LipidQuan: HILIC-Based LC-MS/MS High-Throughput Targeted Phospholipids Screen (PE, LPE, PG, and PI)

Importance of the Topic

Glycerophospholipids such as phosphatidylethanolamine (PE), lysophosphatidylethanolamine (LPE), phosphatidylglycerol (PG), and phosphatidylinositol (PI) are fundamental components of cellular membranes and signaling pathways. Alterations in their abundance are linked to neurodegenerative, infectious, and metabolic disorders. Accurate, high‐throughput quantification of these lipids in biofluids is vital for biomarker discovery, clinical research, and quality control in pharmaceutical and biotechnology sectors.

Study Objectives and Overview

This work describes the development and application of a targeted HILIC‐based LC‐MS/MS workflow (LipidQuan) for rapid screening and quantification of 112 phospholipid species (47 PEs, 11 LPEs, 21 PGs, 33 PIs) in human plasma. The platform leverages standardized Quanpedia™ methods and SOPs to minimize method development time, enhance specificity, and facilitate deployment across laboratories.

Methodology and Instrumentation

A simple protein precipitation using chilled isopropanol was applied to 50 µL plasma samples spiked with stable isotope–labeled (SIL) standards. Chromatographic separation by hydrophilic interaction liquid chromatography employed an ACQUITY UPLC I-Class System with a BEH Amide column at 45 °C. A gradient elution (8‐minute run time, 0.6 mL/min) resolved lipid classes in discrete windows. MS detection utilized a Xevo TQ‐XS, TQ-S, or TQ-S micro in ESI positive mode for LPEs and negative mode for PEs, PGs, and PIs. Multiple reaction monitoring (MRM) transitions for fatty acyl fragments provided class‐specific identification. Data processing and quantification were performed with TargetLynx™ or Skyline using calibration curves generated from plasma spiked with nine concentration levels of SIL standards.

Main Results and Discussion

The HILIC method yielded baseline class separation: PGs at ~1.21 min, PEs at ~1.62 min, LPEs at ~2.34 min, and PIs at ~2.40 min. In an eight‐minute analysis, 112 endogenous lipids were quantified over four orders of magnitude with R² values >0.95 and CVs <30%. Sensitivity was sufficient to detect normal circulating levels from a 50 µL plasma aliquot. Employing a single SIL standard per class reduced cost and simplified quantification. The LipidQuan Quanpedia method file enabled rapid method transfer and eliminated manual entry errors.

Benefits and Practical Applications

• High‐throughput targeted lipid screening in under 10 minutes per sample.
• Robust quantification with class‐specific MRM enhances specificity and reduces isomeric/isobaric interferences.
• Cost savings through reduced SIL standard requirements.
• Easily deployable SOPs and Quanpedia methods minimize training and validation effort.

Future Trends and Potential Applications

Continued expansion of targeted lipid panels to include additional classes, integration with automated sample preparation systems, and coupling to high‐resolution platforms will further enhance lipidomics capacity. Advances in informatics and database integration will enable deeper biological interpretation, paving the way for personalized medicine and large‐scale clinical studies. Emerging lipids as disease biomarkers may be rapidly validated using this scalable workflow.

Conclusion

The LipidQuan HILIC‐LC‐MS/MS platform delivers a fast, reliable, and cost‐effective solution for targeted phospholipid quantification in plasma. Its robust performance, standardized methods, and broad dynamic range make it well suited for research, clinical, and industrial applications.

References

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