Lipidomics in translational research and the clinical significance of lipid-based biomarkers

Lipidomics reveals the serum profiles of pediatric allergic rhinitis and its severity

Allergic rhinitis (AR) is a prevalent upper airway chronic inflammatory disease in children worldwide. The role of bioactive lipids in the regulation of AR has been recognized, but the underlying serum lipidomic basis of its pathology remains unclear. We utilized ultra-performance liquid chromatography (UPLC)-Q-Exactive Orbitrap/mass spectrometry (MS) to investigate the serum lipidomic profiles of children with AR. The lipidomic analysis identified 42 lipids that were differentially expressed (p < 0.05, fold change > 2) between the AR (n = 75) and normal control groups (n = 44). Specifically, the serum levels of diacylglycerol (DG), triacylglycerol (TG), fatty acid (FA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine, phosphatidyl-ethanolamine, and cardiolipins were significantly higher in the AR group. The diagnostic potential of the identified lipids was further evaluated using receiver operating characteristic curve analysis. The analysis revealed that five lipids, including FA 30:7, LPC O-18:1, LPC 18:0, LPC 16:0, and DG 34:0, had area under the curve values greater than 0.9 (p < 0.05). Furthermore, serum levels of IgE and IL-33, markers of AR severity, were found to have a significant positive correlation (p < 0.05) with DGs, LPCs, TGs, and FAs in AR patients. This study revealed the lipid disorders associated with AR and its severity, providing new insights into the pathological process of AR.

Advances in clinical application of lipidomics in healthy ageing and healthy longevity medicine

It is imperative to optimise health and healthspan across the lifespan. The accumulation of reactive oxygen species (ROS) has been implicated in the hallmarks of ageing and inhibiting ROS production can potentially delay ageing whilst increasing healthy longevity. Lipids and lipid mediators (derivatives of lipids) are becoming increasingly recognized as central molecule in tissue and cellular function and are susceptible to peroxidation; hence linked with ageing. Lipid classes implicated in the ageing process include sterols, glycerophospholipids, sphingolipids and the oxidation products of polyunsaturated fatty acids but these are not yet translated into the clinic. Further mechanistic studies are required for the understanding of lipid classes in the ageing process. Lipidomics, the system level characterisation of lipid species with respect to metabolism and function, might provide a significant and useful biological age profiling tool through longitudinal studies. Lipid profiles in different ages among healthy individuals could be harnessed as lipid biomarkers of healthy ageing with potential integration for the development of lipid-based ageing clock (lipid clock). The potential of a lipid clock includes the prediction of future morbidity or mortality, which will promote precision and healthy longevity medicine.

Installation protocol for charge transfer dissociation mass spectrometry on ion trapping mass spectrometers

RATIONALE

Charge transfer dissociation (CTD) is a novel fragmentation technique that demonstrates enhanced structural characterization for a wide variety of molecules compared to standard fragmentation techniques like collision-induced dissociation (CID). Alternative fragmentation techniques, such as electron transfer dissociation, electron capture dissociation, and ultraviolet photodissociation, also overcome many of the shortfalls of CID, but none of them are a silver bullet that can adequately characterize a wide variety of structures and charge states of target compounds. Given the diversity of structural classes and their occasional obstinance towards certain activation techniques, alternative fragmentation techniques are required that rely on novel or alternative modes of activation.

METHODS

Herein, we present a step-by-step protocol for the installation of CTD on a quadrupole ion trap mass spectrometer and best practices for optimizing the signal-to-noise ratio and acquisition times for CTD mass spectra.

RESULTS

In addition to two CTD installations in the Jackson laboratory, CTD has also been installed, and is currently in operation, on two 3D ion trap mass spectrometers in France: one in the laboratory of Dr. David Ropartz and Dr. Hélène Rogneaux at INRAE in Nantes, and the other in the laboratory of Dr. Jean-Yves Salpin at Université d'Évry Val-d'Essonne, part of the Paris-Saclay University system.

CONCLUSIONS

Here, we provide a visual protocol to help others accomplish the instrument modification.

Lipidomic signatures in patients with early-onset and late-onset Preeclampsia

BACKGROUND

Preeclampsia is a pregnancy-specific clinical syndrome and can be subdivided into early-onset preeclampsia (EOPE) and late-onset preeclampsia (LOPE) according to the gestational age of delivery. Patients with preeclampsia have aberrant lipid metabolism. This study aims to compare serum lipid profiles of normal pregnant women with EOPE or LOPE and screening potential biomarkers to diagnose EOPE or LOPE.

METHODS

Twenty normal pregnant controls (NC), 19 EOPE, and 19 LOPE were recruited in this study. Untargeted lipidomics based on ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to compare their serum lipid profiles.

RESULTS

The lipid metabolism profiles significantly differ among the NC, EOPE, and LOPE. Compared to the NC, there were 256 and 275 distinct lipids in the EOPE and LOPE, respectively. Furthermore, there were 42 different lipids between the LOPE and EOPE, of which eight were significantly associated with fetal birth weight and maternal urine protein. The five lipids that both differed in the EOPE and LOPE were DGTS (16:3/16:3), LPC (20:3), LPC (22:6), LPE (22:6), PC (18:5e/4:0), and a combination of them were a potential biomarker for predicting EOPE or LOPE. The receiver operating characteristic analysis revealed that the diagnostic power of the combination for distinguishing the EOPE from the NC and for distinguishing the LOPE from the NC can reach 1.000 and 0.992, respectively. The association between the lipid modules and clinical characteristics of EOPE and LOPE was investigated by the weighted gene co-expression network analysis (WGCNA). The results demonstrated that the main different metabolism pathway between the EOPE and LOPE was enriched in glycerophospholipid metabolism.

CONCLUSIONS

Lipid metabolism disorders may be a potential mechanism of the pathogenesis of preeclampsia. Lipid metabolites have the potential to serve as biomarkers in patients with EOPE or LOPE. Furthermore, lipid metabolites correlate with clinical severity indicators for patients with EOPE and LOPE, including fetal birth weight and maternal urine protein levels.

Lipidomics and plasma hormone analysis differentiate reproductive and pregnancy statuses in Florida manatees (Trichechus manatus latirostris)

Florida manatees (Trichechus manatus latirostris) are protected as a threatened species, and data are lacking regarding their reproductive physiology. This study aimed to (1) quantify plasma steroid hormones in Florida manatees from two field sites, Crystal River and Indian River Lagoon, at different gestational stages and to (2) identify individual lipids associated with pregnancy status. Ultra-high performance liquid chromatography-tandem mass spectrometric analysis was used to measure plasma steroid hormones and lipids. Pregnant female manatees were morphometrically distinct from male and non-pregnant female manatees, characterized by larger body weight and maximal girth. Progesterone concentrations in manatees were also elevated during early gestation versus late gestation. Cholesterol, an important metabolic lipid, and precursor for reproductive steroids, was not different between groups. Mass spectrometry quantified 949 lipids. Plasma concentrations of glycerophospholipids, glycerolipids, sphingolipids, acylcarnitines, and cholesteryl esters were associated with pregnancy status in the Florida manatee. Most of the lipid species associated with pregnancy were triacylglycerides, phosphatidylethanolamines, and ether-linked phosphatidylethanolamines, which may serve as energy sources for fetal development. This research contributes to improving knowledge of manatee reproductive physiology by providing data on plasma steroid hormones relative to reproductive status and by identifying plasma lipids that may be important for pregnancy. Elucidation of lipid species directly associated with pregnancy has the potential to serve as a diagnostic approach to identify pregnant individuals in fresh and archived samples. These biochemical and morphometric indicators of reproductive status advance the understanding of manatee physiology.

