A metabolomics-based approach for predicting stages of chronic kidney disease

被引:33
作者
Kobayashi, Toshihiro [1 ]
Yoshida, Tatsunari [2 ]
Fujisawa, Tatsuya [3 ]
Matsumura, Yuriko [1 ]
Ozawa, Toshihiko [1 ,4 ]
Yanai, Hiroyuki [1 ]
Iwasawa, Atsuo [1 ]
Kamachi, Toshiaki [1 ]
Fujiwara, Kouichi [3 ]
Kohno, Masahiro [1 ]
Tanaka, Noriaki [3 ]
机构
[1] Tokyo Inst Technol, Grad Sch Biosci & Biochem, Dept Bioengn, Midori Ku, Yokohama, Kanagawa 2268502, Japan
[2] Shimadzu Co Ltd, Global Applicat Dev Ctr, Nakagyo Ku, Kyoto 6048511, Japan
[3] Kiyokai Tanaka Kitanoda Hosp, Higashi Ku, Sakai, Osaka 5998123, Japan
[4] Yokohama Coll Pharm, Totsuka Ku, Yokohama, Kanagawa 2450066, Japan
关键词
CKD; Cystatin C; GFR; LC/MS; OPLS; CHRONIC-RENAL-FAILURE; MASS-SPECTROMETRY; UREMIC TOXINS; CYSTATIN C; PERFORMANCE; PLASMA; RISK;
D O I
10.1016/j.bbrc.2014.02.021
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Chronic kidney disease (CKD) is a major epidemiologic problem and a risk factor for cardiovascular events and cerebrovascular accidents. Because CKD shows irreversible progression, early diagnosis is desirable. Renal function can be evaluated by measuring creatinine-based estimated glomerular filtration rate (eGFR). This method, however, has low sensitivity during early phases of CKD. Cystatin C (CysC) may be a more sensitive predictor. Using a metabolomic method, we previously identified metabolites in CKD and hemodialysis patients. To develop a new index of renal hypofunction, plasma samples were collected from volunteers with and without CKD and metabolite concentrations were assayed by quantitative liquid chromatography/mass spectrometry. These results were used to construct a multivariate regression equation for an inverse of CysC-based eGFR, with eGFR and CKD stage calculated from concentrations of blood metabolites. This equation was able to predict CKD stages with 81.3% accuracy (range, 73.9-87.0% during 20 repeats). This procedure may become a novel method of identifying patients with early-stage CKD. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:412 / 416
页数:5
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