Four-dimensional lipidomics profiling in X-linked adrenoleukodystrophy using trapped ion mobility mass spectrometry

Transformative potentials, challenges and innovative solutions of lipidomics in multiple clinical applications

Lipidomics, a rapidly evolving field within metabolomics, provides comprehensive insights into lipid profiles and their roles in health and disease. Advances in lipidomics have enabled the discovery of novel biomarkers with significant clinical applications, revolutionizing the diagnosis, prognosis, and therapeutic monitoring of various diseases. Emerging methodologies, including high-resolution mass spectrometry (HRMS), Ion mobility spectrometry (IMS), and Supercritical Fluid Chromatography (SFC) have enhanced lipid identification and quantification with remarkable analytical whip hands. These advancements are complemented by innovative sample preparation techniques ensuring the recovery of diverse lipid species with minimal degradation. Biomarker discovery with lipidomics has illuminated critical pathways in numerous diseases, including cardiovascular disorders, neurodegenerative conditions, metabolic syndromes, and cancers. Specific lipid classes, such as sphingolipids (SLs) and phospholipids (PLs) have been linked to Alzheimer's disease and diabetes, respectively, while oxylipins and eicosanoids are emerging as inflammatory biomarkers. Furthermore, lipidomic profiles have shown promise in personalized medicine, enabling the stratification of patient sub-populations and tailoring treatment strategies. This review emphasizes the latest innovative developments in analytical technologies, advanced sample preparation techniques and challenges for lipidomics research including bioinformatic tools on multiple clinical conditions. By exploring these cutting-edge developments, this review highlights the transformative potential of lipidomics in biomarker discovery across diverse clinical applications.

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.