Novel Lipidomic Biomarkers in Hyperlipidemia and Cardiovascular Diseases: An Integrative Biology Analysis.
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| Abstract |
Lipidomics is a new frontier of omics research and offers much promise for new-generation biomarkers for common complex phenotypes such as hyperlipidemia (HL) and cardiovascular diseases (CVDs). HL is a disorder characterized by increased levels of blood lipids and is a well-established risk factor for CVD. Traditional clinical markers for prognosis of hyperlipidemic individuals are inadequate to forecast or diagnose cardiac events. In this expert review, lipidomic profiles from recent HL and CVD studies were compared with the normolipidemic profile prepared from the Standard Reference Material. Our analysis showed that palmitoyl-lysophosphatidylcholine [LPC(16:0)], the most abundant LPC species in normolipidemic plasma, decreases in HL causative conditions such as high-fat diet, obesity, and diabetes. This is accompanied by increase in free fatty acids (FFAs) and ceramides (Cers). HL was also found to be characterized by increase in small-chain, saturated fatty acid content of diacylglycerols, triacylglycerols, and phosphatidylcholines (PCs). These factors were also associated with increased CVD risk. The decrease in LPC(16:0) in HL and CVD is consistent with its role in regulation of peroxisome proliferator-activated receptor alpha, an approved HL drug target that impacts the uptake and oxidation of fatty acids. FFAs are involved in endothelial-dependent nitric oxide production and activation of nuclear factor κB signaling. Cers control uptake and anabolic catabolism of nutrients in tissues. However, additional studies are required to establish the range of normal and disease levels of the identified lipids in different populations and conditions. In all, these observations underscore that lipidomics deserves greater research attention from the biomarker and precision medicine research communities.
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| Authors | Sneha Rai, Sonika Bhatnagar |
| Journal | Omics : a journal of integrative biology (OMICS) Vol. 21 Issue 3 Pg. 132-142 (03 2017) ISSN: 1557-8100 [Electronic] United States |
| PMID | 28157411 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't) |
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