Authors: Akiyoshi Hirayama Eitaro Nakashima Masahiro Sugimoto Shinichi Akiyama Waichi Sato Shoichi Maruyama Seiichi Matsuo Masaru Tomita Yukio Yuzawa Tomoyoshi Soga
Publish Date: 2012/09/29
Volume: 404, Issue: 10, Pages: 3101-3109
Abstract
Capillary electrophoresis coupled with timeofflight mass spectrometry was used to explore new serum biomarkers with high sensitivity and specificity for diabetic nephropathy DN diagnosis through comprehensive analysis of serum metabolites with 78 diabetic patients Multivariate analyses were used for identification of marker candidates and development of discriminative models Of the 289 profiled metabolites orthogonal partial leastsquares discriminant analysis identified 19 metabolites that could distinguish between DN with macroalbuminuria and diabetic patients without albuminuria These identified metabolites included creatinine aspartic acid γbutyrobetaine citrulline symmetric dimethylarginine SDMA kynurenine azelaic acid and galactaric acid Significant correlations between all these metabolites and urinary albumintocreatinine ratios p 0009 Spearman’s rank test were observed When five metabolites including γbutyrobetaine SDMA azelaic acid and two unknowns were selected from 19 metabolites and applied for multiple logistic regression model AUC value for diagnosing DN was 0927 using the whole dataset and 0880 in a crossvalidation test In addition when four known metabolites aspartic acid SDMA azelaic acid and galactaric acid were applied the resulting AUC was still high at 0844 with the whole dataset and 0792 with crossvalidation Combination of serum metabolomics with multivariate analyses enabled accurate discrimination of DN patients The results suggest that capillary electrophoresismass spectrometry based metabolome analysis could be used for DN diagnosisWe thank Dr Astuko Watarai Japan Labour Health and Welfare Organization Chubu Rosai Hospital for assistance with sample collection We also thank Maki Sugawara and Hiroko Ueda Institute for Advanced Biosciences Keio University and Jiro Nakamura Department of Endocrinology and Diabetes Nagoya University Graduate School of Medicine for technical support and fruitful discussions This work was supported by a Health and Labour Sciences Research Grant “Research on Biological Markers for New Drug Development” Grants from the Ministry of Health Labour and Welfare of Japan “Research on Rare and Intractable Disease” KAKENHI GrantsinAid for Scientific Research on Priority Areas “Systems Genomes” and “Lifesurveyor” from the Ministry of Education Culture Sports Science and Technology of Japan and research funds from the Yamagata prefectural government and the City of Tsuruoka
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