Serum Lipidome Research Articles

Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, characterized by rapid progression, metastasis, and difficulty in diagnosis. However, there are no effective liquid-based testing methods available for PDAC detection. Here we introduce a minimally invasive approach that uses machine learning (ML) and lipidomics to detect PDAC. Through greedy algorithm and mass spectrum feature selection, we optimized 17 characteristic metabolites as detection features and developed a liquid chromatography-mass spectrometry-based targeted assay. In this study, 1033 patients with PDAC at various stages were examined. This approach has achieved 86.74% accuracy with an area under curve (AUC) of 0.9351 in the large external validation cohort and 85.00% accuracy with 0.9389 AUC in the prospective clinical cohort. Accordingly, single-cell sequencing, proteomics, and mass spectrometry imaging were applied and revealed notable alterations of selected lipids in PDAC tissues. We propose that the ML-aided lipidomics approach be used for early detection of PDAC.

Toxicokinetics of Arenobufagin and its Cardiotoxicity Mechanism Exploration Based on Lipidomics and Proteomics Approaches in Rats.

Arenobufagin (ArBu), one of the main active bufadienolides of toad venom with cardiotonic effect, analgesic effect, and outstanding anti-tumor potentiality, is also a potential cardiotoxic component. In the present study, the cardiac effect of ArBu and its underlying mechanism were explored by integrating data such as heart rates, toxicokinetics, myocardial enzyme and brain natriuretic peptide (BNP) activity, pathological sections, lipidomics and proteomics. Under different doses, the cardiac effects turned out to be different. The oral dose of 60 mg/kg of ArBu sped up the heart rate. However, 120 mg/kg ArBu mainly reduced the heart rate. Over time, they all returned to normal, consisting of the trend of ArBu concentration-time curve. High concentrations of myocardial enzymes and BNP indicated that ArBu inhibited or impaired the cardiac function of rats. Pathological sections of hearts also showed that ArBu caused myocardial fiber disorder and rupture, in which the high-dose group was more serious. At the same time, serum and heart tissue lipidomics were used to explore the changes in body lipid metabolism under different doses. The data indicated a larger difference in the high-dose ArBu group. There were likewise many significant differences in the proteomics of the heart. Furthermore, a multi-layered network was used to integrate the above information to explore the potential mechanism. Finally, 4 proteins that were shown to be significantly and differentially expressed were validated by targeted proteomics using parallel reaction monitoring (PRM) analysis. Our findings indicated that ArBu behaved as a bidirectional regulation of the heart. The potential mechanism of cardiac action was revealed with the increased dose, which provided a useful reference for the safety of clinical application of ArBu.

Serum Metabolomic and Lipidomic Profiling Reveals Novel Biomarkers of Efficacy for Benfotiamine in Alzheimer's Disease.

Serum metabolomics and lipidomics are powerful approaches for discovering unique biomarkers in various diseases and associated therapeutics and for revealing metabolic mechanisms of both. Treatment with Benfotiamine (BFT), a thiamine prodrug, for one year produced encouraging results for patients with mild cognitive impairment and mild Alzheimer’s disease (AD). In this study, a parallel metabolomics and lipidomics approach was applied for the first exploratory investigation on the serum metabolome and lipidome of patients treated with BFT. A total of 315 unique metabolites and 417 lipids species were confidently identified and relatively quantified. Rigorous statistical analyses revealed significant differences between the placebo and BFT treatment groups in 25 metabolites, including thiamine, tyrosine, tryptophan, lysine, and 22 lipid species, mostly belonging to phosphatidylcholines. Additionally, 10 of 11 metabolites and 14 of 15 lipid species reported in previous literature to follow AD progression changed in the opposite direction to those reported to reflect AD progression. Enrichment and pathway analyses show that significantly altered metabolites by BFT are involved in glucose metabolism and biosynthesis of aromatic amino acids. Our study discovered that multiple novel biomarkers and multiple mechanisms that may underlie the benefit of BFT are potential therapeutic targets in AD and should be validated in studies with larger sample sizes.

