"Lipidomics": Mass spectrometric and chemometric analyses of lipids

Establishment of MS LOC platform and its pilot application in clinical lipidomics

Lipidomics has demonstrated significant potential for disease diagnosis and prediction. The development and optimization of a robust mass spectrometry (MS) platform for lipidome analysis is critically important, as it can facilitate biomarker discovery, cohort testing, and performance evaluation in clinical lipidomics studies. In this work, we developed a high-throughput and reliable platform, termed MS Lab on a Chip (MS LOC), which integrates the MetArray chip, an automated lipidomics pretreatment protocol, and the reflectron matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) instrument. The MetArray chip, produced through a mass production process, exhibited exceptional stability as an MS substrate. The integration of automated lipid pretreatment and MS detection processes ensures high throughput, stability and efficiency during sample preparation. The analysis of various lipid standards and different types of biological samples enabled comprehensive investigation of lipid features and annotation using the MS LOC. Furthermore, a small cohort study, consisting of hepatocellular carcinoma (HCC) and non-HCC groups, was conducted on this platform, providing preliminary validation of its performance and suggesting that this platform offers a comprehensive protocol for clinical lipidomics testing.

Raman analysis of lipids in cells: Current applications and future prospects

Lipids play an important role in the regulation of cell life processes. Although there are various lipid detection methods, Raman spectroscopy, a non-invasive technique, provides the detailed chemical composition of lipid profiles without a complex sample preparation procedure and possesses greater potential in basic biology, clinical diagnosis and disease therapy. In this review, we summarized the characteristics and advantages of Raman-based techniques and their primary contribution to illustrating cellular lipid metabolism.

Flammulina velutipes mycorrhizae dietary fiber attenuates the development of obesity via regulating lipid metabolism in high-fat diet-induced obese mice

Introduction

Mounting evidence has shown that Flammulina velutipes mycorrhizae dietary fiber (Fv-DF) has the potential to significantly improve health outcomes by addressing lipid metabolic disorders. However, the mechanism underlying Fv-DF in regulating liver lipid metabolism of high-fat diet (HFD)-induced obese mice still merits to be systematically elaborated.

Methods

Herein, we conducted a comprehensive study utilizing HFD-induced C57BL/6J mice as an obesity model to investigate the impact of Fv-DF on liver lipid accumulation.

Results

The study, which included an evaluation of Fv-DF on a high-fat diet (HFD)-induced obese mice, revealed that Fv-DF supplementation can effectively decrease weight gain, improve serum lipid levels, and reduce fat deposition in adipose tissues. The estimation of Fv-DF on liver tissues demonstrated that Fv-DF supplementation significantly ameliorated lipid metabolism and hepatic injury in HFD-induced obese mice. Furthermore, Fv-DF improved lipid metabolism in obese mice by modifying the abundance and related pathways of TG, PC, PE, and other lipid metabolites. Mechanistically, Fv-DF supplementation significantly suppressed the expression of lipid synthesis-related genes while promoting lipid oxidation-related genes.

Discussion

Collectively, the findings could inspire significant implications for Fv-DF in developing novel treatments for obesity-related metabolic disorders management.

The impact of remnant lipids on keloid formation: a causal analysis using mendelian randomization

Keloids are pathological scars that remain a significant clinical challenge due to their persistence and high recurrence rates. Lipid metabolism disturbances are believed to contribute to keloid formation. However, the causal effect of lipids on keloids has not been established. We employed two-sample Mendelian randomization (TSMR) analyses to explore the causality between 25 lipid parameters and keloid using genome-wide association study data. The inverse variance weighting method was the primary analytical approach for estimating causality. We also conducted sensitivity analyses to validate the stability of TSMR results. Our study provides evidence suggesting a genetic association between remnant lipids and keloid formation, with triglyceride-rich remnant lipoproteins, particularly triglycerides to total lipids ratio in very large VLDL(XL.VLDL.TG), potentially promoting keloid formation and cholesterol-rich remnant lipoproteins possibly offering a protective effect. These findings highlight the potential role of remnant lipid parameters, especially XL.VLDL.TG, in modulating keloid development through inflammatory processes. While these findings provide valuable new insights into lipid metabolism and keloid pathogenesis, further experimental studies are required to clarify the mechanisms and confirm the relevance of these lipid parameters in keloid formation. The identification of remnant lipid parameters as potential biomarkers for keloid risk opens new avenues for diagnostic and therapeutic strategies, but further research is required to apply these findings in clinical practice.

Delta-9 desaturase reduction in gastrointestinal cells induced to senescence by doxorubicin

The condition of cellular senescence has specific features, including an altered lipid metabolism. Delta-9 desaturase (Δ9) catalyzes the conversion of saturated fatty acids, such as palmitic acid and stearic acid, into their monounsaturated forms, palmitoleic and oleic acid, respectively. Δ9 activity is important for most lipid functions, such as membrane fluidity, lipoprotein metabolism and energy storage. The present study aimed to investigate differences in the expression of Δ9 in senescence-induced pancreatic (MIA-PaCa-2 and PANC-1) and hepatic (Hepa-RG and HLF) cancer cell lines. Cellular senescence was induced by growing cells in the presence of the chemotherapic drug doxorubicin. Senescence status was determined by the senescence-associated beta-galactosidase activity assay kit combined with the p21 and senescence associated secretory phenotype protein assay. Δ9 was downregulated in all senescence-induced cell lines compared to control cells, in both the lipidomic analysis and when measuring protein levels via western blotting. Hence, our findings demonstrate that the study of membrane lipid composition and the expression levels of Δ9 could potentially form the basis for future applications investigating the state of cellular senescence.

Understanding the physiological mechanisms and therapeutic targets of diseases: Lipidomics strategies

As a pivotal branch of metabolomics, lipidomics studies global changes in lipid metabolism under different physiological and pathological conditions or drug interventions, discovers key lipid markers, and elaborates the associated lipid metabolism network. There are a considerable number of lipids in the host, which act on various functional networks such as metabolism and immune regulation. As an indispensable research method, lipidomics plays a key character in the analysis of lipid composition in organisms, the elaboration of the physiological mechanism of lipids, and the decoding of their character in the occurrence and development of diseases by exploring the character of lipids in the host environmental network. As an essential means of driving lipidomics research, High-throughput and High-resolution mass spectrometry is helpful in exploring disease phenotypic characteristics, diagnosing disease biomarkers, regulating related metabolic pathways, and discovering related active components. In this paper, we discuss the specific role of lipidomics in the analysis of disease diagnosis, prognosis and treatment, which is conducive to the realization of accurate and personalized medicine.

Causal Association Between Multidimensional Plasma Lipid Composition and Pediatric Asthma: A Mendelian Randomization Study

BACKGROUND

Asthma is the most common chronic disease among children and poses a major threat to their health. Observational studies have shown lipid disorders in children with asthma. However, it was not possible to determine whether there is a causal link between the two. Therefore, the aim of this study was to assess the causal relationship between serum liposomes and asthma in children.

METHODS

We used large-scale publicly available genome-wide association study summary statistics to elucidate causal associations between plasma liposomes and children using a two-sample Mendelian randomization (MR) approach. The IVW method was used as the primary analysis method, and tests such as the Cochran Q test, MR-Egger intercept, and leave-one-out method were utilized to explore whether there was heterogeneity and pleiotropy in the MR results. In addition, Steiger's test and reverse MR analysis were performed to test the directionality of the MR results.

