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Proregenerative responses are required for the restoration of nervous-system functionality in demyelinating diseases such as multiple sclerosis (MS). Yet, the limiting factors responsible for poor CNS repair are only partially understood. Here, we test the impact of a Western diet (WD) on phagocyte function in a mouse model of demyelinating injury that requires microglial innate immune function for a regenerative response to occur. We find that WD feeding triggers an ageing-related, dysfunctional metabolic response that is associated with impaired myelin-debris clearance in microglia, thereby impairing lesion recovery after demyelination. Mechanistically, we detect enhanced transforming growth factor beta (TGFβ) signalling, which suppresses the activation of the liver X receptor (LXR)-regulated genes involved in cholesterol efflux, thereby inhibiting phagocytic clearance of myelin and cholesterol. Blocking TGFβ or promoting triggering receptor expressed on myeloid cells 2 (TREM2) activity restores microglia responsiveness and myelin-debris clearance after demyelinating injury. Thus, we have identified a druggable microglial immune checkpoint mechanism regulating the microglial response to injury that promotes remyelination.

Blood biomarkers of multiple sclerosis (MS) can provide a better understanding of pathophysiology and enable disease monitoring. Here, we performed quantitative shotgun lipidomics on the plasma of a unique cohort of 73 monozygotic twins discordant for MS. We analyzed 243 lipid species, evaluated lipid features such as fatty acyl chain length and number of acyl chain double bonds, and detected phospholipids that were significantly altered in the plasma of co‐twins with MS compared to their non‐affected siblings. Strikingly, changes were most prominent in ether phosphatidylethanolamines and ether phosphatidylcholines, suggesting a role for altered lipid signaling in the disease.

The membrane lipids diacylglycerol (DAG) and phosphatidic acid (PA) are important second messengers that can regulate membrane transport by recruiting proteins to the membrane and by altering biophysical membrane properties. DAG and PA are involved in the transport from the Golgi apparatus to endosomes, and we have here investigated whether changes in these lipids might be important for regulation of transport to the Golgi using the protein toxin ricin. Modulation of DAG and PA levels using DAG kinase (DGK) and phospholipase D (PLD) inhibitors gave a strong increase in retrograde ricin transport, but had little impact on ricin recycling or degradation. Inhibitor treatment strongly affected the endosome morphology, increasing endosomal tubulation and size. Furthermore, ricin was present in these tubular structures together with proteins known to regulate retrograde transport. Using siRNA to knock down different isoforms of PLD and DGK, we found that several isoforms of PLD and DGK are involved in regulating ricin transport to the Golgi. Finally, by performing lipidomic analysis we found that the DGK inhibitor gave a weak, but expected, increase in DAG levels, while the PLD inhibitor gave a strong and unexpected increase in DAG levels, showing that it is important to perform lipidomic analysis when using inhibitors of lipid metabolism. Electronic supplementary material The online version of this article (10.1007/s00018-020-03551-6) contains supplementary material, which is available to authorized users.

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m(2), urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers. Wigger, Barovic and Brunner et al. perform a multidimensional analysis of islets from metabolically characterized patients who had undergone pancreatectomy, observing remarkable heterogeneity between samples from individuals with type 2 diabetes, thus arguing against models of linear beta-cell dedifferentiation in diabetes.