Identification of Plasma Lipid Alterations Associated with Melanoma Metastasis

The aim of this study was to apply a state-of-the-art quantitative lipidomic profiling platform to uncover lipid alterations predictive of melanoma progression. Our study included 151 melanoma patients; of these, 83 were without metastasis and 68 with metastases. Plasma samples were analyzed using a targeted Lipidyzer™ platform, covering 13 lipid classes and over 1100 lipid species. Following quality control filters, 802 lipid species were included in the subsequent analyses. Total plasma lipid contents were significantly reduced in patients with metastasis. Specifically, levels of two out of the thirteen lipid classes (free fatty acids (FFAs) and lactosylceramides (LCERs)) were significantly decreased in patients with metastasis. Three lipids (CE(12:0), FFA(24:1), and TAG47:2-FA16:1) were identified as more effective predictors of melanoma metastasis than the well-known markers LDH and S100B. Furthermore, the predictive value substantially improved upon combining the lipid markers. We observed an increase in the cumulative levels of five lysophosphatidylcholines (LPC(16:0); LPC(18:0); LPC(18:1); LPC(18:2); LPC(20:4)), each individually associated with an elevated risk of lymph node metastasis but not cutaneous or distant metastasis. Additionally, seventeen lipid molecules were linked to patient survival, four of which (CE(12:0), CE(14:0), CE(15:0), SM(14:0)) overlapped with the lipid panel predicting metastasis. This study represents the first comprehensive investigation of the plasma lipidome of melanoma patients to date. Our findings suggest that plasma lipid profiles may serve as important biomarkers for predicting clinical outcomes of melanoma patients, including the presence of metastasis, and may also serve as indicators of patient survival.

Abnormal functional connectivity within the prefrontal cortex is associated with multiple plasma lipid species in major depressive disorder

BACKGROUND

Abnormalities in functional connectivity (FC) in major depressive disorder (MDD) have been widely reported. Analysis of the relationship between FC and plasma lipid profiles would be meaningful in the exploration of pathophysiological mechanisms and helpful for the identification of biomarkers for MDD.

METHODS

Patients with MDD (n = 49) and healthy controls (HC, n = 87) were recruited. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for FC construction. The plasma lipid profiles were acquired using ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS) analysis and clustered as co-expression modules. The differential FC and lipid modules between HCs and patients with MDD were identified, and then the association between FC and lipid co-expression modules was analyzed using correlation analysis. The modules associated molecular function was explored using metabolite set enrichment analysis (MSEA).

RESULTS

MDD-associated FC and lipid co-expression modules were identified. One module was associated with FC values between the right orbital part of the middle frontal gyrus and the opercular part of the left inferior frontal gyrus, which was enriched in lipid sets of diacylglycerols and fatty alcohols; another module was associated with FC values between the right middle frontal gyrus and the right anterior cingulate and paracingulate gyri, which was enriched in lipid sets of glycerophosphocholines and glycerophosphoethanolamines.

CONCLUSION

Our results indicated that abnormal FC in the prefrontal cortex is associated with multiple plasma lipid species, which may provide novel clues for exploring the pathophysiology of MDD.

Integration of lipidomics and metabolomics reveals plasma and urinary profiles associated with pediatric Mycoplasma pneumoniae infections and its severity

Mycoplasma pneumoniae is a significant contributor to lower respiratory infections in children. However, the lipidomics and metabolics bases of childhood M. pneumoniae infections remain unclear. In this study, lipidomics and metabolomics analyses were conducted using UHPLC-LTQ-Orbitrap XL mass spectrometry and gas chromatography-triple quadrupole mass spectrometry on plasma (n = 65) and urine (n = 65) samples. MS-DIAL software, in combination with LipidBlast and Fiehn BinBase DB, identified 163 lipids and 104 metabolites in plasma samples, as well as 208 metabolites in urine samples. Perturbed lipid species (adjusted p < 0.05) were observed, including lysophosphatidylethanolamines, phosphatidylinositols, phosphatidylcholines, phosphatidylethanol amines, and triglycerides. Additionally, differential metabolites (adjusted p < 0.05) exhibited associations with amino acid metabolism, nucleotide metabolism, and energy metabolism. Thirteen plasma metabolites, namely l-hydroxyproline, 3-phosphoglycerate, citric acid, creatine, inosine, ribitol, α tocopherol, cholesterol, cystine, serine, uric acid, tagatose, and glycine, showed significant associations with disease severity (p < 0.05) and exhibited distinct separation patterns in M. pneumoniae-infected bronchitis and pneumonia, with an area under the curve of 0.927. Nine of them exhibited either positive or negative correlations with neutrophil or lymphocyte percentages. These findings indicated significant systemic metabolic shifts in childhood M. pneumoniae infections, offering valuable insights into the associated metabolic alterations and their relationship with disease severity.

Nontargeted metabolomic insights into the behavioral effects of 5-MeO-MiPT in zebrafish (Danio rerio)

5-Methoxy-N-methyl-N-isopropyltryptamine (5-MeO-MiPT) is a novel psychoactive substance exhibiting a tryptamine structure. Despite its increasing prevalence, the environmental impact of 5-MeO-MiPT remains unexplored. Our prior investigation revealed that 5-MeO-MiPT induced inhibited spontaneous movement and prompted anxiety-like behavior in adult zebrafish-a validated toxicological model. To elucidate this phenomenon and establish a correlation between metabolomics and behavioral changes induced by 5-MeO-MiPT, zebrafish were administered varying drug concentrations. Zebrafishes were subjected to injections of different 5-MeO-MiPT concentrations. Subsequent metabolomic analysis of endogenous metabolites affected by the drug unveiled substantial variations in metabolic levels between the control group and the drug-injected cohorts. A total of 22 distinct metabolites emerged as potential biomarkers. Further scrutiny identified seven pathways significantly influenced by 5-MeO-MiPT. A focused exploration into amino acid metabolism, lipid metabolism, and energy metabolism unveiled that the metabolic repercussions of 5-MeO-MiPT on zebrafish resulted in observable brain damage. Notably, the study identified a consequential disruption in the liver-brain pathway. The comprehensive metabolomic approach employed herein effectively discerned the impact of 5-MeO-MiPT on zebrafish metabolism. This approach also shed light on the mechanism underpinning the anxiety-like behavior observed in zebrafish post-drug injection. Specifically, our findings indicate that 5-MeO-MiPT induces brain damage, particularly within the liver-brain pathway.

The role of specialized pro-resolving mediators (SPMs) in inflammatory arthritis: A therapeutic strategy

Rheumatoid arthritis (RA) is classified as a persistent inflammatory autoimmune disorder leading to the subsequent erosion of articular cartilage and bone tissue originating from the synovium. The fundamental objective of therapeutic interventions in RA has been the suppression of inflammation. Nevertheless, conventional medicines that lack target specificity may exhibit unpredictable effects on cell metabolism. In recent times, there has been evidence suggesting that specialized pro-resolving mediators (SPMs), which are lipid metabolites, have a role in facilitating the resolution of inflammation and the reestablishment of tissue homeostasis. SPMs are synthesized by immune cells through the enzymatic conversion of omega-3 fatty acids. In the context of RA, there is a possibility of dysregulation in the production of these SPMs. In this review, we delve into the present comprehension of the endogenous functions of SPMs in RA as lipids that exhibit pro-resolutive, protective, and immunoresolvent properties.

Lipidomics identified novel cholesterol-independent predictors for risk of incident coronary heart disease: Mediation of risk from diabetes and aggravation of risk by ambient air pollution

INTRODUCTION

Previous lipidomics studies have identified various lipid predictors for cardiovascular risk, however, with limited predictive increment, sometimes using too many predictor variables at the expense of practical efficiency.

OBJECTIVES

To search for lipid predictors of future coronary heart disease (CHD) with stronger predictive power and efficiency to guide primary intervention.

METHODS

We conducted a prospective nested case-control study involving 1,621 incident CHD cases and 1:1 matched controls. Lipid profiling of 161 lipid species for baseline fasting plasma was performed by liquid chromatography-mass spectrometry.

