LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring

Lipidomics
is developing as an important area in biomedical and
clinical research. Reliable quantification of lipid species is required
for clinical translation of lipidomic studies. Hydrophilic interaction
chromatography (HILIC), normal-phase liquid chromatography (NPLC),
and supercritical fluid chromatography (SFC) are commonly used techniques
in lipidomics and provide class-based separation of lipids. While
co-elution of lipid species and their internal standards is an advantage
for accurate quantification, it leads to isotopic overlap between
species of the same lipid class. In shotgun lipidomics, isotopic correction
is typically done based on elemental formulas of precursor ions. In
multiple reaction monitoring (MRM) analyses, however, this approach
should not be used, as the overall contribution of heavy isotopes
to the MRM transitions’ intensities depends on their location
in the molecule with respect to the fragmentation pattern. We present
an algorithm, provided in the R programming language, for isotopic
correction in class-based separation using MRM, extracting relevant
structural information from MRM transitions to apply adequate isotopic
correction factors. Using standards, we show that our algorithm accurately
estimates the isotopic contribution of isotopologues to MRM transitions’
measured intensities. Using human plasma as an example, we demonstrate
the necessity of adequate isotopic correction for accurate quantitation
of lipids measured by MRM with class-based chromatographic separation.
We show that over a third of the measured phosphatidylcholine species
had their intensity corrected by more than 10%. This isotopic correction
algorithm and R-implemented application enable a more accurate quantification
of lipids in class-based separation-MRM, a prerequisite for successful
translation of lipidomic applications.