Clusters of adipose tissue dysfunction in adults with type 2 diabetes identify those with worse lipidomic profile despite similar glycaemic control.

AIMS: To investigate clusters of adipose tissue dysfunction, that is, with adipose tissue insulin resistance (ADIPO-IR) and large waist circumference (WC), identify a worse lipidomic profile characterised by a high proportion of lipids rich in saturated fatty acids (SFA). MATERIALS AND METHODS: Hierarchical clustering based on WC and ADIPO-IR (calculated as fasting plasma non-esterified fatty acids times fasting plasma insulin, FFA×INS), was performed in 192 adults with overweight/obesity and type 2 diabetes (T2D) treated with metformin (HbA1c = 7.8%). Free fatty acid composition and lipidomic profile were measured by mass spectrometry (GC-MS and LC-MSQTOF). Indexes of fatty acid desaturation (stearoyl-coA desaturase-1 activity, SCD116 = palmitoleic acid/palmitic acid and SCD118 = oleic acid/stearic acid) and of insulin resistance (HOMA-IR) were also calculated. RESULTS: Three clusters were identified: CL1 (ADIPO-IR = 4.9 ± 2.4 and WC = 96±7 cm, mean ± SD), CL2 (ADIPO-IR = 6.5 ± 2.5 and WC = 114 ± 7 cm), and CL3 (ADIPO-IR = 15.0 ± 4.7 and WC = 107 ± 8 cm). Insulin concentrations, ADIPO-IR, and HOMA-IR significantly increased from CL1 to CL3 (all p < 0.001), while fasting glucose concentrations, HbA1c, dietary lipids and caloric intake were similar. Moreover, CL3 showed significantly higher concentrations of monounsaturated free fatty acids, oleic and palmitoleic acids, triglycerides (TAG) rich in saturated FA and associated with de novo lipogenesis (i.e., TAG 46-50), higher SCD116, SCD118, ceramide (d18:0/18:0), and phosphatidylcholine aa(36:5) compared with CL1/CL2 (all p < 0.005). CONCLUSIONS: High ADIPO-IR and large WC identify a worse lipid profile in T2D characterised by complex lipids rich in SFA, likely due to de novo synthesis given higher plasma monounsaturated FFA and increased desaturase activity indexes. REGISTRATION NUMBER TRIAL: ID NCT00700856 https://clinicaltrials.gov.

Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome.

Objective: To identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods. Methods: Plasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups. Biomarkers were selected using support vector machine recursive feature elimination (SVM-RFE), random forest (rf), and least absolute shrinkage and selection operator (LASSO) regression, and the performance of two biomarker panels was compared across five machine learning models. Results: In the OPLS-DA models, 50 and 89 lipid metabolites were associated with pre-MetS and MetS patients, respectively. Further machine learning identified two sets of plasma metabolites composed of PS(38:3), DG(16:0/18:1), and TG(16:0/14:1/22:6), TG(16:0/18:2/20:4), and TG(14:0/18:2/18:3), which were used as biomarkers for the pre-MetS and MetS discrimination models in this study. Conclusion: In the initial lipidomics analysis of pre-MetS and MetS, we identified relevant lipid features primarily linked to insulin resistance in key biochemical pathways. Biomarker panels composed of lipidomics components can reflect metabolic changes across different stages of MetS, offering valuable insights for the differential diagnosis of pre-MetS and MetS.

Shotgun Lipidomic Profiling of Sebum Lipids via Photocatalyzed Paternò-Büchi Reaction and Ion Mobility-Mass Spectrometry.

Sebum lipids are composed of nonpolar lipids, and they pose challenges for mass spectrometry-based analysis due to low ionization efficiency and the existence of numerous isomers and isobars. To address these challenges, we have developed ethyl 2-oxo-2-(pyridine-3-yacetate as a charge-tagging Paternò-Büchi reagent and Michler's ketone as a highly efficient photocatalyst, achieving ∼90% conversion for C═C derivatization under 440 nm LED irradiation. This derivatization, when coupled with electrospray ionization-tandem mass spectrometry, boosts the detection of sebum lipids and pinpoints C═C location in a chain-specific fashion. Identification and quantitation of isomers are readily achieved for wax esters, a class of underexplored sebum lipids, which have C═C bonds distributed in fatty alcohol and fatty acyl chains. A shotgun analysis workflow has been developed by pairing the offline PB derivatization with cyclic ion mobility spectrometry-mass spectrometry. Besides the dominant n-10 C═C location in unsaturated wax esters, profiling of low abundance isomers, including the rarely reported n-7 and n-13 locations, is greatly enhanced due to separations of C═C diagnostic ions by ion mobility. Over 900 distinct lipid structures from human sebum lipid extract have been profiled at the chain-specific C═C level, including wax esters (500), glycerolipids (393), and cholesterol esters (22), far more exceeding previous reports. Overall, we have developed a fast and comprehensive lipidomic profiling tool for sebum samples, a type of noninvasive biofluids holding potential for the discovery of disease markers in distal organs.

