LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic...

Area of Science:

• Biomedical research
• Clinical research
• Analytical chemistry

Background:

• Lipidomics requires precise lipid quantification for clinical translation.
• Class-based chromatographic separation (HILIC, NPLC, SFC) in lipidomics causes isotopic overlap.
• Existing isotopic correction methods are unsuitable for multiple reaction monitoring (MRM) analyses.

Purpose of the Study:

• To develop and validate an algorithm for accurate isotopic correction in lipidomics using MRM.
• To address the limitations of current isotopic correction methods in MRM analyses with class-based separation.
• To improve the reliability of lipid quantification in clinical lipidomics.

Main Methods:

• Development of an R-based algorithm for isotopic correction using structural information from MRM transitions.
• Validation using analytical standards to assess the accuracy of isotopic contribution estimation.
• Application to human plasma samples to demonstrate the impact on lipid quantitation.

Main Results:

• The algorithm accurately estimates the isotopic contribution of isotopologues to MRM transition intensities.
• Over one-third of phosphatidylcholine species in human plasma required >10% intensity correction.
• Demonstrated the necessity of adequate isotopic correction for accurate lipid quantitation in MRM-based lipidomics.

Conclusions:

• The developed algorithm and R package provide accurate isotopic correction for lipidomics using MRM with class-based separation.
• This method enhances the precision of lipid quantification, crucial for clinical translation.
• Enables more reliable lipidomic data for advancing biomedical and clinical research.