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Type 2 diabetes is a complex, multifactorial disease with varying presentation and underlying pathophysiology. Recent studies using data-driven cluster analysis have led to a stratification of type 2 diabetes into novel subgroups based on six clinical measurements. Whether these subgroups truly correspond to the underlying phenotypic differences is nevertheless unclear. Here, we apply an unsupervised, data-driven clustering method (Similarity Network Fusion) to characterize type 2 diabetes in two independent cohorts involving 1,134 subjects in total based on integrated plasma lipidomics and peptidomics data without pre-selection. Logistic regression was then used to explore clustering based on ≥ 180 circulating lipids and 1,195 protein biomarkers, alongside clinical signatures. Two subgroups were identified, one of which associated with elevated C-peptide levels, diabetic complications and more severe insulin resistance compared to the other. GWAS analysis against 403 type 2 diabetes risk variants revealed associations of several SNPs with clusters and altered molecular profiles. We thus demonstrate that heterogeneity in type 2 diabetes can be captured by circulating omics alone using an unsupervised bottom-up approach. Such multiomics signatures could reflect pathological mechanisms underlying type 2 diabetes and thus may help inform on precision medicine approaches to disease management.

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.

OBJECTIVE Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PCDM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models. RESULTS A T2DM-predictive lipid-PCDM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PCDM of 3.7 (95% CI 2.2–6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2–2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PCDM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PCDM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity. CONCLUSIONS A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.

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.

Lipidomics has become an indispensable method for the quantitative assessment of lipid metabolism in basic, clinical, and pharmaceutical research. It allows for the generation of information-dense datasets in a large variety of experimental setups and model organisms. Previous studies, mostly conducted in mice (Mus musculus), have shown a remarkable specificity of the lipid compositions of different cell types, tissues, and organs. However, a systematic analysis of the overall variation of the mouse lipidome is lacking. To fill this gap, in the present study, the effect of diet, sex, and genotype on the lipidomes of mouse tissues, organs, and bodily fluids has been investigated. Baseline quantitative lipidomes consisting of 796 individual lipid molecules belonging to 24 lipid classes are provided for 10 different sample types. Furthermore, the susceptibility of lipidomes to the tested parameters is assessed, providing insights into the organ-specific lipidomic plasticity and flexibility. This dataset provides a valuable resource for basic and pharmaceutical researchers working with murine models and complements existing proteomic and transcriptomic datasets. It will inform experimental design and facilitate interpretation of lipidomic datasets.

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.

Aims: Inflammation impacts several acute and chronic diseases causing localized stress and cell death, releasing tissue-specific lipids into the circulation from inflamed cells and tissues. The plasma lipidome may be expected to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. Methods and Results: We compared the plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related cardiovascular disease (CVD) including ischemic stroke (IS), and systemic lupus erythematosus (SLE), to each other and to age-matched controls. The controls had never suffered from any of these diseases. Plasma lipidomes were screened by a top-down shotgun MS-based analysis without liquid chromatographic separation. Lipid profiling of 596 lipids based on MS was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes of patients suffering from CVD and SLE allowed clear distinction of these two chronic inflammatory diseases from each other. We demonstrate convincing evidence for the capability of lipidomics to separate the studied chronic and inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.90, Specificity: 0.98; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.88) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls. In addition, CVD severities, as classified into five clinical groups, were partially separable by linear discriminant analysis. Conclusions: Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes. Dysregulated lipids are partially but not fully counterbalanced by statin treatment. Clinical Trial Registration Details: This study was registered with the Clinical Trials number NCT04786431 Funding Information: This work was supported by PTDC/MED-PAT/29395/2017 financially supported by Fundacao paraKS is CEO and shareholder of of Lipotype GmbH. CL and MG are KS is CEO and shareholder of of Lipotype GmbH. CL and MG are employees of Lipotype GmbH. All other authors declare that they do not have any competing interestsemployees of Lipotype GmbH. All other authors declare that they do not have any competing interests424 a Ciencia e a Tecnologia (FCT), through national funds and co-funded by FEDER under the PT2020 Partnership. ND was a holder of PhD fellowship from the FCT (Ref. N°:SFRH/BD/51877/2012), attributed 10 by Inter-University Doctoral Programme in Ageing and Chronic Disease (PhDOC). LA was a holder of a FCT PhD fellowship (PD/BD/114254/2016), attributed by the ProRegem Doctoral Programme in 2016. Declaration of Interests: KS is CEO and shareholder of of Lipotype GmbH. CL and MG are employees of Lipotype GmbH. All other authors declare that they do not have any competing interests. Ethics Approval Statement: The entire process was approved by the Ethical Review Board of the Faculty of Medicine of the New University of Lisbon and the Ethics Committee for Health of the Centro Hospitalar de Lisboa Ocidental, that includes the Hospital Santa Cruz, the Hospital Egas Moniz and Hospital Sao Francisco Xavier, and the Ethics Committee for Health of the Hospital Fernando Fonseca. All experiments were performed in accordance with the guidelines and regulations including, the Universal Declaration on Bioethics and Human Rights of UNESCO, 2005; The Charter of Fundamental rights of the EU, 2012; Ethical principles for medical research involving human subjects - Declaration of Helsinki, 2013; EU Regulation 2016/679 and Good Clinical Practice guidelines (Directive 2001/20/EC) and EU Clinical Trials Directive (2005/28/EC). Moreover, they complied with national legislations for the scientific use of human biological samples (Law No 12/2005 and No 131/2014).