Lipidomic and Metabolomic Signature of Progression of Chronic Kidney Disease in Patients with Severe Obesity.

Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study would justify the use of comprehensive mass spectrometry-based lipidomics to measure other lipids aside from conventional lipid profiles and to validate possible early markers of risk of CKD in patients with severe obesity.

HR-MS Based Untargeted Lipidomics Reveals Characteristic Lipid Signatures of Wilson's Disease.

Background and Aims: The diagnosis of Wilson’s disease (WD) is challenging by clinical or genetic criteria. A typical early pathological change of WD is the increased liver lipid deposition and lowered serum triglyceride (TG). Therefore, the contents of serum lipids may provide evidence for screening of biomarkers for WD. Methods: 34 WD patients, 31 WD relatives, and 65 normal controls were enrolled in this study. Serum lipidomics data was acquired by an ultra-high-performance liquid chromatography high-resolution mass spectrometry system, and the data were analyzed by multivariate statistical methods. Results: Of all 510 identified lipids, there are 297 differential lipids between the WD and controls, 378 differential lipids between the relatives and controls, and 119 differential lipids between the patients and relatives. In WD, the abundances of most saturated TG were increased, whereas other unsaturated lipids decreased, including phosphatidylcholine (PC), sphingomyelin (SM), lysophosphatidylcholine (LPC), ceramide (Cer), and phosphatidylserine (PS). We also found many serum lipid species may be used as biomarkers for WD. The areas under the receiver operating characteristic curve (AUC) of PS (35:0), PS (38:5), and PS (34:0) were 0.919, 0.843, and 0.907. The AUCs of TG (38:0) and CerG1 (d42:2) were 0.948 and 0.915 and the AUCs of LPC (17:0) and LPC (15:0) were 0.980 and 0.960, respectively. The lipid biomarker panel exhibits good diagnostic performance for WD. The correlation networks were built among the different groups and the potential mechanisms of differential lipids were discussed. Interestingly, similar lipid profile of WD is also found in their relatives, which indicated the changes may also related to the mutation of the ATP7B gene. Conclusions: Lipid deregulation is another important hallmark of WD besides the deposition of copper. Our lipidomic results provide new insights into the diagnostic and therapeutic targets of WD.

Link between serum lipid signature and prognostic factors in COVID-19 patients

Although the serum lipidome is markedly affected by COVID-19, two unresolved issues remain: how the severity of the disease affects the level and the composition of serum lipids and whether serum lipidome analysis may identify specific lipids impairment linked to the patients' outcome. Sera from 49 COVID-19 patients were analyzed by untargeted lipidomics. Patients were clustered according to: inflammation (C-reactive protein), hypoxia (Horowitz Index), coagulation state (D-dimer), kidney function (creatinine) and age. COVID-19 patients exhibited remarkable and distinctive dyslipidemia for each prognostic factor associated with reduced defense against oxidative stress. When patients were clustered by outcome (7 days), a peculiar lipidome signature was detected with an overall increase of 29 lipid species, including—among others—four ceramide and three sulfatide species, univocally related to this analysis. Considering the lipids that were affected by all the prognostic factors, we found one sphingomyelin related to inflammation and viral infection of the respiratory tract and two sphingomyelins, that are independently related to patients' age, and they appear as candidate biomarkers to monitor disease progression and severity. Although preliminary and needing validation, this report pioneers the translation of lipidome signatures to link the effects of five critical clinical prognostic factors with the patients' outcomes.

Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma.

