Common Fatty Markers in Diseases with Dysregulated Lipogenesis

Dysregulated glycerophospholipid metabolism in amygdala may mediate favipiravir-induced anxiety-like behaviors in mice

Favipiravir, the first RNA polymerase inhibitor approved to treat resistant influenza, has been reported to be associated with central nervous system (CNS) side effects, particularly anxiety-like behavior; nevertheless, the underlying mechanism remains largely unknown. In this study, we investigated the effect of favipiravir on the neurobehavior of mice, and combined lipidomics and transcriptomics analysis to explore the mechanism underlying this effect. In behavioral tests, the mice displayed anxiety-like behaviors after oral favipiravir administration (200 mg/kg) for 7 days continuously. By lipidomics analysis, we observed that favipiravir induced a dysregulation of glycerophospholipid metabolism in the amygdala. Moreover, favipiravir significantly reduced the mRNA level of glycerol-3-phosphate acyltransferase 2 (Gpat2), the rate-limiting enzyme of glycerophospholipid synthesis. Notably, favipiravir markedly reduced the levels of docosahexaenoic acid-enriched phosphatidylethanolamine or phosphatidylcholine (DHA-PE/PC) and arachidonic acid-enriched phosphatidylethanolamine or phosphatidylcholine (AA-PE/PC), two components of glycerophospholipids, in the amygdala. The increased expression of phospholipase A2 (Pla2) may attribute to the enhanced release of arachidonic acid (AA) from AA-PE/PC. Furthermore, favipiravir altered neurite morphology and reduced neurophysiological activity in amygdala neurons in vitro. Collectively, dysregulated glycerophospholipid metabolism in the amygdala may contribute to the adverse effect of favipiravir.

Trials and tribulations of statistical significance in biochemistry and omics

Over recent years many statisticians and researchers have highlighted that statistical inference would benefit from a better use and understanding of hypothesis testing, p-values, and statistical significance. We highlight three recommendations in the context of biochemical sciences. First recommendation: to improve the biological interpretation of biochemical data, do not use p-values (or similar test statistics) as thresholded values to select biomolecules. Second recommendation: to improve comparison among studies and to achieve robust knowledge, perform complete reporting of data. Third recommendation: statistical analyses should be reported completely with exact numbers (not as asterisks or inequalities). Owing to the high number of variables, a better use of statistics is of special importance in omic studies.

Oogenesis and lipid metabolism in the deep-sea sponge Phakellia ventilabrum (Linnaeus, 1767)

Sponges contain an astounding diversity of lipids that serve in several biological functions, including yolk formation in their oocytes and embryos. The study of lipid metabolism during reproduction can provide information on food-web dynamics and energetic needs of the populations in their habitats, however, there are no studies focusing on the lipid metabolism of sponges during their seasonal reproduction. In this study, we used histology, lipidome profiling (UHPLC-MS), and transcriptomic analysis (RNA-seq) on the deep-sea sponge Phakellia ventilabrum (Demospongiae, Bubarida), a key species of North-Atlantic sponge grounds, with the goal to (i) assess the reproductive strategy and seasonality of this species, (ii) examine the relative changes in the lipidome signal and the gene expression patterns of the enzymes participating in lipid metabolism during oogenesis. Phakellia ventilabrum is an oviparous and most certainly gonochoristic species, reproducing in May and September in the different studied areas. Half of the specimens were reproducing, generating two to five oocytes per mm2. Oocytes accumulated lipid droplets and as oogenesis progressed, the signal of most of the unsaturated and monounsaturated triacylglycerides increased, as well as of a few other phospholipids. In parallel, we detected upregulation of genes in female tissues related to triacylglyceride biosynthesis and others related to fatty acid beta-oxidation. Triacylglycerides are likely the main type of lipid forming the yolk in P. ventilabrum since this lipid category has the most marked changes. In parallel, other lipid categories were engaged in fatty acid beta-oxidation to cover the energy requirements of female individuals during oogenesis. In this study, the reproductive activity of the sponge P. ventilabrum was studied for the first time uncovering their seasonality and revealing 759 lipids, including 155 triacylglycerides. Our study has ecological and evolutionary implications providing essential information for understanding the molecular basis of reproduction and the origins and formation of lipid yolk in early-branching metazoans.

