Analytical challenges in human plasma lipidomics: A winding path towards the truth

Accurate Determination of Circulatory Lipids Using a Combination of HILIC-MRM and RPLC-PRM

Circulatory lipids are important markers for characterizing disease phenotypes; however, accurately determining lipid species remains a significant challenge in lipidomic analysis. Here, we present a novel analytical workflow for accurate lipidome characterization in human plasma using mass spectrometry (MS) through the integration of hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC). This workflow enables rapid screening of 1,966 lipid species across 18 lipid classes using HILIC-multiple reaction monitoring (MRM), which enables facile identification of lipid species by lipid class-based separations. In the NIST Standard Reference Material for Human Plasma (SRM 1950), 489 lipid species were identified using HILIC-MRM and subsequently analyzed with RPLC-parallel reaction monitoring (PRM) to resolve potential lipid isobars within the same lipid class. Notably, RPLC-PRM identified 70 additional lipidomic features in SRM 1950 that were not detectable with HILIC-MRM. Furthermore, a high correlation (Pearson correlation coefficient = 0.81) was observed regarding the concentrations of lipid species not carrying isobaric interferences in between HILIC-MRM and RPLC-PRM, indicating that the individual lipid concentrations measured by each platform can be integrated. The workflow was further applied to a cohort of 284 human plasma samples from chronic kidney disease (CKD) patients, successfully profiling lipidomic phenotypes across CKD subtypes. These findings demonstrate that combining HILIC-MRM and RPLC-PRM as complementary platforms enhances the accuracy and comprehensiveness of lipidomic analysis.

Benchmarking of Trapped Ion Mobility Spectrometry in Differentiating Plasmalogens from Other Ether Lipids in Lipidomics Experiments

Trapped Ion Mobility Spectrometry (TIMS) has demonstrated promising potential as a powerful discriminating method when coupled with mass spectrometry, enhancing the precision of feature annotation. Such a technique is particularly valuable for lipids, where a large number of isobaric but structurally distinct molecular species often coexist within the same sample matrix. In this study, we explored the potential of ion mobility for ether lipid isomer differentiation. Mammalian ether phospholipids are characterized by a fatty alcohol residue at the sn-1 position of their glycerol backbone. They can make up to 20% of the total phospholipid mass and are present in a broad range of tissues. There they are, for example, crucial for nervous system function, membrane homeostasis, and inter- as well as intracellular signaling. Molecular ether lipid species are difficult to distinguish analytically, as they occur as 1-O-alkyl and 1-O-alkenyl subclasses, with the latter being also known as plasmalogens. Isomeric ether lipid pairs can be separated with reversed-phase chromatography. However, their precise identification remains challenging due to the lack of clear internal reference points, inherent to the nature of lipid profiles and the lack of sufficient commercially available standard substances. Here, we demonstrate─with focus on phosphatidylethanolamines─that ion mobility measurements allow to discriminate between the ether lipid subclasses through distinct differences in their gas phase geometries. This approach offers significant advantages as it does not depend on potential retention time differences between different chromatographic systems. However, the current resolution in the ion mobility dimension is not sufficient to baseline separate 1-O-alkyl and 1-O-alkenyl isobars, and the observed differences are not yet accurately represented in existing collision cross section databases. Despite these challenges, the predictable properties of the ion mobility behavior of ether lipid species can significantly support their accurate annotation and hold promise for future advancements in lipid research.

Perspectives on the success of plasma lipidomics in cardiovascular drug discovery and future challenges

INTRODUCTION

Plasma lipidomics has emerged as a powerful tool in cardiovascular drug discovery by providing insights into disease mechanisms, identifying potential biomarkers for diagnosis and prognosis, and discovering novel targets for drug development. Widespread application of plasma lipidomics is hampered by technological limitations and standardization and requires a collaborative approach to maximize its use in cardiovascular drug discovery.

