Equivalent Carbon Number and Interclass Retention Time Conversion Enhance Lipid Identification in Untargeted Clinical Lipidomics

Chromatography is often used as a
method for reducing sample complexity
prior to analysis by mass spectrometry, and the use of retention time
(RT) is becoming increasingly popular to add valuable supporting information
in lipid identification. The RT of lipids with the same headgroup
in reversed-phase separation can be predicted using the equivalent
carbon number (ECN) model. This model describes the effects of acyl
chain length and degree of saturation on lipid RT. For the first time,
we have found a robust correlation in the chromatographic separation
of lipids with different headgroups that share the same fatty acid
motive. This relationship can be exploited to perform interclass RT
conversion (IC-RTC) by building a model from RT measurements from
lipid standards that allows the prediction of RT of one lipid subclass
based on another. Here, we utilize ECN modeling and IC-RTC to build
a glycerophospholipid RT library with 517 entries based on 136 tandem
mass spectrometry-characterized lipid RTs from NIST SRM-1950 plasma
and lipid standards. The library was tested on a patient cohort undergoing
coronary artery bypass grafting surgery (n = 37).
A total of 156 unique circulating glycerophospholipids were identified,
of which 52 (1 LPG, 24 PE, 5 PG, 18 PI, and 9 PS) were detected with
IC-RTC, thereby demonstrating the utility of this technique for the
identification of lipid species not found in commercial standards.