Summary After demyelinating injury of the central nervous system, resolution of the mounting acute inflammation is crucial for the initiation of a regenerative response. Here, we aim to identify fatty acids and lipid mediators that govern the balance of inflammatory reactions within demyelinating lesions. Using lipidomics, we identify bioactive lipids in the resolution phase of inflammation with markedly elevated levels of n-3 polyunsaturated fatty acids. Using fat-1 transgenic mice, which convert n-6 fatty acids to n-3 fatty acids, we find that reduction of the n-6/n-3 ratio decreases the phagocytic infiltrate. In addition, we observe accelerated decline of microglia/macrophages and enhanced generation of oligodendrocytes in aged mice when n-3 fatty acids are shuttled to the brain. Thus, n-3 fatty acids enhance lesion recovery and may, therefore, provide the basis for pro-regenerative medicines of demyelinating diseases in the central nervous system., Graphical abstract, Highlights • Lipid and fatty acid abundance is specifically altered during de- and remyelination • Reduction of pro- and anti-inflammatory lipid mediators impairs lesion recovery • DHA supplementation fosters phagocyte decline and oligodendrocyte generation • n-3 fatty acid supplementation may be a strategy to promote remyelination, Penkert et al. employ sequential proteomics and lipidomics to elucidate the role of lipid mediators in lesion recovery in a mouse model of focal, cerebral demyelination. Using genetic and pharmacologic interventions, they find n-3 fatty acid supplementation, specifically DHA, to enhance innate inflammation resolution and oligodendrocyte generation.

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.

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.

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.

Context Meal timing affects metabolic homeostasis and body weight, but how composition and timing of meals affect plasma lipidomics in humans is not well studied. Objective We used high throughput shotgun plasma lipidomics to investigate effects of timing of carbohydrate and fat intake on lipid metabolism and its relation to glycemic control. Design 29 nondiabetic men consumed (1) a high-carb test meal (MTT-HC) at 09.00 and a high-fat meal (MTT-HF) at 15.40; or (2) MTT-HF at 09.00 and MTT-HC at 15.40. Blood was sampled before and 180 minutes after completion of each MTT. Subcutaneous adipose tissue (SAT) was collected after overnight fast and both MTTs. Prior to each investigation day, participants consumed a 4-week isocaloric diet of the same composition: (1) high-carb meals until 13.30 and high-fat meals between 16.30 and 22:00 or (2) the inverse order. Results 12 hour daily lipid patterns showed a complex regulation by both the time of day (67.8%) and meal composition (55.4%). A third of lipids showed a diurnal variation in postprandial responses to the same meal with mostly higher responses in the morning than in the afternoon. Triacylglycerols containing shorter and more saturated fatty acids were enriched in the morning. SAT transcripts involved in fatty acid synthesis and desaturation showed no diurnal variation. Diurnal changes of 7 lipid classes were negatively associated with insulin sensitivity, but not with glucose and insulin response or insulin secretion. Conclusions This study identified postprandial plasma lipid profiles as being strongly affected by meal timing and associated with insulin sensitivity.

