Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry

Abstract

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.

Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography–Mass Spectrometry (LC-MS)

“…However, we provide evidence that using such an approach can provide value in the biological validation of phenotypes where matched biofluids are not available, indicating that biofluids independently collected using nonmatched protocols (plasma vs serum) may still serve as a valuable validation set to corroborate phenotypic trends and signatures. This builds upon our previous work where we have demonstrated that targeted phenotyping workflows can be robust to different sampling conditions, including blood collection type and degrees of hemolysis when using targeted lipidomic 70 and lipoprotein phenotyping. 71 These findings justify that there remains value in validating biomarker signatures in cohorts in which samples may have been collected or treated differently, withstanding that the methodology is robust to external influences.…”

Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes

“…Plasma lipid analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) using a Exion UHPLC system coupled to a QTRAP 6500+ mass analyzer (Sciex Concord, CA) from a previously published method. 34 In brief, plasma samples (10 μL) were thawed at 4 °C and combined with 90 μL of stable isotopically labeled internal standards diluted in isopropyl alcohol for extraction, utilizing a Biomek i5 liquid handling system for the preparation (Beckman Coulter, Mount Waverley, Victoria 3149, Australia). Samples were chilled and centrifuged for 15 min at 14000 g before 50 μL of supernatant was transferred into a 350 μL 96-well plate for analysis (Eppendorf, Macquarie Park, NSW, Australia).…”

Second Special Issue on Methods for Omics Research: Proteome Research and Beyond

“…25 Ryan et al describe the robust optimization of a clinical analytical pipeline to quantify over 1000 lipid species from plasma and serum using internal standards labeled with stable isotopes (SIL-IS) and targeted mass spectrometry. 26 Finally, two of the computational pipelines described above for deep proteomics were applied to patient samples and shown to significantly improve our ability to detect genomic variants 7 and glycosylated biomarkers. 8 Such technical improvements on both the LC-MS side and the computational analysis of the resulting data sets have the potential to support personalized medicine on a large-scale.…”

“…Spray stability is an important parameter to control when high reproducibility and depth of analysis are of paramount importance, such as for analyzing multiple patient samples . Ryan et al describe the robust optimization of a clinical analytical pipeline to quantify over 1000 lipid species from plasma and serum using internal standards labeled with stable isotopes (SIL-IS) and targeted mass spectrometry . Finally, two of the computational pipelines described above for deep proteomics were applied to patient samples and shown to significantly improve our ability to detect genomic variants and glycosylated biomarkers .…”