AREAS COVERED

This review provides an overview of the utility of plasma lipidomics in cardiovascular drug discovery and discusses the challenges and future perspectives of this rapidly evolving field. The authors discuss the role of lipidomics in understanding the molecular mechanisms of CVD, identifying novel biomarkers for diagnosis and prognosis, and discovering new therapeutic targets for drug development. Furthermore, they highlight the challenges faced in data analysis, standardization, and integration with other omics approaches and propose future directions for the field.

EXPERT OPINION

Plasma lipidomics holds great promise for improving the diagnosis, treatment, and prevention of CVD. While challenges remain in standardization and technology, ongoing research and collaboration among scientists and clinicians will undoubtedly help overcome these obstacles. As lipidomics evolves, its impact on cardiovascular drug discovery and clinical practice is expected to grow, ultimately benefiting patients and healthcare systems worldwide.

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

High Throughput LC-MS Platform for Large Scale Screening of Bioactive Polar Lipids in Human Plasma and Serum

Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples.

A Sample Preparation Method for the Simultaneous Profiling of Signaling Lipids and Polar Metabolites in Small Quantities of Muscle Tissues from a Mouse Model for Sarcopenia

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1^∆/- mouse mutant exhibiting multiple-morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.

Dual-Mechanism-Driven Strategy for High-Coverage Detection of Serum Lipids on a Novel SALDI-MS Target

Serum lipid metabolites have been emerging as ideal biomarkers for disease diagnosis and prediction. In the current stage, nontargeted or targeted lipidomic research mainly relies on a liquid chromatography-mass spectrometry (LC-MS) platform, but future clinical applications need more robust and high-speed platforms. Surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) has shown excellent advantages in the high-speed analysis of lipid metabolites. However, the platform in the positive ion mode is more inclined to target a certain class of lipids, leading to the low coverage of lipid detection and limiting its practical translation to clinical applications. Herein, we proposed a dual-mechanism-driven strategy for high-coverage detection of serum lipids on a novel SALDI-MS target, which is a composite nanostructure comprising vertical silicon nanowires (VSiNWs) decorated with AuNPs and polydopamine (VSiNW-Au-PDA). The performance of laser desorption and ionization on the target can be enhanced by charge-driven desorption coupled with thermal-driven desorption. Simultaneous detection of 236 serum lipids (S/N ≥ 5) including neutral and polar lipids can be achieved in the positive ion mode. Among these, 107 lipid peaks were successfully identified. When combined with VSiNW-Au-PDA and VSiNW chips, 479 lipid peaks can be detected in serum samples in positive and negative ion modes, respectively. Based on the platform, serum samples from 57 hepatocellular carcinoma (HCC) patients and 76 healthy controls were analyzed. After data mining, 14 lipids containing different lipid types (TAG, CE, PC) were selected as potential lipidomic biomarkers. With the assistance of an artificial neural network, a diagnostic model with a sensitivity of 92.7% and a specificity of 96% was constructed for HCC diagnosis.

Clinical lipidomics – A community-driven roadmap to translate research into clinical applications

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Overview of current state of mass spectrometry based lipidomics.

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Highlighting ongoing efforts towards harmonization.

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Invitation to join international community.

Lipid metabolites, beyond triglycerides and cholesterol, have been shown to have vast potential for applications in clinical applications, with substantial societal and economical value. To successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization – if not standardization – of these mass spectrometry-based workflows is necessary. Input on clinical needs and technological capabilities must be obtained from all relevant stakeholders, including wet lab scientists, informaticians and data scientists, manufacturers, and medical professionals. In order to build bridges between this diverse group of professionals, the International Lipidomics Society and its Clinical Lipidomics Interest Group were created. This opinion article is intended to provide an overview of international efforts to tackle the issues of workflow harmonization, and to serve as an open invitation for others to join this growing community.