RESULTS

In search of CHD predictors, seven lipids were selected by elastic-net regression during over 90% of 1000 cross-validation repetitions, and the derived composite lipid score showed an adjusted odds ratio of 3.75 (95% confidence interval: 3.15, 4.46) per standard deviation increase. Addition of the lipid score into traditional risk model increased c-statistic to 0.736 by an increment of 0.077 (0.063, 0.092). From the seven lipids, we found mediation of CHD risk from baseline diabetes through sphingomyelin (SM) 41:1b with a considerable mediation proportion of 36.97% (P < 0.05). We further found that the positive associations of phosphatidylcholine (PC) 36:0a, SM 41:1b, lysophosphatidylcholine (LPC) 18:0 and LPC 20:3 were more pronounced among participants with higher exposure to fine particulate matter or its certain components, also to ozone for LPC 18:0 and LPC 20:3, while the negative association of cholesteryl ester (CE) 18:2 was attenuated with higher black carbon exposure (P < 0.05).

CONCLUSION

We identified seven lipid species with greatest predictive increment so-far achieved for incident CHD, and also found novel biomarkers for CHD risk stratification among individuals with diabetes or heavy air pollution exposure.

Pro-resolving and anti-inflammatory effects of resolvins and protectins in rheumatoid arthritis

Rheumatoid arthritis (RA) is typified by persistent joint inflammation, which leads to the deterioration of bone and cartilage and a reduction in overall quality of life. The global prevalence of pain as a primary symptom in RA is influenced by the interplay between inflammation and its resolution. The identification of a family of lipid mediators known as specialized pro-resolving mediators (SPM)s has contributed to the progress of our comprehension of inflammatory conditions. SPMs have been observed to trigger the process of inflammation resolution, thereby reinstating the homeostasis of the inflammatory response. Autacoids are synthesized through the stereo-selective transformation of essential fatty acids, resulting in molecules dynamically modulated during inflammation and possessing strong immunoregulatory properties. This review delves into the available evidence that supports the involvement of certain SPM as protective lipids, biomarkers with potential, and therapeutic targets in the context of RA.

Effect of biological sex on human circulating lipidome: An overview of the literature

Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.

Lipid composition modulates interactions of p7 viroporin during membrane insertion

Viral proteins interact with lipid membranes during various stages in the viral life cycle to propagate infection. p7 is an ion channel forming protein of Hepatitis C virus (HCV) that participates in viral assembly. Studies show that it has close ties to lipid metabolism in the cell and anionic phosphatidylserine (PS) lipids are suggested to be key for its permeabilizing function, but the mechanism of its interaction with the lipid environment is largely unknown. To begin unraveling the molecular processes of the protein, we evaluated the impact of lipid environment on the binding and insertion mechanism of p7 prior to channel formation and viral assembly using molecular dynamics simulations. It is seen that p7 is sensitive to its lipid environment and results in different remodeling patterns in membranes. Helix 1 (H1) is especially important for peptide insertion, with deeper entry taking place when the membrane contains phosphatidylserine (PS). Helix 2 (H2) and the adjacent loop connecting to Helix 3 (H3) prompts recruitment of phosphatidylethanolamine (PE) lipids to the protein binding site in membrane models with lower surface charge. This work provides perspectives on the interplay between protein-lipid dynamics and membrane composition, and insights on membrane reorganization in mechanisms of disease.

Omics approaches for the assessment of biological responses to nanoparticles

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. While conventional methods have limitations in characterizing responses to NPs, omics approaches can analyze complete sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and analytical methods used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

Relationship between Microflora Changes and Mammary Lipid Metabolism in Dairy Cows with Mastitis

Dairy mastitis is an inflammatory reaction caused by mechanical injury and stress within the mammary gland, during which microbial changes and abnormal lipid metabolism occur. However, the underlying mechanism is still unclear. The present study used a combination of 16S rDNA sequencing technology and lipidomics techniques to reveal the effects of mastitis on lactic microbiota and metabolites in the milk of dairy cows. Twenty multiparous Holstein dairy cows (2-3 parities) with an average body weight of 580 ± 30 kg were selected for this study. The dairy cows were allocated to control group (<5 × 104 cells /mL)) and mastitis group (>5 × 106 cells /mL) based on the somatic cell count. The results showed that mastitis caused a decrease trend in milk production (p = 0.058). The results of the 16 s sequencing indicated a significant decrease (p < 0.05) in the number of Proteobacteria, Tenericutes colonized in mastitis milk, and the number of Firmicutes, Bacteroidetes and Actinobacteria communities increased significantly (p < 0.05). The lipidomics results revealed that the changes in lipid content in mastitis milk were correlated with arachidonic acid metabolism, α -linolenic acid metabolism and glycerol phospholipid metabolism. The results showed that mastitis may cause abnormal lipid metabolism in milk by regulating the diversity of milk microflora, and ultimately affect the milk quality.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.

Disturbed Plasma Lipidomic Profiles in Females with Diffuse Large B-Cell Lymphoma: A Pilot Study

Lipidome dysregulation is a hallmark of cancer and inflammation. The global plasma lipidome and sub-lipidome of inflammatory pathways have not been reported in diffuse large B-cell lymphoma (DLBCL). In a pilot study of plasma lipid variation in female DLBCL patients and BMI-matched disease-free controls, we performed targeted lipidomics using LC-MRM to quantify lipid mediators of inflammation and immunity, and those known or hypothesised to be involved in cancer progression: sphingolipids, resolvin D1, arachidonic acid (AA)-derived oxylipins, such as hydroxyeicosatetraenoic acids (HETEs) and dihydroxyeicosatrienoic acids, along with their membrane structural precursors. We report on the role of the eicosanoids in the separation of DLBCL from controls, along with lysophosphatidylinositol LPI 20:4, implying notable changes in lipid metabolic and/or signalling pathways, particularly pertaining to AA lipoxygenase pathway and glycerophospholipid remodelling in the cell membrane. We suggest here the set of S1P, SM 36:1, SM 34:1 and PI 34:1 as DLBCL lipid signatures which could serve as a basis for the prospective validation in larger DLBCL cohorts. Additionally, untargeted lipidomics indicates a substantial change in the overall lipid metabolism in DLBCL. The plasma lipid profiling of DLBCL patients helps to better understand the specific lipid dysregulations and pathways in this cancer.

Protein-driven membrane remodeling: Molecular perspectives from Flaviviridae infections

The mammalian cell membrane consists of thousands of different lipid species, and this variety is critical for biological function. Alterations to this balance can be dangerous as they can lead to permanent disruption of lipid metabolism, a hallmark in several viral diseases. The Flaviviridae family is made up of positive single-stranded RNA viruses that assemble at or near the location of lipid droplet formation in the endoplasmic reticulum. These viruses are known to interfere with lipid metabolism during the onset of liver disease, albeit to different extents. Pathogenesis of these infections involves specific protein-lipid interactions that alter lipid sorting and metabolism to sustain propagation of the viral infection. Recent experimental studies identify a correlation between viral proteins and lipid content or location in the cell, but these do not assess membrane-embedded interactions. Molecular modeling, specifically molecular dynamics simulations, can provide molecular-level spatial and temporal resolution for characterization of biomolecular interactions. This review focuses on recent advancements and current knowledge gaps in the molecular mechanisms of lipid-mediated liver disease preceded by viral infection. We discuss three viruses from the Flaviviridae family: dengue, zika, and hepatitis C, with a particular focus on lipid interactions with their respective ion channels, known as viroporins.

Circulating protein and lipid markers of early sepsis diagnosis and prognosis: a scoping review

PURPOSE OF REVIEW

Sepsis is the extreme response to infection associated with high mortality, yet reliable biomarkers for its identification and stratification are lacking.

