Effects of Balanced Dietary Patterns and/or Integrated Exercise on Serum 1,5-Anhydroglucitol and CVD Risk Factors in Individuals with Prediabetes

TL;DR

This study identifies 1,5-anhydroglucitol as a key biomarker for diabetes progression and shows that lifestyle changes can improve blood sugar levels in prediabetic individuals.

Contribution

The study introduces 1,5-anhydroglucitol as a sensitive biomarker for dysglycemia that responds to lifestyle interventions.

Findings

1,5-anhydroglucitol (1,5-AG) effectively differentiates prediabetic from diabetic individuals with high accuracy.

A combined diet and exercise intervention improved blood glucose markers and increased serum 1,5-AG levels in prediabetic individuals.

The intervention showed a trend toward reduced diabetes incidence but had limited impact on cardiovascular risk factors like BMI and blood pressure.

Abstract

This study aimed to identify metabolomic biomarkers for diabetes progression and validate their response to lifestyle intervention. A two-phase design was employed: first, untargeted metabolomics distinguished normoglycemic, prediabetic (PDM), and diabetic (DM) individuals, identifying 1,5-anhydroglucitol (1,5-AG) as the most significant biomarker for differentiating PDM from DM (apparent AUC = 0.97, 95% CI: 0.95–1.00; corrected AUC = 0.94, 95% CI: 0.83–1.00; q < 0.001). Second, in a 3-month randomized controlled trial involving 300 adults with PDM, the combined diet and exercise intervention significantly improved fasting blood glucose and glycated hemoglobin levels, while concurrently elevating serum 1,5-AG levels compared with the control group, though it did not yield significant improvements in other cardiovascular disease-related risk factors including body mass index, waist circumference, systolic blood pressure, and diastolic blood pressure. The intervention also showed a trend toward reduced diabetes incidence. Integrated analysis establishes 1,5-AG as a sensitive biomarker of dysglycemia that is responsive to lifestyle modification, supporting its potential as a mechanistic tool for monitoring intervention efficacy in diabetes prevention.

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