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.

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

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.

MotivationAnalyzing associations among multiple omic variables to infer mechanisms that meaningfully link them is a crucial step in systems biology. Gene Set Enrichment Analysis (GSEA) was conceived to pursue this aim in computational genomics, unveiling significant pathways associated to certain gene signatures under investigation. Lipidomics is a rapidly growing omic field, and absolute quantification of lipid abundance by shotgun mass spectrometry is generating high-throughput datasets that depict lipid metabolism in a plethora of conditions and organisms. In addition, high-throughput lipidomics represents a new important ally to develop personalized medicine approaches, investigate the causes and predict effective biomarkers in metabolic diseases, and not only.ResultsHere, we present Lipid Pathway Enrichment Analysis (LIPEA), a web-tool for over-representation analysis of lipid signatures and detection of the biological pathways in which they are enriched. LIPEA is a new valid resource for biologists and physicians to mine pathways significantly associated to a set of lipids, helping them to discover whether common and collective mechanisms are hidden behind those lipids. LIPEA was extensively tested and we provide two examples where our system gave successfully results related with Major Depression Disease (MDD) and insulin re-sistance.AvailabilityThe tool is available as web platform at https://lipea.biotec.tu-dresden.de.

The lysosomal acid beta-glucosidase GBA1 and the non-lysosomal beta-glucosidase GBA2 degrade glucosylceramide (GlcCer) to glucose and ceramide in different cellular compartments. Loss of GBA2 activity and the resulting accumulation of GlcCer results in male infertility, whereas mutations in the GBA1 gene and loss of GBA1 activity cause the lipid-storage disorder Gaucher disease. However, the role of GBA2 in Gaucher disease pathology and its relationship to GBA1 is not well understood. Here, we report a GBA1-dependent down-regulation of GBA2 activity in patients with Gaucher disease. Using an experimental approach combining cell biology, biochemistry, and mass spectrometry, we show that sphingosine, the cytotoxic metabolite accumulating in Gaucher cells through the action of GBA2, directly binds to GBA2 and inhibits its activity. We propose a negative feed-back loop, in which sphingosine inhibits GBA2 activity in Gaucher cells, preventing further sphingosine accumulation and, thereby, cytotoxicity. Our findings add a new chapter to the understanding of the complex molecular mechanism underlying Gaucher disease and the regulation of beta-glucosidase activity in general.

Summary Ectopic lipid deposition and altered mitochondrial dynamics contribute to the development of obesity and insulin resistance. However, the mechanistic link between these processes remained unclear. Here we demonstrate that the C16:0 sphingolipid synthesizing ceramide synthases, CerS5 and CerS6, affect distinct sphingolipid pools and that abrogation of CerS6 but not of CerS5 protects from obesity and insulin resistance. We identify proteins that specifically interact with C16:0 sphingolipids derived from CerS5 or CerS6. Here, only CerS6-derived C16:0 sphingolipids bind the mitochondrial fission factor (Mff). CerS6 and Mff deficiency protect from fatty acid-induced mitochondrial fragmentation in vitro, and the two proteins genetically interact in vivo in obesity-induced mitochondrial fragmentation and development of insulin resistance. Our experiments reveal an unprecedented specificity of sphingolipid signaling depending on specific synthesizing enzymes, provide a mechanistic link between hepatic lipid deposition and mitochondrial fragmentation in obesity, and define the CerS6-derived sphingolipid/Mff interaction as a therapeutic target for metabolic 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

