Untargeted UHPLC-ESI-QTOF-MS/MS analysis with targeted feature extraction at precursor and fragment level for profiling of the platelet lipidome with ex vivo thrombin-activation

Plasma Instead of Serum Avoids Critical Confounding of Clinical Metabolomics Studies by Platelets

Metabolomics is an emerging and powerful bioanalytical method supporting clinical investigations. Serum and plasma are commonly used without rational prioritization. Serum is collected after blood coagulation, a complex biochemical process involving active platelet metabolism. This may affect the metabolome and increase the variance, as platelet counts and function may vary substantially in individuals. A multiomics approach systematically investigating the suitability of serum and plasma for clinical studies demonstrated that metabolites correlated well (n = 461, R2 = 0.991), whereas lipid mediators (n = 83, R2 = 0.906) and proteins (n = 322, R2 = 0.860) differed substantially between specimen. Independently, analysis of platelet releasates identified most biomolecules significantly enriched in serum compared to plasma. A prospective, randomized, controlled parallel group metabolomics trial with acetylsalicylic acid administered for 7 days demonstrated that the apparent drug effects significantly differ depending on the analyzed specimen. Only serum analyses of healthy individuals suggested a significant downregulation of TXB2 and 12-HETE, which were specifically formed during coagulation in vitro. Plasma analyses reliably identified acetylsalicylic acid effects on metabolites and lipids occurring in vivo such as an increase in serotonin, 15-deoxy-PGJ2 and sphingosine-1-phosphate and a decrease in polyunsaturated fatty acids. The present data suggest that plasma should be preferred above serum for clinical metabolomics studies as the serum metabolome may be substantially confounded by platelets.

Machine learning insights into thrombo-ischemic risks and bleeding events through platelet lysophospholipids and acylcarnitine species

Coronary artery disease (CAD) often leads to adverse events resulting in significant disease burdens. Underlying risk factors often remain inapparent prior to disease incidence and the cardiovascular (CV) risk is not exclusively explained by traditional risk factors. Platelets inherently promote atheroprogression and enhanced platelet functions and distinct platelet lipid species are associated with disease severity in patients with CAD. Lipidomics data were acquired using mass spectrometry and processed alongside clinical data applying machine learning to model estimates of an increased CV risk in a consecutive CAD cohort (n = 595). By training machine learning models on CV risk measurements, stratification of CAD patients resulted in a phenotyping of risk groups. We found that distinct platelet lipids are associated with an increased CV or bleeding risk and independently predict adverse events. Notably, the addition of platelet lipids to conventional risk factors resulted in an increased diagnostic accuracy of patients with adverse CV events. Thus, patients with aberrant platelet lipid signatures and platelet functions are at elevated risk to develop adverse CV events. Machine learning combining platelet lipidome data and common clinical parameters demonstrated an increased diagnostic value in patients with CAD and might improve early risk discrimination and classification for CV events.

cGMP modulates hemin-mediated platelet death

BACKGROUND AND AIMS

Hemolysis is a known risk factor for thrombosis resulting in critical limb ischemia and microcirculatory disturbance and organ failure. Intravasal hemolysis may lead to life-threatening complications due to uncontrolled thrombo-inflammation. Until now, conventional antithrombotic therapies failed to control development and progression of these thrombotic events. Thus, the pathophysiology of these thrombotic events needs to be investigated to unravel underlying pathways and thereby identify targets for novel treatment strategies.

METHODS

Here we used classical experimental set-ups as well as high-end flow cytometry, metabolomics and lipidomic analysis to in-depth analyze the effects of hemin on platelet physiology and morphology.

RESULTS

Hemin does strongly and swiftly induce platelet activation and this process is modulated by the sGC-cGMP-cGKI signaling axis. cGMP modulation also reduced the pro-aggregatory potential of plasma derived from patients with hemolysis. Furthermore, hemin-induced platelet death evokes distinct platelet subpopulations. Typical cell death markers, such as ROS, were induced by hemin-stimulation and the platelet lipidome was specifically altered by high hemin concentration. Specifically, arachidonic acid derivates, such as PGE2, TXB2 or 12-HHT, were significantly increased. Balancing the cGMP levels by modulation of the sGC-cGMP-cGKI axis diminished the ferroptotic effect of hemin.

CONCLUSION

We found that cGMP modulates hemin-induced platelet activation and thrombus formation in vitro and cGMP effects hemin-mediated platelet death and changes in the platelet lipidome. Thus, it is tempting to speculate that modulating platelet cGMP levels may be a novel strategy to control thrombosis and critical limb ischemia in patients with hemolytic crisis.