RESULTS

Our MR results identified a causal link between six plasma liposomes and childhood asthma. Among them, negative association between Diacylglycerol (16:0_18:2) (OR = 0.952, 95%CI = 0.913-0.992, p = 0.018), Triacylglycerol (52:4) (OR = 0.949, 95%CI = 0.905-0.994, p = 0.028), Phosphatidylcholine (18:2_20:3) (OR = 0.915, 95%CI = 0.843-0.993, p = 0.034), sterol ester (27:1/22:6) (OR = 0.929, 95% CI = 0.869-0.994, p = 0.031) and childhood asthma. There is a positive association between Phosphatidylcholine (16:0_22:5) (OR = 1.061, 95%CI = 1.006-1.120, p = 0.030), sterol ester (27:1/20:4) (OR = 1.046, 95% CI = 1.021-1.072, p = 0.0003) and pediatric asthma. A series of sensitivity tests also demonstrate the robustness of the results.

CONCLUSION

This MR study identified a causal link between some plasma liposomes and childhood asthma. This will provide new perspectives on the prevention and treatment of childhood asthma in the future.

Lipids in Clinical Nutrition and Health: Narrative Review and Dietary Recommendations

Lipids are essential components of human health, serving as critical structural elements of cell membranes, energy sources, and precursors for bioactive molecules. This narrative review aims to examine the multifaceted roles of lipids in clinical nutrition and health, focusing on their impact on chronic disease prevention, management, and the potential of lipid-based therapies. A narrative review was conducted utilizing Scopus, Google Scholar, and Web of Science databases. Key terms such as lipids, dietary fats, and cholesterol were used to identify and analyze relevant studies. A total of 145 articles meeting inclusion criteria were reviewed for their insights into lipid metabolism, dietary sources, and clinical implications. The analysis highlighted the metabolic significance of various lipid classes-saturated, monounsaturated, and polyunsaturated fatty acids-along with evidence-based recommendations for their dietary intake. Lipids were shown to play a pivotal role in managing chronic diseases such as cardiovascular disease, obesity, and metabolic syndrome. Emerging therapies, including omega-3 fatty acids and medium-chain triglycerides, demonstrated potential benefits in clinical practice. By synthesizing current knowledge, this narrative review provides healthcare professionals with an updated understanding of the roles of lipids in clinical nutrition. The findings emphasize the importance of tailored dietary interventions and lipid-based therapies in optimizing health and managing chronic diseases effectively. Additionally, this review successfully presents practical dietary recommendations to guide clinical practice.

Effects of different Lys/Met ratios on the antioxidant capacity, tissue morphology, and fatty acid composition of subcutaneous fat in Tibetan sheep on low-protein diets: a lipidomic analysis

Introduction

This study employed lipidomics to investigate the effects of varying lysine (Lys)- to-methionine (Met) ratios on the antioxidant capacity, tissue morphology, and fatty acid composition of subcutaneous fat in Tibetan sheep fed a low-protein diet.

Methods

Ninety healthy male Tibetan sheep of similar body weight were randomly allocated into three groups. These sheep were fed a low-protein diet containing Lys/Met ratios of 1:1, 2:1, and 3:1. Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry (UHPLC-MS/MS) was employed to explore the changes in various lipid subclasses in subcutaneous adipose tissue. The expression of genes associated with adipogenesis, antioxidant capacity, and fatty acid metabolism was also examined.

Results

The results indicated that the 1:1 Lys/Met group exhibited significantly higher antioxidant capacity (glutathione peroxidase, GSH-Px), with more orderly adipocyte arrangement, uniform cell size, and a general increase in unsaturated fatty acid levels. Additionally, several lipid molecules associated with the phenotype (Antioxidant index and fatty acid content) were identified, namely, DG(38:3e) + Na, PE(17:1_22:2)-H, PI(17:0_20:3)-H, TG(33:0e) + NH4, Cer(d14:0_17:1) + H, and CL(81:13)-2H. Furthermore, the findings showed that the upregulation of PPARγ, FASN, FAD4, CPT1A, and GPX4 can enhance adipocyte differentiation and lipid accumulation, thereby improving metabolic function in subcutaneous adipose tissue via the regulation of lipid metabolism and oxidative defense mechanisms.

Discussion

In summary, this study provides a theoretical foundation for optimizing precision feeding strategies for Tibetan sheep, offering crucial data to support enhancements in production efficiency and meat quality.

Lipidomics-based natural products for chronic kidney disease treatment

Chronic kidney disease (CKD) is by far the most prevalent disease in the world and is now a major global public health problem because of the increase in diabetes, hypertension and obesity. Traditional biomarkers of kidney function lack sensitivity and specificity for early detection and monitoring of CKD progression, necessitating more sensitive biomarkers for early diagnostic intervention. Dyslipidemia is a hallmark of CKD. Advancements in mass spectrometry (MS)-based lipidomics platforms have facilitated comprehensive analysis of lipids in biological samples and have revealed changes in the lipidome that are associated with metabolic disorders, which can be used as new biomarkers for kidney diseases. It is also critical for the discovery of new therapeutic targets and drugs. In this article, we focus on lipids in CKD, lipidomics methodologies and their applications in CKD. Additionally, we introduce novel biomarkers identified through lipidomics approaches and natural products derived from lipidomics for the treatment of CKD. We believe that our study makes a significant contribution to literature by demonstrating that natural products can improve CKD from a lipidomic perspective.

A simultaneous analysis strategy of glycerophospholipids and lipid mediators based on secondary extraction scheme

Lipid peroxidation plays an important role in physiological and pathophysiological conditions; it occurs mainly in the vicinity of the membrane. Glycerophospholipids are indispensable for normal structure of membranes. Lipid mediators are final products of lipid peroxidation. Glycerophospholipids as a source of lipid mediators are closely related with lipid mediators in lipid peroxidation process. This study developed a strategy for simultaneous analysis of glycerophospholipids and lipid mediators in a sample based on a secondary extraction scheme. Due to differences in physicochemical properties of glycerophospholipids and lipid mediators, we used different solvents and methods to extract glycerophospholipids and lipid mediators based on a sample. In addition, we compared three methods of extracting glycerophospholipids to select the best extraction method. In this study, a UPLC-MRM absolute quantification strategy for three deuterated internal standards of lipid mediator was established. The calibration range of all standards is linear, and the correlation coefficients are greater than 0.999. Quantitative range, precision, and accuracy of all analytes-based analysis method meet requirements of method validation. And the accuracy and precision of this method for glycerophospholipids meet the requirements of method verification. It is satisfactory to apply this method in the analysis of the changes of enzymes in lipid peroxidation during the treatment of asthma with dexamethasone. The quantitative results of phospholipids and lipid mediators in mouse lung tissue were obtained by this method, indicating that dexamethasone may inhibit the activity of phospholipase As enzyme and thus slow down the lipid peroxidation process. This work may be of great significance for exploring the changes of enzymes in lipid peroxidation metabolism.

