LipidQuan for Comprehensive and High-Throughput HILIC-based LC-MS/MS Targeted Lipid Quantitation

Importance of the Topic

Lipids play critical roles in cellular energy storage, membrane structure, and signaling pathways. Recent advances in lipidomics have revealed connections between lipid dysregulation and diseases such as cancer, inflammation, and cardiovascular disorders. However, the extreme chemical diversity of lipids—from highly polar to non-polar species—poses challenges for analytical separation and quantitation. A robust, high-throughput platform capable of resolving lipid classes and quantifying hundreds of molecular species is essential for large-scale studies and clinical applications.

Goals and Study Overview

The study aimed to develop and validate a comprehensive, eight-minute HILIC-based LC-MS/MS method for targeted quantitation of both polar and non-polar lipids in human plasma. Using a structured lipid class separation, the method quantifies over 500 endogenous lipid species across 16 classes in positive and negative ionization modes. The platform leverages Quanpedia™ method files and standardized operating procedures (SOPs) to streamline deployment and reduce training time.

Methodology and Instrumentation

Sample Preparation:

• Protein precipitation of plasma with pre-cooled isopropanol (1:5, v/v) at 4 °C, followed by centrifugation and transfer of supernatant for analysis.

Chromatography and MS Conditions:

• Column: ACQUITY UPLC BEH Amide (1.7 µm, 2.1 × 100 mm), 45 °C.
• Mobile phases: A = 95:5 acetonitrile/water with 10 mM ammonium acetate; B = 50:50 acetonitrile/water with 10 mM ammonium acetate.
• Gradient: 0.1%→20% B in 2 min, 20%→80% B in 3 min, plus 3 min re-equilibration, flow 0.6 mL/min, injection 1 µL.
• Mass spectrometer: Xevo™ TQ-XS or Xevo TQ-S, ESI mode (+/–), MRM acquisition.

Instrumental Support:

• Quanpedia™ for rapid method download.
• TargetLynx™ and Skyline for data processing and visualization.

Main Results and Discussion

The HILIC separation achieved baseline class resolution for 16 lipid categories within eight minutes. A comprehensive MRM database of 2,041 transitions enabled targeted monitoring of 508 lipid species (261 in positive mode, 247 in negative mode). Calibration curves for stable-isotope labeled standards were linear over four orders of magnitude, with average correlation coefficients above 0.99 (positive) and 0.98 (negative). Co-elution of labeled standards and endogenous analytes within each class ensured consistent ionization, minimized isobaric interference, and reduced the number of standards required.

Benefits and Practical Applications

• High throughput: eight-minute runtime supports large cohort studies.
• Comprehensive coverage: quantitation of major polar and non-polar lipids.
• Cost and time savings: fewer internal standards and simplified method setup.
• Ease of deployment: downloadable method files and SOPs lower training barriers.

Future Trends and Opportunities

Integration with automated sample preparation platforms and advanced bioinformatics will further increase throughput and data quality. Expansion of the MRM library to emerging lipid classes and application in clinical diagnostics, biomarker discovery, and nutritional studies will broaden the method’s impact. Coupling HILIC separation with high-resolution mass spectrometry may enable simultaneous targeted and untargeted lipidome profiling.

Conclusion

A robust, high-throughput HILIC LC-MS/MS workflow has been established for targeted quantitation of a broad range of lipid classes in plasma. The method delivers rapid separation, excellent linearity, and reliable quantitation, while reducing resource requirements and operational complexity. Its adaptability and comprehensive coverage make it well-suited for large-scale lipidomics investigations.

Used Instrumentation

• ACQUITY UPLC I-Class System
• BEH Amide Column, 1.7 µm, 2.1 × 100 mm
• Xevo TQ-XS and Xevo TQ-S Triple Quadrupole MS
• TargetLynx Software
• Skyline Informatics Platform

References

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4. Cifkova E., et al. Nontargeted Quantitation of Lipid Classes Using HILIC-ESI-MS with Single Internal Standard. Anal Chem. 2012;84(22):10064–10070.
5. Sarafian M.H., et al. Criteria for Optimization of Sample Preparation for UHPLC-MS Lipid Profiling. Anal Chem. 2014;86(11):5766–5774.