Phosphatidylthreonine is a procoagulant lipid detected in human blood and elevated in coronary artery disease

Aminophospholipids (aPL) such as phosphatidylserine are essential for supporting the activity of coagulation factors, circulating platelets, and blood cells. Phosphatidylthreonine (PT) is an aminophospholipid previously reported in eukaryotic parasites and animal cell cultures, but not yet in human tissues. Here, we evaluated whether PT is present in blood cells and characterized its ability to support coagulation. Several PT molecular species were detected in human blood, washed platelets, extracellular vesicles, and isolated leukocytes from healthy volunteers using liquid chromatography-tandem mass spectrometry. The ability of PT to support coagulation was demonstrated in vitro using biochemical and biophysical assays. In liposomes, PT supported prothrombinase activity in the presence and absence of phosphatidylserine. PT nanodiscs strongly bound FVa and lactadherin (nM affinity) but poorly bound prothrombin and FX, suggesting that PT supports prothrombinase through recruitment of FVa. PT liposomes bearing tissue factor poorly generated thrombin in platelet poor plasma, indicating that PT poorly supports extrinsic tenase activity. On platelet activation, PT is externalized and partially metabolized. Last, PT was significantly higher in platelets and extracellular vesicle from patients with coronary artery disease than in healthy controls. In summary, PT is present in human blood, binds FVa and lactadherin, supports coagulation in vitro through FVa binding, and is elevated in atherosclerotic vascular disease. Our studies reveal a new phospholipid subclass, that contributes to the procoagulant membrane, and may support thrombosis in patients at elevated risk.

Analysis of Phospholipids in Digestion Using Hybrid IDA and SWATH Acquisition: An Example for Krill Oil

The composition and digestion of phospholipid-rich foods have important effects on the health of the body. Herein, a model-assisted liquid chromatography coupling mass spectrometry (LC-MS) method was established to analyze the phosphatidylcholine (PC) and lyso-phosphatidylcholine (LPC) species in krill oil before and after digestion. According to the confirmed PC and LPC species in the IDA (information dependent acquisition) results, three categories of mathematical models were set up, involving the retention time (RT), carbon number and unsaturation degree of the fatty acyl chain. All of the regression coefficient values (R²) were greater than 0.90, showing satisfactory fitting results. On this basis, using the computationally created precursor ion mass of PC and LPC species, 12 extra PC species and 4 LPC species were found in the SWATH (sequential windowed acquisition of all theoretical fragment ions) results. The PC and LPC compositions in the final digestive products had obvious differences among the different krill oils with different phospholipid content. Furthermore, more than half of the LPC species in the final digestive products were newly generated, indicating that LPC was one of basic constituents in the digestive products of krill oil. In conclusion, model-assisted hybrid IDA and SWATH acquisition has excellent detection performance, contributing to deep studies of the formations and functions of phospholipids.

Quantification of bulk lipid species in human platelets and their thrombin-induced release

Lipids play a central role in platelet physiology. Changes in the lipidome have already been described for basal and activated platelets. However, quantitative lipidomic data of platelet activation, including the released complex lipids, are unavailable. Here we describe an easy-to-use protocol based on flow-injection mass spectrometry for the quantitative analysis of bulk lipid species in basal and activated human platelets and their lipid release after thrombin activation. We provide lipid species concentrations of 12 healthy human donors, including cholesteryl ester (CE), ceramide (Cer), free cholesterol (FC), hexosylceramide (HexCer), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), sphingomyelin (SM) and triglycerides (TG). The assay exhibited good technical repeatability (CVs < 5% for major lipid species in platelets). Except for CE and TG, the inter-donor variability of the majority of lipid species concentrations in platelets was < 30% CV. Balancing of concentrations revealed the generation of LPC and loss of TG. Changes in lipid species concentrations indicate phospholipase-mediated release of arachidonic acid mainly from PC, PI, and PE but not from PS. Thrombin induced lipid release was mainly composed of FC, PS, PC, LPC, CE, and TG. The similarity of the released lipidome with that of plasma implicates that lipid release may originate from the open-canalicular system (OCS). The repository of lipid species concentrations determined with this standardized platelet release assay contribute to elucidating the physiological role of platelet lipids and provide a basis for investigating the platelet lipidome in patients with hemorrhagic or thrombotic disorders.

Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy)

COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.

Isomer-selective analysis of inositol phosphates with differential isotope labelling by phosphate methylation using liquid chromatography with tandem mass spectrometry

Inositol phosphates belong to a family of structurally diverse signaling molecules playing crucial role in Ca²⁺ release from intracellular storage vesicles. There are many possibilities of phosphorylation, including their degree and position. Inositol (1,4,5) trisphosphate has been well recognized as the most important second messenger among this family. It remains a challenge to analyse the entire inositol phosphate metabolite family due to its structural complexity, high polarity, and high phosphate density. In this study, we have established an improved UHPLC-ESI-MS/MS method based on a differential isotope labelling methylation strategy. An SPE extraction kit composed of TiO2 and PTFE filter was employed for sample preparation which provided good extraction performance. Samples were methylated (light label) to neutralize the phosphate groups and give better performance in liquid chromatography. Regioisomers and inositol phosphates differing in their number of phosphate residues were successfully separated after optimization on a core-shell cholesterylether-bonded RP-type column (Cosmocore 2.6Cholester) using methanol as organic modifier. Triple quadrupole MS detection was based on selected reaction monitoring (SRM) acquisition with characteristic fragments. Stable isotope labeling methylation was performed to generate internal standards (heavy label). Limits of quantification from 0.32 to 0.89 pmol on column was achieved. This method was validated to be suitable for inositol phosphate profiling in biological samples. After application in cultured HeLa cells, NIST SRM1950 plasma, and human platelets, distinct inositol profiles were obtained. This newly established method exhibited improved analytical performance, holding the potential to advance the understanding of inositol phosphate signaling.