Biomarkers for Prediabetes, Type 2 Diabetes, and Associated Complications

Abstract

Purpose: Diabetes mellitus is a chronic disorder caused by high blood glucose levels due to insulin resistance or insufficient insulin production in pancreatic β-cells. Due to its fastest-growing public health concerns worldwide, it is important to evaluate metabolic profile abnormalities before pre-diabetes or T2DM to anticipate and prevent disease progression. The purpose of the study was to examine the metabolite biomarkers by systematic review and meta-analysis to support early detection of pre-diabetes and T2DM. Methodology: Studies published from the earliest online through May 31, 2023, were searched in the Cochrane Library, EMBASE, PubMed, and Scopus. Article titles, abstracts, and complete texts were reviewed after duplicate records were eliminated. Two writers (Long and Yang) created the following inclusion criteria for the publications before literature screening: The study was conducted on humans, did not involve gestational diabetes mellitus (GDM), type 1 diabetes mellitus (T1DM), or subjects under 18 years old, included a diabetic or prediabetes group, and followed international diagnostic guidelines (American Diabetes Association, 2013). Findings: The study aimed to review the biomarkers that have been utilized for diabetes in previous research. The comparison of the biomarkers mentioned in the provided information revealed a complex interplay of factors influencing the risk and management of Type 2 Diabetes (T2D). These biomarkers encompass genetic, lifestyle, environmental, and insulin-related factors, each with varying degrees of accuracy and specificity in predicting T2D risk or guiding its management. Recommendations: The research will help in spreading awareness among people regarding the identification of diabetes as understanding biomarker-based screening's economic impact can inform healthcare policies. Future studies should validate these biomarkers' diagnostic capacities across varied populations and circumstances. Assessment of these biomarkers' predictive usefulness should be done over time via longitudinal research. Understanding biomarker alterations and diabetes progression improves risk prediction.