RECENT FINDINGS

Our scoping review of studies published from January 2017 to September 2022 that investigated circulating protein and lipid markers to inform non-COVID-19 sepsis diagnosis and prognosis identified interleukin (IL)-6, IL-8, heparin-binding protein (HBP), and angiopoietin-2 as having the most evidence. Biomarkers can be grouped according to sepsis pathobiology to inform biological data interpretation and four such physiologic processes include: immune regulation, endothelial injury and coagulopathy, cellular injury, and organ injury. Relative to proteins, the pleiotropic effects of lipid species' render their categorization more difficult. Circulating lipids are relatively less well studied in sepsis, however, low high-density lipoprotein (HDL) is associated with poor outcome.

SUMMARY

There is a lack of robust, large, and multicenter studies to support the routine use of circulating proteins and lipids for sepsis diagnosis or prognosis. Future studies will benefit from standardizing cohort design as well as analytical and reporting strategies. Incorporating biomarker dynamic changes and clinical data in statistical modeling may improve specificity for sepsis diagnosis and prognosis. To guide future clinical decisions at the bedside, point-of-care circulating biomarker quantification is needed.

Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Mass spectrometry imaging (MSI) is an effective technique for visualizing the distribution of lipids in tissues. The direct extraction-ionization methods using minute volumes of solvent for local components have the advantage of rapid measurement without any sample pretreatment. For effective MSI of tissues, it is necessary to understand the effect of solvent physicochemical properties on ion images. In this study, we report solvent effects on the lipid imaging of mouse brain tissue by tapping-mode scanning probe electrospray ionization (t-SPESI) which is capable of extraction-ionization using sub-pL solvents. To precisely measure lipid ions, we developed a measurement system incorporating a quadrupole-time-of-flight mass spectrometer. The differences in signal intensity and spatial resolution of lipid ion images were investigated using N,N-dimethylformamide (non-protic polar solvent), methanol (protic polar solvent) and their mixture. The mixed solvent was suitable for the protonation of lipids, and it provided high spatial resolution MSI. Results indicate that the mixed solvent improves the extractant transfer efficiency and minimizes charged droplets from an electrospray. The solvent selectivity study revealed the importance of solvent selection based on physicochemical properties for the advancement of MSI by t-SPESI.

Applied Clinical Tandem Mass Spectrometry-Based Quantification Methods for Lipid-Derived Biomarkers, Steroids and Cannabinoids: Fit-for-Purpose Validation Methods

The emergence of metabolomics and quantification approaches is revealing new biomarkers applied to drug discovery. In this context, tandem mass spectrometry is the method of choice, requiring a specific validation process for preclinical and clinical applications. Research on the two classes of lipid mediators, steroids and cannabinoids, has revealed a potential interaction in cannabis addiction and metabolism-related disorders. Here we present the development of GC-MS/MS and LC-MS/MS methods for routine quantification of targeted steroids and cannabinoids, respectively. The methods were developed using an isotopic approach, including validation for linearity, selectivity, LLOQ determination, matrix effect, carryover, between- and within-run accuracy and precision, and stability tests to measure 11 steroids and seven cannabinoids in human plasma. These methods were satisfactory for most validity conditions, although not all met the acceptance criteria for all analytes. A comparison of calibration curves in biological and surrogate matrices and in methanol showed that the latter condition was more applicable for our quantification of endogenous compounds. In conclusion, the validation of our methods met the criteria for GLP-qualified rather than GLP-validated methods, which can be used for routine analytical studies for dedicated preclinical and clinical purposes, by combining appropriate system suitability testing, including quality controls in the biological matrix.

Unraveling propylene glycol-induced lipolysis of the biosynthesis pathway in ultra-high temperature milk using high resolution mass spectrometry untargeted lipidomics and proteomics

In July 2022, the food safety accident that excessive propylene glycol was detected in milk processing factory raised widespread concerns about quality and nutrition of milk with illegal additive. To the best of our knowledge, the influences of propylene glycol to lipids in milk had not been systematically explored. Therefore, spatiotemporal distributions of lipids related to propylene glycol reaction and changes of sensory quality were investigated by food exogenous. Briefly, 10 subclasses (Cer, DG, HexCer, LPC, LPE, PC, PE, PI, SPH and TG) included 147 lipids and 38 pivotal enzymes were annotated. Propylene glycol altered lysophospholipidase and phospholipase A₂ through altering structural order in lipids domains surrounding proteins to inhibit glycerophospholipid metabolism and initiated obvious changes in PC (10.45-27.91 mg kg^-1) and PE (12.92-49.02 mg kg^-1). This study offered insights into influences of propylene glycol doses and storage time on milk metabolism at molecular level to assess the quality of milk.

Robust and high-throughput lipidomic quantitation of human blood samples using flow injection analysis with tandem mass spectrometry for clinical use

Direct infusion of lipid extracts into the ion source of a mass spectrometer is a well-established method for lipid analysis. In most cases, nanofluidic devices are used for sample introduction. However, flow injection analysis (FIA) based on sample infusion from a chromatographic pump can offer a simple alternative to shotgun-based approaches. Here, we describe important modification of a method based on FIA and tandem mass spectrometry (MS/MS). We focus on minimizing contamination of the FIA/MS both to render the lipidomic platform more robust and to increase its capacity and applicability for long-sequence measurements required in clinical applications. Robust validation of the developed method confirms its suitability for lipid quantitation in human plasma analysis. Measurements of standard human plasma reference material (NIST SRM 1950) and a set of plasma samples collected from kidney cancer patients and from healthy volunteers yielded highly similar results between FIA-MS/MS and ultra-high-performance supercritical fluid chromatography (UHPSFC)/MS, thereby demonstrating that all modifications have practically no effect on the statistical output. Newly modified FIA-MS/MS allows for the quantitation of 141 lipid species in plasma (11 major lipid classes) within 5.7 min. Finally, we tested the method in a clinical laboratory of the General University Hospital in Prague. In the clinical setting, the method capacity reached 257 samples/day. We also show similar performance of the classification models trained based on the results obtained in clinical settings and the analytical laboratory at the University of Pardubice. Together, these findings demonstrate the high potential of the modified FIA-MS/MS for application in clinical laboratories to measure plasma and serum lipid profiles.

Alteration of Lipid Metabolism in Prostate Cancer: Multifaceted Oncologic Implications

Cancer is increasingly recognized as an extraordinarily heterogeneous disease featuring an intricate mutational landscape and vast intra- and intertumor variability on both genetic and phenotypic levels. Prostate cancer (PCa) is the second most prevalent malignant disease among men worldwide. A single metabolic program cannot epitomize the perplexing reprogramming of tumor metabolism needed to sustain the stemness of neoplastic cells and their prominent energy-consuming functional properties, such as intensive proliferation, uncontrolled growth, migration, and invasion. In cancerous tissue, lipids provide the structural integrity of biological membranes, supply energy, influence the regulation of redox homeostasis, contribute to plasticity, angiogenesis and microenvironment reshaping, mediate the modulation of the inflammatory response, and operate as signaling messengers, i.e., lipid mediators affecting myriad processes relevant for the development of the neoplasia. Comprehensive elucidation of the lipid metabolism alterations in PCa, the underlying regulatory mechanisms, and their implications in tumorigenesis and the progression of the disease are gaining growing research interest in the contemporary urologic oncology. Delineation of the unique metabolic signature of the PCa featuring major aberrant pathways including de novo lipogenesis, lipid uptake, storage and compositional reprogramming may provide novel, exciting, and promising avenues for improving diagnosis, risk stratification, and clinical management of such a complex and heterogeneous pathology.

