Kidney Week

Abstract: SA-PO795

Urinary Metabolites Associated with Non-Diabetic CKD Progression

Session Information

• CKD: Epidemiology, Risk Factors, Prevention - III
  October 27, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

• 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Yun, Sohyun, Seoul National University, Seoul, Korea (the Republic of)

Sohyun Yun,

• Han, Miyeun, Pusan National University, Pusan, Korea (the Republic of)

Miyeun Han,

• Ryu, Hyunjin, Seoul National University, Seoul, Korea (the Republic of)

Hyunjin Ryu,

• Kang, Eunjeong, Seoul National University, Seoul, Korea (the Republic of)

Eunjeong Kang,

• Kang, Minjung, Seoul National University, Seoul, Korea (the Republic of)

Minjung Kang,

• Bodokhsuren, Tsogbadrakh Bodokhsuren, Seoul National University, Seoul, Korea (the Republic of)

Tsogbadrakh Bodokhsuren Bodokhsuren,

• Lee, Jinho, Seoul National University, Seoul, Korea (the Republic of)

Jinho Lee,

• Ahn, Curie, Seoul National University, Seoul, Korea (the Republic of)

Curie Ahn,

• Oh, Kook-Hwan, Seoul National University, Seoul, Korea (the Republic of)

Kook-Hwan Oh,

Background

Metabolome analyses have been on the rise recently for the discovery of biomarkers for chronic kidney disease. Urinary metabolome can be appropriate prognostic markers to predict CKD progression.

Methods

We conducted a case-control study comparing progressor (case) with non-progressor (control) in non-diabetic chronic kidney disease patients (polycystic kidney disease excluded). Urine samples and clinical data were taken from the KoreaN Cohort Study for Outcome in Patients With Chronic Kidney Disease (KNOW-CKD). These random urine samples were harvested at enrollment. Participants were followed-up for eGFR at 6- or 12-month interval for > 2 years. Subjects of the study were 100 individuals that are comprised of 50 progressors and 50 non-progressors with their age, gender and initial eGFR values matched. Progressor and non-progressor group were divided on the basis of estimated GFR slope, which revealed -0.91±0.75 and 1.43±1.23 ml/min/1.73m²/yr, respectively. The urinary metabolite profiling was performed with an untargeted metabolomics approach using ultra-performance liquid chromatography time-of-flight mass spectrometry in conjugation with multivariate statistical analysis.

Results

A total of 9,345 compound ions were detected in positive ion mode, and 27 endogenous ions satisfied the false discovery rate adjusted p-value (Q-value). Among them, three candidate markers were discovered; X, Y and Z. These three metabolites showed statistically significant difference between CKD progressor and non-progressor group. X and Y had higher concentration in non-progressors unlike Z which were lower in concentration from non-progressors.

Conclusion

We identified three urinary metabolic markers associated with renal progression of non-diabetic chronic kidney disease. They can provide information to predict CKD progression as prognostic markers.

Funding

• Government Support - Non-U.S.