Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study.

INTRODUCTION: Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these. OBJECTIVE: To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD. METHODS: We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling. RESULTS: 499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides. CONCLUSIONS: Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.

An exploratory study on lipidomic profiles in a cohort of individuals with posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) can develop after trauma exposure. Some studies report that women develop PTSD at twice the rate of men, despite greater trauma exposure in men. Lipids and their metabolites (lipidome) regulate a myriad of key biological processes and pathways such as membrane integrity, oxidative stress, and neuroinflammation in the brain by maintaining neuronal connectivity and homeostasis. In this study, we analyzed the lipidome of 40 adults with PTSD and 40 trauma-exposed non-PTSD individuals (n = 20/sex/condition; 19-39 years old). Plasma samples were analyzed for lipidomics using Quadrupole Time-of-Flight (QToF) mass spectrometry. Additionally, ~ 90 measures were collected, on sleep, and mental and physical health indices. Poorer sleep quality was associated with greater PTSD severity in both sexes. The lipidomics analysis identified a total of 348 quantifiable known lipid metabolites and 1951 lipid metabolites that are yet unknown; known metabolites were part of 13 lipid subclasses. After adjusting for BMI and sleep quality, in women with PTSD, only one lipid subclass, phosphatidylethanolamine (PE) was altered, whereas, in men with PTSD, 9 out of 13 subclasses were altered compared to non-PTSD women and men, respectively. Severe PTSD was associated with 22% and 5% of altered lipid metabolites in men and women, respectively. Of the changed metabolites, only 0.5% measures (2 PEs and cholesterol) were common between women and men with PTSD. Several sphingomyelins, PEs, ceramides, and triglycerides were increased in men with severe PTSD. The correlations between triglycerides and ceramide metabolites with cholesterol metabolites and systolic blood pressure were dependent upon sex and PTSD status. Alterations in triglycerides and ceramides are linked with cardiac health and metabolic function in humans. Thus, disturbed sleep and higher body mass may have contributed to changes in the lipidome found in PTSD.

Clinical serum lipidomic profiling revealed potential lipid biomarkers for early diabetic retinopathy.

Diabetic retinopathy (DR) is a serious complication of diabetes featuring abnormal lipid metabolism. However, the specific lipid molecules associated with onset and progression remain unclear. We used a broad-targeted lipidomics approach to assess the lipid changes that occur before the proliferative retinopathy stage and to identify novel lipid biomarkers to distinguish between patients without DR (NDR) and with non-proliferative DR (NPDR). Targeted lipomics analysis was carried out on serum samples from patients with type I diabetes, including 20 NDRs and 20 NPDRs. The results showed that compared with the NDR group, 102 lipids in the NPDR group showed specific expressions. Four lipid metabolites including TAG58:2-FA18:1 were obtained using the Least Absolute Shrink And Selection Operator (LASSO) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methods. The four-lipid combination diagnostic models showed good predictive ability in both the discovery and validation sets, and were able to distinguish between NDR patients and NPDR patients. The identified lipid markers significantly improved diagnostic accuracy within the NPDR group. Our findings help to better understand the complexity and individual differences of DR lipid metabolism.

Profiling lipid mediators in serum from children with H1N1 influenza.

Influenza A virus subtype H1N1 can cause severe acute respiratory distress syndrome and death in young children and elderly individuals. H1N1 initiates inflammatory responses that aim to contain and eliminate microbial invaders. Various lipid mediators (LMs) are biosynthesized and play a critical role in fighting viruses during inflammation; thus, by profiling the LMs in patients, researchers can obtain mechanistic insights into diseases, such as the pathways disrupted. To date, the relationship between molecular alterations in LMs and the pathogenesis of H1N1 influenza in children is poorly understood. Here, we employed a targeted liquid chromatography coupled with tandem mass spectrometry (LC‒MS/MS) to profile LMs in serum from children with H1N1 influenza (H1N1 children) and recovered children. We found that 22 LM species were altered in H1N1 children with mild symptoms. Analysis of the LM profiles of recovered children revealed a decrease in the levels of thromboxane B2 (TxB2) and thromboxane B3 (TxB3) and an increase in the levels of other 8 altered LM species associated with H1N1 influenza, including cytochrome P450 (CYP) enzyme-derived dihydroxyeicosatrienoic acids (DiHETrEs) and hydroxyeicosatetraenoic acids (HETEs) from arachidonic acid (AA), and epoxyoctadecamonoenoic acids (EpOMEs) from linoleic acid (LA). Taken together, the results of this study revealed that serum LMs change dynamically in H1N1 children with mild symptoms. The dramatically altered LMs in H1N1 children could serve as a basis for potential therapeutics or adjuvants against H1N1 influenza.