Comprehensive lipidomic profiling by plasma separation cards

Large-scale lipidomic analyses have been limited by the cost and accessibility of traditional venipuncture sampling. Microsampling techniques offer a less-invasive and more accessible alternative. From a single drop of blood, plasma separation cards (PSC) deliver two volumetric dried plasma samples which are studied here for profiling endogenous blood lipids. Six lots of EDTA-treated human whole blood were used to compare PSC, dried blood spot analyses (DBS), and classic wet plasma extractions. Six replicate extractions were performed for each lot. Nontargeted lipidomics was performed by liquid chromatography-high resolution tandem mass spectrometry. Lipids were annotated by accurate mass/retention time matching and MS/MS spectral library matching using peak intensities for quantitation. Four hundred ninety-eight compounds covering 24 lipid subclasses were annotated. Inter-lot repeatability was evaluated by the percent relative standard deviation (%RSD) for each lot, giving median %RSD values across the lots at 14.6% for PSC, 9.3% for DBS, and 8.6% for wet plasma. Strong correlations of lipid peak intensities between wet plasma and PSCs were observed, but less for DBS. Lipid recovery and stability were comparable between the PSC and DBS samples, with roughly 60% of annotated lipids stable at room temperature after 28 days. Overall, PSCs provide a better alternative for quantitative blood lipidomic analyses compared to dried blood spots. However, problems with lipid stability for samples handled and shipped at room temperature are currently unavoidable outside of a clinical setting. Data transferability and comparability to standard plasma is lipid and lipid class dependent.

Integrative metabolomics of plasma and PBMCs identifies distinctive metabolic signatures in Behçet's disease

BACKGROUND

Behçet's disease (BD) is a systemic inflammatory disease that involves various organs. The clinical manifestation-based diagnosis of BD is a time-consuming process, which makes it difficult to distinguish from patients with similar symptoms. Moreover, an authentic biomarker has not been developed for accurate diagnosis yet. Our current study investigated the unique metabolic signatures of BD and explored biomarkers for precise diagnosis based on an untargeted metabolomic approach.

METHODS

Integrative metabolomic and lipidomic profiling was performed on plasma samples of BD patients (n = 40), healthy controls (HCs, n = 18), and disease controls (DCs, n = 17) using GC-TOF MS and LC-Orbitrap MS. Additionally, the lipid profiles of 66 peripheral blood mononuclear cells (PBMCs) were analyzed from 29 BD patients, 18 HCs, and 19 DCs.

RESULTS

Plasma metabolic dysfunction in BD was determined in carbohydrate, hydroxy fatty acid, and polyunsaturated fatty acid metabolisms. A plasma biomarker panel with 13 compounds was constructed, which simultaneously distinguished BD from HC and DC (AUCs ranged from 0.810 to 0.966). Dysregulated PBMC metabolome was signatured by a significant elevation in lysophosphatidylcholines (LPCs) and ether-linked lysophosphatidylethanolamines (EtherLPEs). Ten PBMC-derived lipid composites showed good discrimination power (AUCs ranged from 0.900 to 0.973). Correlation analysis revealed a potential association between disease activity and the metabolites of plasma and PBMC, including sphingosine-1 phosphate and EtherLPE 18:2.

CONCLUSIONS

We identified metabolic biomarkers from plasma PBMC, which selectively discriminated BD from healthy control and patients with similar symptoms (recurrent mouth ulcers with/without genital ulcers). The strong correlation was determined between the BD activity and the lipid molecules. These findings may lead to the development for diagnostic and prognostic biomarkers based on a better understanding of the BD pathomechanism.

A combination of neuroimaging and plasma metabolomic analysis suggests inflammation is associated with white matter structural connectivity in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common mental disorder with unknown pathophysiology. The abnormality of white matter structural connectivity and dysregulation of metabolome in MDD had been widely reported previously. Exploration of the relationship between white matter structural connectivity and plasma metabolites would be helpful for explanation of molecular mechanism for the findings from neuroimaging researches in MDD.

METHODS

The diffusion spectrum imaging data were collected for identification of difference of white matter structural connectivity between MDD (n = 49) and HC (n = 68). The plasma metabolite profiles were acquired by liquid chromatography-mass spectrometry analysis and clustered as co-expression modules. The correlation analysis was performed to identify structural connectivity associated metabolite.

RESULTS

We identified two structural connectivity related metabolite modules. One module was correlated with fractional anisotropy (FA) value between left middle temporal gyrus and left inferior temporal gyrus, which were enriched in tryptophan metabolism pathway; another module was correlated with fiber numbers (FN) between right fusiform gyrus and right inferior temporal gyrus, which was enriched in lysophosphatidylcholine (LPC), lysophosphatidylinositol (LPI) and lysophosphatidylglycerol (LPG) lipid sets. l-Kynurenine in tryptophan metabolism pathway was negatively correlated with FN between right fusiform gyrus and right inferior temporal gyrus, and LPC was positively correlated with FA value between left middle temporal gyrus and left inferior temporal gyrus in MDD.

LIMITATIONS

First, the sample size was relatively small. Second, the long-term effects of antidepressants were not excluded.

CONCLUSION

The results suggested inflammation-related mechanism was associated with white matter structural connectivity in MDD.

High-Resolution Magic-Angle-Spinning NMR in Revealing Hepatoblastoma Hallmarks

Cancer is one of the leading causes of death in children and adolescents worldwide; among the types of liver cancer, hepatoblastoma (HBL) is the most common in childhood. Although it affects only two to three individuals in a million, it is mostly asymptomatic at diagnosis, so by the time it is detected it has already advanced. There are specific recommendations regarding HBL treatment, and ongoing studies to stratify the risks of HBL, understand the pathology, and predict prognostics and survival rates. Although magnetic resonance imaging spectroscopy is frequently used in diagnostics of HBL, high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy of HBL tissues is scarce. Using this technique, we studied the alterations among tissue metabolites of ex vivo samples from (a) HBL and non-cancer liver tissues (NCL), (b) HBL and adjacent non-tumor samples, and (c) two regions of the same HBL samples, one more centralized and the other at the edge of the tumor. It was possible to identify metabolites in HBL, then metabolites from the HBL center and the border samples, and link them to altered metabolisms in tumor tissues, highlighting their potential as biochemical markers. Metabolites closely related to liver metabolisms such as some phospholipids, triacylglycerides, fatty acids, glucose, and amino acids showed differences between the tissues.

Lipids Alterations Associated with Metformin in Healthy Subjects: An Investigation Using Mass Spectrometry Shotgun Approach

Metformin is an orally effective insulin-sensitizing drug widely prescribed for treating type 2 diabetes mellitus (T2DM). Metformin has been reported to alter lipid metabolism. However, the molecular mechanisms behind its impact on lipid metabolism remain partially explored and understood. In the current study, mass spectrometry-based lipid profiling was used to investigate the lipidomic changes in the serum of 26 healthy individuals after a single-dose intake of metformin. Samples were analyzed at five-time points: preadministration, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-administration. A total of 762 molecules were significantly altered between the five-time points. Based on a comparison between baseline level and Cmax, metformin significantly increased and decreased the level of 33 and 192 lipids, respectively (FDR ≤ 0.05 and fold change cutoff of 1.5). The altered lipids are mainly involved in arachidonic acid metabolism, steroid hormone biosynthesis, and glycerophospholipid metabolism. Furthermore, several lipids acted in an opposed or similar manner to metformin levels and included fatty acyls, sterol lipids, glycerolipids, and glycerophospholipids. The significantly altered lipid species pointed to fundamental lipid signaling pathways that could be linked to the pleiotropic effects of metformin in T2DM, insulin resistance, polycystic ovary syndrome, cancer, and cardiovascular diseases.