We have deployed a multi-omics approach in large cohorts of patients with existing type 2 diabetes to identify biomarkers for disease progression across three molecular classes, metabolites, lipids and proteins. A Cox regression analysis for association with time to insulin requirement in 2,973 patients in the DCS, ANDIS and GoDARTS cohorts identified homocitrulline, isoleucine and 2-aminoadipic acid, as well as the bile acids glycocholic and taurocholic acids, as predictive of more rapid deterioration. Increased levels of eight triacylglycerol species, and lowered levels of the sphingomyelin SM 42:2;2 were also predictive of disease progression. Of ∼1,300 proteins examined in two cohorts, levels of GDF-15/MIC1, IL-18RA, CRELD1, NogoR, FAS, and ENPP7 were associated with faster progression, whilst SMAC/DIABLO, COTL1, SPOCK1 and HEMK2 predicted lower progression rates. Strikingly, identified proteins and lipids were also associated with diabetes incidence and prevalence in external replication cohorts. Implicating roles in disease compensation, NogoR/RTN4R improved glucose tolerance in high fat-fed mice and tended to improved insulin signalling in liver cells whilst IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. Conversely, high NogoR levels led to islet cell apoptosis. This comprehensive, multi-disciplinary approach thus identifies novel biomarkers with potential prognostic utility, provides evidence for new disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Objectives To find plasma biomarkers prognostic of type 2 diabetes, which could also inform on pancreatic β-cell deregulations or defects in the function of insulin target tissues. Methods We conducted a systems biology approach to characterize the plasma lipidomes of C57Bl/6J, DBA/2J, and BALB/cJ mice under different nutritional conditions, as well as their pancreatic islet and liver transcriptomes. We searched for correlations between plasma lipids and tissue gene expression modules. Results We identified strong correlation between plasma triacylglycerols (TAGs) and islet gene modules that comprise key regulators of glucose- and lipid-regulated insulin secretion and of the insulin signaling pathway, the two top hits were Gck and Abhd6 for negative and positive correlations, respectively. Correlations were also found between sphingomyelins and islet gene modules that overlapped in part with the gene modules correlated with TAGs. In the liver, the gene module most strongly correlated with plasma TAGs was enriched in mRNAs encoding fatty acid and carnitine transporters as well as multiple enzymes of the β-oxidation pathway. In humans, plasma TAGs also correlated with the expression of several of the same key regulators of insulin secretion and the insulin signaling pathway identified in mice. This cross-species comparative analysis further led to the identification of PITPNC1 as a candidate regulator of glucose-stimulated insulin secretion. Conclusion TAGs emerge as biomarkers of a liver-to-β-cell axis that links hepatic β-oxidation to β-cell functional mass and insulin secretion., Highlights • Plasma triacylglycerols correlated with genes controlling β-cell mass and function. • Plasma triacylglycerols correlated with genes controlling liver β-oxidation. • In humans, triacylglycerols also correlated with key regulators of insulin secretion. • Mouse and human data identified PITPNC1 as a candidate regulator of insulin secretion. • Triacylglycerols are biomarkers of the liver-to-β-cell axis and β-cell function.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

Aims/hypothesisFive clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes (T2D). In the current study we replicate and cross-validate these T2D clusters in three large cohorts using readily measured variables in the clinic.MethodsIn this cross-sectional study, 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide and HDL in three independent cohorts. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort’s cluster centres.ResultsFive distinct T2D clusters were identified and mapped back to the original four ANDIS clusters. Using C-peptide and HDL instead of HOMA-B and HOMA-S three of the clusters mapped with high sensitivity (80.6 – 90.7%) to the previously identified Severe Insulin Deficient (SIDD), Severe insulin resistant (SIRD) and Obese (MOD) clusters. The previously described ANDIS MARD cluster could be mapped to the two milder groups in our study – one characterised by high HDL, and the other having not any extreme characteristic (MDH cluster). When these two milder groups were combined they mapped well to the previously labelled MARD cluster (sensitivity 79.4%). In the cross-validation between cohorts, particularly the SIDD and MDH cluster cross-validated well with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity ranging from 36.1% to 92.3% where individuals shifted from SIRD to MD and vice versa.Conclusions/interpretationClusters based on C-peptide instead of HOMA measures result in clusters that resemble those based on HOMA measures, especially for SIDD, SIRD and MOD. By adding HDL, the MARD cluster based upon HOMA measures resulted in the current clustering in two clusters with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts.