Adverse Effects of Refeeding on the Plasma Lipidome in Young Individuals With Anorexia Nervosa?

OBJECTIVE

Refeeding is the cornerstone of anorexia nervosa (AN) treatment, but little is known regarding the optimal pace and dietary composition or possible adverse effects of current clinical practices. Plasma lipids may be a moderating factor underlying unfavorable refeeding effects in AN, such as an abnormal central body fat distribution. The objective of this study was to analyze the plasma lipidome in the acutely underweight state of AN before and after refeeding.

METHOD

Using high-throughput quantitative mass spectrometry-based shotgun lipidomics, we measured 13 lipid classes and 204 lipid species or subspecies in the plasma of young female patients with acute AN, before (n = 39) and after (n = 23) short-term weight restoration during an intensive inpatient refeeding program (median body mass index [BMI] increase = 26.4%), in comparison to those in healthy control participants (n = 37).

RESULTS

Before inpatient treatment, patients with AN exhibited increased concentrations of cholesterol and several other lipid classes. After refeeding, multiple lipid classes including cholesterol and ceramides, as well as certain ceramide species previously associated with obesity or overfeeding, showed increased concentrations, and a pattern of shorter and more saturated triacylgycerides emerged. A machine learning model trained to predict BMI based on the lipidomic profiles revealed a sizable overprediction in patients with AN after weight restoration.

CONCLUSION

The results point toward a profound lipid dysregulation with similarities to obesity and other features of the metabolic syndrome after short-term weight restoration. Thus, this study provides evidence for possible short-term adverse effects of current refeeding practices on the metabolic state and should inspire more research on nutritional interventions in AN.

Investigating Global Lipidome Alterations with the Lipid Network Explorer

Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container.

Multi-omics: Opportunities for research on mechanism of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a burdensome global disease. In-depth understanding of its mechanism will help to optimize diagnosis and treatment, which reduces the burden. Multi-omics research has unparalleled advantages in contributing to the overall understanding of the mechanism of this chronic metabolic disease. In the past two decades, the study of multi-omics on T2DM-related intestinal flora perturbation and plasma dyslipidemia has shown tremendous potential and is expected to achieve major breakthroughs. The regulation of intestinal flora in diabetic patients has been confirmed by multiple studies. The use of metagenomics, 16S RNA sequencing, and metabolomics has comprehensively identified the overall changes in the intestinal flora and the metabolic disturbances that could directly or indirectly participate in the intestinal flora-host interactions. Lipidomics combined with other “omics” has characterized lipid metabolism disorders in T2DM. The combined application and cross-validation of multi-omics can screen for dysregulation in T2DM, which will provide immense opportunities to understand the mechanisms behind T2DM.

Circulating Glycerolipids, Fatty Liver Index, and Incidence of Type 2 Diabetes: A Prospective Study Among Chinese

CONTEXT

Few lipidomic studies have specifically investigated the association of circulating glycerolipids and type 2 diabetes (T2D) risk, especially among Asian populations. It remains unknown whether or to what degree fatty liver could explain the associations between glycerolipids and T2D.

OBJECTIVE

We aimed to assess associations between plasma glycerolipids and incident T2D and to explore a potential role of liver fat accumulation in the associations.

METHODS

This was a prospective cohort study with 6 years of follow-up. The study population included 1781 Chinese participants aged 50 to 70 years. The main outcome measure was incident T2D.