Sphingosine-1-phosphate and ceramide-1-phosphate promote migration, pro-inflammatory and pro-fibrotic responses in retinal pigment epithelium cells

Retinal pigment epithelium (RPE) cells, essential for preserving retina homeostasis, also contribute to the development of retina proliferative diseases, through their exacerbated migration, epithelial to mesenchymal transition (EMT) and inflammatory response. Uncovering the mechanisms inducing these changes is crucial for designing effective treatments for these pathologies. Sphingosine-1-phosphate (S1P) and ceramide-1-phosphate (C1P) are bioactive sphingolipids that promote migration and inflammation in several cell types; we recently established that they stimulate the migration of retina Müller glial cells (Simón et al., 2015; Vera et al., 2021). We here analyzed whether S1P and C1P regulate migration, inflammation and EMT in RPE cells. We cultured two human RPE cell lines, ARPE-19 and D407 cells, and supplemented them with either 5 μM S1P or 10 μM C1P, or their vehicles, for 24 h. Analysis of cell migration by the scratch wound assay showed that S1P addition significantly enhanced migration in both cell lines. Pre-treatment with W146 and BML-241, antagonists for S1P receptor 1 (S1P1) and 3 (S1P3), respectively, blocked exogenous S1P-induced migration. Inhibiting sphingosine kinase 1 (SphK1), the enzyme involved in S1P synthesis, significantly reduced cell migration and exogenous S1P only partially restored it. Addition of C1P markedly stimulated cell migration. Whereas inhibiting C1P synthesis did not affect C1P-induced migration, inhibiting S1P synthesis strikingly decreased it; noteworthy, addition of C1P promoted the transcription of SphK1. These results suggest that S1P and C1P stimulate RPE cell migration and their effect requires S1P endogenous synthesis. Both S1P and C1P increase the transcription of pro-inflammatory cytokines IL-6 and IL-8, and of EMT marker α-smooth muscle actin (α-SMA) in ARPE-19 cells. Collectively, our results suggest new roles for S1P and C1P in the regulation of RPE cell migration and inflammation; since the deregulation of sphingolipid metabolism is involved in several proliferative retinopathies, targeting their metabolism might provide new tools for treating these pathologies.

Application of plasma metabolome for monitoring the effect of rivaroxaban in patients with nonvalvular atrial fibrillation

Rivaroxaban, an oral factor Xa inhibitor, has been used to treating a series of thromboembolic disorders in clinical practice. Measurement of the anticoagulant effect of rivaroxaban is important to avoid serious bleeding events, thus ensuring the safety and efficacy of drug administration. Metabolomics could help to predict differences in the responses among patients by profiling metabolites in biosamples. In this study, plasma metabolomes before and 3 hours after rivaroxaban intake in 150 nonvalvular atrial fibrillation (NVAF) patients and 100 age/gender-matched controls were analyzed by liquid chromatography coupled with mass spectrometry (LC-MS/MS). When compared with controls, a total of thirteen plasma metabolites were differentially expressed in the NVAF patients. Pathway analysis revealed that purine and lipid metabolism were dysregulated. A panel of three metabolites (17a-ethynylestradiol, tryptophyl-glutamate and adenosine) showed good predictive ability to distinguish nonvalvular atrial fibrillation with an area under the receiver operating characteristic curve (AUC) of 1 for the discovery phase and 1 for validation. Under rivaroxaban treatment, a total of seven metabolites changed, the lipid and glycosylphosphatidylinositol biosynthesis pathways were altered and the panel consisting of avocadene, prenyl glucoside and phosphatidylethanolamine showed predictive ability with an AUC of 0.86 for the discovery dataset and 0.82 for the validation. The study showed that plasma metabolomic analyses hold the potential to differentiate nonvalvular atrial fibrillation and can help to monitor the effect of rivaroxaban anticoagulation.

Analysis of Brain Lipids in the Early-Onset Tay–Sachs Disease Mouse Model With the Combined Deficiency of β-Hexosaminidase A and Neuraminidase 3

Introduction: Tay–Sachs disease is an autosomal recessively inherited lysosomal storage disease that results from loss-of-function mutations in the HEXA gene coding β-hexosaminidase A. HEXA gene deficiency affects the central nervous system owing to GM2 ganglioside accumulation in lysosomes resulting in progressive neurodegeneration in patients. We recently generated a novel mice model with a combined deficiency of β-hexosaminidase A and neuraminidase 3 (Hexa−/−Neu3−/−) that mimics both the neuropathological and clinical abnormalities of early-onset Tay–Sachs disease. Here, we aimed to explore the secondary accumulation of lipids in the brain of Hexa−/−Neu3−/− mice.

Materials and Methods: In the cortex and hippocampus of five-month-old WT, Hexa−/−, Neu3−/−, and Hexa−/−Neu3−/− mice, lipid levels belonging to glycerolipids, glycerophospholipids, and sterol lipids were evaluated using a shotgun lipidomics approach. The levels of myelin were also assessed by luxol fast blue staining and immunohistochemistry using antibodies against myelin basic protein. We further examined glycoconjugate and cholesterol levels by periodic acid–Schiff and filipin staining, respectively. Toluidine blue staining was also performed to display axonal degeneration.

Results: Among glycerophospholipids, we demonstrated elevated levels of phosphatidylcholine-ether and lysophosphatidylcholine while decreased levels of phosphatidylcholine and phosphatidylserine in both cortex and hippocampus of Hexa−/−Neu3−/− mice. In the glycerolipid class, we showed an alleviated level of sphingomyelin in both cortex and hippocampus, but the higher levels of diacylglycerol and triacylglycerol were detected in only the hippocampus of Hexa−/−Neu3−/− mice. The lower level of sterol was also detected in the cortex of Hexa−/−Neu3−/− mice but not in the hippocampus.

Histochemical studies showed a decrease in the myelin level and axonal degeneration indicating neuronal pathology in the brain of Hexa−/−Neu3−/− mice. Although glycoconjugate accumulation was evident both in the cortex and hippocampus, we did not detect any changes in the level of cholesterol.

Conclusion: Our results indicate that alterations in lipid metabolism and neuropathology, such as demyelination and axonal degeneration, might be related to the dysfunctionality of lipid-related cellular pathways like autophagy. Understanding of brain-specific lipid alterations contributes to evaluating the effectiveness of treatments in Hexa−/−Neu3−/− mice in future studies.

Platelet Lipidome Fingerprint: New Assistance to Characterize Platelet Dysfunction in Obesity

Obesity is associated with a pro-inflammatory and pro-thrombotic state that supports atherosclerosis progression and platelet hyper-reactivity. During the last decade, the platelet lipidome has been considered a treasure trove, as it is a source of biomarkers for preventing and treating different pathologies. The goal of the present study was to determine the lipid profile of platelets from non-diabetic, severely obese patients compared with their age- and sex-matched lean controls. Lipids from washed platelets were isolated and major phospholipids, sphingolipids and neutral lipids were analyzed either by gas chromatography or by liquid chromatography coupled to mass spectrometry. Despite a significant increase in obese patient’s plasma triglycerides, there were no significant differences in the levels of triglycerides in platelets among the two groups. In contrast, total platelet cholesterol was significantly decreased in the obese group. The profiling of phospholipids showed that phosphatidylcholine and phosphatidylethanolamine contents were significantly reduced in platelets from obese patients. On the other hand, no significant differences were found in the sphingomyelin and ceramide levels, although there was also a tendency for reduced levels in the obese group. The outline of the glycerophospholipid and sphingolipid molecular species (fatty-acyl profiles) was similar in the two groups. In summary, these lipidomics data indicate that platelets from obese patients have a unique lipid fingerprint that may guide further studies and provide mechanistic-driven perspectives related to the hyperactivate state of platelets in obesity.