The unfolded protein response (UPR) is central to endoplasmic reticulum (ER) homeostasis by controlling its size and protein folding capacity. When activated by unfolded proteins in the ER-lumen or aberrant lipid compositions, the UPR adjusts the expression of hundreds of target genes to counteract ER stress. The proteotoxic drugs dithiothreitol (DTT) and tunicamycin (TM) are commonly used to induce misfolding of proteins in the ER and to study the UPR. However, their potential impact on the cellular lipid composition has never been systematically addressed. Here, we report the quantitative, cellular lipid composition of Saccharomyces cerevisiae during acute, proteotoxic stress in both rich and synthetic media. We show that DTT causes rapid remodeling of the lipidome when used in rich medium at growth-inhibitory concentrations, while TM has only a marginal impact on the lipidome under our conditions of cultivation. We formulate recommendations on how to study UPR activation by proteotoxic stress without interferences from a perturbed lipid metabolism. Furthermore, our data suggest an intricate connection between the cellular growth rate, the abundance of the ER, and the metabolism of fatty acids. We show that Saccharomyces cerevisiae can produce asymmetric lipids with two saturated fatty acyl chains differing substantially in length. These observations indicate that the pairing of saturated fatty acyl chains is tightly controlled and suggest an evolutionary conservation of asymmetric lipids and their biosynthetic machineries.

Aneuploidy disrupts cellular homeostasis. However, the molecular mechanisms underlying the physiological responses and adaptation to aneuploidy are not well understood. Deciphering these mechanisms is important because aneuploidy is associated with diseases, including intellectual disability and cancer. Although tumors and mammalian aneuploid cells, including several cancer cell lines, show altered levels of sphingolipids, the role of sphingolipids in aneuploidy remains unknown. Here, we show that ceramides and long-chain bases, sphingolipid molecules that slow proliferation and promote survival, are increased by aneuploidy. Sphingolipid levels are tightly linked to serine synthesis, and inhibiting either serine or sphingolipid synthesis can specifically impair the fitness of aneuploid cells. Remarkably, the fitness of aneuploid cells improves or deteriorates upon genetically decreasing or increasing ceramides, respectively. Combined targeting of serine and sphingolipid synthesis could be exploited to specifically target cancer cells, the vast majority of which are aneuploid.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

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., Obesity is associated with changes in plasma lipids, but while simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. A machine learning study based on lipidomes of a total of 1,311 individuals reveals improved associations of plasma lipids with total body fat and fat distribution compared to routine clinical laboratory variables.

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P, Cardiovascular diseases (CVD) are associated with plasma lipid levels. Here, Tabassum et al. perform genome-wide association studies for lipidomic profiles with 141 (non-standard) lipid species which highlights shared genetic loci with CVD and that traditional lipids have low genetic correlation with other lipids.

The plasma membrane (PM) is composed of a complex lipid mixture that forms heterogeneous membrane environments. Yet, how small-scale lipid organization controls physiological events at the PM remains largely unknown. Here, we show that ORP-related Osh lipid exchange proteins are critical for the synthesis of phosphatidylinositol (4,5)-bisphosphate [PI(4,5)P2], a key regulator of dynamic events at the PM. In real-time assays, we find that unsaturated phosphatidylserine (PS) and sterols, both Osh protein ligands, synergistically stimulate phosphatidylinositol 4-phosphate 5-kinase (PIP5K) activity. Biophysical FRET analyses suggest an unconventional co-distribution of unsaturated PS and phosphatidylinositol 4-phosphate (PI4P) species in sterol-containing membrane bilayers. Moreover, using in vivo imaging approaches and molecular dynamics simulations, we show that Osh protein-mediated unsaturated PI4P and PS membrane lipid organization is sensed by the PIP5K specificity loop. Thus, ORP family members create a nanoscale membrane lipid environment that drives PIP5K activity and PI(4,5)P2 synthesis that ultimately controls global PM organization and dynamics.

Degradable bone substitutes made of magnesium alloys are an alternative to biological bone grafts. The main advantage is that they can be manufactured location- and patient-specific. To develop and scale appropriate implants using computational models, knowledge about the mechanical properties and especially the change in the properties during the degradation process is essential. Therefore, degraded open-pored implants were investigated using scanning electron microscope and nanoindentation to find their material composition and mechanical properties. Using both techniques the correlation of the material composition and the average modulus was determined. It could be shown that the average modulus of the degradation layer is distinctly lower than that of the base material. The local average modulus of degrading implant highly depends on the magnesium concentration and the accumulation of elements from the environment. A decrease in magnesium concentration leads to a decrease in the average modulus. Thus, the degrading implant had a lower stiffness than the initial structure.