Lipid imaging mass spectrometry: Towards a new molecular histology

Lipid research is attracting greater attention, as these molecules are key components to understand cell metabolism and the connection between genotype and phenotype. The study of lipids has also been fueled by the development of new and powerful technologies, able to identify an increasing number of species in a single run and at decreasing concentrations. One of such key developments has been the image techniques that enable the visualization of lipid distribution over a tissue with cell resolution. Thanks to the spatial information reported by such techniques, it is possible to associate a lipidome trait to individual cells, in fixed metabolic stages, which greatly facilitates understanding the metabolic changes associated to diverse pathological conditions, such as cancer. Furthermore, the image of lipids is becoming a kind of new molecular histology that has great chances to make an impact in the diagnostic units of the hospitals. Here, we examine the current state of the technology and analyze what the next steps to bring it into the diagnosis units should be. To illustrate the potential and challenges of this technology, we present a case study on clear cell renal cell carcinoma, a good model for analyzing malignant tumors due to their significant cellular and molecular heterogeneity.

Novel insights into the role of metabolic disorder in osteoarthritis

Osteoarthritis (OA) is a prevalent condition that affects individuals worldwide and is one of the leading causes of disability. Nevertheless, the underlying pathological mechanisms of OA remain inadequately understood. Current treatments for OA include non-drug therapies, pharmacological interventions, and surgical procedures. These treatments are mainly focused on alleviating clinical manifestations and improving patients' quality of life, but are not effective in limiting the progression of OA. The detailed understanding of the pathogenesis of OA is extremely significant for the development of OA treatment. Metabolic syndrome has become a great challenge for medicine and public health, In recent years, several studies have demonstrated that the metabolic syndrome and its individual components play a crucial role in OA. Consequently, this review summarizes the mechanisms and research progress on how metabolic syndrome and its components affect OA. The aim is to gain a deeper understanding of the pathogenesis of OA and explore effective treatment strategies.

Exploring the versatility of Porphyridium sp.: A comprehensive review of cultivation, bio-product extraction, purification, and characterization techniques

Interest in red microalgae of the Porphyridium genus has surged due to their richness in phycobiliproteins, polyunsaturated fatty acids, and sulfated polysaccharides. These biomasses and their derivatives find applications across food, feed, nutraceutical, pharmaceutical, and cosmetic industries. A deeper understanding of their properties and extraction methods is essential to optimize downstream processing. This paper comprehensively reviews Porphyridium sp., focusing on cultivation techniques, bioproduct extraction, purification, and characterization. It delves into protein, lipid, and polysaccharide extraction, considering the influence of culture conditions on biomass yield. Various methods like chromatography, electrophoresis, and membrane-based techniques for cell lysis and bioproduct recovery are explored, highlighting their pros and cons. By offering diverse insights, this review aims to inspire innovative research and industry progress in red microalgae biotechnology, contributing to sustainable solutions across sectors.

Omics-Enhanced Nanomedicine for Cancer Therapy

Cancer nanomedicine has emerged as a promising approach to overcome the limitations of conventional cancer therapies, offering enhanced efficacy and safety in cancer management. However, the inherent heterogeneity of tumors presents increasing challenges for the application of cancer nanomedicine in both diagnosis and treatment. This heterogeneity necessitates the integration of advanced and high-throughput analytical techniques to tailor nanomedicine strategies to individual tumor profiles. Omics technologies, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and more, provide unparalleled insights into the molecular and cellular mechanisms underlying cancer. By dissecting tumor heterogeneity across multiple levels, these technologies offer robust support for the development of personalized and precise cancer nanomedicine strategies. In this review, the principles, techniques, and applications of key omics technologies are summarized. Especially, the synergistic integration of omics and nanomedicine in cancer therapy is explored, focusing on enhanced diagnostic accuracy, optimized therapeutic strategies and the assessment of nanomedicine-mediated biological responses. Moreover, this review addresses current challenges and outlines future directions in the field of omics-enhanced nanomedicine. By offering valuable insights and guidance, this review aims to advance the integration of omics with nanomedicine, ultimately driving improved diagnostic and therapeutic strategies for cancer.

Ultra-High-Performance Liquid Chromatography-Orbitrap-MS-Based Untargeted Lipidomics Reveal Lipid Characteristics of a Clinical Strain of Mycoplasma bovis from Holstein Cow

Mycoplasma bovis is a global concern for the cattle industry owing to its high rates of infection and resulting morbidity, but there are no reports on the lipid composition and metabolic pathways. This study examined the lipidomics of M. bovis to better investigate the biological characteristics of clinical isolates of M. bovis. The M. bovis strains NX114 and PG45, cultivated to log-phase, underwent untargeted lipidomics via ultra-high-performance liquid chromatography-mass spectrometry for differential analysis. Over 65 lipid types and 1476 lipid molecules were identified. We found that glycerophospholipids and sphingolipids constitute the predominant lipid components of M. bovis, with significant constituents of its cell membrane comprising ceramides, phosphatidylglycerols, sphingomyelins, triacylglycerols, hexosylceramides, ether-linked oxidized phosphatidylcholines, and oxidized phosphatidylglycerols. Secondly, 562 differentially expressed lipid molecules were identified, including 17 lipid subclasses (15 up-regulated and 2 down-regulated) with significant differences in relative content. These findings indicate that distinct M. bovis isolates contain structurally varied lipid molecules, with sphingomyelin, phosphatidylinositol, cardiolipin, and phosphatidylcholine being characteristic lipids. The glycerophospholipid metabolism pathway was identified as a key pathway regulating lipid metabolism in M. bovis by KEGG pathway enrichment analysis. The results indicated alterations in the lipid metabolism of M. bovis, offering insights into its pathogenic mechanisms.

Effects of different processing methods on the lipid composition of seabuckthorn fruit oil based on lipidomics

Employing lipidomics, this study investigated the lipid composition of seabuckthorn fruit oil processed via supercritical CO2 extraction and centrifugal separation. Qualitative analysis showed that a total of 2861 lipid molecules were identified in seabuckthorn fruit oil. Quantitative analysis showed that the content of lipids in seabuckthorn fruit oil extracted by supercritical CO2 extraction (927,539.84 µg/mL) was significantly higher than that in centrifugal-separated seabuckthorn fruit oil (735,717.63 µg/mL), with 17 distinct lipid classes and 215 lipid molecules differentiated through multivariate statistical analysis. Lipid molecules, such as diacylglycerol (DG), ceramides (Cer), monohexosyl ceramide, phosphatidylglycerol, phosphatidylinositol, phosphatidylethanolamine, and monogalactosyl DG, were predominantly found in the oil extracted using supercritical CO2. In contrast, monogalactosyl monoacylglycerol, diglycosyl ceramide, and Cer phosphate were significantly present in the oil extracted by centrifugal separation. These findings contribute new insights into how processing methods affect the quality and composition of seabuckthorn fruit oil and provide a basis for detecting oil adulteration.

