Urinary Metabolite Profile Predicting the Progression of CKD

被引:3
作者
Kim, Yaerim [1 ]
Lee, Jueun [2 ]
Kang, Mi Sun [2 ]
Song, Jeongin [3 ]
Kim, Seong Geun [4 ]
Cho, Semin [5 ]
Huh, Hyuk [6 ]
Lee, Soojin [7 ]
Park, Sehoon [3 ,8 ]
Jo, Hyung Ah [9 ]
Yang, Seung Hee [10 ]
Paek, Jin Hyuk [1 ]
Park, Woo Yeong [1 ]
Han, Seung Seok [3 ]
Lee, Hajeong [3 ]
Lee, Jung Pyo [11 ,12 ]
Joo, Kwon Wook [3 ,12 ]
Lim, Chun Soo [11 ,12 ]
Hwang, Geum-Sook [2 ,13 ,15 ]
Kim, Dong Ki [1 ,3 ,12 ,14 ]
机构
[1] Keimyung Univ, Sch Med, Dept Internal Med, Daegu 42601, South Korea
[2] Korea Basic Sci Inst, Western Seoul Ctr, Integrated Metabol Res Grp, Seoul 120140, South Korea
[3] Seoul Natl Univ Hosp, Dept Internal Med, Seoul 03080, South Korea
[4] Inje Univ, Sanggye Paik Hosp, Dept Internal Med, Seoul 139707, South Korea
[5] Hanyang Univ, Coll Med, Myongji Hosp, Dept Internal Med, Gyeonggi Do, South Korea
[6] Inje Univ, Busan Paik Hosp, Dept Internal Med, Pusan 633165, South Korea
[7] Uijeongbu Eulji Univ, Med Ctr, Dept Internal Med, Uijongbu, Gyeonggi Do, South Korea
[8] Seoul Natl Univ, Coll Med, Dept Biomed Sci, Seoul, South Korea
[9] Inje Univ, Ilsan Paik Hosp, Dept Internal Med, Goyang, South Korea
[10] Seoul Natl Univ, Kidney Res Inst, Seoul, South Korea
[11] SMG SNU, Boramae Med Ctr, Dept Internal Med, Seoul 156707, South Korea
[12] Seoul Natl Univ, Coll Med, Dept Internal Med, Seoul, South Korea
[13] Chung Ang Univ, Coll Pharm, Seoul, South Korea
[14] Seoul Natl Univ, Coll Med, Dept Internal Med, 101 Daehak-ro,Jongno-gu, Seoul 03080, South Korea
[15] Western Seoul Ctr, Korea Basic Sci Inst, Integrated Metabol Res Grp, 150 Bukahyeon-ro, Seodaemun-gu, Seoul, South Korea
来源
KIDNEY360 | 2023年 / 4卷 / 08期
关键词
CKD; disease progression; urinary metabolites; biomarkers; METABOLOMICS; FUMARATE; DISEASES;
D O I
10.34067/KID.0000000000000158
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页码:1048 / 1057
页数:10
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