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low‐density lipoprotein cholesterol ( LDL ‐C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population‐based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first‐degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL ‐C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta‐analysis of the hyperlipidemic families and the population cohort (high LDL ‐C: hazard ratio, 1.74 [95% CI, 1.48–2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09–1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid‐lowering medication. In lipidomic profiling, high LDL ‐C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P ‐value range 0.038–2.3×10 −56 ). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL ‐C: r =0.80; triacylglycerides: r =0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population‐based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL ‐C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population‐ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

The development of degradable bone implants, in particular made of metal materials, is an emerging field. The advantage of degradable implants is that they do not have to be removed later. In order to be able to develop and scale appropriate implants for different applications, it is necessary to know the change in mechanical properties of the implant during the degradation process in general and at different locations. One area of bone implants are bone substitute materials. They are deployed when there is a defect in the bone which cannot be filled autonomously by the body. In this study, a numerical degradation model of magnesium-based bone substitute materials is developed using the finite element method. Computational models are being developed to reduce experimental animal research in future. Magnesium is a naturally occurring material which is needed to build enzymes in the body. Additionally, magnesium has a Young's modulus close to native bone, wherefore it is attractive for medical applications with bone contact. The simulation model is based on the assumption that the degradation is a diffusion-controlled process driven by the dissolution of magnesium. The model is adapted to a 3D open-pored structure made of the magnesium alloy LAE442. Previous studies showed that implants made of LAE442 lose stiffness without a volume reduction. To simulate the change in mechanical properties, a concentration-dependent Young's modulus is assumed. With this model the formation of the degradation layer is computable as well as the change in mechanical properties, as measured by the effective Young's modulus of the structure. The movement of the interface between the not-degraded and degraded material is modelled using the level set method.

Objective Shotgun lipidomics enables an extensive analysis of lipids from tissues and fluids. Each specimen requires appropriate extraction and processing procedures to ensure good coverage and reproducible quantification of the lipidome. Adipose tissue (AT) has become a research focus with regard to its involvement in obesity-related pathologies. However, the quantification of the AT lipidome is particularly challenging due to the predominance of triacylglycerides, which elicit high ion suppression of the remaining lipid classes. Methods We present a new and validated method for shotgun lipidomics of AT, which tailors the lipid extraction procedure to the target specimen and features high reproducibility with a linear dynamic range of at least 4 orders of magnitude for all lipid classes. Results Utilizing this method, we observed tissue-specific and diet-related differences in three AT types (brown, gonadal, inguinal subcutaneous) from lean and obese mice. Brown AT exhibited a distinct lipidomic profile with the greatest lipid class diversity and responded to high-fat diet by altering its lipid composition, which shifted towards that of white AT. Moreover, diet-induced obesity promoted an overall remodeling of the lipidome, where all three AT types featured a significant increase in longer and more unsaturated triacylglyceride and phospholipid species. Conclusions The here presented method facilitates reproducible systematic lipidomic profiling of AT and could be integrated with further –omics approaches used in (pre-) clinical research, in order to advance the understanding of the molecular metabolic dynamics involved in the pathogenesis of obesity-associated disorders., Graphical abstract Image 1, Highlights • Validated shotgun lipidomics method of AT covering 300 lipids of 20 classes and linear dynamic range of 4 orders of magnitude. • Increase of longer and more unsaturated triacylglycerides and phospholipids in brown and white AT under high-fat diet. • Differences in the lipidomes of gonadal, subcutaneous and brown AT.

