Metabolic Dysregulation of the Lysophospholipid/Autotaxin Axis in the Chromosome 9p21 Gene SNP rs10757274

LC-ESI-HRMS - lipidomics of phospholipids : Characterization of extraction, chromatography and detection parameters

Lipids are a diverse class of molecules involved in many biological functions including cell signaling or cell membrane assembly. Owing to this relevance, LC-MS/MS-based lipidomics emerged as a major field in modern analytical chemistry. Here, we thoroughly characterized the influence of MS and LC settings - of a Q Exactive HF operated in Full MS/data-dependent MS2 TOP N acquisition mode - in order to optimize the semi-quantification of polar lipids. Optimization of MS-source settings improved the signal intensity by factor 3 compared to default settings. Polar lipids were separated on an ACQUITY Premier CSH C18 reversed-phase column (100 × 2.1 mm, 1.7 µm, 130 Å) during an elution window of 28 min, leading to a sufficient number of both data points across the chromatographic peaks, as well as MS2 spectra. Analysis was carried out in positive and negative ionization mode enabling the detection of a broader spectrum of lipids and to support the structural characterization of lipids. Optimal sample preparation of biological samples was achieved by liquid-liquid extraction using MeOH/MTBE resulting in an excellent extraction recovery > 85% with an intra-day and inter-day variability < 15%. The optimized method was applied on the investigation of changes in the phospholipid pattern in plasma from human subjects supplemented with n3-PUFA (20:5 and 22:6). The strongest increase was observed for lipids bearing 20:5, while 22:4 bearing lipids were lowered. Specifically, LPC 20:5_0:0 and PC 16:0_20:5 were found to be strongest elevated, while PE 18:0_22:4 and PC 18:2_18:2 were decreased by n3-PUFA supplementation. These results were confirmed by targeted LC-MS/MS using commercially available phospholipids as standards.

From 'Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators

PURPOSE OF REVIEW

'Omics studies provide a comprehensive characterisation of a biological entity, such as the genome, epigenome, transcriptome, proteome, metabolome, or microbiome. This review covers the unique properties of these types of 'omics and their roles as causal mediators in cardiovascular disease. Moreover, applications and challenges of integrating multiple types of 'omics data to increase predictive power, improve causal inference, and elucidate biological mechanisms are discussed.

RECENT FINDINGS

Multi-omics approaches are growing in adoption as they provide orthogonal evidence and overcome the limitations of individual types of 'omics data. Studies with multiple types of 'omics data have improved the diagnosis and prediction of disease states and afforded a deeper understanding of underlying pathophysiological mechanisms, beyond any single type of 'omics data. For instance, disease-associated loci in the genome can be supplemented with other 'omics to prioritise causal genes and understand the function of non-coding variants. Alternatively, techniques, such as Mendelian randomisation, can leverage genetics to provide evidence supporting a causal role for disease-associated molecules, and elucidate their role in disease pathogenesis. As technologies improve, costs for 'omics studies will continue to fall and datasets will become increasingly accessible to researchers. The intrinsically unbiased nature of 'omics data is well-suited to exploratory analyses that discover causal mediators of disease, and multi-omics is an emerging discipline that leverages the strengths of each type of 'omics data to provide insights greater than the sum of its parts.

Effect of 9p21.3 (lncRNA and CDKN2A/2B) variant on lipid profile

Background

Several 9p21.3 variants, such as rs1333049, rs4977574, rs10757274, rs10757278, and rs10811661, identified from recent genome-wide association studies (GWASs) are reported to be associated with coronary artery disease (CAD) susceptibility but independent of dyslipidemia. This study investigated whether these 9p21.3 variants influenced lipid profiles.

Methods and results

By searching the PubMed and Cochrane databases, 101,099 individuals were included in the analysis. The consistent finding for the rs1333049 C allele on lipid profiles increased the triglyceride (TG) levels. Moreover, the rs4977574 G allele and the rs10757274 G allele, respectively, increased low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels. However, the rs10811661 C allele largely reduced LDL-C levels. Subgroup analyses indicated that the effects of the rs1333049 C allele, rs4977574 G allele, and rs10757274 G allele on lipid profiles were stronger in Whites compared with Asians. In contrast, the effect of the rs10811661 C allele on lipid profiles was stronger in Asians compared with Whites.

Conclusion

The rs1333049 C allele, rs4977574 G allele, and rs10757274 G allele of lncRNA, and the rs10811661 G allele of CDKN2A/2B had a significant influence on lipid levels, which may help the understanding of the underlying mechanisms between 9p21.3 variants and CAD.

