Literature DB >> 25344987

Metabolomics in dyslipidemia.

Hua Chen, Hua Miao, Ya-Long Feng, Ying-Yong Zhao, Rui-Chao Lin.   

Abstract

Hyperlipidemia is an important public health problem with increased incidence and prevalence worldwide. Current clinical biomarkers, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol lack the necessary specificity and sensitivity and only increase significantly after serious dyslipidemia. Therefore, sensitive biomarkers are needed for hyperlipidemia. Hyperlipidemia-specific biomarkers would improve clinical diagnosis and therapeutic treatment at early disease stages. The aim of metabolomics is to identify untargeted and global small-molecule metabolite profiles from cells, biofluids, and tissues. This method offers the potential for a holistic approach to improve disease diagnoses and our understanding of underlying pathologic mechanisms. This review summarizes analytical techniques, data collection and analysis for metabolomics, and metabolomics in hyperlipidemia animal models and clinical studies. Mechanisms of hypolipemia and antilipemic drug therapy are also discussed. Metabolomics provides a new opportunity to gain insight into metabolic profiling and pathophysiologic mechanisms of hyperlipidemia.

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Year:  2014        PMID: 25344987     DOI: 10.1016/b978-0-12-801401-1.00004-9

Source DB:  PubMed          Journal:  Adv Clin Chem        ISSN: 0065-2423            Impact factor:   5.394


  24 in total

1.  Metabolomic characterization of hypertension and dyslipidemia.

Authors:  Chaofu Ke; Xiaohong Zhu; Yuxia Zhang; Yueping Shen
Journal:  Metabolomics       Date:  2018-08-31       Impact factor: 4.290

2.  1,5-Anhydroglucitol predicts CKD progression in macroalbuminuric diabetic kidney disease: results from non-targeted metabolomics.

Authors:  Gesiane Tavares; Gabriela Venturini; Kallyandra Padilha; Roberto Zatz; Alexandre C Pereira; Ravi I Thadhani; Eugene P Rhee; Silvia M O Titan
Journal:  Metabolomics       Date:  2018-02-27       Impact factor: 4.290

3.  Omics, big data and machine learning as tools to propel understanding of biological mechanisms and to discover novel diagnostics and therapeutics.

Authors:  Nikolaos Perakakis; Alireza Yazdani; George E Karniadakis; Christos Mantzoros
Journal:  Metabolism       Date:  2018-08-08       Impact factor: 8.694

4.  Variables associated with poor health-related quality of life among patients with dyslipidemia in Jordan.

Authors:  Anan S Jarab; Eman A Alefishat; Walid Al-Qerem; Tareq L Mukattash; Lina Abu-Zaytoun
Journal:  Qual Life Res       Date:  2021-01-01       Impact factor: 4.147

5.  Integrated metabolomics coupled with pattern recognition and pathway analysis to reveal molecular mechanism of cadmium-induced diabetic nephropathy.

Authors:  Pin Gong; Mengrao Wang; Wenjuan Yang; Xiangna Chang; Lan Wang; Fuxin Chen
Journal:  Toxicol Res (Camb)       Date:  2021-07-06       Impact factor: 2.680

6.  A pharmaco-metabonomic study on chronic kidney disease and therapeutic effect of ergone by UPLC-QTOF/HDMS.

Authors:  Ying-Yong Zhao; Hua Chen; Ting Tian; Dan-Qian Chen; Xu Bai; Feng Wei
Journal:  PLoS One       Date:  2014-12-23       Impact factor: 3.240

7.  An integrated lipidomics and metabolomics reveal nephroprotective effect and biochemical mechanism of Rheum officinale in chronic renal failure.

Authors:  Zhi-Hao Zhang; Nosratola D Vaziri; Feng Wei; Xian-Long Cheng; Xu Bai; Ying-Yong Zhao
Journal:  Sci Rep       Date:  2016-02-23       Impact factor: 4.379

8.  Integrative analysis of metabolome and gut microbiota in diet-induced hyperlipidemic rats treated with berberine compounds.

Authors:  Meng Li; Xiangbing Shu; Hanchen Xu; Chunlei Zhang; Lili Yang; Li Zhang; Guang Ji
Journal:  J Transl Med       Date:  2016-08-05       Impact factor: 5.531

9.  Navy Bean and Rice Bran Intake Alters the Plasma Metabolome of Children at Risk for Cardiovascular Disease.

Authors:  Katherine J Li; Erica C Borresen; NaNet Jenkins-Puccetti; Gary Luckasen; Elizabeth P Ryan
Journal:  Front Nutr       Date:  2018-01-19

10.  Modulation of the Gut Microbiota by Krill Oil in Mice Fed a High-Sugar High-Fat Diet.

Authors:  Chenyang Lu; Tingting Sun; Yanyan Li; Dijun Zhang; Jun Zhou; Xiurong Su
Journal:  Front Microbiol       Date:  2017-05-17       Impact factor: 5.640

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