As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

In this study, we sought to determine whether asthma has a metabolic profile and whether this profile is related to disease severity.We characterised the serum from 22 healthy individuals and 54 asthmatics (12 mild, 20 moderate, 22 severe) using liquid chromatography–high-resolution mass spectrometry-based metabolomics. Selected metabolites were confirmed by targeted mass spectrometry assays of eicosanoids, sphingolipids and free fatty acids.We conclusively identified 66 metabolites; 15 were significantly altered with asthma (p≤0.05). Levels of dehydroepiandrosterone sulfate, cortisone, cortisol, prolylhydroxyproline, pipecolate and N-palmitoyltaurine correlated significantly (p<0.05) with inhaled corticosteroid dose, and were further shifted in individuals treated with oral corticosteroids. Oleoylethanolamide increased with asthma severity independently of steroid treatment (p<0.001). Multivariate analysis revealed two patterns: 1) a mean difference between controls and patients with mild asthma (p=0.025), and 2) a mean difference between patients with severe asthma and all other groups (p=1.7×10−4). Metabolic shifts in mild asthma, relative to controls, were associated with exogenous metabolites (e.g. dietary lipids), while those in moderate and severe asthma (e.g. oleoylethanolamide, sphingosine-1-phosphate, N-palmitoyltaurine) were postulated to be involved in activating the transient receptor potential vanilloid type 1 (TRPV1) receptor, driving TRPV1-dependent pathogenesis in asthma.Our findings suggest that asthma is characterised by a modest systemic metabolic shift in a disease severity-dependent manner, and that steroid treatment significantly affects metabolism.

Quantitative determination of lipid species provides insights to lipid homeostasis and its dysregulation in diseased states. Thus, lipidomic approaches by mass spectrometrybased technology are attractive for characterization of specifi c lipids as modulators or disruptors of signaling and metabolic pathways, or as biomarkers in the clinical setting ( 1-5 ). Particularly, mass spectrometry and advanced bioinformatics tools enable such approaches today ( 6, 7 ).Direct infusion shotgun mass spectrometry is established for "global" lipidomic analysis ( 8-13 ). It is fast and simple, but it suffers from inherent ion suppression effects that may be of advantage in some cases ( 14 ). Yet, for certain triacylglycerol-rich samples, a precleaning step is necessary ( 13 ). As an alternative approach, liquid chromatography coupled to mass spectrometry (i.e., LC/ESI-MS) can be used. Here, a variety of different reversed-phase and normal-phase liquid chromatographic separation techniques afford higher detection sensitivity in mass spectrometers (15)(16)(17)(18)(19)(20)(21)(22)(23)

We developed decision rule sets for Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2), enabling automated and reliable annotation of lipid species and their molecular structures in high-throughput data from chromatography-coupled tandem mass spectrometry. Platform independence was proven in various mass spectrometric experiments, comprising low- and high-resolution instruments and several collision energies. We propose that this independence and the capability to identify novel lipid molecular species render current state-of-the-art lipid libraries now obsolete.

One decade after the genomic and the proteomic life science revolution, new ‘omics’ fields are emerging. The metabolome encompasses the entity of small molecules—Most often end products of a catalytic process regulated by genes and proteins—with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like ‘shotgun lipidomics’, liquid chromatography—Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most ‘omics’ workflows.