RESULTS

At the 6-year resurvey, 463 participants had developed T2D. At the false discovery rate (FDR) of 5%, 43 of 104 glycerolipids were significantly associated with incident T2D risk after multivariate adjustment for conventional risk factors. After further controlling for glycated hemoglobin (HbA1c), 9 of the 43 glycerolipids remained significant, including 2 diacylglycerols (DAGs) (16:1/20:4, 18:2/20:5) and 7 triacylglycerols (TAGs) (46:1, 48:0, 48:1, 50:0, 50:1, 50:2, and 52:2), with relative risks (RRs) (95% CIs) ranging from 1.16 (1.05-1.27) to 1.23 (1.11-1.36) per SD increment of glycerolipids. However, additional adjustment for fatty liver index largely attenuated these findings (RR [95% CI] 0.88 [0.81 to 0.95] to 1.10 [1.01 to 1.21]). Mediation analyses suggested that the fatty liver index explained 12% to 28% of the glycerolipids-T2D associations (all P < 0.01).

CONCLUSION

Higher plasma levels of DAGs and TAGs were associated with increased incident T2D risk in this Chinese population, which might be partially explained by liver fat accumulation.

Anthracyclins Increase PUFAs: Potential Implications in ER Stress and Cell Death

Metabolic and personalized interventions in cancer treatment require a better understanding of the relationship between the induction of cell death and metabolism. Consequently, we treated three primary liver cancer cell lines with two anthracyclins (doxorubicin and idarubin) and studied the changes in the lipidome. We found that both anthracyclins in the three cell lines increased the levels of polyunsaturated fatty acids (PUFAs) and alkylacylglycerophosphoethanolamines (etherPEs) with PUFAs. As PUFAs and alkylacylglycerophospholipids with PUFAs are fundamental in lipid peroxidation during ferroptotic cell death, our results suggest supplementation with PUFAs and/or etherPEs with PUFAs as a potential general adjuvant of anthracyclins. In contrast, neither the markers of de novo lipogenesis nor cholesterol lipids presented the same trend in all cell lines and treatments. In agreement with previous research, this suggests that modulation of the metabolism of cholesterol could be considered a specific adjuvant of anthracyclins depending on the type of tumor and the individual. Finally, in agreement with previous research, we found a relationship across the different cell types between: (i) the change in endoplasmic reticulum (ER) stress, and (ii) the imbalance between PUFAs and cholesterol and saturated lipids. In the light of previous research, this imbalance partially explains the sensitivity to anthracyclins of the different cells. In conclusion, our results suggest that the modulation of different lipid metabolic pathways may be considered for generalized and personalized metabochemotherapies.

Liver lipidome signature and metabolic pathways in nonalcoholic fatty liver disease induced by a high-sugar diet

Dietary sugar is an important determinant of the development and progression of nonalcoholic fatty liver disease (NAFLD). However, the molecular mechanisms underlying the deleterious effects of sugar intake on NAFLD under energy-balanced conditions are still poorly understood. Here, we provide a comprehensive analysis of the liver lipidome and mechanistic insights into the pathogenesis of NAFLD induced by the chronic consumption of high-sugar diet (HSD). Newly weaned male Wistar rats were fed either a standard chow diet or an isocaloric HSD for 18 weeks. Livers were harvested for histological, oxidative stress, gene expression, and lipidomic analyses. Intake of HSD increased oxidative stress and induced severe liver injury, microvesicular steatosis, and ballooning degeneration of hepatocytes. Using untargeted lipidomics, we identified and quantified 362 lipid species in the liver. Rats fed with HSD displayed increased hepatic levels of triacylglycerol enriched in saturated and monounsaturated fatty acids, lipids related to mitochondrial function/structure (phosphatidylglycerol, cardiolipin, and ubiquinone), and acylcarnitine (an intermediate lipid of fatty acid beta-oxidation). HSD-fed animals also presented increased levels of some species of membrane lipids and a decreased content of phospholipids containing omega-6 fatty acids. These changes in the lipidome were associated with the downregulation of genes involved in fatty acid oxidation in the liver. In conclusion, our data suggest that the chronic intake of a HSD, even under isocaloric conditions, induces lipid overload, and inefficient/impaired fatty acid oxidation in the liver. Such events lead to marked disturbance in hepatic lipid metabolism and the development of NAFLD.

