Novel biomarkers of kidney disease in type 1 diabetes

The National Institute of Diabetes and Digestive and Kidney Diseases awarded the University of Pittsburgh $812,862 on June 12, 2026, under the Diabetes, Digestive, and Kidney Diseases Extramural Research program (CFDA 93.847) to identify novel biomarkers of early progressive kidney function decline in type 1 diabetes.

The research will use urinary and plasma peptidomics—analysis of synthesized peptides and protein degradation fragments—to discover prognostic markers that predict diabetic kidney disease progression before clinical albumin and glomerular filtration rate changes become detectable. The study addresses gaps in existing literature by examining degradome changes over time in relation to clinical endpoints including end-stage kidney disease, integrating protease activity and genetic factors causally linked to kidney disease, and including diverse populations across sex, glycemic control intensity, and non-white participants. The investigation uses existing data and biological samples from three well-phenotyped type 1 diabetes cohorts, including the EDC cohort.

Work is performed in Pittsburgh, Pennsylvania. The period of performance runs through March 31, 2030. The award is classified as a Project Grant, the primary assistance type under the program for investigator-initiated basic and clinical research.

Abstract

Diabetic kidney disease (DKD) continues to be a highly prevalent and severe complication of type 1 diabetes (T1D). However, although its early detection and prevention is of utmost importance, current screening recommendations are based on annual assessments of urinary albumin excretion rate and glomerular filtration rate (GFR), changes that become detectable only after the biological processes causing kidney impairment have already been initiated. Our objective is to identify new, reliable, minimally invasive, prognostic markers of early progressive kidney function decline (ERFD) in T1D. The peptidome comprises an array of synthesized peptides and degraded protein fragments (i.e., degradome), whose differential abundance and/or excretion may provide clues into the underlying processes leading to DKD, then leading to the discovery of new biomarkers for early DKD prognosis. Indeed, urinary peptidomics have shown good potential in identifying albuminuria and ERFD in diabetes. However, these studies have been limited by small sample sizes and have generally not considered urine and plasma degradome, degradome changes over time, or their prognostic value for endpoints of clinical therapeutic relevance (i.e., eskd). Existing studies have also not addressed the degradome - DKD association by intensive T1 therapy or SEX, nor have they included non-white persons. Our study will fill these knowledge gaps while also assessing degradome integration with imputed protease activity and genetic/clinical factors causally linked to DKD. Our hypothesis is that urinary/plasma degradome independently predicts both early (ERFD) and advanced (doubling of serum creatinine / end-stage kidney disease, dscr/eskd) DKD in T1D overall, by glycemic control, intensive therapy, and SEX. We will investigate this hypothesis using existing data and samples from three well-phenotyped T1D cohorts: (1) the EDC (N=470, urine/plasma); (2) the dcct/edic trial (N=517, urine); and (3) the new jersey (NJ) 725 (african americans, N=169, urine/plasma). We will measure unbiased peptidomics in stored samples and develop innovative machine learning models to predict incident early and advanced DKD, using baseline and longitudinal multi-modal data, including T1D-specific (e.g., glycemic control), clinical (e.g., lipids), demographic (e.g., age, SEX), and genetic features. Immunoassays will be used to screen and validate a select set of degradomic markers. Finally, our analyses will extend to an interventional cohort to investigate the effect of intensive T1D treatment. In analysis of trajectories, we will identify SEX-specific and general patterns of change in degradomic features over time and test their ability to predict early/advanced DKD. At the conclusion of this study, we will have identified novel, unique and shared, urine/plasma biomarkers of early and advanced DKD in T1D overall, by SEX and prior intensive therapy in black and white men and women with T1D, generating hypotheses of interactions among clinical, molecular and gwas data. We will thus provide insight on the most relevant factors for ERFD and dscr/eskd, potentially identifying novel targets for therapeutic interventions/drug development.