The identification of novel schizophrenia-related metabolites using untargeted lipidomics.

Human lipidome still remains largely unexplored among Chinese schizophrenia patients. We aimed to identify novel lipid molecules associated with schizophrenia and cognition among schizophrenia patients. The current study included 96 male schizophrenia patients and 96 gender-matched healthy controls. Untargeted lipidomics profiling was conducted among all participants. Logistic regression models were used to assess metabolite associations with schizophrenia. We further assessed the incremental predictive value of identified metabolites beyond conventional risk factors on schizophrenia status. In addition, identified metabolites were tested for association with cognitive function among schizophrenia patients using linear regression models. A total of 34 metabolites were associated with schizophrenia. Addition of these identified metabolites to age, body mass index, smoking, and education significantly increased the risk reclassification of schizophrenia. Among the schizophrenia-related metabolites, 10 were further associated with cognition in schizophrenia patients, including four metabolites associated with immediate memory, two metabolites associated with delayed memory, three metabolites associated with visuospatial, four metabolites associated with language, one metabolite associated with attention, and two metabolites associated with the total score. Our findings provide novel insights into the biological mechanisms of schizophrenia, suggesting that lipid metabolites may serve as potential diagnostic or therapeutic targets of schizophrenia.

Lipidomic Analysis of Liver and Adipose Tissue in a High-Fat Diet-Induced Non-Alcoholic Fatty Liver Disease Mice Model Reveals Alterations in Lipid Metabolism by Weight Loss and Aerobic Exercise.

Detailed investigation of the lipidome remodeling upon normal weight conditions, obesity, or weight loss, as well as the influence of physical activity, can help to understand the mechanisms underlying dyslipidemia in metabolic conditions correlated to the emergence and progression of non-alcoholic fatty liver disease (NAFLD). C57BL/6 male mice were fed a normal diet (ND) or a high-fat diet (HFD) for 20 weeks. Subgroups within the high-fat diet (HFD) group underwent different interventions: some engaged in exercise (HFDex), others were subjected to weight loss (WL) by changing from the HFD to ND, and some underwent a combination of weight loss and exercise (WLex) during the final 8 weeks of the 20-week feeding period. To support our understanding, not only tissue-specific lipid remodeling mechanisms but also the cross-talk between different tissues and their impact on the systemic regulation of lipid metabolism are essential. Exercise and weight loss-induced specific adaptations in the liver and visceral adipose tissue lipidomes of mice were explored by the UPLC-TOF-MS/MS untargeted lipidomics methodology. Lipidomic signatures of ND and HFD-fed mice undergoing weight loss were compared with animals with and without physical exercise. Several lipid classes were identified as contributing factors in the discrimination of the groups by multivariate analysis models, such as glycerolipids, glycerophospholipids, sphingolipids, and fatty acids, with respect to liver samples, whereas triglycerides were the only lipid class identified in visceral adipose tissue. Lipids found to be dysregulated in HFD animals are related to well-established pathways involved in the biosynthesis of PC, PE, and TG metabolism. These show a reversing trend back to basic levels of ND when animals change to a normal diet after 12 weeks, whereas the impact of exercise, though in some cases it slightly enhances the reversing trend, is not clear.

The impact of lipidome on breast cancer: a Mendelian randomization study.

