Urinary Metabolite Profile Predicting the Progression of CKD

尿液代谢物特征可预测 CKD 进展

阅读:6
作者:Yaerim Kim, Jueun Lee, Mi Sun Kang, Jeongin Song, Seong Geun Kim, Semin Cho, Hyuk Huh, Soojin Lee, Sehoon Park, Hyung Ah Jo, Seung Hee Yang, Jin Hyuk Paek, Woo Yeong Park, Seung Seok Han, Hajeong Lee, Jung Pyo Lee, Kwon Wook Joo, Chun Soo Lim, Geum-Sook Hwang, Dong Ki Kim2

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.

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.

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。