BackgroundAs a key precancerous lesion, colorectal advanced adenoma (CAA) is closely related to the occurrence and development of colorectal cancer (CRC). Effective identification of CAA-related biomarkers can prevent CRC morbidity and mortality. Lipids, as an important endogenous substance, have been proved to be involved in the occurrence and development of CRC. Lipidomics is an advanced technique that studies lipid metabolism and biomarkers of diseases. However, there are no lipidomics studies based on large serum samples to explore diagnostic biomarkers for CAA.MethodsAn integrated serum lipid profile from 50 normal (NR) and 46 CAA subjects was performed using ultra-high performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS). Lipidomic data were acquired for negative and positive ionization modes, respectively. Differential lipids were selected by univariate and multivariate statistics analyses. A receiver operator characteristic curve (ROC) analysis was conducted to evaluate the diagnostic performance of differential lipids.ResultsA total of 53 differential lipids were obtained by combining univariate and multivariate statistical analyses (P < 0.05 and VIP > 1). In addition, 12 differential lipids showed good diagnostic performance (AUC > 0.90) for the discrimination of NR and CAA by receiver operating characteristic curve (ROC) analysis. Of them, the performance of PC 44:5 and PC 35:6e presented the outstanding performance (AUC = 1.00, (95% CI, 1.00–1.00)). Moreover, triglyceride (TAG) had the highest proportion (37.74%) as the major dysregulated lipids in the CAA.ConclusionThis is the first study that profiled serum lipidomics and explored lipid biomarkers with good diagnostic ability of CAA to contribute to the early prevention of CRC. Twelve differential lipids that effectively discriminate between NR and CAA serve as the potential diagnostic markers of CAA. An obvious perturbation of TAG metabolism could be involved in the CAA formation.

The altered serum lipidome and its diagnostic potential for Non-Alcoholic Fatty Liver (NAFL)-associated hepatocellular carcinoma.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is affecting more people globally. Indeed, NAFLD is a spectrum of metabolic dysfunctions that can progress to hepatocellular carcinoma (NAFLD-HCC). This development can occur in a non-cirrhotic liver and thus, often lack clinical surveillance. The aim of this study was to develop non-invasive surveillance method for NAFLD-HCC.MethodsUsing comprehensive ultra-high-performance liquid chromatography mass-spectrometry, we investigated 1,295 metabolites in serum from 249 patients. Area under the receiver operating characteristic curve was calculated for all detected metabolites and used to establish their diagnostic potential. Logistic regression analysis was used to establish the diagnostic score.FindingsWe show that NAFLD-HCC is characterised by a complete rearrangement of the serum lipidome, which distinguishes NAFLD-HCC from non-cancerous individuals and other HCC patients. We used machine learning to build a diagnostic model for NAFLD-HCC. We quantified predictive metabolites and developed the NAFLD-HCC Diagnostic Score (NHDS), presenting superior diagnostic potential compared to alpha-fetoprotein (AFP). Patients’ metabolic landscapes show a progressive depletion in unsaturated fatty acids and acylcarnitines during transformation. Upregulation of fatty acid transporters in NAFLD-HCC tumours contribute to fatty acid depletion in the serum.InterpretationNAFLD-HCC patients can be efficiently distinguished by serum metabolic alterations from the healthy population and from HCC patients related to other aetiologies (alcohol and viral hepatitis). Our model can be used for non-invasive surveillance of individuals with metabolic syndrome(s), allowing for early detection of NAFLD-HCC. Therefore, serum metabolomics may provide valuable insight to monitor patients at risk, including morbidly obese, diabetics, and NAFLD patients.FundingThe funding sources for this study had no role in study design, data collection, data analyses, interpretation or writing of the report as it is presented herein.

Nontargeted Serum Lipid Profiling of Nonalcoholic Steatohepatitis by Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry: A Multiplexed Separation Platform for Resolving Ionic Lipids.