The cisternal progression/maturation model of Golgi trafficking predicts that cis-Golgi cisternae are formed de novo on the cis-side of the Golgi. Here we describe structural and functional intermediates of the cis cisterna assembly process in high-pressure frozen algae (Scherffelia dubia, Chlamydomonas reinhardtii) and plants (Arabidopsis thaliana, Dionaea muscipula; Venus Flytrap) as determined by electron microscopy, electron tomography and immuno-electron microscopy techniques. Our findings are as follows: (1) The cis-most (C1) Golgi cisternae are generated de novo from cisterna initiators produced by the fusion of 3–5 COPII vesicles in contact with a C2 cis cisterna. (2) COPII vesicles fuel the growth of the initiators, which then merge into a coherent C1 cisterna. (3) When a C1 cisterna nucleates its first cisterna initiator it becomes a C2 cisterna. (4) C2-Cn cis cisternae grow through COPII vesicle fusion. (5) ER-resident proteins are recycled from cis cisternae to the ER via COPIa-type vesicles. (6) In S. dubia the C2 cisternae are capable of mediating the self-assembly of scale protein complexes. (7) In plants, ~90% of native α-mannosidase I localizes to medial Golgi cisternae. (8) Biochemical activation of cis cisternae appears to coincide with their conversion to medial cisternae via recycling of medial cisterna enzymes. We propose how the different cis cisterna assembly intermediates of plants and algae may actually be related to those present in the ERGIC and in the pre-cis Golgi cisterna layer in mammalian cells.

Summary Human immunodeficiency virus type 1 (HIV-1) is a retrovirus that obtains its lipid envelope by budding through the plasma membrane of infected host cells. Various studies indicated that the HIV-1 membrane differs from the producer cell plasma membrane suggesting virus budding from pre-existing subdomains or virus-mediated induction of a specialized budding membrane. To perform a comparative lipidomics analysis by quantitative mass spectrometry, we first evaluated two independent methods to isolate the cellular plasma membrane. Subsequent lipid analysis of plasma membranes and HIV-1 purified from two different cell lines revealed a significantly different lipid composition of the viral membrane compared with the host cell plasma membrane, independent of the cell type investigated. Virus particles were significantly enriched in phosphatidylserine, sphingomyelin, hexosylceramide and saturated phosphatidylcholine species when compared with the host cell plasma membrane of the producer cells; they showed reduced levels of unsaturated phosphatidylcholine species, phosphatidylethanolamine and phosphatidylinositol. Cell type-specific differences in the lipid composition of HIV-1 and donor plasmamembranes were observed for plasmalogen–phosphatidylethanolamine and phosphatidylglycerol, which were strongly enriched only in HIV-1 derived from MT-4 cells. MT-4 cell-derived HIV-1 also contained dihydrosphingomyelin as reported previously, but this lipid class was also enriched in the host cell membrane. Taken together, these data strongly support the hypothesis that HIV-1 selects a specific lipid environment for its morphogenesis.

Sphingolipids are essential structural components of cellular membranes and are crucial regulators of cellular processes. While current high-throughput approaches allow for the systematic mapping of interactions of soluble proteins with their lipid-binding partners, photo-cross-linking is the only technique that enables for the proteome-wide mapping of integral membrane proteins with their direct lipid environment. Here, we report the synthesis of a photoactivatable and clickable analog of sphingosine (pacSph). When administered to sphingosine-1-phosphate lyase deficient cells, pacSph allows its metabolic fate and the subcellular flux of de novo synthesized sphingolipids to be followed in a time-resolved manner. The chemoproteomic profiling yielded over 180 novel sphingolipid-binding proteins, of which we validated a number, demonstrating the unique value of this technique as a discovery tool. This work provides an important resource for the understanding of the global cellular interplay between sphingolipids and their interacting proteins.

Analysis of the lipid composition of influenza virus–infected cells provides support for the membrane raft-based biogenesis model., The influenza virus (IFV) acquires its envelope by budding from host cell plasma membranes. Using quantitative shotgun mass spectrometry, we determined the lipidomes of the host Madin–Darby canine kidney cell, its apical membrane, and the IFV budding from it. We found the apical membrane to be enriched in sphingolipids (SPs) and cholesterol, whereas glycerophospholipids were reduced, and storage lipids were depleted compared with the whole-cell membranes. The virus membrane exhibited a further enrichment of SPs and cholesterol compared with the donor membrane at the expense of phosphatidylcholines. Our data are consistent with and extend existing models of membrane raft-based biogenesis of the apical membrane and IFV envelope.

Ten years ago, we wrote a Review on lipid rafts and signalling in the launch issue of Nature Reviews Molecular Cell Biology. At the time, this field was suffering from ambiguous methodology and imprecise nomenclature. Now, new techniques are deepening our insight into the dynamics of membrane organization. Here, we discuss how the field has matured and present an evolving model in which membranes are occupied by fluctuating nanoscale assemblies of sphingolipids, cholesterol and proteins that can be stabilized into platforms that are important in signalling, viral infection and membrane trafficking.

