Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

A comprehensive UHPLC-MS/MS method for metabolomics profiling of signaling lipids: Markers of oxidative stress, immunity and inflammation.

Signaling lipids (SLs) play a crucial role in various signaling pathways, featuring diverse lipid backbone structures. Emerging evidence showing the biological significance and biomedical values of SLs has strongly spurred the advancement of analytical approaches aimed at profiling SLs. Nevertheless, the dramatic differences in endogenous abundances across lipid classes as well as multiple isomers within the same lipid class makes the development of a generic analytical method challenging. A better analytical method that combines comprehensive coverage and high sensitivity is needed to enable us to gain a deeper understanding of the biochemistry of these molecules in health and disease. In this study, we developed a fast and comprehensive targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for profiling SLs. The platform enables analyses of 260 metabolites covering oxylipins (isoprostanes, prostaglandins and other oxidized lipids), free fatty acids, lysophospholipids, sphingoid bases (C16, C18), platelet activating factors (C16, C18), endocannabinoids and bile acids. Various validation parameters including linearity, limit of detection, limit of quantification, extraction recovery, matrix effect, intra-day and inter-day precision were used to characterize this method. Metabolite quantitation was successfully achieved in both NIST Standard Reference Material for human plasma (NIST SRM 1950) and pooled human plasma, with 109 and 144 metabolites quantitated. The quantitation results in NIST SRM 1950 plasma demonstrated good correlations with certified or previously reported values in published literature. This study introduced quantitative data for 37 SLs for the first time. Metabolite concentrations measured in NIST SRM 1950 will serve as essential reference data for facilitating interlaboratory comparisons. The methodology established here will be the cornerstone for in-depth profiling of signaling lipids across diverse biological samples and contexts.

Targeted proteomics and metabolomics for biomarker discovery in abdominal aortic aneurysm and post-EVAR sac volume.

BACKGROUND AND AIMS: Abdominal aortic aneurysm (AAA) patients undergo uniform surveillance programs both leading up to, and following surgery. Circulating biomarkers could play a pivotal role in individualizing surveillance. We applied a multi-omics approach to identify relevant biomarkers and gain pathophysiological insights. MATERIALS AND METHODS: In this cross-sectional study, 108 AAA patients and 200 post-endovascular aneurysm repair (post-EVAR) patients were separately investigated. We performed partial least squares regression and ingenuity pathway analysis on circulating concentrations of 96 proteins (92 Olink Cardiovascular-III panel, 4 ELISA-assays) and 199 metabolites (measured by LC-TQMS), and their associations with CT-based AAA/sac volume. RESULTS: The median (25th-75th percentile) maximal diameter was 50.0 mm (46.0, 53.0) in the AAA group, and 55.4 mm (45.0, 64.2) in the post-EVAR group. Correcting for clinical characteristics in AAA patients, the aneurysm volume Z-score differed 0.068 (95 %CI: (0.042, 0.093)), 0.066 (0.047, 0.085) and -0.051 (-0.064, -0.038) per Z-score valine, leucine and uPA, respectively. After correcting for clinical characteristics and orthogonalization in the post-EVAR group, the sac volume Z-score differed 0.049 (0.034, 0.063) per Z-score TIMP-4, -0.050 (-0.064, -0.037) per Z-score LDL-receptor, -0.051 (-0.062, -0.040) per Z-score 1-OG/2-OG and -0.056 (-0.066, -0.045) per Z-score 1-LG/2-LG. CONCLUSIONS: The branched-chain amino acids and uPA were related to AAA volume. For post-EVAR patients, LDL-receptor, monoacylglycerols and TIMP-4 are potential biomarkers for sac volume. Additionally, distinct markers for sac change were identified.

High-resolution ion mobility spectrometry-mass spectrometry for isomeric separation of prostanoids after Girard's reagent T derivatization.

RATIONALE: Isomeric separation of prostanoids is often a challenge and requires chromatography and time-consuming sample preparation. Multiple prostanoid isomers have distinct in vivo functions crucial for understanding the inflammation process, including prostaglandins E2 (PGE2 ) and D2 (PGD2 ). High-resolution ion mobility spectrometry (IMS) based on linear ion transport in low-to-moderate electric fields and nonlinear ion transport in strong electric fields emerges as a broad approach for rapid separations prior to mass spectrometry. METHODS: Derivatization with Girard's reagent T (GT) was used to overcome inefficient ionization of prostanoids in negative ionization mode due to poor deprotonation of the carboxylic acid group. Three high-resolution IMS techniques, namely linear cyclic IMS, linear trapped IMS, and nonlinear high-field asymmetric waveform IMS, were compared for the isomeric separation and endogenous detection of prostanoids present in intestinal tissue. RESULTS: Direct infusion of GT-derivatized prostanoids proved to increase the ionization efficiency in positive ionization mode by a factor of >10, which enabled detection of these molecules in endogenous concentration levels. The high-resolution IMS comparison revealed its potential for rapid isomeric analysis of biologically relevant prostanoids. Strengths and weaknesses of both linear and nonlinear IMS are discussed. Endogenous prostanoid detection in intestinal tissue extracts demonstrated the applicability of our approach in biomedical research. CONCLUSIONS: The applied derivatization strategy offers high sensitivity and improved stereoisomeric separation for screening of complex biological systems. The high-resolution IMS comparison indicated that the best sensitivity and resolution are achieved by linear and nonlinear IMS, respectively.

Plasma Oxylipins and Their Precursors Are Strongly Associated with COVID-19 Severity and with Immune Response Markers.