OBJECTIVE: This study aims to investigate the association between specific lipidomes and the risk of breast cancer (BC) using the Two-Sample Mendelian Randomization (TSMR) approach and Bayesian Model Averaging Mendelian Randomization (BMA-MR) method. METHOD: The study analyzed data from large-scale GWAS datasets of 179 lipidomes to assess the relationship between lipidomes and BC risk across different molecular subtypes. TSMR was employed to explore causal relationships, while the BMA-MR method was carried out to validate the results. The study assessed heterogeneity and horizontal pleiotropy through Cochran's Q, MR-Egger intercept tests, and MR-PRESSO. Moreover, a leave-one-out sensitivity analysis was performed to evaluate the impact of individual single nucleotide polymorphisms on the MR study. RESULTS: By examining 179 lipidome traits as exposures and BC as the outcome, the study revealed significant causal effects of glycerophospholipids, sphingolipids, and glycerolipids on BC risk. Specifically, for estrogen receptor-positive BC (ER+ BC), phosphatidylcholine (P < 0.05) and phosphatidylinositol (OR: 0.916-0.966, P < 0.05) within glycerophospholipids play significant roles, along with the importance of glycerolipids (diacylglycerol (OR = 0.923, P < 0.001) and triacylglycerol, OR: 0.894-0.960, P < 0.05)). However, the study did not observe a noteworthy impact of sphingolipids on ER+BC. In the case of estrogen receptor-negative BC (ER- BC), not only glycerophospholipids, sphingolipids (OR = 1.085, P = 0.008), and glycerolipids (OR = 0.909, P = 0.002) exerted an influence, but the protective effect of sterols (OR: 1.034-1.056, P < 0.05) was also discovered. The prominence of glycerolipids was minimal in ER-BC. Phosphatidylethanolamine (OR: 1.091-1.119, P < 0.05) was an important causal effect in ER-BC. CONCLUSIONS: The findings reveal that phosphatidylinositol and triglycerides levels decreased the risk of BC, indicating a potential protective role of these lipid molecules. Moreover, the study elucidates BC's intricate lipid metabolic pathways, highlighting diverse lipidome structural variations that may have varying effects in different molecular subtypes.

Lipidomics analysis unveils the dynamic alterations of lipid degradation in rice bran during storage.

Recent explorations into rice bran oil (RBO) have highlighted its potential, owing to an advantageous fatty acid profile in the context of health and nutrition. Despite this, the susceptibility of rice bran lipids to oxidative degradation during storage remains a critical concern. This study focuses on the evolution of lipid degradation in RBO during storage, examining the increase in free fatty acids (FFAs), the formation of oxylipids, and the generation of volatile secondary oxidation products. Our findings reveal a substantial rise in FFA levels, from 109.55 to 354.06 mg/g, after 14 days of storage, highlighting significant lipid deterioration. Notably, key oxylipids, including 9,10-EpOME, 12,13(9,10)-DiHOME, and 13-oxoODE, were identified, with a demonstrated positive correlation between total oxylipids and free polyunsaturated fatty acids (PUFAs), specifically linoleic acid (LA) and α-linolenic acid (ALA). Furthermore, the study provides a detailed analysis of primary volatile secondary oxidation products. The insights gained from this study not only sheds light on the underlying mechanisms of lipid rancidity in rice bran but also offers significant implications for extending the shelf life and preserving the nutritional quality of RBO, aligning with the increasing global interest in this high-quality oil.

Concomitant investigation of crustacean amphipods lipidome and metabolome during the molting cycle by Zeno SWATH data-independent acquisition coupled with electron activated dissociation and machine learning.

BACKGROUND: DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) initially developed for proteomics studies and recently emerging in metabolomics and lipidomics. It provides a comprehensive and unbiased coverage of molecules with improved reproducibility and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field. RESULTS: DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to characterize molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified significant features. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra database annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness. SIGNIFICANCE: Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing enhances detection sensitivity and targeted fragmentation with EAD in positive polarity provides orthogonal fragmentation information. In our study, Zeno-DIA and EAD thereby facilitated a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying informative biomarkers on the health status of an environmental sentinel species.

Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS.

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

Identification of multiple plasma lipids as diagnostic biomarkers of hypercholesterolemia and the underlying mechanisms based on pseudo-targeted lipidomics.

RATIONALE: Hypercholesterolemia is an important risk factor for cardiovascular diseases and death. This study performed pseudo-targeted lipidomics to identify differentially expressed plasma lipids in hypercholesterolemia, to provide a scientific basis for the diagnosis and pathogenesis of hypercholesterolemia. METHODS: Pseudo-targeted lipidomic analyses of plasma lipids from 20 patients with hypercholesterolemia and 20 normal control subjects were performed using liquid chromatography-mass spectrometry. Differentially expressed lipids were identified by principal component analysis and orthogonal partial least squares discriminant analysis. Receiver operating characteristic curves were used to identify differentially expressed lipids with high diagnostic value. The Kyoto Encyclopedia of Genes and Genomes pathway database was used to identify enriched metabolic pathways. RESULTS: We identified 13 differentially expressed lipids in hypercholesterolemia using variable importance of projection > 1 and p < 0.05 as threshold parameters. The levels of eight sphingomyelins and cholesterol sulfate were higher and those of three triacylglycerols and lysophosphatidylcholine were reduced in hypercholesterolemia. Seven differentially expressed plasma lipids showed high diagnostic value for hypercholesterolemia. Functional enrichment analyses showed that pathways related to necroptosis, sphingolipid signaling, sphingolipid metabolism, and steroid hormone biosynthesis were enriched. CONCLUSIONS: This pseudo-targeted lipidomics study demonstrated that multiple sphingomyelins and cholesterol sulfate were differentially expressed in the plasma of patients with hypercholesterolemia. We also identified seven plasma lipids, including six sphingomyelins and cholesterol sulfate, with high diagnostic value.

