Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.bbrc.2018.04.076
Title: Sphingolipidomics analysis of large clinical cohorts. Part 1: Technical notes and practical considerations
Authors: Chew, Wee Siong 
Seow, Wei Lun 
Chong, Joyce R
Lai, Mitchell KP 
Torta, Federico
Wenk, Markus R 
Herr, Deron R 
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Biophysics
Sphingolipid
Lipidomics
Mass spectrometry
Sphingomyelin
Ceramide
Sphingosine 1-phosphate
TANDEM MASS-SPECTROMETRY
QUANTITATIVE-ANALYSIS
METABONOMIC ANALYSIS
HIGH-THROUGHPUT
BLOOD-PLASMA
HUMAN URINE
HPLC-MS
LIPIDS
METABOLOMICS
EXTRACTION
Issue Date: 7-Oct-2018
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Citation: Chew, Wee Siong, Seow, Wei Lun, Chong, Joyce R, Lai, Mitchell KP, Torta, Federico, Wenk, Markus R, Herr, Deron R (2018-10-07). Sphingolipidomics analysis of large clinical cohorts. Part 1: Technical notes and practical considerations. BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS 504 (3) : 596-601. ScholarBank@NUS Repository. https://doi.org/10.1016/j.bbrc.2018.04.076
Abstract: © 2018 Elsevier Inc. Lipids comprise an exceptionally diverse class of bioactive macromolecules. While quantitatively abundant lipid species serve fundamental roles in cell structure and energy metabolism, thousands of structurally-distinct, quantitatively minor species may serve as important regulators of cellular processes. Historically, a complete understanding of the biological roles of these lipids has been limited by a lack of sensitive, discriminating analytical techniques. The class of sphingolipids alone, for example, is known to consist of over 600 different confirmed species, but is likely to include tens of thousands of metabolites with potential biological significance. Advances in mass spectrometry (MS) have improved the throughput and discrimination of lipid analysis, allowing for the determination of detailed lipid profiles in large cohorts of clinical samples. Databases emerging from these studies will provide a rich resource for the identification of novel biomarkers and for the discovery of potential drug targets, analogous to that of existing genomics databases. In this review, we will provide an overview of the field of sphingolipidomics, and will discuss some of the challenges and considerations facing the generation of robust lipidomics databases.
Source Title: BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
URI: https://scholarbank.nus.edu.sg/handle/10635/173261
ISSN: 0006291X
10902104
DOI: 10.1016/j.bbrc.2018.04.076
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