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Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline

Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagn...

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Autores principales: Zhang, Lin, Li, Meng, Zhan, Libin, Lu, Xiaoguang, Liang, Lina, Su, Benli, Sui, Hua, Gao, Zhengnan, Li, Yuzhong, Liu, Ying, Wu, Benhui, Liu, Qigui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431856/
https://www.ncbi.nlm.nih.gov/pubmed/25974350
http://dx.doi.org/10.1371/journal.pone.0126952
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author Zhang, Lin
Li, Meng
Zhan, Libin
Lu, Xiaoguang
Liang, Lina
Su, Benli
Sui, Hua
Gao, Zhengnan
Li, Yuzhong
Liu, Ying
Wu, Benhui
Liu, Qigui
author_facet Zhang, Lin
Li, Meng
Zhan, Libin
Lu, Xiaoguang
Liang, Lina
Su, Benli
Sui, Hua
Gao, Zhengnan
Li, Yuzhong
Liu, Ying
Wu, Benhui
Liu, Qigui
author_sort Zhang, Lin
collection PubMed
description Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of DACD remain somewhat elusive. To understand the pathophysiological changes that underpin the development and progression of DACD, we carried out a global analysis of metabolic alterations in response to DACD. The metabolic alterations associated with DACD were first investigated in humans, using plasma metabonomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. The related pathway of each metabolite of interest was searched in database online. The network diagrams were established KEGGSOAP software package. Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic accuracy of metabolites. This is the first report of reliable biomarkers of DACD, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of DACD. The disorders of sphingolipids metabolism, bile acids metabolism, and uric acid metabolism pathway were found in T2DM and DACD. On the other hand, differentially expressed plasma metabolites offer unique metabolic signatures for T2DM and DACD patients. These are potential biomarkers for disease monitoring and personalized medication complementary to the existing clinical modalities.
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spelling pubmed-44318562015-05-27 Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline Zhang, Lin Li, Meng Zhan, Libin Lu, Xiaoguang Liang, Lina Su, Benli Sui, Hua Gao, Zhengnan Li, Yuzhong Liu, Ying Wu, Benhui Liu, Qigui PLoS One Research Article Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of DACD remain somewhat elusive. To understand the pathophysiological changes that underpin the development and progression of DACD, we carried out a global analysis of metabolic alterations in response to DACD. The metabolic alterations associated with DACD were first investigated in humans, using plasma metabonomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. The related pathway of each metabolite of interest was searched in database online. The network diagrams were established KEGGSOAP software package. Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic accuracy of metabolites. This is the first report of reliable biomarkers of DACD, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of DACD. The disorders of sphingolipids metabolism, bile acids metabolism, and uric acid metabolism pathway were found in T2DM and DACD. On the other hand, differentially expressed plasma metabolites offer unique metabolic signatures for T2DM and DACD patients. These are potential biomarkers for disease monitoring and personalized medication complementary to the existing clinical modalities. Public Library of Science 2015-05-14 /pmc/articles/PMC4431856/ /pubmed/25974350 http://dx.doi.org/10.1371/journal.pone.0126952 Text en © 2015 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zhang, Lin
Li, Meng
Zhan, Libin
Lu, Xiaoguang
Liang, Lina
Su, Benli
Sui, Hua
Gao, Zhengnan
Li, Yuzhong
Liu, Ying
Wu, Benhui
Liu, Qigui
Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title_full Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title_fullStr Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title_full_unstemmed Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title_short Plasma Metabolomic Profiling of Patients with Diabetes-Associated Cognitive Decline
title_sort plasma metabolomic profiling of patients with diabetes-associated cognitive decline
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431856/
https://www.ncbi.nlm.nih.gov/pubmed/25974350
http://dx.doi.org/10.1371/journal.pone.0126952
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