The Effects of Pregestational Overweight and Obesity on Maternal Lipidome in Pregnancy: Implications for Newborns' Characteristics.

Obesity is an important risk factor for the development of pregnancy complications. We investigated the effects of pregestational overweight and obesity on maternal lipidome during pregnancy and on newborns' characteristics. The study encompassed 131 pregnant women, 99 with pre-pregnancy body mass index (BMI) < 25 kg/m2 and 32 with BMI ≥ 25 kg/m2. Maternal lipid status parameters, plasma markers of cholesterol synthesis and absorption and sphingolipids were determined in each trimester. Data on neonatal height, weight and APGAR scores were assessed. The results showed a higher prevalence (p < 0.05) of pregnancy and childbirth complications among the participants with elevated pregestational BMI. Levels of total cholesterol, HDL-cholesterol (p < 0.05) and LDL-cholesterol (p < 0.01) were significantly lower, and concentrations of triglycerides were higher (p < 0.05) in women with increased pre-gestational BMI. Lower concentrations of the cholesterol synthesis marker, desmosterol, in the 2nd trimester (p < 0.01) and the cholesterol absorption marker, campesterol, in each trimester (p < 0.01, p < 0.05, p < 0.01, respectively) were also found in this group. Markers of maternal cholesterol synthesis were in positive correlation with neonatal APGAR scores in the group of mothers with healthy pre-pregnancy weight but in negative correlation in the overweight/obese group. Our results indicate that gestational adaptations of maternal lipidome depend on her pregestational nutritional status and that such changes may affect neonatal outcomes.

Small and Large Extracellular Vesicles of Porcine Seminal Plasma Differ in Lipid Profile.

Seminal plasma contains a heterogeneous population of extracellular vesicles (sEVs) that remains poorly characterized. This study aimed to characterize the lipidomic profile of two subsets of differently sized sEVs, small (S-) and large (L-), isolated from porcine seminal plasma by size-exclusion chromatography and characterized by an orthogonal approach. High-performance liquid chromatography-high-resolution mass spectrometry was used for lipidomic analysis. A total of 157 lipid species from 14 lipid classes of 4 major categories (sphingolipids, glycerophospholipids, glycerolipids, and sterols) were identified. Qualitative differences were limited to two cholesteryl ester species present only in S-sEVs. L-sEVs had higher levels of all quantified lipid classes due to their larger membrane surface area. The distribution pattern was different, especially for sphingomyelins (more in S-sEVs) and ceramides (more in L-sEVs). In conclusion, this study reveals differences in the lipidomic profile of two subsets of porcine sEVs, suggesting that they differ in biogenesis and functionality.

Zebrafish as a Model for Lipidomics and Similar Investigations.

Zebrafish (Danio rerio) has emerged as a pivotal model organism in vertebrate development research over several decades. Beyond its contributions to developmental biology, zebrafish have increasingly played a crucial role in the field of lipidomics. Lipidomics, a comprehensive analysis of lipids within biological systems, offers profound insights into lipid metabolism and signaling pathways. This chapter explores the zebrafish's unique attributes that make it an ideal candidate for lipidomics studies. With a genome sharing numerous genetic similarities with humans, zebrafish serve as a powerful model for dissecting lipid metabolism and unraveling the complexities of lipid mediator-related diseases. In this chapter, we delve into specific protocols tailored for utilizing zebrafish in lipidomics research and similar investigations. Through a comprehensive exploration of zebrafish as a model organism, this chapter aims to provide researchers with valuable insights and methodologies for advancing lipidomics studies using zebrafish.

Market Needs and Methodologies Associated with Patient Lipidomic Diagnoses and Analyses.