Nonalcoholic fatty liver disease stratification by liver lipidomics

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

A normalized signal calibration with a long-term reference improves the robustness of RPLC-MRM/MS lipidomics in plasma

Improving the reliability of quantification in lipidomic analyses is crucial for its successful application in the discovery of new biomarkers or in clinical practice. In this study, we propose a workflow to improve the accuracy and precision of lipidomic results issued by the laboratory. Lipid species from 11 classes were analyzed by a targeted RPLC-MRM/MS method. The peak areas of species were used to estimate concentrations by an internal standard calibration approach (IS-calibration) and by an alternative normalization signal calibration schema (NS-calibration). The latter uses a long-term reference plasma material as a matrix-matched external calibrator whose accuracy was compared to the NIST SRM-1950 mean consensus values reported by the Interlaboratory Lipidomics Comparison Exercise. The bias of lipid concentrations showed a good accuracy for 69 of 89 quantified lipids. The quantitation of species by the NS-calibration schema improved the within- and between-batch reproducibility in quality control samples, in comparison to the usual IS-calibration approach. Moreover, the NS-calibration workflow improved the robustness of the lipidomics measurements reducing the between-batch variability (relative standard deviation <10% for 95% of lipid species) in real conditions tested throughout the analysis of 120 plasma samples. In addition, we provide a free access web tool to obtain the concentration of lipid species by the two previously mentioned quantitative approaches, providing an easy follow-up of quality control tasks related to lipidomics.

Single-Step Extraction Coupled with Targeted HILIC-MS/MS Approach for Comprehensive Analysis of Human Plasma Lipidome and Polar Metabolome

Expanding metabolome coverage to include complex lipids and polar metabolites is essential in the generation of well-founded hypotheses in biological assays. Traditionally, lipid extraction is performed by liquid-liquid extraction using either methyl-tert-butyl ether (MTBE) or chloroform, and polar metabolite extraction using methanol. Here, we evaluated the performance of single-step sample preparation methods for simultaneous extraction of the complex lipidome and polar metabolome from human plasma. The method performance was evaluated using high-coverage Hydrophilic Interaction Liquid Chromatography-ESI coupled to tandem mass spectrometry (HILIC-ESI-MS/MS) methodology targeting a panel of 1159 lipids and 374 polar metabolites. The criteria used for method evaluation comprised protein precipitation efficiency, and relative MS signal abundance and repeatability of detectable lipid and polar metabolites in human plasma. Among the tested methods, the isopropanol (IPA) and 1-butanol:methanol (BUME) mixtures were selected as the best compromises for the simultaneous extraction of complex lipids and polar metabolites, allowing for the detection of 584 lipid species and 116 polar metabolites. The extraction with IPA showed the greatest reproducibility with the highest number of lipid species detected with the coefficient of variation (CV) < 30%. Besides this difference, both IPA and BUME allowed for the high-throughput extraction and reproducible measurement of a large panel of complex lipids and polar metabolites, thus warranting their application in large-scale human population studies.

Recent advances in analytical strategies for mass spectrometry-based lipidomics

Lipids are vital biological molecules and play multiple roles in cellular function of mammalian organisms such as cellular membrane anchoring, signal transduction, material trafficking and energy storage. Driven by the biological significance of lipids, lipidomics has become an emerging science in the field of omics. Lipidome in biological systems consists of hundreds of thousands of individual lipid molecules that possess complex structures, multiple categories, and diverse physicochemical properties assembled by different combinations of polar headgroups and hydrophobic fatty acyl chains. Such structural complexity poses a huge challenge for comprehensive lipidome analysis. Thanks to the great innovations in chromatographic separation techniques and the continuous advances in mass spectrometric detection tools, analytical strategies for lipidomics have been highly diversified so that the depth and breadth of lipidomics have been greatly enhanced. This review will present the current state of mass spectrometry-based analytical strategies including untargeted, targeted and pseudotargeted lipidomics. Recent typical applications of lipidomics in biomarker discovery, pathogenic mechanism and therapeutic strategy are summarized, and the challenges facing to the field of lipidomics are also discussed.

