4.6 Article

Characterization of Bulk Phosphatidylcholine Compositions in Human Plasma Using Side-Chain Resolving Lipidomics

Journal

METABOLITES
Volume 9, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/metabo9060109

Keywords

metabolomics; lipidomics; phospholipids; isobaric phosphatidylcholines; lipid species; fatty acid composition; platform comparison; harmonization; imputation

Funding

  1. Else Kroener-Fresenius-Foundation, Bad Homburg v.d.H., Germany
  2. Biomedical Research Program at Weill Cornell Medicine-Qatar (WCM-Q)
  3. Qatar Foundation
  4. National Institute on Aging (NIA) [RF1 AG058942-01, R01-AG057452-01, R01-AG059093-01, U01-AG061359-01]
  5. Qatar National Research Fund [NPRP8-061-3-011]

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Kit-based assays, such as AbsoluteIDQ(TM) p150, are widely used in large cohort studies and provide a standardized method to quantify blood concentrations of phosphatidylcholines (PCs). Many disease-relevant associations of PCs were reported using this method. However, their interpretation is hampered by lack of functionally-relevant information on the detailed fatty acid side-chain compositions as only the total number of carbon atoms and double bonds is identified by the kit. To enable more substantiated interpretations, we characterized these PC sums using the side-chain resolving Lipidyzer(TM) platform, analyzing 223 samples in parallel to the AbsoluteIDQ(TM). Combining these datasets, we estimated the quantitative composition of PC sums and subsequently tested their replication in an independent cohort. We identified major constituents of 28 PC sums, revealing also various unexpected compositions. As an example, PC 16:0_22:5 accounted for more than 50% of the PC sum with in total 38 carbon atoms and 5 double bonds (PC aa 38:5). For 13 PC sums, we found relatively high abundances of odd-chain fatty acids. In conclusion, our study provides insights in PC compositions in human plasma, facilitating interpretation of existing epidemiological data sets and potentially enabling imputation of PC compositions for future meta-analyses of lipidomics data.

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