This chapter conducts an in-depth exploration of the impact of musculoskeletal (MSK) disorders and injuries, with a specific emphasis on their consequences within the older population demographic. It underscores the escalating demand for innovative interventions in MSK tissue engineering. The chapter also highlights the fundamental role played by lipid signaling mediators (LSMs) in tissue regeneration, with relevance to bone and muscle recovery. Remarkably, Prostaglandin E2 (PGE2) emerges as a central orchestrator in these regenerative processes. Furthermore, the chapter investigates the complex interplay between bone and muscle tissues, explaining the important influence exerted by LSMs on their growth and differentiation. The targeted modulation of LSM pathways holds substantial promise as a beneficial way for addressing muscle disorders. In addition to these conceptual understandings, the chapter provides a comprehensive overview of methodologies employed in the identification of LSMs, with a specific focus on the Liquid Chromatography-Mass Spectrometry (LC-MS). Furthermore, it introduces a detailed LC MS/MS-based protocol tailored for the detection of PGE2, serving as an invaluable resource for researchers immersed in this dynamic field of study.

Effects of a Laparotomy on Targeted Lipidomics Profiles in a Mouse Model of Surgical Stress During Aging.

Laparotomy (EL) is one of the most common procedures performed among surgical specialties. Previous research demonstrates that surgery is associated with an increased inflammatory response. Low psoas muscle mass and quality markers are associated with increased mortality rates after emergency laparotomy. Analysis of lipid mediators in serum and muscle by using liquid chromatography-mass spectrometry (LC-MS)-based lipidomics has proven to be a sensitive and precise technique. In this chapter, we describe an LC-MS/MS protocol for the profiling and quantification of signaling lipids formed from Eicosapentaenoic Acid (EPA) and Eicosatetranoic acid (ETA) by 5, 12, or 15 lipoxynases. This protocol has been developed for and validated in serum and muscle samples in a mouse model of surgical stress caused by laparotomy.

Optimized Lipidomics Extraction of Sphingosine and Sphinganine from Optic Nerve for Signaling Studies.

Interconvertible sphingolipid metabolites represent germane constituents of eukaryotic membranes and are vital in the regulation of cellular homeostasis, proliferation, survival, and induction of autophagy. This protocol describes a step-by-step method for extractions of sphingosine and sphinganine from mammalian tissue samples, particularly from the murine optic nerve. These lipids are partitioned into a binary mixture of chloroform and methanol in a modified Bligh and Dyer method. This is followed with reverse phase ultrahigh-performance liquid chromatography fractionation with a C18+ column and subsequent tandem mass spectrometry (UHPLC-MS-MS) analysis of the biological abundance. These free sphingoid bases dissociate to form structurally distinctive carbocation product ions that can be confirmed with annotations of lipidomic databases or in-house fragmentation software.

Detailed Protocol for Solid-Phase Extraction for Lipidomic Analysis.

Developing robust analytical techniques is a vital phase to facilitate understanding the roles and impacts of various omic profilings in cellular functions. The comprehensive analysis of various biological molecules within a biological system requires a precise sample preparation technique. Solid-Phase Extraction (SPE) has proven to be an indispensable method in lipidomic analysis, providing an uncomplicated and user-friendly technique for extraction and purification of lipid components from complex biological matrices. Of all the factors influencing the reliability and success of SPE, column or adsorbent materials, flow rate, and storage conditions are paramount in terms of their significance. In this chapter, we will discuss in detail the SPE steps for lipidomic analysis in biofluid samples (serum and plasma) and muscle tissues.

Lipidomics Profiling of the Linoleic Acid Metabolites After Whole-Body Vibration in Humans.

Bioactive lipids have been identified as dynamic signaling lipid mediators (LMs). These fats have the ability to activate responses and control bodily functions either directly or indirectly. Linoleic Acid (LA) and Alpha Linoleic Acid (ALA) are types of omega 3 fatty acids that possess inflammatory properties and promote resolution of inflammation either through their own actions or through their metabolites known as oxylipins. In this chapter, we provide an explanation of a method that combines chromatography with tandem mass spectroscopy (LC MS/MS) to identify and measure all the metabolites derived from LA and ALA. Additionally, we employed the described methodology to analyze human serum samples obtained before and after whole-body vibration exercise training. The results indicated an increase in some of the LA and ALA LMs that have beneficial effects in regulating the cardiovascular system.