Structural Elucidation of Ether Glycerophospholipids Using Gas-Phase Ion/Ion Charge Inversion Chemistry

Ether lipids represent a unique subclass of glycerophospholipid (GPL) that possesses a 1-O-alkyl (i.e., plasmanyl subclass) or a 1-O-alk-1'-enyl (i.e., plasmenyl subclass) group linked at the sn-1 position of the glycerol backbone. As changes in ether GPL composition and abundance are associated with numerous human pathologies, analytical strategies capable of providing high-level structural detail are desirable. While mass spectrometry (MS) has emerged as a prominent tool for lipid structural elucidation in biological extracts, distinctions between the various isomeric forms of ether-linked GPLs have remained a significant challenge for tandem MS, principally due to similarities in the conventional tandem mass spectra obtained from the two ether-linked subclasses. To distinguish plasmanyl and plasmenyl GPLs, a multistage (i.e., MSn where n = 3 or 4) mass spectrometric approach reliant on low-energy collision-induced dissociation (CID) is required. While this method facilitates assignment of the sn-1 bond type (i.e., 1-O-alkyl versus 1-O-alk-1'-enyl), a composite distribution of isomers is left unresolved, as carbon-carbon double-bond (C=C) positions cannot be localized in the sn-2 fatty acyl substituent. In this study, we combine a systematic MSn approach with two unique gas-phase charge inversion ion/ion chemistries to elucidate ether GPL structures with high-level detail. Ultimately, we assign both the sn-1 bond type and sites of unsaturation in the sn-2 fatty acyl substituent using an entirely gas-phase MS-based workflow. Application of this workflow to human blood plasma extract permitted isomeric resolution and in-depth structural identification of major and, in some cases, minor isomeric contributors to ether GPLs that have been previously unresolved when examined via conventional methods.

Imaging of Triglycerides in Tissues Using Nanospray Desorption Electrospray Ionization (Nano-DESI) Mass Spectrometry

Nonpolar triglycerides (TGs) are rarely detected in mass spectrometry imaging (MSI) experiments unless they are abundant in the sample. Herein, we use nanospray desorption electrospray ionization (nano-DESI) to explore the role of the solvent composition and ionic dopants on the detection of TGs in a murine gastrocnemius muscle tissue used as a model system. We evaluated three solvent mixtures for their ability to extract nonpolar TG species: MeOH:H2O 9:1 (v/v), MeOH:DCM 6:4 (v/v) and MeOH:AcN:tol 5:3.5:1.5 (v/v/v). We observe that TGs are mainly detected as [M+K]+ adducts and their extraction efficiency is improved using less polar solvents: MeOH:DCM and MeOH:AcN:tol. We also explore whether the ionization efficiency of TGs may be improved by doping the MeOH:AcN:tol solvent with ammonium formate (AF) and other ionic additives. However, the formation of [M+NH4]+ adducts of TGs is less efficient than the formation of [M+K]+ adducts in the range of AF concentrations from 0.1 to 10 mM. Chemical derivatization using 100 μM of Girard T reagent predominately generates reaction products of phosphatidylcholine rather than TG species. Moreover, the presence of the Girard T reagent suppresses ion signals of all the species in the spectrum including TGs. Nano-DESI MSI experiments performed using MeOH:AcN:tol solvent enable imaging of TGs without any detectable adverse effect on signals of other lipids and metabolites. Specifically, 10 out of 14 TG species were detected exclusively using MeOH:AcN:tol and the sensitivity towards other TGs was improved by at least an order of magnitude. Although polyunsaturated TGs may be detected using both solvents, saturated and monounsaturated TGs are only detected using MeOH:AcN:tol. Our results provide a direct path for the improved detection of TGs in tissue imaging experiments using liquid-based ambient ionization techniques.

Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.