Structural elucidation of triacylglycerol using online acetone Paternò-Büchi reaction coupled with reversed-phase liquid chromatography mass spectrometry

Triacylglycerol (TG) is a class of lipids that is responsible for energy storage and cell metabolism in biological systems; it is found in relatively high abundances in biological fluids such as human plasma. Due to structural complexity, analyzing TGs using shotgun lipidomic approaches is challenging because of the presence of multiple fatty acyl compositional isomers. In this work, reversed-phase liquid chromatography (RPLC) was used for separation of TG species due to the capability of separating lipids based on fatty acyl chain lengths and degrees of unsaturation. RPLC alone does not provide structurally informative information for the location of carbon-carbon double-bonds (C[double bond, length as m-dash]Cs) without using synthesized standards that correspond to each species analyzed. The Paternò-Büchi (PB) reaction was employed online to confidently characterize the location of C[double bond, length as m-dash]Cs within lipid species via photo-initiated modification of the alkene group with acetone, which was later subjected to electrospray ionization (ESI) and tandem mass spectrometry (MS/MS) to form signature fragmentation peaks. This online RPLC-PB-MS/MS system was able to distinguish fatty acyl level and C[double bond, length as m-dash]C level isomeric species. The systems allowed for the identification of 46 TG molecular species in human plasma with confident C[double bond, length as m-dash]C location assignment in fatty acyls at a limit of identification of 50 nM.

Lipidomics Issues on Human Positive ssRNA Virus Infection: An Update

The pathogenic mechanisms underlying the Biology and Biochemistry of viral infections are known to depend on the lipid metabolism of infected cells. From a lipidomics viewpoint, there are a variety of mechanisms involving virus infection that encompass virus entry, the disturbance of host cell lipid metabolism, and the role played by diverse lipids in regard to the infection effectiveness. All these aspects have currently been tackled separately as independent issues and focused on the function of proteins. Here, we review the role of cholesterol and other lipids in ssRNA+ infection.

Lipidomic-Based Advances in Diagnosis and Modulation of Immune Response to Cancer

While immunotherapies for diverse types of cancer are effective in many cases, relapse is still a lingering problem. Like tumor cells, activated immune cells have an anabolic metabolic profile, relying on glycolysis and the increased uptake and synthesis of fatty acids. In contrast, immature antigen-presenting cells, as well as anergic and exhausted T-cells have a catabolic metabolic profile that uses oxidative phosphorylation to provide energy for cellular processes. One goal for enhancing current immunotherapies is to identify metabolic pathways supporting the immune response to tumor antigens. A robust cell expansion and an active modulation via immune checkpoints and cytokine release are required for effective immunity. Lipids, as one of the main components of the cell membrane, are the key regulators of cell signaling and proliferation. Therefore, lipid metabolism reprogramming may impact proliferation and generate dysfunctional immune cells promoting tumor growth. Based on lipid-driven signatures, the discrimination between responsiveness and tolerance to tumor cells will support the development of accurate biomarkers and the identification of potential therapeutic targets. These findings may improve existing immunotherapies and ultimately prevent immune escape in patients for whom existing treatments have failed.