Quantifying ABCA1/apoA-1 Signaling Pathways with AFM Imaging and Lipidomic Analysis.

The role of lipid metabolic pathways in the pathophysiology of primary open-angle glaucoma (POAG) has been thoroughly elucidated, with pathways involved in lipid-related disorders such as hypercholesterolemia and hyperlipoprotein accumulation being of particular interest. The ABCA1/apoA-1 transduction pathway moderates reverse cholesterol transport (RCT), facilitating the transport of free cholesterol (FC) and phospholipids (PL) and preventing intracellular lipid aggregates in retinal ganglion cells (RGCs) due to excess FCs and PLs. A deficiency of ABCA1 transporters, and thus, dysregulation of the ABCA1/apoA-1 transduction pathway, may potentiate cellular lipid accumulation, which affects the structural and mechanical features of the cholesterol-rich RGC membranes. Atomic force microscopy (AFM) is a cutting-edge imaging technique suitable for imaging topographical surfaces of a biological specimen and determining its mechanical properties and structural features. The versatility and precision of this technique may prove beneficial in understanding the effects of ABCA1/apoA-1 pathway downregulation and decreased cholesterol efflux in RGCs and their membranes. In this protocol, ABCA1-/- RGC mouse models are prepared over the course of 3 days and are then compared with non-knockout ABCA1 RGC mouse models through AFM imaging of topographical surfaces to examine the difference in membrane dynamics of knockout vs. non-knockout models. Intracellular and extracellular levels of lipids are quantified through high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS).

Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels.

Glycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò-Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.

Using the yeast vacuole as a system to test the lipidic drivers of membrane heterogeneity in living cells.

The biophysical drivers of membrane lateral heterogeneity, often termed lipid rafts, have been largely explored using synthetic liposomes or mammalian plasma membrane-derived giant vesicles. Yeast vacuoles, an organelle comparable to mammalian lysosomes, is the only in vivo system that shows stable micrometer scale phase separation in unperturbed cells. The ease of manipulating lipid metabolism in yeast makes this a powerful system for identifying lipids involved in the onset of vacuole membrane heterogeneity. Vacuole domains are induced by stationary stage growth and nutritional starvation, during which they serve as a docking and internalization site for lipid droplet energy stores. Here we describe methods for characterizing vacuole phase separation, its physiological function, and its lipidic drivers. First, we detail methodologies for robustly inducing vacuole domain formation and quantitatively characterizing during live cell imaging experiments. Second, we detail a new protocol for biochemical isolation of stationary stage vacuoles, which allows for lipidomic dissection of membrane phase separation. Third, we describe biochemical techniques for analyzing lipid droplet internalization in vacuole domains. When combined with genetic or chemical perturbations to lipid metabolism, these methods allow for systematic dissection of lipid composition in the structure and function of ordered membrane domains in living cells.

Ammonium bicarbonate buffers combined with hybrid surface technology columns improve the peak shape of strongly tailing lipids.

BACKGROUND: Lipids such as phosphatidic acids (PAs) and cardiolipins (CLs) present strongly tailing peaks in reversed phase liquid chromatography, which entails low detectability. They are usually analyzed by hydrophilic interaction liquid chromatography (HILIC), which hampers high-throughput lipidomics. Thus, there is a great need for improved analytical methods in order to obtain a broader coverage of the lipidome in a single chromatographic method. We investigated the effect of ammonium bicarbonate (ABC) on peak asymmetry and detectability, in comparison with ammonium formate (AFO) on both a conventional BEH C18 column and an HST-CSH C18 column. RESULTS: The combination of 2.5 mM ABC buffer pH 8 with an HST-CSH C18 column produced significantly improved results, reducing the asymmetry factor at 10 % peak height of PA 16:0/18:1 from 8.4 to 1.6. Furthermore, on average, there was up to a 54-fold enhancement in the peak height of its [M - H]- ion compared to AFO and the BEH C18 column. We confirmed this beneficial effect on other strongly tailing lipids, with accessible phosphate moieties e.g., cardiolipins, phosphatidylinositol phosphate, phosphatidylinositol bisphosphate, phosphorylated ceramide and phosphorylated sphingosine. Furthermore, we found an increased detectability of phospho- and sphingolipids up to 28 times in negative mode when using an HST-CSH C18 column. The method was successfully applied to mouse liver samples, where previously undetected endogenous phospholipids could be analyzed with improved chromatographic separation. SIGNIFICANCE: In conclusion, the use of 2.5 mM ABC substantially improved the peak shape of PAs and enhanced the detectability of the lipidome in negative mode on an RPLC-ESI-Q-TOF-MS system on both BEH C18 and HST-CSH C18 columns. This method provides a wider coverage of the lipidome with one single injection for future lipidomic applications in negative mode.

