Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry
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https://figshare.com/articles/dataset/Comprehensive_Lipidomic_Workflow_for_Multicohort_Population_Phenotyping_Using_Stable_Isotope_Dilution_Targeted_Liquid_Chromatography-Mass_Spectrometry/22177607
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资源简介:
Dysregulated lipid
metabolism underpins many chronic diseases including
cardiometabolic diseases. Mass spectrometry-based lipidomics is an
important tool for understanding mechanisms of lipid dysfunction and
is widely applied in epidemiology and clinical studies. With ever-increasing
sample numbers, single batch acquisition is often unfeasible, requiring
advanced methods that are accurate and robust to batch-to-batch and
interday analytical variation. Herein, an optimized comprehensive
targeted workflow for plasma and serum lipid quantification is presented,
combining stable isotope internal standard dilution, automated sample
preparation, and ultrahigh performance liquid chromatography-tandem
mass spectrometry with rapid polarity switching to target 1163 lipid
species spanning 20 subclasses. The resultant method is robust to
common sources of analytical variation including blood collection
tubes, hemolysis, freeze–thaw cycles, storage stability, analyte
extraction technique, interinstrument variation, and batch-to-batch
variation with 820 lipids reporting a relative standard deviation
of <30% in 1048 replicate quality control plasma samples acquired
across 16 independent batches (total injection count = 6142). However,
sample hemolysis of ≥0.4% impacted lipid concentrations, specifically
for phosphatidylethanolamines (PEs). Low interinstrument variability
across two identical LC-MS systems indicated feasibility for intra/inter-lab
parallelization of the assay. In summary, we have optimized a comprehensive
lipidomic protocol to support rigorous analysis for large-scale, multibatch
applications in precision medicine. The mass spectrometry lipidomics
data have been deposited to massIVE: data set identifiers MSV000090952
and 10.25345/C5NP1WQ4S.
创建时间:
2023-02-24



