Bioinformatics Analysis Identifies the Association Between Glucose Markers and Disease-Related Functions in Diabetes

Diabetes, a chronic disease characterized by insufficient insulin production, affects approximately 422 million people globally.While researchers have achieved notable advancements in identifying new blood and tissue-based biomarkers related to diabetes, a more detailed and comprehensive investigation is needed.In this study, we conducted a systematic bioinformatics analysis using the Diabetes Complications Early Warning database to examine these associations.First, we identified the association of glucose-related markers with major markers related to blood lipid metabolism, renal function, and liver function.Second, we applied bioinformatics analysis to screen for major markers and diseases capable of categorizing subpopulations within the diabetic population and identified twelve blood markers and four disease markers.We discover that complete blood count (CBC) and blood chemistry (BC) biomarkers of different diabetic patients exhibit subtle changes in their performances.This may be attributed to their differential diabetic complications.Our study enhances the understanding of diabetes mechanisms and provides new avenues for developing precision medicine and therapeutic strategies.