UHPLC-HRMS–based serum lipisdomics reveals novel biomarkers to assist in the discrimination between colorectal adenoma and cancer

The development of a colorectal adenoma (CA) into carcinoma (CRC) is a long and stealthy process. There remains a lack of reliable biomarkers to distinguish CA from CRC. To effectively explore underlying molecular mechanisms and identify novel lipid biomarkers promising for early diagnosis of CRC, an ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS) method was employed to comprehensively measure lipid species in human serum samples of patients with CA and CRC. Results showed significant differences in serum lipid profiles between CA and CRC groups, and 85 differential lipid species (P &lt; 0.05 and fold change &gt; 1.50 or &lt; 0.67) were discovered. These significantly altered lipid species were mainly involved in fatty acid (FA), phosphatidylcholine (PC), and triacylglycerol (TAG) metabolism with the constituent ratio &gt; 63.50%. After performance evaluation by the receiver operating characteristic (ROC) curve analysis, seven lipid species were ultimately proposed as potential biomarkers with the area under the curve (AUC) &gt; 0.800. Of particular value, a lipid panel containing docosanamide, SM d36:0, PC 36:1e, and triheptanoin was selected as a composite candidate biomarker with excellent performance (AUC = 0.971), and the highest selected frequency to distinguish patients with CA from patients with CRC based on the support vector machine (SVM) classification model. To our knowledge, this study was the first to undertake a lipidomics profile using serum intended to identify screening lipid biomarkers to discriminate between CA and CRC. The lipid panel could potentially serve as a composite biomarker aiding the early diagnosis of CRC. Metabolic dysregulation of FAs, PCs, and TAGs seems likely involved in malignant transformation of CA, which hopefully will provide new clues to understand its underlying mechanism.

Identifying potential biomarkers and therapeutic targets for dogs with sepsis using metabolomics and lipidomics analyses

Sepsis is a diagnostic and therapeutic challenge and is associated with morbidity and a high risk of death. Metabolomic and lipidomic profiling in sepsis can identify alterations in metabolism and might provide useful insights into the dysregulated host response to infection, but investigations in dogs are limited. We aimed to use untargeted metabolomics and lipidomics to characterize metabolic pathways in dogs with sepsis to identify therapeutic targets and potential diagnostic and prognostic biomarkers. In this prospective observational cohort study, we examined the plasma metabolomes and lipidomes of 20 healthy control dogs and compared them with those of 21 client-owned dogs with sepsis. Patient data including signalment, physical exam findings, clinicopathologic data and clinical outcome were recorded. Metabolites were identified using an untargeted mass spectrometry approach and pathway analysis identified multiple enriched metabolic pathways including pyruvaldehyde degradation; ketone body metabolism; the glucose-alanine cycle; vitamin-K metabolism; arginine and betaine metabolism; the biosynthesis of various amino acid classes including the aromatic amino acids; branched chain amino acids; and metabolism of glutamine/glutamate and the glycerophospholipid phosphatidylethanolamine. Metabolites were identified with high discriminant abilities between groups which could serve as potential biomarkers of sepsis including 13,14-Dihydro-15-keto Prostaglandin A₂; 12(13)-DiHOME (12,13-dihydroxy-9Z-octadecenoic acid); and 9-HpODE (9-Hydroxyoctadecadienoic acid). Metabolites with higher abundance in samples from nonsurvivors than survivors included 3-(2-hydroxyethyl) indole, indoxyl sulfate and xanthurenic acid. Untargeted lipidomic profiling revealed multiple sphingomyelin species (SM(d34:0)+H; SM(d36:0)+H; SM(d34:0)+HCOO; and SM(d34:1D3)+HCOO); lysophosphatidylcholine molecules (LPC(18:2)+H) and lipophosphoserine molecules (LPS(20:4)+H) that were discriminating for dogs with sepsis. These biomarkers could aid in the diagnosis of dogs with sepsis, provide prognostic information, or act as potential therapeutic targets.

Influence of the Human Lipidome on Epicardial Fat Volume in Mexican American Individuals

Introduction

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and is the leading cause of death in the US. Lipid dysregulation is a well-known precursor to metabolic diseases, including CVD. There is a growing body of literature that suggests MRI-derived epicardial fat volume, or epicardial adipose tissue (EAT) volume, is linked to the development of coronary artery disease. Interestingly, epicardial fat is also actively involved in lipid and energy homeostasis, with epicardial adipose tissue having a greater capacity for release and uptake of free fatty acids. However, there is a scarcity of knowledge on the influence of plasma lipids on EAT volume.

Aim

The focus of this study is on the identification of novel lipidomic species associated with CMRI-derived measures of epicardial fat in Mexican American individuals.

Methods

We performed lipidomic profiling on 200 Mexican American individuals. High-throughput mass spectrometry enabled rapid capture of precise lipidomic profiles, providing measures of 799 unique species from circulating plasma samples. Because of our extended pedigree design, we utilized a standard quantitative genetic linear mixed model analysis to determine whether lipids were correlated with EAT by formally testing for association between each lipid species and the CMRI epicardial fat phenotype.

Results

After correction for multiple testing using the FDR approach, we identified 135 lipid species showing significant association with epicardial fat. Of those, 131 lipid species were positively correlated with EAT, where increased circulating lipid levels were correlated with increased epicardial fat. Interestingly, the top 10 lipid species associated with an increased epicardial fat volume were from the deoxyceramide (Cer(m)) and triacylglycerol (TG) families. Deoxyceramides are atypical and neurotoxic sphingolipids. Triacylglycerols are an abundant lipid class and comprise the bulk of storage fat in tissues. Pathologically elevated TG and Cer(m) levels are related to CVD risk and, in our study, to EAT volume.

Conclusion

Our results indicate that specific lipid abnormalities such as enriched saturated triacylglycerols and the presence of toxic ceramides Cer(m) in plasma of our individuals could precede CVD with increased EAT volume.

Ceramide kinase regulates acute wound healing by suppressing 5-oxo-ETE biosynthesis and signaling via its receptor OXER1

The sphingolipid, ceramide-1-phosphate (C1P), has been shown to promote the inflammatory phase and inhibit the proliferation and remodeling stages of wound repair via direct interaction with group IVA cytosolic phospholipase A2, a regulator of eicosanoid biosynthesis that fine-tunes the behaviors of various cell types during wound healing. However, the anabolic enzyme responsible for the production of C1P that suppresses wound healing as well as bioactive eicosanoids and target receptors that drive enhanced wound remodeling have not been characterized. Herein, we determined that decreasing C1P activity via inhibitors or genetic ablation of the anabolic enzyme ceramide kinase (CERK) significantly enhanced wound healing phenotypes. Importantly, postwounding inhibition of CERK enhanced the closure rate of acute wounds, improved the quality of healing, and increased fibroblast migration via a "class switch" in the eicosanoid profile. This switch reduced pro-inflammatory prostaglandins (e.g., prostaglandin E2) and increased levels of 5-hydroxyeicosatetraenoic acid and the downstream metabolite 5-oxo-eicosatetraenoic acid (5-oxo-ETE). Moreover, dermal fibroblasts from mice with genetically ablated CERK showed enhanced wound healing markers, while blockage of the murine 5-oxo-ETE receptor (oxoeicosanoid receptor 1) inhibited the enhanced migration phenotype of these cell models. Together, these studies reinforce the vital roles eicosanoids play in the wound healing process and demonstrate a novel role for CERK-derived C1P as a negative regulator of 5-oxo-ETE biosynthesis and the activation of oxoeicosanoid receptor 1 in wound healing. These findings provide foundational preclinical results for the use of CERK inhibitors to shift the balance from inflammation to resolution and increase the wound healing rate.

