Abstract: FR-OR038
Urinary Metabolomic Age Acceleration Predicts Mortality in Patients with CKD: The CRIC Study
Session Information
- Exciting Developments in CKD Research: From Diagnostics to Management and More
October 23, 2026 | Location: Mile High Ballroom 1D, Convention Center
Abstract Time: 04:40 PM - 04:50 PM
Category: CKD (Non-Dialysis)
- 2202 CKD (Non-Dialysis): Clinical, Outcomes, and Trials
Authors
- Zhang, Ruiyuan, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Liu, Yizhuo, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Li, Mingyue, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Li, Xiang, University of Illinois Chicago College of Medicine, Chicago, Illinois, United States
- Kelly, Tanika, University of Illinois Chicago College of Medicine, Chicago, Illinois, United States
- Grams, Morgan, New York University Grossman School of Medicine, New York, New York, United States
- Bazzano, Lydia, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Chen, Jing, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- He, Jiang, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Li, Changwei, The University of Texas Southwestern Medical Center, Dallas, Texas, United States
Background
Biological age often deviates from chronological age in chronic kidney disease (CKD) due to profound metabolic disruption. We aimed to quantify the deviation using metabolomics approach and evaluate its impact on adverse clinical outcomes in 1,513 Black patients with CKD from the Chronic Renal Insufficiency Cohort (CRIC).
Methods
Metabolomics were profiled using an untargeted approach from baseline 24-hour urine samples. All-cause mortality, cardiovascular disease (CVD), and CKD progression were ascertained during up to 20 years follow-up. Using a 10x5 nested cross-validation framework, we applied elastic net regression to derive an unbiased, out-of-sample metabolomic age (MA). Metabolomic age acceleration (MAA) was calculated as the residual from regressing MA on chronological age, sex, and study site. Associations between MAA and adverse outcomes were analyzed using Cox proportional hazards models adjusted for demographic, lifestyle, and clinical covariates, with stratification by estimated glomerular filtration rate (eGFR) threshold of 30 mL/min/1.73m2. Competing risk was assessed using Fine-Gray models.
Results
At baseline, CRIC participants (51.0% female) had a mean age of 57.8 years and a mean eGFR of 41.9 mL/min/1.73m2. MA was strongly correlated with chronological age (r=0.76). Metabolites in the MA were enriched in amino acid turnover and SLC-mediated tubular transport. Over a median of 13 years of follow-up, 787 deaths occurred. Elevated MAA predicted higher all-cause mortality (Hazard Ratio [HR]: 1.10, per SD increase; 95% Confidence Interval [CI]: 1.01-1.19), with the risk amplified in participants with eGFR ≤ 30 (HR: 1.20; 95% CI: 1.04-1.38) versus those with eGFR > 30 (HR: 1.07; 95% CI: 0.97-1.18, Pinteraction=0.19). While MAA showed no relationship with CKD progression or CVD in cause-specific models, Fine-Gray analysis revealed an inverse association with CKD progression (subdistribution HR: 0.91, 95% CI: 0.85-0.98). This inverse finding underscores a profound competing risk: metabolically frail individuals succumb to systemic mortality before localized kidney failure can manifest, leaving metabolically younger patients to survive to end stage CKD. MAA remained unassociated with CVD in competing risks frameworks.
Conclusion
In CKD, urinary MAA captures systemic vulnerability and mortality risk that is distinct from traditional CVD and CKD progression risk factors.
Funding
- Other NIH Support