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Title: Metabolomic signatures of chronic kidney disease of diverse etiologies in the rats and humans

Abstract

Chronic kidney disease (CKD) has emerged as a major public health problem worldwide. It frequently progresses to end-stage renal disease, which is related to very high cost and mortality. Novel biomarkers can provide insight into the novel mechanism, facilitate early detection, and monitor progression of CKD and its response to therapeutic interventions. To identify potential biomarkers, we applied an UPLC-HDMS together with univariate and multivariate statistical analyses using plasma samples from patients with CKD of diverse etiologies (100 sera in discovery set and 120 sera in validation set) and two different rat models of CKD. Using comprehensive screening and validation workflow, we identified a panel of seven metabolites that were shared by all patients and animals regardless of the underlying cause of CKD. These included ricinoleic acid, stearic acid, cytosine, LPA(16:0), LPA(18:2), 3-methylhistidine, and argininic acid. The combination of these seven biomarkers enabled the discrimination of patients with CKD from healthy subjects with a sensitivity of 83.3% and a specificity of 96.7%. In addition, these biomarkers accurately reflected improvements in renal function in response to the therapeutic interventions. Lastly, our results indicated that the identified biomarkers may improve the diagnosis of CKD and provide a novel tool for monitoring ofmore » the progression of disease and response to treatment in CKD patients.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Northwest Univ., Shaanxi (China)
  3. Univ. of California, Irvine, CA (United States)
  4. Affiliated Hospital of Shaanxi Institute of Traditional Chinese Medicine, Shaanxi (China)
  5. Xi'an No. 4 Hospital. Shaanxi (China)
  6. Water Technologies (Shanghai) Ltd., Shanghai (China)
  7. Northwest Univ., Shaanxi (China); Univ. of California, Irvine, CA (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1350944
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Proteome Research
Additional Journal Information:
Journal Volume: 15; Journal Issue: 10; Journal ID: ISSN 1535-3893
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 5/6 nephrectomized rats; adenine-induced CKD rats; biomarker; chronic kidney disease; enalapril; irbesartan; metabolomics; plasma

Citation Formats

Zhang, Zhi -Hao, Chen, Hua, Vaziri, Nosratola D., Mao, Jia -Rong, Zhang, Li, Bai, Xu, and Zhao, Ying -Yong. Metabolomic signatures of chronic kidney disease of diverse etiologies in the rats and humans. United States: N. p., 2016. Web. doi:10.1021/acs.jproteome.6b00583.
Zhang, Zhi -Hao, Chen, Hua, Vaziri, Nosratola D., Mao, Jia -Rong, Zhang, Li, Bai, Xu, & Zhao, Ying -Yong. Metabolomic signatures of chronic kidney disease of diverse etiologies in the rats and humans. United States. doi:10.1021/acs.jproteome.6b00583.
Zhang, Zhi -Hao, Chen, Hua, Vaziri, Nosratola D., Mao, Jia -Rong, Zhang, Li, Bai, Xu, and Zhao, Ying -Yong. Fri . "Metabolomic signatures of chronic kidney disease of diverse etiologies in the rats and humans". United States. doi:10.1021/acs.jproteome.6b00583. https://www.osti.gov/servlets/purl/1350944.
@article{osti_1350944,
title = {Metabolomic signatures of chronic kidney disease of diverse etiologies in the rats and humans},
author = {Zhang, Zhi -Hao and Chen, Hua and Vaziri, Nosratola D. and Mao, Jia -Rong and Zhang, Li and Bai, Xu and Zhao, Ying -Yong},
abstractNote = {Chronic kidney disease (CKD) has emerged as a major public health problem worldwide. It frequently progresses to end-stage renal disease, which is related to very high cost and mortality. Novel biomarkers can provide insight into the novel mechanism, facilitate early detection, and monitor progression of CKD and its response to therapeutic interventions. To identify potential biomarkers, we applied an UPLC-HDMS together with univariate and multivariate statistical analyses using plasma samples from patients with CKD of diverse etiologies (100 sera in discovery set and 120 sera in validation set) and two different rat models of CKD. Using comprehensive screening and validation workflow, we identified a panel of seven metabolites that were shared by all patients and animals regardless of the underlying cause of CKD. These included ricinoleic acid, stearic acid, cytosine, LPA(16:0), LPA(18:2), 3-methylhistidine, and argininic acid. The combination of these seven biomarkers enabled the discrimination of patients with CKD from healthy subjects with a sensitivity of 83.3% and a specificity of 96.7%. In addition, these biomarkers accurately reflected improvements in renal function in response to the therapeutic interventions. Lastly, our results indicated that the identified biomarkers may improve the diagnosis of CKD and provide a novel tool for monitoring of the progression of disease and response to treatment in CKD patients.},
doi = {10.1021/acs.jproteome.6b00583},
journal = {Journal of Proteome Research},
number = 10,
volume = 15,
place = {United States},
year = {Fri Sep 16 00:00:00 EDT 2016},
month = {Fri Sep 16 00:00:00 EDT 2016}
}

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