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QUANTIFYING THE LIPIDOME FOR RESPIRATORYDISEASE: A RAPID AND COMPREHENSIVE HILIC-BASED TARGETED APPROACH

Posters | 2019 | WatersInstrumentation
LC/MS, LC/MS/MS, LC/QQQ
Industries
Lipidomics
Manufacturer
Waters

Summary

Význam tématu

Lipid profiling in respiratory disease research addresses critical needs in understanding molecular drivers of chronic conditions such as COPD, asthma and infection. Alterations in lipid composition can reflect disease progression, therapeutic response and phenotypic differences. A rapid, comprehensive and cost-effective targeted workflow enables high-throughput quantification of over 400 lipid species, supporting both basic research and clinical biomarker discovery.

Cíle a přehled studie / článku

The study presents a HILIC-based LC-MS/MS approach, LipidQuan, designed for lipid class separation and targeted quantification using more than 2,000 MRM transitions. Key objectives include reducing identification ambiguity, minimizing the number of stable isotope-labelled standards required, and demonstrating applicability to respiratory disease cohorts.

Použitá metodika a instrumentace

  • Sample preparation: Protein precipitation of plasma with ice-cold isopropanol (1:5, v/v) at 4 °C.
  • Chromatography: ACQUITY UPLC I-Class with FTN or fixed-loop injector; BEH Amide column (2.1 × 100 mm, 1.7 µm); column at 45 °C; 2 µL injection; mobile phases: A (95/5 ACN/water, 10 mM NH4OAc), B (50/50 ACN/water, 10 mM NH4OAc); gradient from 0.1 to 20% B over 2 min, 20 to 80% B over 3 min, then re-equilibration.
  • Mass spectrometry: Xevo TQ-XS or TQ-S micro; ESI in positive/negative modes; capillary voltage 2.8 kV (+), 1.9 kV (−); source temp 120 °C; desolvation 500 °C, 1,000 L/h; cone gas 150 L/h; acquisition via MRM with fatty acyl and headgroup transitions.
  • Informatics: LipidQuan Quanpedia method file containing LC and MS settings, >2,000 MRM transitions, and TargetLynx processing for retention time alignment and quantification.

Hlavní výsledky a diskuse

  • Chromatographic class separation achieved baseline resolution of polar and non-polar lipid classes, enabling targeted detection with RSDs <2% over 1,500 injections.
  • Fatty acyl-based MRM transitions improved isobaric species discrimination (e.g., PC(16:0p/22:6) vs PC(18:2p/20:4)) beyond conventional headgroup fragments.
  • Application to a COPD/asthma cohort revealed distinct lipid expression patterns by PLS-DA (R2=0.843, Q2=0.844) and hierarchical clustering of top differential lipids (FDR<1%).
  • Reduction in stable isotope lipid standards lowered per‐sample costs without compromising quantitation accuracy.

Přínosy a praktické využití metody

  • High-throughput workflow from sample prep to data analysis allows >150 samples per day.
  • Class-based separation decreases standard requirements, cutting costs significantly.
  • Robust quantification supports QA/QC in clinical and industrial laboratory settings.
  • Flexible data processing using TargetLynx, Skyline, and visualization via SIMCA-P+ or MetaboAnalyst.

Budoucí trendy a možnosti využití

  • Integration with other omics platforms (proteomics, metabolomics) for multi-layered biomarker panels.
  • Expansion to novel lipid classes and modifications (e.g., oxidized lipids, sphingolipid subclasses).
  • Advanced data analysis using AI/ML for pattern recognition and predictive diagnostics.
  • Development of simplified kits and standardized libraries for broader adoption in clinical labs.

Závěr

The LipidQuan HILIC-based targeted LC-MS/MS approach provides a streamlined, sensitive and cost-effective solution for comprehensive lipid quantification in respiratory disease research. Its robustness, high throughput and improved specificity support large cohort studies and accelerate biomarker discovery and validation.

Reference

  1. Munjoma N., Isaac G., Plumb R., Gethings L. (2019) Quantifying the Lipidome for a Respiratory Disease Study Using LipidQuan: A Rapid and Comprehensive Targeted Approach. Application Note 720006542EN.
  2. Isaac G., Munjoma N., Gethings L., Plumb R. (2018) LipidQuan for Comprehensive and High-Throughput HILIC-based LC-MS/MS Targeted Lipid Quantitation. Application Note 720006402EN.

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