Proteomic and Lipidomic Profiling of Calves Experimentally Co-Infected with Influenza D Virus and Mycoplasma bovis: Insights into the Host-Pathogen Interactions.

The role of Influenza D virus (IDV) in bovine respiratory disease remains unclear. An in vivo experiment resulted in increased clinical signs, lesions, and pathogen replication in calves co-infected with IDV and Mycoplasma bovis (M. bovis), compared to single-infected calves. The present study aimed to elucidate the host-pathogen interactions and profile the kinetics of lipid mediators in the airways of these calves. Bronchoalveolar lavage (BAL) samples collected at 2 days post-infection (dpi) were used for proteomic analyses by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, lipidomic analyses were performed by LC-MS/MS on BAL samples collected at 2, 7 and 14 dpi. Whereas M. bovis induced the expression of proteins involved in fibrin formation, IDV co-infection counteracted this coagulation mechanism and downregulated other acute-phase response proteins, such as complement component 4 (C4) and plasminogen (PLG). The reduced inflammatory response against M. bovis likely resulted in increased M. bovis replication and delayed M. bovis clearance, which led to a significantly increased abundance of oxylipids in co-infected calves. The identified induced oxylipids mainly derived from arachidonic acid; were likely oxidized by COX-1, COX-2, and LOX-5; and peaked at 7 dpi. This paper presents the first characterization of BAL proteome and lipid mediator kinetics in response to IDV and M. bovis infection in cattle and raises hypotheses regarding how IDV acts as a co-pathogen in bovine respiratory disease.

MALDI-MSI-LC-MS/MS Workflow for Single-Section Single Step Combined Proteomics and Quantitative Lipidomics.

We introduce a novel approach for comprehensive molecular profiling in biological samples. Our single-section methodology combines quantitative mass spectrometry imaging (Q-MSI) and a single step extraction protocol enabling lipidomic and proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis on the same tissue area. The integration of spatially correlated lipidomic and proteomic data on a single tissue section allows for a comprehensive interpretation of the molecular landscape. Comparing Q-MSI and Q-LC-MS/MS quantification results sheds new light on the effect of MSI and related sample preparation. Performing MSI before Q-LC-MS on the same tissue section led to fewer protein identifications and a lower correlation between lipid quantification results. Also, the critical role and influence of internal standards in Q-MSI for accurate quantification is highlighted. Testing various slide types and the evaluation of different workflows for single-section spatial multiomics analysis emphasized the need for critical evaluation of Q-MSI data. These findings highlight the necessity for robust quantification methods comparable to current gold-standard LC-MS/MS techniques. The spatial information from MSI allowed region-specific insights within heterogeneous tissues, as demonstrated for glioblastoma multiforme. Additionally, our workflow demonstrated the efficiency of a single step extraction for lipidomic and proteomic analyses on the same tissue area, enabling the examination of significantly altered proteins and lipids within distinct regions of a single section. The integration of these insights into a lipid-protein interaction network expands the biological information attainable from a tissue section, highlighting the potential of this comprehensive approach for advancing spatial multiomics research.

Comparative lipidome study of maternal plasma, milk, and lamb plasma in sheep.

Lipids play a critical role in neonate development and breastmilk is the newborn's major source of lipids. Milk lipids directly influence the neonate plasma lipid profile. The milk lipidome is dynamic, influenced by maternal factors and related to the maternal plasma lipidome. The close inter-relationship between the maternal plasma, milk and neonate plasma lipidomes is critical to understanding maternal-child health and nutrition. In this exploratory study, lipidomes of blood and breast milk from Suffolk sheep and matched lamb blood (n = 13), were profiled on day 34 post birth by untargeted mass spectrometry. Comparative multivariate analysis of the three matrices identified distinct differences in lipids and class of lipids amongst them. Paired analysis identified 346 differential lipids (DL) and 31 correlated lipids (CL) in maternal plasma and milk, 340 DL and 32 CL in lamb plasma and milk and 295 DL and 16 CL in maternal plasma and lamb plasma. Conversion of phosphatidic acid to phosphatidyl inositol was the most active pathway in lamb plasma compared to maternal plasma. This exploratory study illustrates the partitioning of lipids across maternal plasma, milk and lamb plasma and the dynamic relationship between them, reiterating the need to study these three matrices as one biological system.

Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus.

BACKGROUND: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. METHODS: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. RESULTS: A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. CONCLUSIONS: Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Lipidome Unsaturation Affects the Morphology and Proteome of the Drosophila Eye.

Organisms respond to dietary and environmental challenges by altering the molecular composition of their glycerolipids and glycerophospholipids (GPLs), which may favorably adjust the physicochemical properties of lipid membranes. However, how lipidome changes affect the membrane proteome and, eventually, the physiology of specific organs is an open question. We addressed this issue in Drosophila melanogaster, which is not able to synthesize sterols and polyunsaturated fatty acids but can acquire them from food. We developed a series of semisynthetic foods to manipulate the length and unsaturation of fatty acid moieties in GPLs and singled out proteins whose abundance is specifically affected by membrane lipid unsaturation in the Drosophila eye. Unexpectedly, we identified a group of proteins that have muscle-related functions and increased their abundances under unsaturated eye lipidome conditions. In contrast, the abundance of two stress response proteins, Turandot A and Smg5, is decreased by lipid unsaturation. Our findings could guide the genetic dissection of homeostatic mechanisms that maintain visual function when the eye is exposed to environmental and dietary challenges.

Effects of Konjac Glucomannan on Weight Management and Liver Health: Insights from Liver Lipidomics in Obese and Nonobese Mice.

Konjac glucomannan (KGM) is a water-soluble dietary fiber and is used for weight management. However, there is a lack of research on KGM for weight management in nonobese groups and the effects of high-dose KGM supplementation on liver function. This study investigated the metabolic responses to KGM intervention in obese and nonobese mice and explored the underlying mechanisms based on lipidomics. The findings demonstrated that KGM supplementation decreased body weight and mitigated lipid metabolism disorders at the mRNA and protein levels in obese mice. In contrast, no significant impact on these parameters was observed in nonobese mice. Interestingly, KGM had a more significant impact on remodeling hepatic lipid composition in obese mice compared to nonobese mice, leading to reducing harmful lipids and increasing beneficial lipids. However, high-dose KGM increased the risk of hepatocyte bile acid toxicity in obese mice and did not promote liver antioxidant status in nonobese mice. In summary, this study identified distinct metabolic responses to KGM intervention between obese and nonobese mice, providing insights for weight management using KGM.

Dissecting new lipids and their composition in herbal tea using untargeted LC/MS.

Herbal teas and beverages have gained global attention because they are rich in natural bioactive compounds, which are known to have diverse biological effects, including antioxidant and anticarcinogenic properties. However, the lipidomic profiles of herbal teas remain unclear. In this study, we applied an untargeted lipidomics approach using high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry to comprehensively profile, compare, and identify unknown lipids in four herbal teas: dokudami, kumazasa, sugina, and yomogi. A total of 341 molecular species from five major classes of lipids were identified. Multivariate principal component analysis revealed distinct lipid compositions for each of the herbs. The fatty acid α-linolenic acid (FA 18:3) was found to be abundant in kumazasa, whereas arachidonic acid (FA 20:4) was the most abundant in sugina. Interestingly, novel lipids were discovered for the first time in plants; specifically, short-chain fatty acid esters of hydroxy fatty acids (SFAHFAs) with 4-hydroxy phenyl nonanoic acid as the structural core. This study provides insight into the lipidomic diversity and potential bioactive lipid components of herbal teas, offering a foundation for further research into their health-promoting properties and biological significance.

Lipidomics analysis of rice bran during storage unveils mechanisms behind dynamic changes in functional lipid molecular species.

Rice bran, recognized for its rich lipids and health-beneficial bioactive compounds, holds considerable promise in applications such as rice bran oil production. However, its susceptibility to lipid hydrolysis and oxidation during storage presents a significant challenge. In response, we conducted an in-depth metabolic profiling of rice bran over a storage period of 14 days. We focused on the identification of bioactive compounds and functional lipid species (25 acylglycerols and 53 phospholipids), closely tracking their dynamic changes over time. Our findings revealed significant reductions in these lipid molecular species, highlighting the impact of rancidity processes. Furthermore, we identified 19 characteristic lipid markers and elucidated that phospholipid and glycerolipid metabolism were key metabolic pathways involved. By shedding light on the mechanisms driving lipid degradation in stored rice bran, our study significantly advanced the understanding of lipid stability. These information provided valuable insights for countering rancidity and optimizing rice bran preservation strategies.