Entity

Time filter

Source Type

Higashimurayama-shi, Japan

Sato E.,Tohoku University | Kohno M.,Tohoku University | Yamamoto M.,Kiyokai Hojyo Tanaka Hospital | Fujisawa T.,Kiyokai Tanaka Kitanoda Hospital | And 2 more authors.
European Journal of Clinical Investigation | Year: 2011

Background Urea and creatinine are widely used as biomarkers for disease. However, these parameters have been criticized as markers for several reasons. Thus, we conducted this study to identify novel biomarkers that can be used as alternatives to urea and creatinine to estimate the adequate dialysis dose by metabolomic analyses of plasma samples from patients undergoing haemodialysis. Material and methods Liquid chromatography-electrospray ionization (ESI)-time-of-flight mass spectrometry (MS) was used to analyse low molecular weight molecules present in the plasma samples of 10 patients with end-stage renal disease (ESRD) who were being treated with haemodialysis, and in 16 healthy subjects. Results In plasma samples obtained after haemodialysis, the relative quantities of 54 peaks were significantly (P<0·05) decreased when compared with those in the plasma before haemodialysis. The candidate biomarkers were allocated to three groups. Molecules in Group A improved completely with a large variance, molecules in Group B improved partially but with a large variance, and molecules in Group C improved partially with low variance after haemodialysis. Small cohort validation study consisting of the patients with ESRD undergoing haemodialysis indicates that three candidate biomarkers in Group C would be a very useful marker to estimate adequate haemodialysis dose. Conclusions 1-Methylinosine and two unknown molecules whose m/z at ESI-positive mode are 257·1033 and 413·1359 were found as effective candidate biomarkers to estimate adequate haemodialysis dose, which has to be confirmed in prospective studies. © 2010 The Authors. European Journal of Clinical Investigation © 2010 Stichting European Society for Clinical Investigation Journal Foundation.


Kobayashi T.,Tokyo Institute of Technology | Matsumura Y.,Tokyo Institute of Technology | Ozawa T.,Tokyo Institute of Technology | Ozawa T.,Yokohama College of Pharmacy | And 6 more authors.
Analytical and Bioanalytical Chemistry | Year: 2014

To identify blood markers for early stages of chronic kidney disease (CKD), blood samples were collected from rats with adenine-induced CKD over 28 days. Plasma samples were subjected to metabolomic profiling by liquid chromatography-mass spectrometry, followed by multivariate analyses. In addition to already-identified uremic toxins, we found that plasma concentrations of N6-succinyl adenosine, lysophosphatidylethanolamine 20:4, and glycocholic acid were altered, and that these changes during early CKD were more sensitive markers than creatinine concentration, a universal indicator of renal dysfunction. Moreover, the increase in plasma indoxyl sulfate concentration occurred earlier than increases in phenyl sulfate and p-cresol sulfate. These novel metabolites may serve as biomarkers in identifying early stage CKD. © 2013 Springer-Verlag Berlin Heidelberg.


Kobayashi T.,Tokyo Institute of Technology | Yoshida T.,Shimadzu Corporation | Fujisawa T.,Kiyokai Tanaka Kitanoda Hospital | Matsumura Y.,Tokyo Institute of Technology | And 8 more authors.
Biochemical and Biophysical Research Communications | Year: 2014

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. © 2014 Elsevier Inc. All rights reserved.

Discover hidden collaborations