Diacylglycerol kinase η regulates C2C12 myoblast proliferation through the mTOR signaling pathway

Diacylglycerol kinase (DGK) phosphorylates diacylglycerol to produce phosphatidic acid (PA). The η isozyme of DGK is abundantly expressed in C2C12 myoblasts. However, the role of DGKη in skeletal muscle cells remains unknown. In the present study, we showed that DGKη was downregulated at an early stage of myogenic differentiation. The knockdown of DGKη by siRNAs significantly inhibited C2C12 myoblast proliferation but did not inhibit differentiation. Moreover, the suppression of DGKη expression decreased the expression levels of mammalian target of rapamycin (mTOR), which is a key regulator of cell proliferation, and fatty acid synthase (FASN), which catalyzes the de novo synthesis of fatty acids for cell proliferation and is transcriptionally regulated via mTOR signaling. Furthermore, the knockdown of mTOR or raptor, which is a component of mTOR complex 1 (mTORC1), decreased the amount of FASN. These results indicate that DGKη regulates myoblast proliferation through the mTOR (mTORC1)-FASN pathway. Interestingly, the knockdown of mTOR reduced the expression levels of DGKη, implying mutual regulation between DGKη and mTOR. In DGKη-knockdown myoblasts, C30-C36-PA species, mTOR activators, were decreased, suggesting that the modulation of mTOR activity through these PA species also plays an important role in myoblast proliferation.

Development of a sensitive and quantitative method for the identification of two major furan fatty acids in human plasma

This article focuses on the establishment of an accurate and sensitive quantitation method for the analysis of furan fatty acids. In particular, the sensitivity of GC/MS and UPLC/ESI/MS/MS was compared for the identification and quantification of furan fatty acids. Different methylation methods were tested with respect to GC/MS analysis. Special attention needs to be paid to the methylation of furan fatty acids, as acidic catalysts might lead to the degradation of the furan ring. GC/MS analysis in full-scan mode demonstrated that the limit of quantitation was 10 μM. UPLC/ESI/MS/MS in multiple reaction monitoring mode displayed a higher detection sensitivity than GC/MS. Moreover, the identification of furan fatty acids with charge-reversal derivatization was tested in the positive mode with two widely used pyridinium salts. Significant oxidation was unexpectedly observed using N-(4-aminomethylphenyl) pyridinium as a derivatization agent. The formed 3-acyl-oxymethyl-1-methylpyridinium iodide derivatized by 2-bromo-1-methylpyridinium iodide and 3-carbinol-1-methylpyridinium iodide improved the sensitivity more than 2,000-fold compared with nonderivatization in the negative mode by UPLC/ESI/MS/MS. This charge-reversal derivatization enabled the targeted quantitation of furan fatty acids in human plasma. Thus, it is anticipated that this protocol could greatly contribute to the clarification of pathological mechanisms related to furan fatty acids and their metabolites.

Anabolic androgenic steroids exert a selective remodeling of the plasma lipidome that mirrors the decrease of the de novo lipogenesis in the liver

INTRODUCTION

The abuse of anabolic androgenic steroids (AASs) is a source of public concern because of their adverse effects. Supratherapeutic doses of AASs are known to be hepatotoxic and regulate the lipoproteins in plasma by modifying the metabolism of lipids in the liver, which is associated with metabolic diseases. However, the effect of AASs on the profile of lipids in plasma is unknown.

OBJECTIVES

To describe the changes in the plasma lipidome exerted by AASs and to discuss these changes in the light of previous research about AASs and de novo lipogenesis in the liver.

METHODS

We treated male Wistar rats with supratherapeutic doses of nandrolone decanoate and testosterone undecanoate. Subsequently, we isolated the blood plasma and performed lipidomics analysis by liquid chromatography-high resolution mass spectrometry.

RESULTS

Lipid profiling revealed a decrease of sphingolipids and glycerolipids with palmitic, palmitoleic, stearic, and oleic acids. In addition, lipid profiling revealed an increase in free fatty acids and glycerophospholipids with odd-numbered chain fatty acids and/or arachidonic acid.

CONCLUSION

The lipid profile presented herein reports the imprint of AASs on the plasma lipidome, which mirrors the downregulation of de novo lipogenesis in the liver. In a broader perspective, this profile will help to understand the influence of androgens on the lipid metabolism in future studies of diseases with dysregulated lipogenesis (e.g. type 2 diabetes, fatty liver disease, and hepatocellular carcinoma).

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays.