Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease

Abstract Conventional disease animal models have limitations on the conformity to the actual clinical situation. Disease-syndrome combination (DS) modeling may provide a more efficient strategy for biomedicine research. Disease model and DS model of renal fibrosis in chronic kidney disease were esta...

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Autores principales:	Shasha Li, Peng Xu, Ling Han, Wei Mao, Yiming Wang, Guoan Luo, Nizhi Yang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/40756b0c090a4c42b1a589c4caaaa939
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spelling	oai:doaj.org-article:40756b0c090a4c42b1a589c4caaaa9392021-12-02T15:06:12ZDisease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease10.1038/s41598-017-09311-02045-2322https://doaj.org/article/40756b0c090a4c42b1a589c4caaaa9392017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-09311-0https://doaj.org/toc/2045-2322Abstract Conventional disease animal models have limitations on the conformity to the actual clinical situation. Disease-syndrome combination (DS) modeling may provide a more efficient strategy for biomedicine research. Disease model and DS model of renal fibrosis in chronic kidney disease were established by ligating the left ureter and by ligating unilateral ureteral combined with exhaustive swimming, respectively. Serum metabolomics was conducted to evaluate disease model and DS model by using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Potential endogenous biomarkers were identified by multivariate statistical analysis. There are no differences between two models regarding their clinical biochemistry and kidney histopathology, while metabolomics highlights their difference. It is found that abnormal sphingolipid metabolism is a common characteristic of both models, while arachidonic acid metabolism, linolenic acid metabolism and glycerophospholipid metabolism are highlighted in DS model. Metabolomics is a promising approach to evaluate experiment animal models. DS model are comparatively in more coincidence with clinical settings, and is superior to single disease model for the biomedicine research.Shasha LiPeng XuLing HanWei MaoYiming WangGuoan LuoNizhi YangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shasha Li Peng Xu Ling Han Wei Mao Yiming Wang Guoan Luo Nizhi Yang Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
description	Abstract Conventional disease animal models have limitations on the conformity to the actual clinical situation. Disease-syndrome combination (DS) modeling may provide a more efficient strategy for biomedicine research. Disease model and DS model of renal fibrosis in chronic kidney disease were established by ligating the left ureter and by ligating unilateral ureteral combined with exhaustive swimming, respectively. Serum metabolomics was conducted to evaluate disease model and DS model by using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Potential endogenous biomarkers were identified by multivariate statistical analysis. There are no differences between two models regarding their clinical biochemistry and kidney histopathology, while metabolomics highlights their difference. It is found that abnormal sphingolipid metabolism is a common characteristic of both models, while arachidonic acid metabolism, linolenic acid metabolism and glycerophospholipid metabolism are highlighted in DS model. Metabolomics is a promising approach to evaluate experiment animal models. DS model are comparatively in more coincidence with clinical settings, and is superior to single disease model for the biomedicine research.
format	article
author	Shasha Li Peng Xu Ling Han Wei Mao Yiming Wang Guoan Luo Nizhi Yang
author_facet	Shasha Li Peng Xu Ling Han Wei Mao Yiming Wang Guoan Luo Nizhi Yang
author_sort	Shasha Li
title	Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
title_short	Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
title_full	Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
title_fullStr	Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
title_full_unstemmed	Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
title_sort	disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/40756b0c090a4c42b1a589c4caaaa939
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_version_	1718388577075724288

Disease-syndrome combination modeling: metabolomic strategy for the pathogenesis of chronic kidney disease

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