Jueun Lee1, Ji-Young Choi2, Yong-Kook Kwon3, Doohae Lee4, Hee-Yeon Jung2, Hye-Myung Ryu2, Jang-Hee Cho2, Do Hyun Ryu5, Yong-Lim Kim6, Geum-Sook Hwang7. 1. Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Republic of Korea; Department of Chemistry, Sungkyunkwan University, Suwon 16419, Republic of Korea. 2. Division of Nephrology, Department of Internal Medicine, Kyungpook National University School of Medicine, 130, Dongduk-ro, Jung-gu, Daegu 41944, Republic of Korea. 3. Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Republic of Korea. 4. Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Republic of Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea. 5. Department of Chemistry, Sungkyunkwan University, Suwon 16419, Republic of Korea. Electronic address: dhryu@skku.edu. 6. Division of Nephrology, Department of Internal Medicine, Kyungpook National University School of Medicine, 130, Dongduk-ro, Jung-gu, Daegu 41944, Republic of Korea. Electronic address: ylkim@knu.ac.kr. 7. Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Republic of Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, Republic of Korea; Department of Chemistry and Nano Science, Ewha Womans University, Seoul, Republic of Korea. Electronic address: gshwang@kbsi.re.kr.
Abstract
BACKGROUND: The renal dysfunction of chronic kidney disease (CKD) alters serum metabolite levels, but it is not clear how diabetes mellitus (DM) affects the metabolic changes in CKD. METHODS: Serum metabolites from pre-dialysis CKD patients (n=291) with or without DM and from healthy controls (n=56) was measured using nuclear magnetic resonance. RESULTS: Initial principal components analysis and partial least squares-discriminant analysis score plots segregated the CKD patients according to CKD stage and separated DM from non-DM patients. In the CKD patients, associations were seen with clinical characteristics, hyperglycemia, altered amino acid metabolism, accumulated uremic toxins, and dyslipidemia. Of interest, diabetes more strongly affected the metabolic signature during early stage CKD. Furthermore, serum metabolite profiles were successfully applied to the PLS regression model to predict the estimated glomerular filtration rate. The R(2) values from the PLS models for CKD patients with DM were higher than those for CKD without DM. CONCLUSIONS: Metabolomics is useful clinically for providing a metabolic signature that is associated with the CKD phenotype and diabetes more seriously affects patients with early stage CKD compared to those with advanced CKD.
BACKGROUND: The renal dysfunction of chronic kidney disease (CKD) alters serum metabolite levels, but it is not clear how diabetes mellitus (DM) affects the metabolic changes in CKD. METHODS: Serum metabolites from pre-dialysis CKDpatients (n=291) with or without DM and from healthy controls (n=56) was measured using nuclear magnetic resonance. RESULTS: Initial principal components analysis and partial least squares-discriminant analysis score plots segregated the CKDpatients according to CKD stage and separated DM from non-DMpatients. In the CKDpatients, associations were seen with clinical characteristics, hyperglycemia, altered amino acid metabolism, accumulated uremic toxins, and dyslipidemia. Of interest, diabetes more strongly affected the metabolic signature during early stage CKD. Furthermore, serum metabolite profiles were successfully applied to the PLS regression model to predict the estimated glomerular filtration rate. The R(2) values from the PLS models for CKDpatients with DM were higher than those for CKD without DM. CONCLUSIONS: Metabolomics is useful clinically for providing a metabolic signature that is associated with the CKD phenotype and diabetes more seriously affects patients with early stage CKD compared to those with advanced CKD.
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