More than 30% of patients with type 1 diabetes develop diabetic kidney disease (DKD), which significantly increases 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 proteins, called MG adducts. Urinary MG adducts were measured in samples from patients with type 1 diabetes enrolled in DCCT/EDIC who did (case patients; n = 90) or did not (control patients; n = 117) develop DKD. Univariate and multivariable analyses revealed that measurements of MG adducts independently predict DKD 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, and to aid in identifying at-risk individuals and personalized risk management.

Article Highlights
  • Diabetic kidney disease (DKD) is a common cause of death in patients with type 1 diabetes, and there is an unmet need to identify novel biomarkers to predict DKD.

  • We sought to elucidate if methylglyoxal adducts, which are a marker of altered metabolism, have predictive utility for DKD in patients with type 1 diabetes.

  • We found that methylglyoxal adducts predict the risk of DKD at least 16 years before diagnosis.

  • Our data present a novel class of biomarkers with potential utility for predicting DKD risk to supplement existing tools such as HbA1c, albumin excretion rate, and glomerular filtration rate.

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

Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/journals/pages/license.
You do not currently have access to this content.