New methods are needed for global lipid profiling due to the complex chemical structures and diverse physicochemical properties of lipids. Herein we introduce a robust data workflow to unambiguously select lipid features from serum ether extracts by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS). An iterative three-stage screening strategy is developed for nontargeted lipid analyses when using multiplexed electrophoretic separations coupled to an Orbitrap mass analyzer under negative ion mode. This approach enables the credentialing of 270 serum lipid features annotated based on their accurate mass and relative migration time, including 128 ionic lipids reliably measured (median CV ≈ 13%) in most serum samples (>75%) from nonalcoholic steatohepatitis (NASH) patients (n = 85). A mobility map is introduced to classify charged lipid classes over a wide polarity range with selectivity complementary to chromatographic separations, including lysophosphatidic acids, phosphatidylcholines, phosphatidylinositols, phosphatidylethanolamines, and nonesterified fatty acids (NEFAs). Serum lipidome profiles were also used to differentiate high- from low-risk NASH patients using a k-means clustering algorithm, where elevated circulating NEFAs (e.g., palmitic acid) were associated with increased glucose intolerance, more severe liver fibrosis, and greater disease burden. MSI-NACE-MS greatly expands the metabolome coverage of conventional aqueous-based CE-MS protocols and is a promising platform for large-scale lipidomic studies.

Serum lipids are associated with nonalcoholic fatty liver disease: a pilot case-control study in Mexico

BackgroundNonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and cirrhosis. NAFLD is mediated by changes in lipid metabolism and known risk factors include obesity, metabolic syndrome, and diabetes. The aim of this study was to better understand differences in the lipid composition of individuals with NAFLD compared to controls, by performing direct infusion lipidomics on serum biospecimens from a cohort study of adults in Mexico.MethodsA nested case-control study was conducted with a sample of 98 NAFLD cases and 100 healthy controls who are participating in an on-going, longitudinal study in Mexico. NAFLD cases were clinically confirmed using elevated liver enzyme tests and liver ultrasound or liver ultrasound elastography, after excluding alcohol abuse, and 100 controls were identified as having at least two consecutive normal alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (< 40 U/L) results in a 6-month period, and a normal liver ultrasound elastography result in January 2018. Samples were analyzed on the Sciex Lipidyzer Platform and quantified with normalization to serum volume. As many as 1100 lipid species can be identified using the Lipidyzer targeted multiple-reaction monitoring list. The association between serum lipids and NAFLD was investigated using analysis of covariance, random forest analysis, and by generating receiver operator characteristic (ROC) curves.ResultsNAFLD cases had differences in total amounts of serum cholesterol esters, lysophosphatidylcholines, sphingomyelins, and triacylglycerols (TAGs), however, other lipid subclasses were similar to controls. Analysis of individual TAG species revealed increased incorporation of saturated fatty acyl tails in serum of NAFLD cases. After adjusting for age, sex, body mass index, and PNPLA3 genotype, a combined panel of ten lipids predicted case or control status better than an area under the ROC curve of 0.83.ConclusionsThese preliminary results indicate that the serum lipidome differs in patients with NAFLD, compared to healthy controls, and suggest that assessing the desaturation state of TAGs or a specific lipid panel may be useful clinical tools for the diagnosis of NAFLD.

Serum lipidomics reveals distinct metabolic profiles for asymptomatic hyperuricemic and gout patients.

This study aimed to characterize the systemic lipid profile of patients with asymptomatic hyperuricemia (HUA) and gout using lipidomics, and to find potential underlying pathological mechanisms therefrom. Sera were collected from Affiliated Hospital of Nanjing University of Chinese Medicine as centre 1 (discovery and internal validation sets) and Suzhou Hospital of Traditional Chinese Medicine as centre 2 (external validation set), including 88 normal subjects, 157 HUA and 183 gout patients. Lipidomics was performed byultra high performance liquid chromatography plus Q-Exactive mass spectrometry (UHPLC-Q Exactive MS). Differential metabolites were identifed by both variable importance in the projection ≥1 in orthogonal partial least-squares discriminant analysis mode and false discovery rate adjusted P ≤ 0.05. Biomarkers were found by logistic regression and receiver operating characteristic (ROC) analysis. In the discovery set, a total of 245 and 150 metabolites, respectively, were found for normal subjects vs HUA and normal subjects vs gout. The disturbed metabolites included diacylglycerol, triacylglycerol (TAG), phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, etc. We also found 116 differential metabolites for HUA vs gout. Among them, the biomarker panel of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 could differentiate well between HUA and gout. The area under the receiver operating characteristic ROC curve was 0.8288, the sensitivity was 82% and the specificity was 78%, at a 95% CI 0.747, 0.9106. In the internal validation set, the predictive accuracy of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 panel for differentiation of HUA and gout reached 74.38%, while it was 84.03% in external validation set. We identified serum biomarkers panel that have the potential to predict and diagnose HUA and gout patients.