We thank the nursing staff at the Hospital Santa Cruz, in particular Edite Tomas Mateus and Manuel Belo Costa for their enthusiastic involvement in this project and help in blood collection. This work was supported by iNOVA4Health - UID/Multi/04462/2013, a program financially supported by FCT (Foundation for Science and Technology of the Portuguese Ministry of Science and Higher Education) through national funds and co-funded by FEDER under the PT2020 Partnership, and Programas de Atividades Conjuntas (PAC) (Ref. No 03/SAICT/2015). ND is a holder of PhD fellowship from the FCT (Ref. No: SFRH/BD/51877/2012). Shotgun lipidomic analysis of 203 lipids in 13 lipid classes performed on blood plasma of donors who had just suffered an acute coronary syndrome (ACS, n = 74), or an ischemic stroke (IS, n = 21), or who suffer from stable angina pectoris (SAP, n = 78), and an age-matched control cohort (n = 52), showed some of the highest inter-lipid class correlations between cholesteryl esters (CE) and phosphatidylcholines (PC) sharing a common fatty acid. The concentration of lysophospatidylcholine (LPC) and ratios of concentrations of CE to free cholesterol (Chol) were also lower in the CVD cohorts than in the control cohort, indicating a deficient conversion of Chol to CE in the blood plasma in the CVD subjects. A non-equilibrium reaction quotient, Q′, describing the global homeostasis of cholesterol as manifested in the blood plasma was shown to have a value in the CVD cohorts (Q′ACS = 0.217 ± 0.084; Q′IS = 0.201 ± 0.084; Q′SAP = 0.220 ± 0.071) that was about one third less than in the control cohort (Q′Control = 0.320 ± 0.095, p < 1 × 10−4), suggesting its potential use as a rapid predictive/diagnostic measure of CVD-related irregularities in cholesterol homeostasis. publishersversion published

// Maria L. Torgersen 1 , Tove Irene Klokk 1 , Simona Kavaliauskiene 1, 2 , Christian Klose 3 , Kai Simons 3 , Tore Skotland 1 , Kirsten Sandvig 1, 2 1 Department of Molecular Cell Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Norway, and Centre for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Norway 2 Department of Molecular Biosciences, University of Oslo, Norway 3 Lipotype GmbH, Dresden, Germany Correspondence to: Maria L. Torgersen, email: marialy@rr-research.no Keywords: hydroxyoleic acid, minerval, membrane lipid therapy, EGFR, ricin Received: June 20, 2016 Accepted: October 17, 2016 Published: November 22, 2016 ABSTRACT 2-hydroxyoleic acid (OHOA, Minerval ® ) is an example of a substance used for membrane lipid therapy, where the cellular membranes rather than specific proteins constitute the therapeutical target. OHOA is thought to mediate its anti-tumor effect by affecting the biophysical properties of membranes, which leads to altered recruitment and activation of amphitropic proteins, altered cellular signaling, and eventual cell death. Little is known about the initial signaling events upon treatment with OHOA, and whether the altered membrane properties would have any impact on the dynamic intracellular transport system. In the present study we demonstrate that treatment with OHOA led to a rapid release of intracellular calcium and activation of multiple signaling pathways in HeLa cells, including the PI3K-AKT1-MTOR pathway and several MAP kinases, in a process independent of the EGFR. By lipidomics we confirmed that OHOA was incorporated into several lipid classes. Concomitantly, OHOA potently increased retrograde transport of the plant toxin ricin from endosomes to the Golgi and further to the endoplasmic reticulum. The OHOA-stimulated ricin transport seemed to require several amphitropic proteins, including Src, phospholipase C, protein kinase C, and also Ca 2+ /calmodulin. Interestingly, OHOA induced a slight increase in endosomal localization of the retromer component VPS35. Thus, our data show that addition of a lipid known to alter membrane properties not only affects signaling, but also intracellular transport.

Acute metabolic changes in plasma membrane (PM) lipids, such as those mediating signalling reactions, are rapidly compensated by homeostatic responses whose molecular basis is poorly understood. Here we show that the extended synaptotagmins (E-Syts), endoplasmic reticulum (ER) proteins that function as PtdIns(4,5)P2- and Ca2+-regulated tethers to the PM, participate in these responses. E-Syts transfer glycerolipids between bilayers in vitro, and this transfer requires Ca2+ and their lipid-harbouring SMP domain. Genome-edited cells lacking E-Syts do not exhibit abnormalities in the major glycerolipids at rest, but exhibit enhanced and sustained accumulation of PM diacylglycerol following PtdIns(4,5)P2 hydrolysis by PLC activation, which can be rescued by expression of E-Syt1, but not by mutant E-Syt1 lacking the SMP domain. The formation of E-Syt-dependent ER–PM tethers in response to stimuli that cleave PtdIns(4,5)P2 and elevate Ca2+ may help reverse accumulation of diacylglycerol in the PM by transferring it to the ER for metabolic recycling. Accepted version