The trans-Golgi network (TGN) is the major sorting station in the secretory pathway of all eukaryotic cells. How the TGN sorts proteins and lipids to generate the enrichment of sphingolipids and sterols at the plasma membrane is poorly understood. To address this fundamental question in membrane trafficking, we devised an immunoisolation procedure for specific recovery of post-Golgi secretory vesicles transporting a transmembrane raft protein from the TGN to the cell surface in the yeast Saccharomyces cerevisiae. Using a novel quantitative shotgun lipidomics approach, we could demonstrate that TGN sorting selectively enriched ergosterol and sphingolipid species in the immunoisolated secretory vesicles. This finding, for the first time, indicates that the TGN exhibits the capacity to sort membrane lipids. Furthermore, the observation that the immunoisolated vesicles exhibited a higher membrane order than the late Golgi membrane, as measured by C-Laurdan spectrophotometry, strongly suggests that lipid rafts play a role in the TGN-sorting machinery.

Cell membranes predominantly consist of lamellar lipid bilayers. When studied in vitro, however, many membrane lipids can exhibit non-lamellar morphologies, often with cubic symmetries. An open issue is how lipid polymorphisms influence organelle and cell shape. Here, we used controlled dimerization of artificial membrane proteins in mammalian tissue culture cells to induce an expansion of the endoplasmic reticulum (ER) with cubic symmetry. Although this observation emphasizes ER architectural plasticity, we found that the changed ER membrane became sequestered into large autophagic vacuoles, positive for the autophagy protein LC3. Autophagy may be targeting irregular membrane shapes and/or aggregated protein. We suggest that membrane morphology can be controlled in cells.

Protein–lipid interactions within the membrane are difficult to detect with mass spectrometry because of the hydrophobicity of tryptic cleavage peptides on the one hand and the noncovalent nature of the protein–lipid interaction on the other hand. Here we describe a proof-of-principle method capable of resolving hydrophobic and acylated (e.g., myristoylated) peptides by optimizing the steps in a mass spectrometric workflow. We then use this optimized workflow to detect a protein–lipid interaction in vitro within the hydrophobic phase of the membrane that is preserved via a covalent cross-link using a photoactivatable lipid. This approach can also be used to map the site of a protein–lipid interaction as we identify the peptide in contact with the fatty acid part of ceramide in the START domain of the CERT protein.

Cell membranes contain hundreds to thousands of individual lipid species that are of structural importance but also specifically interact with proteins. Due to their highly controlled synthesis and role in signaling events sphingolipids are an intensely studied class of lipids. In order to investigate their metabolism and to study proteins interacting with sphingolipids, metabolic labeling based on photoactivatable sphingoid bases is the most straightforward approach. In order to monitor protein-lipid-crosslink products, sphingosine derivatives containing a reporter moiety, such as a radiolabel or a clickable group, are used. In normal cells, degradation of sphingoid bases via action of the checkpoint enzyme sphingosine-1-phosphate lyase occurs at position C2-C3 of the sphingoid base and channels the resulting hexadecenal into the glycerolipid biosynthesis pathway. In case the functionalized sphingosine looses the reporter moiety during its degradation, specificity towards sphingolipid labeling is maintained. In case degradation of a sphingosine derivative does not remove either the photoactivatable or reporter group from the resulting hexadecenal, specificity towards sphingolipid labeling can be achieved by blocking sphingosine-1-phosphate lyase activity and thus preventing sphingosine derivatives to be channeled into the sphingolipid-to-glycerolipid metabolic pathway. Here we report an approach using clustered, regularly interspaced, short palindromic repeats (CRISPR)-associated nuclease Cas9 to create a sphingosine-1-phosphate lyase (SGPL1) HeLa knockout cell line to disrupt the sphingolipid-to-glycerolipid metabolic pathway. We found that the lipid and protein compositions as well as sphingolipid metabolism of SGPL1 knock-out HeLa cells only show little adaptations, which validates these cells as model systems to study transient protein-sphingolipid interactions.

