Over 30% of patients with type 1 diabetes develop diabetic kidney disease (DKD), significantly increasing mortality risk. The Diabetes Control and Complications Trial (DCCT) and follow-up study Epidemiology of Diabetes Interventions and Complications (EDIC) established that glycemic control measured by HbA1c predicts DKD risk. However, the continued high incidence of DKD reinforces the urgent need for additional biomarkers to supplement HbA1c. Here, we assessed biomarkers induced by methylglyoxal (MG), a metabolic by-product that forms covalent adducts on DNA, RNA, and protein called MG-adducts. Urinary MG-adducts were measured from patients with type 1 diabetes enrolled in DCCT/EDIC who did (cases, n=90) or did not (controls, n=117) develop DKD. Univariate and multivariable analysis revealed that measurements of MG-adducts independently predict DKD, even before established DKD biomarkers such as glomerular filtration rate and albumin excretion rate. Elevated levels of MG-adducts bestowed the greatest risk of developing DKD in a multivariable model that included HbA1c and other clinical covariates. Our work establishes a novel class of biomarkers to predict DKD risk and suggests that inclusion of MG-adducts may be a valuable tool to improve existing predictors of complications like DKD prior to overt disease to aid in identifying at-risk individuals and personalized risk management.

This article contains supplementary material online at https://doi.org/10.2337/figshare.24550600.

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