glycaemic dysregulation in patients with diabetes, prediabetes, and impaired fasting glucose. Methods: A systematic review and meta-analysis was performed according to PRISMA 2020 guidelines. Electronic databases including PubMed, Scopus, Embase, Web of Science, and Cochrane Library were searched from inception until March 2025. Observational studies evaluating serum GGT levels in adults with diabetes, impaired fasting glucose, or prediabetes were included. Data extraction and quality assessment using the Newcastle–Ottawa Scale (NOS) were independently performed by reviewers. Random-effects meta-analysis was used to estimate pooled standardized mean differences with 95% confidence intervals. Results: Seventeen observational studies involving 61,189 participants met eligibility criteria for qualitative synthesis, while nine studies were included in quantitative meta-analysis. Pooled analysis demonstrated a significant association between elevated serum GGT levels and impaired glycaemic status. Considerable heterogeneity was observed among studies (I² = 98.81%). Subgroup analysis suggested a stronger association among obese individuals and Asian populations. Funnel plot assessment indicated possible publication bias. Conclusion: Elevated serum GGT levels are significantly associated with impaired glucose metabolism and diabetes risk. GGT may serve as an inexpensive and easily available biomarker for early metabolic risk stratification. Further large scale longitudinal studies are needed to establish causality and standardise clinical application.