A Randomized Controlled Dietary Intervention Improved the Serum Lipid Signature towards a Less Atherogenic Profile in Patients with Rheumatoid Arthritis.

Diet is a major modifiable risk factor for cardiovascular disease (CVD). One explanation for this is its effect on specific lipids. However, knowledge on how the lipidome is affected is limited. We aimed to investigate if diet can change the new ceramide- and phospholipid-based CVD risk score CERT2 and the serum lipidome towards a more favorable CVD signature. In a crossover trial (ADIRA), 50 patients with rheumatoid arthritis (RA) had 10 weeks of a Mediterranean-style diet intervention or a Western-style control diet and then switched diets after a 4-month wash-out-period. Five hundred and thirty-eight individual lipids were measured in serum by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Lipid risk scores were analyzed by Wilcoxon signed-rank test or mixed model and lipidomic data with multivariate statistical methods. In the main analysis, including the 46 participants completing ≥1 diet period, there was no significant difference in CERT2 after the intervention compared with the control, although several CERT2 components were changed within periods. In addition, triacylglycerols, cholesteryl esters, phosphatidylcholines, alkylphosphatidylcholines and alkenylphosphatidylcholines had a healthier composition after the intervention compared to after the control diet. This trial indicates that certain dietary changes can improve the serum lipid signature towards a less atherogenic profile in patients with RA.

Anti-TNFα treatment in Crohn's disease: Impact on hepatic steatosis, gut-derived hormones and metabolic status.

An association between Crohn's disease (CD) and hepatic steatosis has been reported. However, the underlying mechanisms of steatosis progression in CD are not clear. Among the most effective CD treatments are agents that inhibit Tumor-Necrosis-Factor (TNF) activity, yet it is unclear why anti-TNFα agents would affect steatosis in CD. Recent studies suggest that microbiome can affect both, CD and steatosis pathogenesis. Therefore, we here analysed a potential relationship between anti-TNF treatment and hepatic steatosis in CD, focusing on the gut-liver axis. This cross-sectional study evaluated patients with established CD, with and without anti-TNFα treatment, analysing serum markers of liver injury, measurement of transient elastography, controlled attenuation parameter (CAP) and MRI for fat detection. Changes in lipid and metabolic profiles were assessed by serum and stool lipidomics and metabolimics. Additionally, we analysed gut microbiota composition and mediators of bile acid (BA) signalling via stool and serum analysis. Patients on anti-TNFα treatment had less hepatic steatosis as assessed by CAP and MRI. Serum FGF19 levels were significantly higher in patients on anti-TNFα therapy and associate with reduced steatosis and increased bowel motility. Neutral lipids including triglycerides were reduced in the serum of patients on anti-TNF treatment. Bacteria involved in BA metabolism and FGF19 regulation, including Firmicutes, showed group-specific alterations with low levels in patients without anti-TNFα treatment. Low abundance of Firmicutes was associated with higher triglyceride levels. Anti-TNFα treatment is associated with reduced steatosis, lower triglyceride levels, alterations in FXR-signalling (eg FGF19) and microbiota composition in CD.

Comprehensive Serum Lipidomics for Detecting Incipient Dementia in Parkinson's Disease.

While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Lipidomics Identified Lyso-Phosphatidylcholine and Phosphatidylethanolamine as Potential Biomarkers for Diagnosis of Laryngeal Cancer.

