Literature DB >> 25858872

Lipidomics: new insight into kidney disease.

Ying-Yong Zhao1, Nosratola D Vaziri2, Rui-Chao Lin3.   

Abstract

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.
© 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Inflammation; Kidney diseases; Lipid profiling; Lipidomics; Mass spectrometry; Renal diseases; System biology

Mesh:

Substances:

Year:  2015        PMID: 25858872     DOI: 10.1016/bs.acc.2014.11.002

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


  38 in total

1.  Plasma metabolic profiling analysis of Strychnos nux-vomica Linn. and Tripterygium wilfordii Hook F-induced renal toxicity using metabolomics coupled with UPLC/Q-TOF-MS.

Authors:  Houmin Luo; Caiyun Gu; Chuanxin Liu; Yuming Wang; Hao Wang; Yubo Li
Journal:  Toxicol Res (Camb)       Date:  2018-07-25       Impact factor: 3.524

2.  Early lipid changes in acute kidney injury using SWATH lipidomics coupled with MALDI tissue imaging.

Authors:  Sangeetha Rao; Kelly B Walters; Landon Wilson; Bo Chen; Subhashini Bolisetty; David Graves; Stephen Barnes; Anupam Agarwal; Janusz H Kabarowski
Journal:  Am J Physiol Renal Physiol       Date:  2016-02-24

3.  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

4.  DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules.

Authors:  Guanshi Zhang; Jialing Zhang; Rachel J DeHoog; Subramaniam Pennathur; Christopher R Anderton; Manjeri A Venkatachalam; Theodore Alexandrov; Livia S Eberlin; Kumar Sharma
Journal:  Metabolomics       Date:  2020-01-10       Impact factor: 4.290

5.  Urinary Lipidomics: evidence for multiple sources and sexual dimorphism in healthy individuals.

Authors:  J Graessler; C S Mehnert; K-M Schulte; S Bergmann; S Strauss; T D Bornstein; J Licinio; M-L Wong; A L Birkenfeld; S R Bornstein
Journal:  Pharmacogenomics J       Date:  2017-06-13       Impact factor: 3.550

Review 6.  The Updates of Podocyte Lipid Metabolism in Proteinuric Kidney Disease.

Authors:  Yu Sun; Sijia Cui; Yunfeng Hou; Fan Yi
Journal:  Kidney Dis (Basel)       Date:  2021-09-01

7.  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

8.  Shenkang Injection for Treating Renal Fibrosis-Metabonomics and Regulation of E3 Ubiquitin Ligase Smurfs on TGF-β/Smads Signal Transduction.

Authors:  Junju Zou; Xiaotao Zhou; Xian Chen; Yuerong Ma; Rong Yu
Journal:  Front Pharmacol       Date:  2022-06-02       Impact factor: 5.988

Review 9.  HDL abnormalities in nephrotic syndrome and chronic kidney disease.

Authors:  Nosratola D Vaziri
Journal:  Nat Rev Nephrol       Date:  2015-11-16       Impact factor: 28.314

10.  Lipid imaging for visualizing cilastatin amelioration of cisplatin-induced nephrotoxicity.

Authors:  Estefanía Moreno-Gordaliza; Diego Esteban-Fernández; Alberto Lázaro; Sarah Aboulmagd; Blanca Humanes; Alberto Tejedor; Michael W Linscheid; M Milagros Gómez-Gómez
Journal:  J Lipid Res       Date:  2018-07-26       Impact factor: 5.922

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