Metabolomics in degenerative brain diseases

Among the most studied diseases that affect the central nervous system are Parkinson's, Alzheimer's, and Huntington's diseases, but the lack of effective biomarkers, accurate diagnosis, and precise treatment for each of them is currently an issue. Due to the contribution of biomarkers in supporting diagnosis, many recent efforts have focused on their identification and validation at the beginning or during the progression of the mental illness. Metabolome reveals the metabolic processes that result from protein activities under the guided gene expression and environmental factors, either in healthy or pathological conditions. In this context, metabolomics has proven to be a valuable approach. Currently, magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the most commonly used bioanalytical techniques for metabolomics. MS-assisted profiling is considered the most versatile technique, and the NMR is the most reproductive. However, each one of them has its drawbacks. In this review, we summarized several alterations in metabolites that have been reported for these three classic brain diseases using MS and NMR-based research, which might suggest some possible biomarkers to support the diagnosis and/or new targets for their treatment.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

Non-targeted Lipidomics Using a Robust and Reproducible Lipid Separation Using UPLC with Charged Surface Hybrid Technology and High-Resolution Mass Spectrometry

Lipids play an important role in the energy storage, cellular signaling, and pathophysiology of diseases such as cancer, neurodegenerative diseases, infections, and diabetes. Due to high importance of diverse lipid classes in human health and disease, manipulating lipid abundance and composition is an important target for metabolic engineering. The extreme structural diversity of lipids in real biological samples is challenging for analytical techniques due to large difference in physicochemical properties of individual lipid species. This chapter describes lipidomic analysis of large sample sets requiring reliable and robust methodology. Rapid and robust methods facilitate the support of longitudinal studies allowing the transfer of methodology between laboratories. We describe a high-throughput reversed-phase LC-MS methodology using Ultra Performance Liquid Chromatography (UPLC^®) with charged surface hybrid technology and accurate mass detection for high-throughput non-targeted lipidomics. The methodology showed excellent specificity, robustness, and reproducibility for over 100 LC-MS injections.

Mass Spectrometry Imaging Deciphers Dysregulated Lipid Metabolism in the Human Hippocampus Affected by Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is the most prevalent form of human epilepsy, often accompanied by neurodegeneration in the hippocampus. Like other neurological diseases, TLE is expected to disrupt lipid homeostasis. However, the lipid architecture of the human TLE brain is relatively understudied, and the molecular mechanism of epileptogenesis is poorly understood. We performed desorption electrospray ionization mass spectrometry imaging of 39 fresh frozen surgical specimens of the human hippocampus to investigate lipid profiles in TLE with hippocampal sclerosis (n = 14) and control (non-TLE; n = 25) groups. In contrast to several previous studies on animal models of epilepsy, we report reduced expression of various important lipids, notably phosphatidylcholine (PC) and phosphatidylethanolamine (PE), in the human TLE hippocampus. In addition, metabolic pathway analysis suggested the possible dysregulation of the Kennedy pathway in TLE, resulting in striking reductions of PC and PE levels. This revelation opens up opportunities to further investigate the associated molecular mechanisms and possible therapeutic targets for TLE.

Quantitative global lipidomics analysis of patients with ovarian cancer versus benign adnexal mass

Altered lipid metabolism has emerged as an important feature of ovarian cancer (OC), yet the translational potential of lipid metabolites to aid in diagnosis and triage remains unproven. We conducted a multi-level interrogation of lipid metabolic phenotypes in patients with adnexal masses, integrating quantitative lipidomics profiling of plasma and ascites with publicly-available tumor transcriptome data. Using Sciex Lipidyzer, we assessed concentrations of > 500 plasma lipids in two patient cohorts-(i) a pilot set of 100 women with OC (50) or benign tumor (50), and (ii) an independent set of 118 women with malignant (60) or benign (58) adnexal mass. 249 lipid species and several lipid classes were significantly reduced in cases versus controls in both cohorts (FDR < 0.05). 23 metabolites-triacylglycerols, phosphatidylcholines, cholesterol esters-were validated at Bonferroni significance (P < 9.16 × 10-5). Certain lipids exhibited greater alterations in early- (diacylglycerols) or late-stage (lysophospholipids) cases, and multiple lipids in plasma and ascites were positively correlated. Lipoprotein receptor gene expression differed markedly in OC versus benign tumors. Importantly, several plasma lipid species, such as DAG(16:1/18:1), improved the accuracy of CA125 in differentiating early-stage OC cases from benign controls, and conferred a 15-20% increase in specificity at 90% sensitivity in multivariate models adjusted for age and BMI. This study provides novel insight into systemic and local lipid metabolic differences between OC and benign disease, further implicating altered lipid uptake in OC biology, and advancing plasma lipid metabolites as a complementary class of circulating biomarkers for OC diagnosis and triage.

Complex Alterations of Fatty Acid Metabolism and Phospholipidome Uncovered in Isolated Colon Cancer Epithelial Cells

The development of colon cancer, one of the most common malignancies, is accompanied with numerous lipid alterations. However, analyses of whole tumor samples may not always provide an accurate description of specific changes occurring directly in tumor epithelial cells. Here, we analyzed in detail the phospholipid (PL), lysophospholipid (lysoPL), and fatty acid (FA) profiles of purified EpCAM⁺ cells, isolated from tumor and adjacent non-tumor tissues of colon cancer patients. We found that a number of FAs increased significantly in isolated tumor cells, which also included a number of long polyunsaturated FAs. Higher levels of FAs were associated with increased expression of FA synthesis genes, as well as with altered expression of enzymes involved in FA elongation and desaturation, including particularly fatty acid synthase, stearoyl-CoA desaturase, fatty acid desaturase 2 and ELOVL5 fatty acid elongase 5 We identified significant changes in ratios of specific lysoPLs and corresponding PLs. A number of lysophosphatidylcholine and lysophosphatidylethanolamine species, containing long-chain and very-long chain FAs, often with high numbers of double bonds, were significantly upregulated in tumor cells. Increased de novo synthesis of very long-chain FAs, or, altered uptake or incorporation of these FAs into specific lysoPLs in tumor cells, may thus contribute to reprogramming of cellular phospholipidome and membrane alterations observed in colon cancer.

Lipidomic Signatures for Colorectal Cancer Diagnosis and Progression Using UPLC-QTOF-ESI+MS

Metabolomics coupled with bioinformatics may identify relevant biomolecules such as putative biomarkers of specific metabolic pathways related to colorectal diagnosis, classification and prognosis. This study performed an integrated metabolomic profiling of blood serum from 25 colorectal cancer (CRC) cases previously classified (Stage I to IV) compared with 16 controls (disease-free, non-CRC patients), using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI⁺ MS). More than 400 metabolites were separated and identified, then all data were processed by the advanced Metaboanalyst 5.0 online software, using multi- and univariate analysis, including specificity/sensitivity relationships (area under the curve (AUC) values), enrichment and pathway analysis, identifying the specific pathways affected by cancer progression in the different stages. Several sub-classes of lipids including phosphatidylglycerols (phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and PAs), fatty acids and sterol esters as well as ceramides confirmed the “lipogenic phenotype” specific to CRC development, namely the upregulated lipogenesis associated with tumor progression. Both multivariate and univariate bioinformatics confirmed the relevance of some putative lipid biomarkers to be responsible for the altered metabolic pathways in colorectal cancer.

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses

Mass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses. This work investigates the impact of the choices made at the peak selection step, which often occurs early in the data processing pipeline. The discussion is done in terms of visualization and interpretation of the results of two commonly used unsupervised approaches: t-distributed stochastic neighbor embedding and k-means clustering, which differ in nature and complexity. Criteria considered for peak selection include those based on hypotheses (exemplified herein in the analysis of metabolic alterations in genetically engineered mouse models of human colorectal cancer), particular molecular classes, and ion intensity. The results suggest that the choices made at the peak selection step have a significant impact in the visual interpretation of the results of either dimensionality reduction or clustering techniques and consequently in any downstream analysis that relies on these. Of particular significance, the results of this work show that while using the most abundant ions can result in interesting structure-related segmentation patterns that correlate well with histological features, using a smaller number of ions specifically selected based on prior knowledge about the biochemistry of the tissues under investigation can result in an easier-to-interpret, potentially more valuable, hypothesis-confirming result. Findings presented will help researchers understand and better utilize unsupervised machine learning approaches to mine high-dimensionality data.