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

• Published in: Biochemical and biophysical research communications Vol. 445; no. 2; pp. 412 - 416
• Main Authors: Kobayashi, Toshihiro, Yoshida, Tatsunari, Fujisawa, Tatsuya, Matsumura, Yuriko, Ozawa, Toshihiko, Yanai, Hiroyuki, Iwasawa, Atsuo, Kamachi, Toshiaki, Fujiwara, Kouichi, Kohno, Masahiro, Tanaka, Noriaki
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 07.03.2014
• Subjects: Adult; Aged; Aged, 80 and over; blood; Chromatography, Liquid - methods; CKD; Cystatin C; Cystatin C - blood; Cystatin C - metabolism; Early Diagnosis; equations; Female; GFR; Glomerular Filtration Rate; hemodialysis; Humans; Kidney - metabolism; Kidney - physiopathology; kidney diseases; LC/MS; Linear Models; liquid chromatography; Male; mass spectrometry; Mass Spectrometry - methods; metabolites; metabolomics; Metabolomics - methods; Middle Aged; Multivariate Analysis; OPLS; patients; prediction; Renal Insufficiency, Chronic - blood; Renal Insufficiency, Chronic - diagnosis; Renal Insufficiency, Chronic - physiopathology; risk factors; volunteers; eGFR; LC/MS; GFR; HMDB; CysC; K/DOQI; Cystatin C; IS; CKD; OPLS
• ISSN: 0006-291X; 1090-2104; 1090-2104
• DOI: 10.1016/j.bbrc.2014.02.021

•Metabolites indicative of CKD were formerly identified using a metabolomic method.•In this study, CKD-related plasma metabolites were quantified by LC/MS.•A multivariate regression equation was constructed using nine plasma metabolites.•This equation was predictive of the severity of CKD.•This may be a novel method of identifying patients with early-stage CKD. 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.