BackgroundLaryngeal cancer (LaC) remains one of the most common tumors of the respiratory tract with higher incidence in men than in women. The larynx is a small but vital organ on the neck. The dysfunction of the larynx can cause serious health problems such as hoarseness, respiratory distress, and dysphonia. Many lipids (e.g. phospholipid, cholesterol, fatty acid) have been recognized as a crucial role in tumorigenesis. However, the lipid biomarkers are lacking and the lipid molecular pathogenesis of LaC is still unclear.MethodsThis study aims to identify new LaC-related lipid biomarkers used for the diagnosis or early diagnosis of LaC and to uncover their molecular characteristics. Thus, we conducted serum and tissue nontargeted lipidomics study from LaC patients (n = 29) and normal controls (NC) (n = 36) via ultra-high performance liquid chromatography (UHPLC) coupled with high resolution mass spectrometry (HRMS). Multivariate and univariate statistics analyses were used to discriminate LaC patients from NC.ResultsAs expected, a lipid panel including LPC (16:0) and PE (18:0p_20:4) was defined to distinguish the LaC patients from healthy individuals with very high diagnosis performance (area under the curve (AUC) value = 1.000, sensitivity value = 1.000, and specificity value = 1.000). In addition, the levels of Cer, CerG1, SM, PC, PC-O, PE, PI, PS, and ChE in the LaC group significantly increased as compared with the NC group. However, the levels of LPC, LPC-O, LPE, LPE-p, and DG in the LaC group significantly deceased when the one was compared with the NC group. Among significantly changed lipid species, lysophospholipids containing a palmitoyl chain or an arachidonic acid acyl chain remarkably decreased and phospholipids including a palmitoyl chain or an arachidonic acid acyl chain increased in the LaC patients.ConclusionOur results not only indicate that lipidomics is powerful tool to explore abnormal lipid metabolism for the laC, but suggest that lysophospholipids and phospholipids may serve as potential biomarkers for diagnosis of LaC.

Lipidomics study of the therapeutic mechanism of Plantaginis Semen in potassium oxonate-induced hyperuricemia rat

BackgroundPlantaginis Semen has been widely used as folk medicine and health care food against hyperuricemia (HUA) and gout, but its pharmacological mechanism remains unclear. This study investigated the therapeutic mechanism of Plantaginis Semen extract on potassium oxonate -induced HUA rats based on a lipidomics approach.MethodsA model of HUA was established by potassium oxonate intragastric administration. 42 Sprague-Dawley (SD) male rats were randomly divided into the control group, model group, benzbromarone group (10 mg/kg) and three Plantaginis Semen groups (n = 7). The Plantaginis Semen groups were treated orally with Plantaginis Semen, 0.9375, 1.875 or 3.75 g/kg for 28 days. The levels of serum uric acid (UA), creatinine (Cr), triacylglycerol (TG) and tumor necrosis factor-α (TNF-α) were measured using enzyme-linked immunosorbent assay kits. Ultra performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF/MS) was used for the serum lipidomics analysis, multivariate statistical analysis and independent samples t-test were carried out for the pattern recognition and characteristic metabolites identification. The relative levels of critical regulatory factors were determined by quantitative real-time polymerase chain reaction (RT-qPCR).ResultsCompared with the model group, the levels of serum UA, Cr, TG and TNF-α were significantly (p < 0.05) decreased in benzbromarone and three Plantaginis Semen groups. With lipidomics analysis, significant lipid metabolic perturbations were observed in HUA rats, 13 metabolites were identified as potential biomarkers and glycerophospholipid metabolism pathway was most affected. These perturbations were partially restored via treatment of benzbromarone and Plantaginis Semen. Additionally, the mRNA expression levels of urate anion transporter 1 (URAT1) and phosphatidylinositol 3-kinase/protein kinases B (PI3K/Akt) were significantly decreased (p < 0.01) after treatment with benzbromarone and high dose of Plantaginis Semen.ConclusionsPlantaginis Semen had significant effects on anti-HUA, anti-inflammatory and renal protection. It attenuated potassium oxonate-induced HUA through regulation of lipid metabolism disorder.