Toward Complete Structure Elucidation of Glycerophospholipids in the Gas Phase through Charge Inversion Ion/Ion Chemistry

Shotgun lipidomics has recently gained popularity for lipid analysis. Conventionally, shotgun analysis of glycerophospholipids via direct electrospray ionization tandem mass spectrometry (ESI-MS/MS) provides glycerophospholipid (GPL) class (i.e., headgroup composition) and fatty acyl composition. Reliant on low-energy collision-induced dissociation (CID), traditional ESI-MS/MS fails to define fatty acyl regiochemistry along the glycerol backbone or carbon-carbon double bond position(s) in unsaturated fatty acyl substituents. Therefore, isomeric GPLs are often unresolved, representing a significant challenge for shotgun-MS approaches. We developed a top-down shotgun-MS method utilizing gas-phase ion/ion charge inversion chemistry that provides near-complete GPL structural identification. First, in negative ion mode, CID of mass-selected GPL anions generates fatty acyl carboxylate anions via fragmentation of ester bonds linking the fatty acyl substituents at the sn-1 and sn-2 positions of the glycerol backbone. Product anions, including fatty acyl carboxylate ions, were then derivatized in the mass spectrometer via an ion/ion charge inversion reaction with tris-phenanthroline magnesium dications. Subsequent CID of charge-inverted fatty acyl complex cations yielded isomer-specific product ion spectra that permit (i) unambiguous assignment of carbon-carbon double bond position(s) and (ii) relative quantitation of isomeric fatty acyl substituents. The outlined strategy was applied to the analysis of targeted GPLs extracted from human plasma, including several proposed plasma biomarkers. A single experiment thus facilitates assignment of the GPL headgroup, fatty acyl composition, carbon-carbon double bond position(s) in unsaturated fatty acyl chains, and, in some cases, fatty acyl sn-position and relative abundances for isomeric fatty acyl substituents. Ultimately, this MSn platform paired with ion/ion chemistry permitted identification of major, and some minor, isomeric contributors that are unresolved using conventional ESI-MS/MS.

Quantitative Fragmentation Model for Bottom-Up Shotgun Lipidomics

Quantitative bottom-up shotgun lipidomics relies on molecular species-specific "signature" fragments consistently detectable in tandem mass spectra of analytes and standards. Molecular species of glycerophospholipids are typically quantified using carboxylate fragments of their fatty acid moieties produced by higher-energy collisional dissociation of their molecular anions. However, employing standards whose fatty acids moieties are similar, yet not identical, to the target lipids could severely compromise their quantification. We developed a generic and portable fragmentation model implemented in the open-source LipidXte software that harmonizes the abundances of carboxylate anion fragments originating from fatty acid moieties having different sn-1/2 positions at the glycerol backbone, length of the hydrocarbon chain, and number and location of double bonds. The postacquisition adjustment enables unbiased absolute (molar) quantification of glycerophospholipid species independent of instrument settings, collision energy, and employed internal standards.

Mapping Unsaturation in Human Plasma Lipids by Data-Independent Ozone-Induced Dissociation

Over 1500 different lipids have been reported in human plasma at the sum composition level. Yet the number of unique lipids present is surely higher, once isomeric contributions from double bond location(s) and fatty acyl regiochemistry are considered. In order to resolve this ambiguity, herein, we describe the incorporation of ozone-induced dissociation (OzID) into data-independent shotgun lipidomics workflows on a high-resolution hybrid quadrupole-Orbitrap platform. In this configuration, [M + Na]⁺ ions generated by electrospray ionization of a plasma lipid extract were transmitted through the quadrupole in 1 Da segments. Reaction of mass-selected lipid ions with ozone in the octopole collision cell yielded diagnostic ions for each double bond position. The increased ozone concentration in this region significantly improved ozonolysis efficiency compared with prior implementations on linear ion-trap devices. This advancement translates into increased lipidome coverage and improvements in duty cycle for data-independent MS/MS analysis using shotgun workflows. Grouping all precursor ions with a common OzID neutral loss enables straightforward classification of the lipidome by unsaturation position (with respect to the methyl terminus). Two-dimensional maps obtained from this analysis provide a powerful visualization of structurally related lipids and lipid isomer families within plasma. Global profiling of lipid unsaturation in plasma extracts reveals that most unsaturated lipids are present as isomeric mixtures. These new insights provide a unique picture of underlying metabolism that could in the future provide novel indicators of health and disease.