Gene and protein expression data provide useful resources for understanding brain function, but little is known about the lipid composition of the brain. Here, we perform quantitative shotgun lipidomics, which enables a cell-type-resolved assessment of the mouse brain lipid composition. We quantify around 700 lipid species and evaluate lipid features including fatty acyl chain length, hydroxylation, and number of acyl chain double bonds, thereby identifying cell-type- and brain-region-specific lipid profiles in adult mice, as well as in aged mice, in apolipoprotein-E-deficient mice, in a model of Alzheimer's disease, and in mice fed different diets. We also integrate lipid with protein expression profiles to predict lipid pathways enriched in specific cell types, such as fatty acid beta-oxidation in astrocytes and sphingolipid metabolism in microglia. This resource complements existing brain atlases of gene and protein expression and may be useful for understanding the role of lipids in brain function. Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

AimGenetic investigation of human plasma lipidome to get insights into lipid-related disorders beyond traditional lipid measures.Methods and ResultsWe performed a genome-wide association study (GWAS) of 141 lipid species (n=2,181 individuals), followed by phenome-wide scans (PheWAS) with 44 clinical endpoints related to cardiometabolic, psychiatric and gastrointestinal disorders (n=456,941 individuals). SNP-based heritability for lipid species ranged from 0.10-0.54. Lipids with long-chain polyunsaturated fatty acids showed higher heritability and genetic sharing, suggesting considerable genetic regulation at acyl chains levels. We identified 35 genomic regions associated with at least one lipid species (P−8), revealing 37 new SNP-lipid species pair associations e.g. new association between ABCG5/8 and CE(20:2;0). PheWAS of lipid-species-associated loci suggested new associations of BLK with obesity, FADS2 with thrombophlebitis, and BLK and SPTLC3 with gallbladder disease (false discovery rate SYNGR1, MIR100HG, and PTPRN2 in desaturation and/or elongation of fatty acids. At known lipid loci (FADS2, APOA5 and LPL), genetic associations provided detailed insights to their roles in lipid biology and diseases. We also show that traditional lipid measures may fail to capture lipids such as lysophospatidylcholines (LPCs) and phosphatidylcholines (PCs) that are potential disease risk factors, but are not included in routine screens. The full genome-wide association statistics are available on the web-based database (http://35.205.141.92).ConclusionOur study reveals genetic regulation of plasma lipidome and highlights the potential of lipidomic profiling in disease gene mapping.

Aims: To characterize and compare coronary artery disease (CAD) risk and detailed lipidomic profiles of individuals with familial and population-ascertained hyperlipidemias.Methods and Results: We determined incident CAD risk for 760 members of 66 hyperlipidemic families (≥ 2 first degree relatives with the same hyperlipidemia) and 19,644 Finnish FINRISK population study participants. We also quantified 151 lipid species in plasma or serum samples from 550 members of 73 hyperlipidemic pedigrees and 897 FINRISK participants using a mass spectrometric shotgun lipidomics platform. Hyperlipidemias (LDL-C or triacylglycerides over 90th population percentile) were associated with increased CAD risk (high LDL-C: HR 1.74, 95% CI 1.48–2.04; high triacylglycerides: HR 1.38, 95% CI 1.09–1.74) and the risk estimates were very similar between the family and population samples. High LDL-C was associated with altered levels of 105 lipid species in families (p-value range 0.033–7.3*10−20 at 5% false discovery rate) and 51 species in the population samples (p-value range 0.017–6.8*10−21). Hypertriglyceridemia was associated with altered levels of 117 lipid species in families (p-value range 0.035–1.8*10−49) and 119 species in the population sample (p-value range 0.038–2.3*10−56). The lipidomics profiles of hyperlipidemias were highly similar in families and population samples.Conclusion: We identified distinct lipidomic profiles associated with high LDL-C and triacylglyceride levels. CAD risk, lipidomic profiles and genetic profiles are highly similar between familial and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms. Our results do not support different screening and treatment for such hyperlipidemias.