Apo E protein and related markers show the prognosis of stress urinary incontinence rats treated with modified Buzhong Yiqi Decoction

Stress urinary incontinence (SUI) is a common disease that seriously affects the quality of life of patients. In recent years, studies have shown that apolipoprotein E (ApoE) plays a role in neuroprotection and repair, but its specific role in SUI remains unclear. The aim of this study was to investigate the effect of macromolecular protein ApoE related markers on the prognosis of rats with SUI treated by modified Buzhong Yiqi Decoction (MBZYQD), in order to provide a new target for the treatment of SUI. Healthy rats were selected to establish a SUI model and divided into groups. The levels of ApoE related metabolites in blood of rats were detected by Metabolomics analysis and Lipidomics analysis. The urine leakage point pressure (LPP) were compared in each group, and the therapeutic effect of MBZYQD was evaluated. Compared with the model group, the LPP of rats in MBZYQD supplemented group was significantly higher. Compared with the control group, the LPP of MBZYQD was not statistically significant before and after treatment. The macromolecular protein ApoE may plays a key role in the treatment of SUI by MBZYQD, which can improve symptoms by regulating lipid metabolism repair.

Simultaneous Determination of the Position and Cis-Trans Configuration of Lipid C═C Bonds via Asymmetric Derivatization and Ion Mobility-Mass Spectrometry

The position and cis-trans configuration of C═C bonds in unsaturated lipids significantly affect their biological activities. Simultaneous identification of the position and cis-trans configuration of C═C bonds in unsaturated lipids is important; nonetheless, it still remains a challenging task. Herein, a stereoselective asymmetric reaction was used to recognize cis-trans isomers of the C═C bonds, and the derivatized precursor ions and product ions were subjected to tandem ion mobility-mass spectrometry (IM-MS) analysis. The theoretical calculation revealed that the formation of intramolecular hydrogen bonds after the cyclization reaction amplified the structural difference between diastereomers and increased the separation efficiency in IM. Consequently, a simple, sensitive, and highly selective platform for simultaneous determination of the position and cis-trans configuration of various C═C bonds in unsaturated lipids was established. It was then successfully applied to pinpoint the cis-trans geometry conversion of the located C═C bonds in lipids of the bacterial membrane under environmental stress and track the heterogeneous distribution of unsaturated lipids in rats after spinal cord injury. The present study also offers new insights into the application of IM-MS technology in resolving molecular structures and demonstrates the potential as a platform for a broad range of applications.

Unraveling the complexity of glycosphingolipidome: the key role of mass spectrometry in the structural analysis of glycosphingolipids

Glycosphingolipids (GSL) are a highly heterogeneous class of lipids representing the majority of the sphingolipid category. GSL are fundamental constituents of cellular membranes that have key roles in various biological processes, such as cellular signaling, recognition, and adhesion. Understanding the structural complexity of GSL is pivotal for unraveling their functional significance in a biological context, specifically their crucial role in the pathophysiology of various diseases. Mass spectrometry (MS) has emerged as a versatile and indispensable tool for the structural elucidation of GSL enabling a deeper understanding of their complex molecular structures and their key roles in cellular dynamics and patholophysiology. Here, we provide a thorough overview of MS techniques tailored for the analysis of GSL, emphasizing their utility in probing GSL intricate structures to advance our understanding of the functional relevance of GSL in health and disease. The application of tandem MS using diverse fragmentation techniques, including novel ion activation methodologies, in studying glycan sequences, linkage positions, and fatty acid composition is extensively discussed. Finally, we address current challenges, such as the detection of low-abundance species and the interpretation of complex spectra, and offer insights into potential solutions and future directions by improving MS instrumentation for enhanced sensitivity and resolution, developing novel ionization techniques, or integrating MS with other analytical approaches for comprehensive GSL characterization.

Lipid profile in the aqueous humor of patients with myopia

We examined the lipid profiles in the aqueous humor (AH) of myopic patients to identify differences and investigate the relationships among dissertating lipids. Additionally, we assessed spherical equivalents and axial lengths to explore the pathogenesis of myopia. Ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was employed to qualitatively and quantitatively analyze the lipid composition of samples from myopic patients with axial lengths <26 mm (Group A) and >28 mm (Group B). Differences in lipid profiles between the two groups were determined using univariate and multivariate analyses. Receiver operator characteristic (ROC) curves were used to identify discriminating lipids. Spearman correlation analysis explored the associations between lipid concentrations and biometric parameters. Three hundred and nine lipids across 21 lipid classes have been identified in this study. Five lipids showed significant differences between Group B and Group A (VIP >1, P < 0.05): BMP (20:3/22:3), PG (22:1/24:0), PS (14:1/22:4), TG (44:2)_FA18:2, and TG (55:3)_FA18:1. The area under the curve (AUC) for these lipids was >0.75. Notably, the concentrations of BMP (20:3/22:3), PS (14:1/22:4), and TG (55:3)_FA18:1 were correlated with spherical equivalents, while BMP (20:3/22:3) and PS (14:1/22:4) correlated with axial lengths. Our study identified five differential lipids in myopic patients, with three showing significant correlations with the degree of myopia. These findings enhance our understanding of myopia pathogenesis through lipidomic alterations, emphasizing changes in cell membrane composition and function, energy metabolism and storage, and pathways involving inflammation, peroxisome proliferator-activated receptors (PPAR), and metabolic processes related to phosphatidylserine, phosphatidylglycerol, triglycerides, polyunsaturated fatty acids, and cholesterol.

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics: Future challenges and perspectives

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

Investigating the effects of dexamethasone on pulmonary surfactant lipids based on lipidomics studies

Dexamethasone, a glucocorticoid commonly used in pediatric patients, has potent anti-inflammatory and immunosuppressive properties. However, it is associated with side effects such as reduced lung function and decreased immunity. Pulmonary surfactant lipids are closely linked to lung disease and play a role in reducing surface tension, immune response and antiviral activity. The dysregulation of lipid metabolism is closely associated with lung disease. Hence, untargeted lipidomics may be instrumental in elucidating the effects of dexamethasone on pulmonary surfactant lipids. We obtained surfactant lipid samples from the bronchoalveolar lavage fluid of young mice injected subcutaneously with dexamethasone and conducted a comprehensive lipidomic analysis, comparing them with a control group. We observed a decrease in lipids, such as phosphatidylcholine, phosphatidylglycerol and phosphatidylethanolamine, and an increase in ceramide, fatty acid, diacylglycerol and monoglyceride, which may impact lung health. This study revealed the influence of dexamethasone on pulmonary surfactant lipids, offering new insights into adverse reactions in clinical settings.

Peripheral Lipid Signatures, Metabolic Dysfunction, and Pathophysiology in Schizophrenia Spectrum Disorders

Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and AP-induced metabolic dysfunction are unknown, but dysregulated lipid metabolism may play a role. Lipidomics, which detects lipid metabolites in a biological sample, represents an analytical tool to examine lipid metabolism. This systematic review aims to determine peripheral lipid signatures that are dysregulated among individuals with SSDs (1) with minimal exposure to APs and (2) during AP treatment. To accomplish this goal, we searched MEDLINE, Embase, and PsychINFO databases in February 2024 to identify all full-text articles written in English where the authors conducted lipidomics in SSDs. Lipid signatures reported to significantly differ in SSDs compared to controls or in relation to AP treatment and the direction of dysregulation were extracted as outcomes. We identified 46 studies that met our inclusion criteria. Most of the lipid metabolites that significantly differed in minimally AP-treated patients vs. controls comprised glycerophospholipids, which were mostly downregulated. In the AP-treated group vs. controls, the significantly different metabolites were primarily fatty acyls, which were dysregulated in conflicting directions between studies. In the pre-to-post AP-treated patients, the most impacted metabolites were glycerophospholipids and fatty acyls, which were found to be primarily upregulated and conflicting, respectively. These lipid metabolites may contribute to SSD pathophysiology and metabolic dysfunction through various mechanisms, including the modulation of inflammation, cellular membrane permeability, and metabolic signaling pathways.