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.

BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

Lipidomics profile and volatile compounds of squids (Illex argentinus, Ommastrephes Bartram and Dosidicus gigas) in the Argentine, North Pacific Ocean, Equator and Peru by UPLC-triple TOF-MS and HS-SPME-GC-O-MS.

Comprehensive lipid and volatile compound analyses were performed with squids collected from four varied geographical locations to discriminate the regional characteristics. A total of 1442 lipid molecules and 110 volatiles were detected in the squid muscle samples. There were significant differences in the lipid profiles between Argentine squid (Illex argentinus, AGT), North Pacific Ocean squid (Ommastrephes Bartram, NPO), Equatorial squid (Dosidicus gigas, EQ), and Peruvian squid (Dosidicus gigas, PR) muscle. Phosphatidylcholines (14.64%), triacylglycerols (12.42%), and ceramides (10.97%) were the main lipid components. The contents of polyunsaturated fatty acid in phospholipids and in glycerolipids were 30.35-52.05% and 18.11-25.15%, respectively. The volatiles in squids exhibited significant regional variation; 1-pentanol and 1-octanol, 2-ethyl-1-hexanol and terpinen-4-ol, 2,7-ethyl-1-hexanol, 3-methy-1-butanol and 2-propyl-1-pentanol were identified as characteristic flavor compounds in AGT, NPO, EQ, and PR, respectively. Sphingomyelin, phosphatidylserine, phosphatidylethanolamine, and ceramide were strongly correlated with volatiles in squid muscle. Our study is a reference for the lipid nutritional value and flavor compounds of squids.

High coverage of targeted lipidomics revealed lipid changes in the follicular fluid of patients with insulin-resistant polycystic ovary syndrome and a positive correlation between plasmalogens and oocyte quality.

Background: Polycystic ovary syndrome with insulin resistance (PCOS-IR) is the most common endocrine and metabolic disease in women of reproductive age, and low fertility in PCOS patients may be associated with oocyte quality; however, the molecular mechanism through which PCOS-IR affects oocyte quality remains unknown. Methods: A total of 22 women with PCOS-IR and 23 women without polycystic ovary syndrome (control) who underwent in vitro fertilization and embryo transfer were recruited, and clinical information pertaining to oocyte quality was analyzed. Lipid components of follicular fluid (FF) were detected using high-coverage targeted lipidomics, which identified 344 lipid species belonging to 19 lipid classes. The exact lipid species associated with oocyte quality were identified. Results: The number (rate) of two pronuclear (2PN) zygotes, the number (rate) of 2PN cleaved embryos, and the number of high-quality embryos were significantly lower in the PCOS-IR group. A total of 19 individual lipid classes and 344 lipid species were identified and quantified. The concentrations of the 19 lipid species in the normal follicular fluid (control) ranged between 10-3 mol/L and 10-9 mol/L. In addition, 39 lipid species were significantly reduced in the PCOS-IR group, among which plasmalogens were positively correlated with oocyte quality. Conclusions: This study measured the levels of various lipids in follicular fluid, identified a significantly altered lipid profile in the FF of PCOS-IR patients, and established a correlation between poor oocyte quality and plasmalogens in PCOS-IR patients. These findings have contributed to the development of plasmalogen replacement therapy to enhance oocyte quality and have improved culture medium formulations for oocyte in vitro maturation (IVM).

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.