ENPP2 (Endothelial Ectonucleotide Pyrophosphatase/Phosphodiesterase 2) Increases Atherosclerosis in Female and Male Mice

BACKGROUND

Maladapted endothelial cells (ECs) secrete ENPP2 (ectonucleotide pyrophosphatase/phosphodiesterase 2; autotaxin)-a lysophospholipase D that generates lysophosphatidic acids (LPAs). ENPP2 derived from the arterial wall promotes atherogenic monocyte adhesion induced by generating LPAs, such as arachidonoyl-LPA (LPA20:4), from oxidized lipoproteins. Here, we aimed to determine the role of endothelial ENPP2 in the production of LPAs and atherosclerosis.

METHODS

We quantified atherosclerosis in mice harboring loxP-flanked Enpp2 alleles crossed with Apoe^-/- mice expressing tamoxifen-inducible Cre recombinase under the control of the EC-specific bone marrow X kinase promoter after 12 weeks of high-fat diet feeding.

RESULTS

A tamoxifen-induced EC-specific Enpp2 knockout decreased atherosclerosis, accumulation of lesional macrophages, monocyte adhesion, and expression of endothelial CXCL (C-X-C motif chemokine ligand) 1 in male and female Apoe^-/- mice. In vitro, ENPP2 mediated the mildly oxidized LDL (low-density lipoprotein)-induced expression of CXCL1 in aortic ECs by generating LPA20:4, palmitoyl-LPA (LPA16:0), and oleoyl-LPA (LPA18:1). ENPP2 and its activity were detected on the endothelial surface by confocal imaging. The expression of endothelial Enpp2 established a strong correlation between the plasma levels of LPA16:0, stearoyl-LPA (LPA18:0), and LPA18:1 and plaque size and a strong negative correlation between the LPA levels and ENPP2 activity in the plasma. Moreover, endothelial Enpp2 knockout increased the weight of high-fat diet-fed male Apoe^-/- mice.

CONCLUSIONS

We demonstrated that the expression of ENPP2 in ECs promotes atherosclerosis and endothelial inflammation in a sex-independent manner. This might be due to the generation of LPA20:4, LPA16:0, and LPA18:1 from mildly oxidized lipoproteins on the endothelial surface.

Effect of Sampling Rate and Data Pretreatment for Targeted and Nontargeted Analysis by Means of Liquid Chromatography Coupled to Drift Time Ion Mobility Quadruple Time-of-Flight Mass Spectrometry

Ion mobility as an additional separation dimension can help to resolve and annotate metabolite and lipid biomarkers and provides important information about the components in a sample. Identifying relevant information in the resulting data is challenging because of the complexity of the data and data evaluation strategies for both targeted or nontargeted workflows. Frequently, feature analysis is used as a first step to search for differences between samples in discovery workflows. However, follow-up experimentation often leads to more targeted data extraction methods. In both cases, optimizing data sets for data extraction can make an important contribution to the overall results. In this work, we evaluate the effect of experimental conditions including acquisition sampling rate and data pretreatment on lipid standards and lipid extracts as examples of complex biological samples analyzed by liquid chromatography coupled to drift time ion mobility quadrupole time-of-flight mass spectrometry. The results show that a reduction of both peak variation and background noise can be achieved by optimizing the sampling rate. The use of data pretreatment including data smoothing, intensity thresholding, and spike removal also play an important role in improving detection and annotation of analytes from complex biological samples, whereas nonoptimal data sampling rates and preprocessing can lead to adverse effects including the loss or alternation of small, or closely eluting, low-abundant peaks.

Acute coronary syndrome is associated with a substantial change in the platelet lipidome

AIMS

Platelets play a key role in the pathophysiology of coronary artery disease (CAD) and patients with enhanced platelet activation are at increased risk to develop adverse cardiovascular events. Beyond reliable cardiovascular risk factors such as dyslipoproteinaemia, significant changes of platelet lipids occur in patients with CAD. In this study, we investigate the platelet lipidome by untargeted liquid chromatography-mass spectrometry, highlighting significant changes between acute coronary syndrome (ACS) and chronic coronary syndrome (CCS) patients. Additionally, we classify the platelet lipidome, spotlighting specific glycerophospholipids as key players in ACS patients. Furthermore, we examine the impact of significantly altered lipids in ACS on platelet-dependent thrombus formation and aggregation.

METHODS AND RESULTS

In this consecutive study, we characterized the platelet lipidome in a CAD cohort (n = 139) and showed significant changes of lipids between patients with ACS and CCS. We found that among 928 lipids, 7 platelet glycerophospholipids were significantly up-regulated in ACS, whereas 25 lipids were down-regulated compared to CCS. The most prominent up-regulated lipid in ACS, PC18:0 (PC 10:0-8:0), promoted platelet activation and ex vivo platelet-dependent thrombus formation.

CONCLUSIONS

Our results reveal that the platelet lipidome is altered in ACS and up-regulated lipids embody primarily glycerophospholipids. Alterations of the platelet lipidome, especially of medium chain lipids, may play a role in the pathophysiology of ACS.