Lipidomic analyses reveal potential biomarkers for predicting death and heart failure after acute myocardial infarction

Background Acute myocardial infarction (AMI) and postmyocardial infarction heart failure (pMIHF) have high mortality rates worldwide. This study aimed to explore lipidomic profiles and identify potential biomarkers for the prediction of death and heart failure (HF) after AMI. Methods All serum samples were collected at Xuanwu Hospital, Capital Medical University, and their clinical characteristics and lipidomic profiles were analyzed in different groups. LC-MS/MS was used for lipidomic analyses, and underlying biomarkers were screened by receiver operating characteristic (ROC) curve analysis. Results Lipidomic analyses of the survival and nonsurvival groups revealed that the decrease of the content of SM (d18:1/22:0), PE (P-20:1/18:0), PC (18:2), LPE (18:2), PE (P-20:0/18:0), LPC (18:0) and PC (20:0/20:3) while increase of the content of PG (18:1/18:1) could increase the risk of death after AMI. In parallel, the lipidomic analysis of the HF and non-HF groups revealed that the decrease of the content of PC (20:3/20:4), LPC (20:3), LPC (18:0), LPC (18:2), LPC (20:0), LPC (18:3), LPE (16:1) and PC (18:2/20:3) could increase the risk of HF after AMI. Conclusion Several lipids could be potential biomarkers for the prediction of death and HF after AMI.

Lipidomic Profiling of Flammulina velutipes (Curtis) Singer (Agaricomycetes) through Ultra-Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Mass Spectrometry: Examining Lipid Dynamics Changes during Fruiting Body Formation and Development

Flammulina velutipes (enokitake) is widely recognized for its nutritional and medicinal properties. Understanding the biochemical processes, such as lipid metabolism during fruiting body formation, is essential for enhancing mushroom cultivation and utilization. This study aimed at elucidating the dynamic lipidomic changes during seven growth stages of F. velutipes using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Our results revealed significant increases in ceramides along with the growth and a sharp decline in phosphatidylinositols from mycelial to primordial stages. Fatty acid esters of hydroxy fatty acids, recently discovered for their bioactivities, showed high intensities in the mycelial and primordial stages but decreased rapidly thereafter. These findings provide profound insights into the lipid profiles associated with mushroom morphology and development. This lipidomics study establishes a foundational understanding for future research in agricultural and food chemistry applications, potentially improving industrial production and quality control of F. velutipes.

Diet Supplemented with Special Formula Milk Powder Promotes the Growth of the Brain in Rats

This investigation was to study the effects of different formula components on the brain growth of rats. Fifty male SD rats were randomly divided into five groups: a basic diet group; a 20% ordinary milk powder group; a 20% special milk powder group; a 30% ordinary milk powder group; and a 30% special milk powder group by weight. LC-MS was used to detect brain lipidomics. After 28 days of feeding, compared with the basic diet group, the brain/body weights of rats in the 30% ordinary milk powder group were increased. The serum levels of 5-HIAA in the 30% ordinary milk powder group were lower than in the 20% ordinary milk powder group. Compared with the basic diet group, the expressions of DLCL, MePC, PI, and GM1 were higher in the groups with added special milk powder, while the expressions of LPE, LdMePE, SM, and MGTG were higher in the groups with added ordinary milk powder. The expression of MBP was significantly higher in the 20% ordinary group. This study found that different formula components of infant milk powder could affect brain growth in SD rats. The addition of special formula infant milk powder may have beneficial effects on rat brains by regulating brain lipid expression.

Dexborneol Amplifies Pregabalin's Analgesic Effect in Mouse Models of Peripheral Nerve Injury and Incisional Pain

Pregabalin is a medication primarily used in the treatment of neuropathic pain and anxiety disorders, owing to its gabapentinoid properties. Pregabalin monotherapy faces limitations due to its variable efficacy and dose-dependent adverse reactions. In this study, we conducted a comprehensive investigation into the potentiation of pregabalin's analgesic effects by dexborneol, a neuroprotective bicyclic monoterpenoid compound. We performed animal experiments where pain models were induced using two methods: peripheral nerve injury, involving axotomy and ligation of the tibial and common peroneal nerves, and incisional pain through a longitudinal incision in the hind paw, while employing a multifaceted methodology that integrates behavioral pharmacology, molecular biology, neuromorphology, and lipidomics to delve into the mechanisms behind this potentiation. Dexborneol was found to enhance pregabalin's efficacy by promoting its transportation to the central nervous system, disrupting self-amplifying vicious cycles via the reduction of HMGB1 and ATP release, and exerting significant anti-oxidative effects through modulation of central lipid metabolism. This combination therapy not only boosted pregabalin's analgesic property but also notably decreased its side effects. Moreover, this therapeutic cocktail exceeded basic pain relief, effectively reducing neuroinflammation and glial cell activation-key factors contributing to persistent and chronic pain. This study paves the way for more tolerable and effective analgesic options, highlighting the potential of dexborneol as an adjuvant to pregabalin therapy.

Lipids and lipid metabolism in cellular senescence: Emerging targets for age-related diseases

Cellular senescence is a kind of cellular state triggered by endogenous or exogenous stimuli, which is mainly characterized by stable cell cycle arrest and complex senescence-associated secretory phenotype (SASP). Once senescent cells accumulate in tissues, they may eventually accelerate the progression of age-related diseases, such as atherosclerosis, osteoarthritis, chronic lung diseases, cancers, etc. Recent studies have shown that the disorders of lipid metabolism are not only related to age-related diseases, but also regulate the cellular senescence process. Based on existing research evidences, the changes in lipid metabolism in senescent cells are mainly concentrated in the metabolic processes of phospholipids, fatty acids and cholesterol. Obviously, the changes in lipid-metabolizing enzymes and proteins involved in these pathways play a critical role in senescence. However, the link between cellular senescence, changes in lipid metabolism and age-related disease remains to be elucidated. Herein, we summarize the lipid metabolism changes in senescent cells, especially the senescent cells that promote age-related diseases, as well as focusing on the role of lipid-related enzymes or proteins in senescence. Finally, we explore the prospect of lipids in cellular senescence and their potential as drug targets for preventing and delaying age-related diseases.

Lc-ms-based lipidomics analyses revealed changes in lipid profiles in Asian sea bass (Lates calcarifer) with dielectric barrier discharge (DBD) atmospheric plasma treatment

A comprehensive LC-MS-based lipidomics analysis of Asian sea bass (Lates calcarifer) muscle after dielectric barrier discharge (DBD) atmospheric plasma treatment was performed. Through the analysis, 1500 lipid species were detected, phosphatidylcholine (PC, 27.80%) was the most abundant lipid, followed by triglyceride (TG, 20.50%) and phosphatidylethanolamine (PE, 17.10%). Among them, 125 lipid species were detected and identified as differentially abundant lipids in Asian sea bass (ASB). PCA and OPLS-DA showed that ASB lipids changed significantly after DBD treatment. Moreover, glycerophospholipid metabolism was key metabolic pathways, as PC, PE, and lysophosphatidylcholine (LPC) were key lipid metabolites. The findings concerning fatty acids revealed that the saturated fatty acids (SFA) content of ASB after DBD treatment increased by 8.54%, while the content of monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) decreased by 13.77% and 9.16%, respectively. Our study establishes a foundation for the lipid oxidation mechanism of ASB following DBD treatment.

Levels of lipid-derived gut microbial metabolites differ among plant matrices in an in vitro model of colon fermentation

This study explored differences in microbial lipid metabolites among sunflower seeds, soybeans, and walnuts. The matrices were subjected to in vitro digestion and colonic fermentation. Defatted digested materials and fiber/phenolics extracted therefrom were added to sunflower oil (SO) and also fermented. Targeted and untargeted lipidomics were employed to monitor and tentatively identify linoleic acid (LA) metabolites. Walnut fermentation produced the highest free fatty acids (FFAs), LA, and conjugated LAs (CLAs). Defatted digested walnuts added to SO boosted FFAs and CLAs production; the addition of fibre boosted CLAs, whereas the addition of phenolics only increased 9e,11z-CLA and 10e,12z-CLA. Several di-/tri-hydroxy-C18-FAs, reported as microbial LA metabolites for the first time, were annotated. Permutational multivariate analysis of variance indicated significant impacts of food matrix presence and type on lipidomics and C18-FAs. Our findings highlight how the food matrices affect CLA production from dietary lipids, emphasizing the role of food context in microbial lipid metabolism.

Cholesterol and low-density lipoprotein as a cause of psoriasis: Results from bidirectional Mendelian randomization

BACKGROUND

Psoriasis is an inflammatory disease that affects many people. However, the causal effect of lipid metabolism on psoriasis has not yet been verified. This study aimed to identify the genetic relationship between serum lipid levels and psoriasis.

METHODS

Bidirectional two-sample Mendelian randomization (MR) was used to analyse the causal relationship between cholesterol and psoriasis. The outcome of the forward causality test was psoriasis. In the analysis of reverse causality, psoriasis was exposed, and 79 single-nucleotide polymorphisms were detected in the genome-wide association study (GWASs) database from the IEU GWASs Project. MR-Egger regression, inverse variance-weighted, weighted median, weighted mode and simple mode were used for the MR analyses.

RESULTS

The level of triglyceride, lipase member N, chylomicrons, extremely large very low-density lipoprotein (VLDL) particles, high-density lipoprotein (HDL) cholesterol levels, cholesterol esters in large HDL, cholesterol esters in medium HDL and cholesterol esters in medium VLDL have not affected the development of psoriasis. However, total cholesterol, total free cholesterol, low-density lipoprotein (LDL) cholesterol levels, cholesterol esters in large VLDL and cholesterol esters in medium LDL were unidirectional causal effects on psoriasis.

CONCLUSION

Bidirectional two-sample MR analysis indicated that high levels of total cholesterol, total free cholesterol, LDL cholesterol, cholesterol esters in large VLDL and cholesterol esters in medium LDL are genetic risk factors for psoriasis.

From big data to big insights: statistical and bioinformatic approaches for exploring the lipidome

The goal of lipidomic studies is to provide a broad characterization of cellular lipids present and changing in a sample of interest. Recent lipidomic research has significantly contributed to revealing the multifaceted roles that lipids play in fundamental cellular processes, including signaling, energy storage, and structural support. Furthermore, these findings have shed light on how lipids dynamically respond to various perturbations. Continued advancement in analytical techniques has also led to improved abilities to detect and identify novel lipid species, resulting in increasingly large datasets. Statistical analysis of these datasets can be challenging not only because of their vast size, but also because of the highly correlated data structure that exists due to many lipids belonging to the same metabolic or regulatory pathways. Interpretation of these lipidomic datasets is also hindered by a lack of current biological knowledge for the individual lipids. These limitations can therefore make lipidomic data analysis a daunting task. To address these difficulties and shed light on opportunities and also weaknesses in current tools, we have assembled this review. Here, we illustrate common statistical approaches for finding patterns in lipidomic datasets, including univariate hypothesis testing, unsupervised clustering, supervised classification modeling, and deep learning approaches. We then describe various bioinformatic tools often used to biologically contextualize results of interest. Overall, this review provides a framework for guiding lipidomic data analysis to promote a greater assessment of lipidomic results, while understanding potential advantages and weaknesses along the way.

Combined quantitative lipidomics and back-propagation neural network approach to discriminate the breed and part source of lamb

The study successfully utilized an analytical approach that combined quantitative lipidomics with back-propagation neural networks to identify breed and part source of lamb using small-scale samples. 1230 molecules across 29 lipid classes were identified in longissimus dorsi and knuckle meat of both Tan sheep and Bahan crossbreed sheep. Applying multivariate statistical methods, 12 and 7 lipid molecules were identified as potential markers for breed and part identification, respectively. Stepwise linear discriminant analysis was applied to select 3 and 4 lipid molecules, respectively, for discriminating lamb breed and part sources, achieving correct rates of discrimination of 100 % and 95 %. Additionally, back-propagation neural network proved to be a superior method for identifying sources of lamb meat compared to other machine learning approaches. These findings indicate that integrating lipidomics with back-propagation neural network approach can provide an effective strategy to trace and certify lamb products, ensuring their quality and protecting consumer rights.

Exploring the plant lipidome: techniques, challenges, and prospects

Plant lipids are a diverse group of biomolecules that play essential roles in plant architecture, physiology, and signaling. To advance our understanding of plant biology and facilitate innovations in plant-based product development, we must have precise methods for the comprehensive analysis of plant lipids. Here, we present a comprehensive overview of current research investigating plant lipids, including their structures, metabolism, and functions. We explore major lipid classes, i.e. fatty acids, glyceroglycolipids, glycerophospholipids, sphingolipids, and phytosterols, and discuss their subcellular distributions. Furthermore, we emphasize the significance of lipidomics research techniques, particularly chromatography-mass spectrometry, for accurate lipid analysis. Special attention is given to lipids as crucial signal receptors and signaling molecules that influence plant growth and responses to environmental challenges. We address research challenges in lipidomics, such as in identifying and quantifying lipids, separating isomers, and avoiding batch effects and ion suppression. Finally, we delve into the practical applications of lipidomics, including its integration with other omics methodologies, lipid visualization, and innovative analytical approaches. This review thus provides valuable insights into the field of plant lipidomics and its potential contributions to plant biology.

Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes

Gestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Recent Analytical Methodologies in Lipid Analysis

Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods

BACKGROUND

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities.

OBJECTIVE

The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters.

METHOD

The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Predicting prognosis outcomes of primary central nervous system lymphoma with high-dose methotrexate-based chemotherapeutic treatment using lipidomics

Background

Primary central nervous system lymphoma (PCNSL) is a rare extranodal lymphomatous malignancy which is commonly treated with high-dose methotrexate (HD-MTX)-based chemotherapy. However, the prognosis outcome of HD-MTX-based treatment cannot be accurately predicted using the current prognostic scoring systems, such as the Memorial Sloan-Kettering Cancer Center (MSKCC) score.

