Urinary Metabolite Profile Predicting the Progression of CKD

Author:

Kim Yaerim1ORCID,Lee Jueun2ORCID,Kang Mi Sun2,Song Jeongin3,Kim Seong Geun4ORCID,Cho Semin5,Huh Hyuk6,Lee Soojin7,Park Sehoon38,Jo Hyung Ah9,Yang Seung Hee10,Paek Jin Hyuk1,Park Woo Yeong1ORCID,Han Seung Seok3ORCID,Lee Hajeong3,Lee Jung Pyo1112,Joo Kwon Wook312ORCID,Lim Chun Soo1112ORCID,Hwang Geum-Sook213,Kim Dong Ki312ORCID

Affiliation:

1. Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea

2. Integrated Metabolomics Research Group, Western Seoul center, Korea Basic Science Institute, Seoul, Republic of Korea

3. Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea

4. Department of Internal Medicine, Inje University Sanggye Paik Hospital, Seoul, Korea

5. Department of Internal Medicine, Chungang University Gwangmyeong hospital, Gyeonggi-do, Korea

6. Department of Internal Medicine, Inje University Busan Paik Hospital, Busan, Korea

7. Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Korea

8. Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea

9. Department of Internal Medicine, Inje University Ilsan Paik Hospital, Ilsan, Korea

10. Kidney Research Institute, Seoul National University, Seoul, Korea

11. Department of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, Korea

12. Departement of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea

13. College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea

Abstract

Key Points As a biomarker, urinary metabolites could bridge the gap between genetic abnormalities and phenotypes of diseases.We found that levels of betaine, choline, fumarate, citrate, and glucose were significantly correlated with kidney function and could predict kidney outcomes, providing prognostic biomarkers in CKD. Background Because CKD is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted. Methods We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy participants using nuclear magnetic resonance. The composite outcome was defined as a 30% decline in eGFR, doubling of serum creatinine levels, or end-stage kidney disease. Results Among the 28 candidate metabolites, we identified seven metabolites showing (1) good discrimination between healthy controls and patients with stage 1 CKD and (2) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the seven metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein–creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P < 0.05) and integrated discrimination improvement (P < 0.05) to predict the composite outcome. Conclusion Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury–related metabolites, it would be warranted to monitor to predict the renal outcome.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Psychiatry and Mental health,Neuropsychology and Physiological Psychology

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