Lipidomics of Serum and Hippocampus Reveal the Protective Effects of Fermented Soybean Lipid on Rats of Microwave-Induced Cognitive Damage.

Fermented soybean lipids (FSE-C) is an extract enriched in active lipid classes. To explore whether FSE-C can alleviate cognitive damage triggered by the exposure to microwave radiation through regulating lipid metabolism, we employed lipidomic profiling based on a UPLC-MS to investigate differential lipid metabolites in the serum and hippocampus of rats. The results showed that orally administered FSE-C could protect from cognitive damage in microwave-induced rats. Serum lipidomics indicated that FSE-C effectively facilitated the recovery of 43 differential lipid metabolites including 6 phosphatidylcholines (PCs), 5 phosphatidylethanolamines (PEs), 1 phosphatidylinositol, 3 lysophosphatidylcholines (LPCs), 6 lysophosphatidylethanolamines (LPEs), and 22 triglycerides (TGs), which was consistent with the analysis of serum TG levels. Moreover, FSE-C positively coordinated hexacosanoic acid, 2 PCs, 4 sphingomyelins (SMs), and 11 TGs, through the hippocampal lipidomics. Collectively, these findings suggested that phospholipid and TG metabolisms were significantly modified in microwave-exposed rats. TGs may be regarded as potential biomarkers to further investigate and evaluate the roles and functions of FSE-C on the attenuation of cognitive damage induced by microwave radiation.

Extending the Lipidome Coverage by Combining Different Mass Spectrometric Platforms: An Innovative Strategy to Answer Chemical Food Safety Issues.

From a general public health perspective, a strategy combining non-targeted and targeted lipidomics MS-based approaches is proposed to identify disrupted patterns in serum lipidome upon growth promoter treatment in pigs. Evaluating the relative contributions of the platforms involved, the study aims at investigating the potential of innovative analytical approaches to highlight potential chemical food safety threats. Serum samples collected during an animal experiment involving control and treated pigs, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer™ platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The strategy enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation to cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of non-targeted and targeted MS approaches, various compartments of the pig serum lipidome could be explored, including commonly characterised lipids (Lipidyzer™), triglyceride isomers (Triglyceride platform) and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced coverage, level of characterization and applicability.

Identification of diagnostic markers and lipid dysregulation in oesophageal squamous cell carcinoma through lipidomic analysis and machine learning.

Oesophageal cancer (EC) ranks high in both morbidity and mortality. A non-invasive and high-sensitivity diagnostic approach is necessary to improve the prognosis of EC patients. A total of 525 serum samples were subjected to lipidomic analysis. We combined serum lipidomics and machine-learning algorithms to select important metabolite features for the detection of oesophageal squamous cell carcinoma (ESCC), the major subtype of EC in developing countries. A diagnostic model using a panel of selected features was developed and evaluated. Integrative analyses of tissue transcriptome and serum lipidome were conducted to reveal the underlying mechanism of lipid dysregulation. Our optimised diagnostic model with a panel of 12 lipid biomarkers together with age and gender reaches a sensitivity of 90.7%, 91.3% and 90.7% and an area under receiver-operating characteristic curve of 0.958, 0.966 and 0.818 in detecting ESCC for the training cohort, validation cohort and independent validation cohort, respectively. Integrative analysis revealed matched variation trend of genes encoding key enzymes in lipid metabolism. We have identified a panel of 12 lipid biomarkers for diagnostic modelling and potential mechanisms of lipid dysregulation in the serum of ESCC patients. This is a reliable, rapid and non-invasive tumour-diagnostic approach for clinical application.

Metabolic View on Human Healthspan: A Lipidome-Wide Association Study.

As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied ‘omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level.