Methods

We studied 2 cohorts of patients with PCNSL and applied lipidomic analysis to their cerebrospinal fluid (CSF) samples. After removing the batch effects and features engineering, we applied and compared several classic machine-learning models based on lipidomic data of CSF to predict the relapse of PCNSL in patients who were treated with HD-MTX-based chemotherapy.

Results

We managed to remove the batch effects and get the optimum features of each model. Finally, we found that Cox regression had the best prediction performance (AUC = 0.711) on prognosis outcomes.

Conclusions

We developed a Cox regression model based on lipidomic data, which could effectively predict PCNSL patient prognosis before the HD-MTX-based chemotherapy treatments.

A lipidomic approach to bisphenol F-induced non-alcoholic fatty liver disease-like changes: altered lipid components in a murine model

Bisphenol A (BPA), a typical environmental endocrine disruptor, is an "obesogen" that can induce lipid accumulation in the liver. Highly similar in structure to BPA, bisphenol F (BPF) is becoming the dominant BPA substitute on the market, which attracts more and more attention due to its potential adverse effects. Recently, BPF exposure is found to cause non-alcoholic fatty liver disease (NAFLD)-like changes; however, the underlying toxic effects remain poorly understood. Therefore, in the current study, we focused on BPF-mediated lipid homeostasis, especially the alterations of lipid components and metabolism. In human serum, the BPF levels in healthy controls and NAFLD patients were assessed by ELISA, and BPF-induced disturbance of lipid metabolism was evaluated in mouse model via non-targeted lipomic methods with ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. It suggested that BPF exposure was positively correlated with NAFLD severity and triglyceride level in patients. Based on the relationships, lipid metabolites were assessed in mouse livers between control and BPF-treated group, and it revealed that twenty-six lipid metabolites (including phospholipids, sphingolipids, and glycerides) were significantly changed in mouse livers. Phosphatidylcholine, phosphatidylethanolamine, and diglyceryl ester levels were lower than those in the control mice; hexose ceramide content in sphingolipids markedly increased in BPF-treated mouse livers. Noteworthily, the glycerophospholipid metabolic pathway was found to be the most pronounced in BPF-induced disturbance of lipid metabolism. Therefore, the current study, for the first time, is deciphering the BPF-induced lipid metabolic disturbance, which may provide novel intervention strategies for BPF-induced NAFLD-like changes.

Differences in the lipid metabolism profile and clinical characteristics between eosinophilic and non-eosinophilic acute exacerbation of chronic obstructive pulmonary disease

Objective: In this study, we aimed to investigate the differences in serum lipid metabolite profiles and their relationship with clinical characteristics between patients with eosinophilic and non-eosinophilic AECOPD. Methods: A total of 71 AECOPD patients were enrolled. Eosinophilic AECOPD was defined as blood EOS% ≥ 2% (n = 23), while non-eosinophilic AECOPD, as blood EOS< 2% (n = 48). Clinical data were collected, and serum lipid metabolism profiles were detected by liquid chromatography-mass spectrometry (LC-MS). The XCMS software package was used to pre-process the raw data, and then, lipid metabolite identification was achieved through a spectral match using LipidBlast library. Differences in lipid profiles and clinical features between eosinophilic and non-eosinophilic groups were analyzed by generalized linear regression. The least absolute shrinkage and selection operator (LASSO) was applied to screen the most characteristic lipid markers for the eosinophilic phenotype. Results: Eosinophilic AECOPD patients had less hypercapnic respiratory failures, less ICU admissions, a shorter length of stay in the hospital, and a lower fibrinogen level. In the lipid metabolism profiles, 32 significantly different lipid metabolites were screened through a t-test adjusted by using FDR (FDR-adjusted p < 0.05 and VIP> 1). Nine differential lipid metabolites were found to be associated with the three clinical features, namely, hypercapnia respiratory failure, ICU admission, and fibrinogen in further integration analysis. The species of triacylglycerol (TAG), phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and diacylglyceryl trimethylhomoserine (DGTS) were high in these eosinophilic AECOPD. The LASSO was applied, and three lipid metabolites were retained, namely, LPC (16:0), TAG (17:0/17:2/17:2), and LPC (20:2). The logistic regression model was fitted using these three markers, and the area under the ROC curve of the model was 0.834 (95% CI: 0.740-0.929). Conclusion: Patients with eosinophilic AECOPD had a unique lipid metabolism status. Species of TAGs and LPCs were significantly increased in this phenotype and were associated with better clinical outcomes.

Autologous hematopoietic stem cell transplantation significantly alters circulating ceramides in peripheral blood of relapsing-remitting multiple sclerosis patients

BACKGROUND

The common inflammatory disease multiple sclerosis (MS) is a disease of the central nervous system. For more than 25 years autologous hematopoietic stem cell transplantation (AHSCT) has been used to treat MS. It has been shown to be highly effective in suppressing inflammatory activity in relapsing-remitting MS (RRMS) patients. This treatment is thought to lead to an immune system reset, inducing a new, more tolerant system; however, the precise mechanism behind the treatment effect in MS patients is unknown. In this study, the effect of AHSCT on the metabolome and lipidome in peripheral blood from RRMS patients was investigated.

METHODS

Peripheral blood samples were collected from 16 patients with RRMS at ten-time points over the five months course of AHSCT and 16 MS patients not treated with AHSCT. Metabolomics and lipidomics analysis were performed using liquid-chromatography high-resolution mass spectrometry. Mixed linear models, differential expression analysis, and cluster analysis were used to identify differentially expressed features and groups of features that could be of interest. Finally, in-house and in-silico libraries were used for feature identification, and enrichment analysis was performed.

RESULTS

Differential expression analysis found 657 features in the lipidomics dataset and 34 in the metabolomics dataset to be differentially expressed throughout AHSCT. The administration of cyclophosphamide during mobilization and conditioning was associated with decreased concentrations in glycerophosphoinositol species. Thymoglobuline administration was associated with an increase in ceramide and glycerophosphoethanolamine species. After the conditioning regimen, a decrease in glycerosphingoidlipids concentration was observed, and following hematopoietic stem cell reinfusion glycerophosphocholine concentrations decreased for a short period of time. Ceramide concentrations were strongly associated with leukocyte levels during the procedure. The ceramides Cer(d19:1/14:0) and Cer(d20:1/12:0) were found to be increased (P < .05) in concentration at the three-month follow-up compared to baseline. C16 ceramide, Cer(D18:2/16:0), and CerPE(d16:2(4E,6E)/22:0) were found to be significantly increased in concentration after AHSCT compared to prior to treatment as well as compared to newly diagnosed RRMS patients.

CONCLUSION

AHSCT had a larger impact on the lipids in peripheral blood compared to metabolites. The variation in lipid concentration reflects the transient changes in the peripheral blood milieu during the treatment, rather than the changes in the immune system that are assumed to be the cause of clinical improvement within RRMS patients treated with AHSCT. Ceramide concentrations were affected by AHSCT and associated with leukocyte counts and were altered three months after treatment, suggesting a long-lasting effect.

Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic steatohepatitis (NASH) is a condition characterized by inflammation and hepatic injury/fibrosis caused by the accumulation of ectopic fats in the liver. Recent advances in lipidomics have allowed the identification and characterization of lipid species and have revealed signature patterns of various diseases. Here, we describe a lipidomics workflow to assess the lipid profiles of liver homogenates taken from a NASH mouse model. The protocol described below was used to extract and analyze the metabolites from the livers of mice with NASH by liquid chromatography-mass spectrometry (LC-MS); however, it can be applied to other tissue homogenate samples. Using this method, over 1,000 species of lipids from five classes can be analyzed in a single run on the LC-MS. Also, partial elucidation of the identity of neutral lipid (triacylglycerides and diacylglycerides) aliphatic chains can be performed with this simple LC-MS setup. Key features Over 1,000 lipid species (sphingolipids, cholesteryl esters, neutral lipids, phospholipids, fatty acids) are analyzed in one run. Analysis of liver lipids in non-alcoholic steatohepatitis (NASH) mouse model. Normal-phase chromatography coupled to a triple quadrupole mass spectrometer.

Untargeted Lipidomics and Chemometric Tools for the Characterization and Discrimination of Irradiated Camembert Cheese Analyzed by UHPLC-Q-Orbitrap-MS

In this work, an investigation using UHPLC-Q-Orbitrap-MS and multivariate statistics was conducted to obtain the lipid fingerprint of Camembert cheese and to explore its correlated variation with respect to X-ray irradiation treatment. A total of 479 lipids, categorized into 16 different lipid subclasses, were measured. Furthermore, the identification of oxidized lipids was carried out to better understand the possible phenomena of lipid oxidation related to this technological process. The results confirm that the lipidomic approach adopted is effective in implementing the knowledge of the effects of X-ray irradiation on food and evaluating its safety aspects. Furthermore, Partial Least Squares-Discriminant Analysis (PLS-DA) and Linear Discriminant Analysis (LDA) were applied showing high discriminating ability with excellent values of accuracy, specificity and sensitivity. Through the PLS-DA and LDA models, it was possible to select 40 and 24 lipids, respectively, including 3 ceramides (Cer), 1 hexosyl ceramide (HexCer), 1 lysophosphatidylcholine (LPC), 1 lysophosphatidylethanolamine (LPE), 3 phosphatidic acids (PA), 4 phosphatidylcholines (PC), 10 phosphatidylethanolamines (PE), 5 phosphatidylinositols (PI), 2 phosphatidylserines (PS), 3 diacylglycerols (DG) and 9 oxidized triacylglycerols (OxTG) as potential markers of treatment useful in food safety control plans.

Contrastive Learning-Based Embedder for the Representation of Tandem Mass Spectra

Tandem mass spectrometry (MS/MS) shows great promise in the research of metabolomics, providing an abundance of information on compounds. Due to the rapid development of mass spectrometric techniques, a large number of MS/MS spectral data sets have been produced from different experimental environments. The massive data brings great challenges into the spectral analysis including compound identification and spectra clustering. The core challenge in MS/MS spectral analysis is how to describe a spectrum more quantitatively and effectively. Recently, emerging deep-learning-based technologies have brought new opportunities to handle this challenge in which high-quality descriptions of MS/MS spectra can be obtained. In this study, we propose a novel contrastive learning-based method for the representation of MS/MS spectra, called CLERMS, which is based on transformer architecture. Specifically, an optimized model architecture equipped with a sinusoidal embedder and a novel loss function composed of InfoNCE loss and MSE loss has been proposed for the attainment of good embedding from the peak information and the metadata. We evaluate our method using a GNPS data set, and the results demonstrate that the learned embedding can not only distinguish spectra from different compounds but also reveal the structural similarity between them. Additionally, the comparison between our method and other methods on the performance of compound identification and spectra clustering shows that our method can achieve significantly better results.

Crosstalk between cholesterol metabolism and psoriatic inflammation

Psoriasis is a chronic autoinflammatory skin disease associated with multiple comorbidities, with a prevalence ranging from 2 to 3% in the general population. Decades of preclinical and clinical studies have revealed that alterations in cholesterol and lipid metabolism are strongly associated with psoriasis. Cytokines (tumor necrosis factor-α (TNF-α), interleukin (IL)-17), which are important in the pathogenesis of psoriasis, have been shown to affect cholesterol and lipid metabolism. Cholesterol metabolites and metabolic enzymes, on the other hand, influence not only the biofunction of keratinocytes (a primary type of cell in the epidermis) in psoriasis, but also the immune response and inflammation. However, the relationship between cholesterol metabolism and psoriasis has not been thoroughly reviewed. This review mainly focuses on cholesterol metabolism disturbances in psoriasis and their crosstalk with psoriatic inflammation.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

Mechanism of Cytotoxic Action of Gold Nanorods Photothermal Therapy for A549 Cell

Photothermal therapy has developed into an important field of tumor treatment research, and numerous studies have focused on the preparation of photothermal therapeutic agents, tumor targeting, diagnosis, and treatment integration. However, there are few studies on the mechanism of photothermal therapy acting on cancer cells. Here we investigated the metabolomics of lung cancer cell A549 during gold nanorod (GNR) photothermal treatment by high-resolution LC/MS, and several differential metabolites and corresponding metabolic pathways during photothermal therapy were found. The main differential metabolites contained 18-hydroxyoleate, beta-alanopine and cis-9,10-epoxystearic acid, and phosphorylcholine. Pathway analysis also showed metabolic changes involving cutin, suberine, and wax biosynthesis, pyruvate and glutamic acid synthesis, and choline metabolism. Analysis also showed that the photothermal process of GNRs may induce cytotoxicity by affecting pyruvate and glutamate synthesis, normal choline metabolism, and ultimately apoptosis.

Untargeted Lipidomic Profiling Reveals Lysophosphatidylcholine and Ceramide as Atherosclerotic Risk Factors in apolipoprotein E Knockout Mice

Despite the availability and use of numerous cholesterol-lowering drugs, atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality globally. Many researchers have focused their effort on identifying modified lipoproteins. However, lipid moieties such as lysophosphatidylcholine (LPC) and ceramide (CER) contribute to atherogenic events. LPC and CER both cause endothelial mitochondrial dysfunction, leading to fatty acid and triglyceride (TG) accumulation. In addition, they cause immune cells to differentiate into proinflammatory phenotypes. To uncover alternative therapeutic approaches other than cholesterol- and TG-lowering medications, we conducted untargeted lipidomic investigations to assess the alteration of lipid profiles in apolipoprotein E knockout (apoE^-/-) mouse model, with or without feeding a high-fat diet (HFD). Results indicated that, in addition to hypercholesterolemia and hyperlipidemia, LPC levels were two to four times higher in apoE^-/- mice compared to wild-type mice in C57BL/6 background, regardless of whether they were 8 or 16 weeks old. Sphingomyelin (SM) and CER were elevated three- to five-fold in apoE^-/- mice both at the basal level and after 16 weeks when compared to wild-type mice. After HFD treatment, the difference in CER levels elevated more than ten-fold. Considering the atherogenic properties of LPC and CER, they may also contribute to the early onset of atherosclerosis in apoE^-/- mice. In summary, the HFD-fed apoE^-/- mouse shows elevated LPC and CER contents and is a suitable model for developing LPC- and CER-lowering therapies.