COVID-19 is characterised by a dysregulated immune response, that involves signalling lipids acting as mediators of the inflammatory process along the innate and adaptive phases. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The second publication in a series reports the results of quantitative LC-MS/MS profiling of 63 small lipids including oxylipins, free fatty acids, and endocannabinoids. Compared to samples taken from ward patients, intensive care unit (ICU) patients had 2−4-fold lower levels of arachidonic acid (AA) and its cyclooxygenase-derived prostanoids, as well as lipoxygenase derivatives, exhibiting negative correlations with inflammation markers. The same derivatives showed 2−5-fold increases in recovering ward patients, in paired comparison to early hospitalisation. In contrast, ICU patients showed elevated levels of oxylipins derived from poly-unsaturated fatty acids (PUFA) by non-enzymatic peroxidation or activity of soluble epoxide hydrolase (sEH), and these oxylipins positively correlated with markers of macrophage activation. The deficiency in AA enzymatic products and the lack of elevated intermediates of pro-resolving mediating lipids may result from the preference of alternative metabolic conversions rather than diminished stores of PUFA precursors. Supporting this, ICU patients showed 2-to-11-fold higher levels of linoleic acid (LA) and the corresponding fatty acyl glycerols of AA and LA, all strongly correlated with multiple markers of excessive immune response. Our results suggest that the altered oxylipin metabolism disrupts the expected shift from innate immune response to resolution of inflammation.

Quantitative mass spectrometry imaging of drugs and metabolites: a multiplatform comparison.

Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 µg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97-112% accuracy. Other MS modes resulted in LOD 6.7-569.4 and 2.6-119.1 µg/g tissue, R2 0.86-0.98 and 0.86-0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70-356% and 64-398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.

Ion mobility spectrometry combined with multivariate statistical analysis: revealing the effects of a drug candidate for Alzheimer's disease on Aß1-40 peptide early assembly.

Inhibition of the initial stages of amyloid-ß peptide self-assembly is a key approach in drug development for Alzheimer's disease, in which soluble and highly neurotoxic low molecular weight oligomers are produced and aggregate in the brain over time. Here we report a high-throughput method based on ion mobility mass spectrometry and multivariate statistical analysis to rapidly select statistically significant early-stage species of amyloid-ß1-40 whose formation is inhibited by a candidate theranostic agent. Using this method, we have confirmed the inhibition of a Zn-porphyrin-peptide conjugate in the early self-assembly of Aß40 peptide. The MS/MS fragmentation patterns of the species detected in the samples containing the Zn-porphyrin-peptide conjugate suggested a porphyrin-catalyzed oxidation at Met-35(O) of Aß40. We introduce ion mobility MS combined with multivariate statistics as a systematic approach to perform data analytics in drug discovery/amyloid research that aims at the evaluation of the inhibitory effect on the Aß early assembly in vitro models at very low concentration levels of Aß peptides.

Targeted Drug and Metabolite Imaging: Desorption Electrospray Ionization Combined with Triple Quadrupole Mass Spectrometry.

Mass spectrometry imaging (MSI) has proven to be a valuable tool for drug and metabolite imaging in pharmaceutical toxicology studies and can reveal, for example, accumulation of drug candidates in early drug development. However, the lack of sample cleanup and chromatographic separation can hamper the analysis due to isobaric interferences. Multiple reaction monitoring (MRM) uses unique precursor ion-product ion transitions to add specificity which leads to higher selectivity. Here, we present a targeted imaging platform where desorption electrospray ionization is combined with a triple quadrupole (QqQ) system to perform MRM imaging. The platform was applied to visualize (i) lipids in mouse brain tissue sections and (ii) a drug candidate and metabolite in canine liver tissue. All QqQ modes were investigated to show the increased detection time provided by MRM as well as the possibility to perform dual polarity imaging. This is very beneficial for lipid imaging because some phospholipid classes ionize in opposite polarity (e.g., phosphatidylcholine/sphingomyelin in positive ion mode and phosphatidylserine/phosphatidylethanolamine in negative ion mode). Drug and metabolite images were obtained to show its strength in drug distribution studies. Multiple MRM transitions were used to confirm the local presence and selective detection of pharmaceutical compounds.

Integration of Ion Mobility MSE after Fully Automated, Online, High-Resolution Liquid Extraction Surface Analysis Micro-Liquid Chromatography.

Direct analysis by mass spectrometry (imaging) has become increasingly deployed in preclinical and clinical research due to its rapid and accurate readouts. However, when it comes to biomarker discovery or histopathological diagnostics, more sensitive and in-depth profiling from localized areas is required. We developed a comprehensive, fully automated online platform for high-resolution liquid extraction surface analysis (HR-LESA) followed by micro-liquid chromatography (LC) separation and a data-independent acquisition strategy for untargeted and low abundant analyte identification directly from tissue sections. Applied to tissue sections of rat pituitary, the platform demonstrated improved spatial resolution, allowing sample areas as small as 400 µm to be studied, a major advantage over conventional LESA. The platform integrates an online buffer exchange and washing step for removal of salts and other endogenous contamination that originates from local tissue extraction. Our carry over-free platform showed high reproducibility, with an interextraction variability below 30%. Another strength of the platform is the additional selectivity provided by a postsampling gas-phase ion mobility separation. This allowed distinguishing coeluted isobaric compounds without requiring additional separation time. Furthermore, we identified untargeted and low-abundance analytes, including neuropeptides deriving from the pro-opiomelanocortin precursor protein and localized a specific area of the pituitary gland (i.e., adenohypophysis) known to secrete neuropeptides and other small metabolites related to development, growth, and metabolism. This platform can thus be applied for the in-depth study of small samples of complex tissues with histologic features of ∼400 µm or more, including potential neuropeptide markers involved in many diseases such as neurodegenerative diseases, obesity, bulimia, and anorexia nervosa.