Human immunodeficiency virus type 1 (HIV-1) is a retrovirus that obtains its lipid envelope by budding through the plasma membrane of infected host cells. Various studies indicated that the HIV-1 membrane differs from the producer cell plasma membrane suggesting virus budding from pre-existing subdomains or virus-mediated induction of a specialized budding membrane. To perform a comparative lipidomics analysis by quantitative mass spectrometry, we first evaluated two independent methods to isolate the cellular plasma membrane. Subsequent lipid analysis of plasma membranes and HIV-1 purified from two different cell lines revealed a significantly different lipid composition of the viral membrane compared with the host cell plasma membrane, independent of the cell type investigated. Virus particles were significantly enriched in phosphatidylserine, sphingomyelin, hexosylceramide and saturated phosphatidylcholine species when compared with the host cell plasma membrane of the producer cells; they showed reduced levels of unsaturated phosphatidylcholine species, phosphatidylethanolamine and phosphatidylinositol. Cell type-specific differences in the lipid composition of HIV-1 and donor plasmamembranes were observed for plasmalogen-phosphatidylethanolamine and phosphatidylglycerol, which were strongly enriched only in HIV-1 derived from MT-4 cells. MT-4 cell-derived HIV-1 also contained dihydrosphingomyelin as reported previously, but this lipid class was also enriched in the host cell membrane. Taken together, these data strongly support the hypothesis that HIV-1 selects a specific lipid environment for its morphogenesis.

Mass spectrometry-based shotgun lipidomics has enabled the quantitative and comprehensive assessment of cellular lipid compositions. The yeast Saccharomyces cerevisiae has proven to be a particularly valuable experimental system for studying lipid-related cellular processes. Here, by applying our shotgun lipidomics platform, we investigated the influence of a variety of commonly used growth conditions on the yeast lipidome, including glycerophospholipids, triglycerides, ergosterol as well as complex sphingolipids. This extensive dataset allowed for a quantitative description of the intrinsic flexibility of a eukaryotic lipidome, thereby providing new insights into the adjustments of lipid biosynthetic pathways. In addition, we established a baseline for future lipidomic experiments in yeast. Finally, flexibility of lipidomic features is proposed as a new parameter for the description of the physiological state of an organism.

With cellular organelles coming in all shapes and sizes, the principle 'form follows function' is readily discernible through the cytologist's lens. Architecturally, one might ask whether there is feedback in this organization. Does a cell 'know' when it has constructed membrane into the stacks of the Golgi, the cisternae of the mitochondria or the tubules of the endoplasmic reticulum? Proofreading can occur in vivo as both errors in nucleic acids and misfolds in proteins are recognized by the cell. Are there analogous systems which maintain/regulate the architectural integrity of organelles? Our recent paper entitled Generation of cubic membranes from controlled homotypic interactions of membrane proteins in the endoplasmic reticulum suggests that autophagy may play such a role.

The yeast Saccharomyces cerevisiae is able to use some biotin precursors for biotin biosynthesis. Insertion of a sulfur atom into desthiobiotin, the final step in the biosynthetic pathway, is catalyzed by biotin synthase (Bio2). This mitochondrial protein contains two iron-sulfur (Fe/S) clusters that catalyze the reaction and are thought to act as a sulfur donor. To identify new components of biotin metabolism, we performed a genetic screen and found that Isa2, a mitochondrial protein involved in the formation of Fe/S proteins, is necessary for the conversion of desthiobiotin to biotin. Depletion of Isa2 or the related Isa1, however, did not prevent the de novo synthesis of any of the two Fe/S centers of Bio2. In contrast, Fe/S cluster assembly on Bio2 strongly depended on the Isu1 and Isu2 proteins. Both isa mutants contained low levels of Bio2. This phenotype was also found in other mutants impaired in mitochondrial Fe/S protein assembly and in wild-type cells grown under iron limitation. Low Bio2 levels, however, did not cause the inability of isa mutants to utilize desthiobiotin, since this defect was not cured by overexpression of BIO2 . Thus, the Isa proteins are crucial for the in vivo function of biotin synthase but not for the de novo synthesis of its Fe/S clusters. Our data demonstrate that the Isa proteins are essential for the catalytic activity of Bio2 in vivo.