The size of all cells, from bacteria to vertebrates, is proportional to the growth rate set by nutrient availability, but the underlying mechanisms are unknown. Here, we show that nutrients modulate cell size andgrowth rate via the TORC2 signaling network in budding yeast. An important function of the TORC2 network is to modulate synthesis of ceramide lipids, which play roles in signaling. TORC2-dependent control of ceramide signaling strongly influences both cell size and growth rate. Thus, cells that cannot make ceramides fail to modulate their growth rate or size in response to changes in nutrients. PP2A associated with the Rts1 regulatory subunit (PP2ARts1) is embedded in a feedback loop that controls TORC2 signaling and helps set the level of TORC2 signaling to match nutrient availability. Together, the data suggest a model in which growth rate and cell size are mechanistically linked by ceramide-dependent signals arising from the TORC2 network.

Shotgun lipidomics is the comprehensive and quantitative analysis of the lipid composition of biological and clinical samples. Here we describe the application and performance of the Lipotype shotgun lipidomics technology in clinical high throughput screening projects for the identification of disease-specific lipid patterns as well as in organ-wide analysis aiming at the systemic understanding of lipid-related physiological processes.

Dietary lipids change membrane phenotypes, which can be used to affect lineage specification in stem cells., Mammalian cells produce hundreds of dynamically regulated lipid species that are actively turned over and trafficked to produce functional membranes. These lipid repertoires are susceptible to perturbations from dietary sources, with potentially profound physiological consequences. However, neither the lipid repertoires of various cellular membranes, their modulation by dietary fats, nor their effects on cellular phenotypes have been widely explored. We report that differentiation of human mesenchymal stem cells (MSCs) into osteoblasts or adipocytes results in extensive remodeling of the plasma membrane (PM), producing cell-specific membrane compositions and biophysical properties. The distinct features of osteoblast PMs enabled rational engineering of membrane phenotypes to modulate differentiation in MSCs. Specifically, supplementation with docosahexaenoic acid (DHA), a lipid component characteristic of osteoblast membranes, induced broad lipidomic remodeling in MSCs that reproduced compositional and structural aspects of the osteoblastic PM phenotype. The PM changes induced by DHA supplementation potentiated osteogenic differentiation of MSCs concurrent with enhanced Akt activation at the PM. These observations prompt a model wherein the DHA-induced lipidome leads to more stable membrane microdomains, which serve to increase Akt activity and thereby enhance osteogenic differentiation. More broadly, our investigations suggest a general mechanism by which dietary fats affect cellular physiology through remodeling of membrane lipidomes, biophysical properties, and signaling.

Background Diabetes mellitus ( DM ) and cardiovascular disease are associated with dyslipidemia, but the detailed lipid molecular pattern in both diseases remains unknown. Methods and Results We used shotgun mass spectrometry to determine serum levels of 255 molecular lipids in 316 controls, 171 DM , and 99 myocardial infarction ( MI ) events from a cohort derived from the Malmö Diet and Cancer study. Orthogonal projections to latent structures analyses were conducted between the lipids and clinical parameters describing DM or MI . Fatty acid desaturases ( FADS ) and elongation of very long chain fatty acid protein 5 ( ELOVL 5) activities were estimated by calculating product to precursor ratios of polyunsaturated fatty acids in complex lipids. FADS genotypes encoding these desaturases were then tested for association with lipid levels and ratios. Differences in the levels of lipids belonging to the phosphatidylcholine and triacylglyceride ( TAG ) classes contributed the most to separating DM from controls. TAG s also played a dominating role in discriminating MI from controls. Levels of C18:2 fatty acids in complex lipids were lower both in DM and MI versus controls ( DM , P =0.004; MI , P =6.0E‐06) at least due to an acceleration in the metabolic flux from C18:2 to C20:4 (eg, increased estimated ELOVL 5: DM , P =0.02; MI , P =0.04, and combined elongase‐desaturase activities: DM , P =3.0E‐06; MI , P =2.0E‐06). Minor allele carriers of FADS genotypes were associated with increased levels of C18:2 ( P ≤0.007) and lower desaturase activity ( P ≤0.002). Conclusions We demonstrate a possible relationship between decreased levels of C18:2 in complex lipids and DM or MI . We thereby highlight the importance of molecular lipids in the pathogenesis of both diseases.

Familial hyperlipidemias including but not limited to familial hypercholesterolemia (FH) are often evaluated distinctly from population-based hyperlipidemias. We asked whether this practice is warranted either by greater coronary artery disease (CAD) risk or by different detailed lipid profiles in