Kidney Week

Abstract: SA-PO0436

Urinary Metabolomic Signatures Predict Rapid eGFR Decline in the Cardiovascular-Kidney-Metabolic (CKM) Syndrome Population

Session Information

• CKM: Clinical - Epidemiology and Outcomes
  October 24, 2026 | Location: Exhibit Hall A, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Cardiovascular-Kidney-Metabolic Health

• 602 Cardiovascular-Kidney-Metabolic Health: Clinical

Authors

• Shi, Caifeng, Center for Kidney Diseases, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

Caifeng Shi, MD

• Liu, Shuo, Center for Kidney Diseases, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

Shuo Liu, MMSc

• Zong, Biao, Center for Kidney Diseases, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

Biao Zong, MBBS

• Dai, Chunsun, Center for Kidney Diseases, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

Chunsun Dai, MD, PhD

• Zhou, Yang, Center for Kidney Diseases, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

Yang Zhou, MD, PhD

Background

Among individuals with cardiorenal-metabolic (CKM) syndrome, a subset experiences rapid kidney function decline difficult to identify by routine monitoring. CKM syndrome substantially alters the urinary metabolome. This study aimed to determine whether urinary metabolomic profile predicts rapid kidney disease progression in the CKM population.

Methods

CKM patients were classified by annualized eGFR slope: rapid progression (>5 mL/min/1.73 m²/year decline) versus stable (slower decline). Baseline urinary metabolites were quantified by targeted mass spectrometry and normalized to urinary creatinine. Differential metabolites were identified by univariate Welch's t-test, followed by LASSO regression. The intersection set was combined into a logistic model, with performance assessed by AUC and benchmarked against baseline urinary protein.

Results

Of 326 CKM patients enrolled (median age 56 [IQR 46–61] years; median follow-up 42 [22.5–56] months), 73 were rapid-progressors (median slope −8.88) and 253 stable (median slope −1.32 mL/min/1.73 m²/year). Of 254 urinary metabolites, 21 were significant by t-test (19 higher in rapid-progressors including LPC 18:2 and oxalic acid; 2 lower); 16 were retained by LASSO. The 7-metabolite intersection set (including LPC 18:1) achieved an AUC of 0.75 for predicting rapid eGFR decline, outperforming baseline urinary protein (AUC 0.66).

Conclusion

A composite baseline urinary metabolite signature predicts rapid kidney function decline in CKM patients and outperforms proteinuria. Urinary metabolomic profiling may improve early risk identification for kidney disease progression in the CKM population and warrants validation in independent cohorts.

Funding

• Government Support – Non-U.S.