LipidQuan: HILIC-Based LC-MS/MS High-Throughput Targeted Phospholipids Screen (PC, LPC, SM)

Importance of the topic

Choline‐containing phospholipids including phosphatidylcholines (PCs), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs) are essential constituents of cell membranes and have been implicated in various diseases such as multiple sclerosis and Niemann–Pick disease. Reliable, high‐throughput quantification of these lipids in biological matrices is critical for biomarker discovery, clinical research, and quality control in pharmaceutical and biomedical laboratories.

Objectives and study overview

The primary goal was to establish and validate a targeted HILIC‐based LC‐MS/MS workflow (LipidQuan) for rapid quantification of 106 choline‐containing phospholipids (61 PCs, 24 SMs, 21 LPCs) in human plasma. This application note demonstrates method performance, instrument configuration, data processing, and practical implementation using a standardized Quanpedia method file and SOPs.

Methodology and instrumentation

Sample preparation:

• Protein precipitation of 50 µL plasma with ice‐cold isopropanol (1:5 v/v), vortexing, –20 °C incubation, and 4 °C precipitation.
• Centrifugation at 10 300 g, 4 °C for 10 min; supernatant transferred for analysis.

Chromatography and mass spectrometry:

• Waters ACQUITY UPLC I‐Class system with BEH Amide HILIC column (2.1×100 mm, 1.7 µm) at 45 °C.
• Gradient elution from 0.1% to 80% mobile phase B (acetonitrile/water 50:50 + 10 mM ammonium acetate) over 5 min; 8 min total run time; 0.6 mL/min flow rate; 1 µL injection.
• Xevo TQ‐S micro, TQ‐XS or TQ‐S operated in ESI positive/negative modes; MRM acquisition of head group and fatty acyl fragments.
• Data processing with TargetLynx Software or Skyline; Quanpedia method file provided retention times, transitions, and processing parameters.

Main results and discussion

HILIC separation yielded distinct class elution: PCs at ~1.52 min, SMs at ~1.92 min, LPCs at ~2.15 min. The method quantified 61 PCs, 24 SMs, and 21 LPCs in 8 min per run. Calibration using stable isotope‐labeled standards spiked into plasma demonstrated:

• Four orders of linear dynamic range (e.g., 3–1500 ng/mL for SM; 2.5–1250 ng/mL for LPC; 16–8000 ng/mL for PC).
• Correlation coefficients (R²) ≥ 0.95 and precision (CV < 30%) across replicates.
• Reduced isobaric/isomeric interferences via class‐based separation and specific MRM transitions.

Benefits and practical applications

• High throughput: up to 106 lipid species quantified in an 8-minute run.
• Cost efficiency: single stable isotope standard per lipid class reduces reagent expense.
• Robustness and ease of deployment: Quanpedia files and SOPs minimize method setup time and error.
• Flexibility of data processing: compatibility with commercial and open‐source informatics.

Future trends and applications

Advances may include integration with comprehensive lipid panels covering additional classes (e.g., phosphatidylethanolamines), adoption of data-independent acquisition (DIA) strategies for untargeted profiling, automation of sample handling, and inter‐laboratory harmonization to support large-scale clinical studies and regulatory applications.

Conclusion

The LipidQuan HILIC‐based LC-MS/MS platform provides a rapid, sensitive, and cost-effective workflow for targeted quantification of choline-containing phospholipids in plasma. Its streamlined sample preparation, class-based separation, and standardized method files enable reproducible results, facilitating routine lipidomic analyses in research and industry settings.

References

1. Van Meer G, Voelker DR, Feigenson GW. Membrane lipids: where they are and how they behave. Nat Rev Mol Cell Biol. 2008;9(2):112–124.
2. Hendriksz CJ et al. The Hidden Niemann-Pick Type C Patient: Clinical Niches for a Rare Inherited Metabolic Disease. Curr Med Res Opin. 2017;33(5):877–890.
3. Lee CY, Lesimple A, Larsen Å, Mamer O, Genest J. ESI-MS quantitation of increased sphingomyelin in Niemann-Pick disease type B HDL. J Lipid Res. 2005;46(6):1213–1228.
4. Cífková E et al. Nontargeted quantitation of lipid classes using HILIC-ESI-MS with single internal standard and response factor approach. Anal Chem. 2012;84(22):10064–10070.