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Background\udPsychotic experiences (PEs) are associated with an increased risk of future psychotic and non-psychotic mental disorders. The identification of biomarkers of PEs may provide insights regarding the underlying pathophysiology.\ud\udMethods\udThe current study applied targeted lipidomic approaches to compare plasma lipid profiles in participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who did (n = 206) or did not (n = 206) have PEs when aged approximately 24 years.\ud\udResults\udIn total, 202 lipids including 8 lipid classes were measured by using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). Eight lipid clusters were generated. Thirteen individual lipids were nominally significantly higher in the PEs group compared to the control group. After correction for multiple comparisons, 9 lipids comprising 3 lysophosphatidylcholines (LPCs), 2 phosphatidylcholines (PCs) and 4 triacylglycerols (TGs) remained significant. In addition, PEs cases had increased levels of TGs and LPCs with a low double bond count.\ud\udConclusions\udThese findings indicate plasma lipidomic abnormalities in individuals experiencing PEs. The lipidomic profile measures could aid our understanding of the underlying pathophysiological mechanisms.

Supplementary Methods from Novel Theranostic Opportunities Offered by Characterization of Altered Membrane Lipid Metabolism in Breast Cancer Progression

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Aims Pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is expressed mainly in the liver and at low levels in the heart, regulates cholesterol levels by directing low-density lipoprotein receptors to degradation. Studies to determine the role of PCSK9 in the heart are complicated by the close link between cardiac function and systemic lipid metabolism. Here, we sought to elucidate the function of PCSK9 specifically in the heart by generating and analysing mice with cardiomyocyte-specific Pcsk9 deficiency (CM-Pcsk9−/− mice) and by silencing Pcsk9 acutely in a cell culture model of adult cardiomyocyte-like cells. Methods and results Mice with cardiomyocyte-specific deletion of Pcsk9 had reduced contractile capacity, impaired cardiac function, and left ventricular dilatation at 28 weeks of age and died prematurely. Transcriptomic analyses revealed alterations of signalling pathways linked to cardiomyopathy and energy metabolism in hearts from CM-Pcsk9−/− mice vs. wild-type littermates. In agreement, levels of genes and proteins involved in mitochondrial metabolism were reduced in CM-Pcsk9−/− hearts. By using a Seahorse flux analyser, we showed that mitochondrial but not glycolytic function was impaired in cardiomyocytes from CM-Pcsk9−/− mice. We further showed that assembly and activity of electron transport chain (ETC) complexes were altered in isolated mitochondria from CM-Pcsk9−/− mice. Circulating lipid levels were unchanged in CM-Pcsk9−/− mice, but the lipid composition of mitochondrial membranes was altered. In addition, cardiomyocytes from CM-Pcsk9−/− mice had an increased number of mitochondria–endoplasmic reticulum contacts and alterations in the morphology of cristae, the physical location of the ETC complexes. We also showed that acute Pcsk9 silencing in adult cardiomyocyte-like cells reduced the activity of ETC complexes and impaired mitochondrial metabolism. Conclusion PCSK9, despite its low expression in cardiomyocytes, contributes to cardiac metabolic function, and PCSK9 deficiency in cardiomyocytes is linked to cardiomyopathy, impaired heart function, and compromised energy production.

Current evidence suggests that gut microbiome derived lipids play crucial role in the regulation of host lipid metabolism. However, not much is known about the dynamics of gut microbial lipids within the distinct gut biogeographic. Here we employed targeted and untargeted lipidomics in thein vitroderived feces. Simulated intestinal chyme was collected fromin vitrogut vessels (V1–V4), representing proximal to distal parts of the colon after 24 and 48 h with/without PDX treatment. In total 44 simulated chyme samples were collected from thein vitrocolon simulator. Factor analysis showed that vessel and time had the strongest impact on the simulated intestinal chyme lipid profiles. We found that levels of phosphatidylcholines, sphingomyelins, triacylglycerols and endocannabinoids were altered in at least one vessel (V1–V4) during simulation. We also found that concentrations of triacylglycerols, diacylglycerols and endocannabinoids changed with time (24 vs. 48 h simulation). Together, we found that the simulated intestinal chyme revealed a wide range of lipids that remained altered in different compartments of the human colon model over time.

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data. Funding Agencies|SciLifeLab; Swedish Research Council (Vetenskapsradet)Swedish Research Council [D0886501]; US National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [MH077139, MH1095320]; European UnionEuropean Commission [610307, 733161, 825843]; Swedish Cancer SocietySwedish Cancer Society; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-02837, 2014-03352, 2009-1039, 2018-03307]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation; Karolinska Institutet, Karolinska University HospitalKarolinska Institutet; Radiumhemmets Forskningsfonder; European Research CouncilEuropean Research Council (ERC)European Commission [CoG-2015_681742_NASCENT]; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation [20160872]; Swedish Foundation for Strategic Research (IRC Center); Novo Nordisk FoundationNovo Nordisk FoundationNovocure Limited; ALF; Strategic Research Area Epidemiology at Karolinska Institutet; Swedish Rheumatism Association; Vth 80-year Foundation; Swedish Society of Medicine; Clinical Research Support (Avtal om Lakarutbildning och Forskning); Swedish government; county councils; ALF-agreement; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [15-0067]; IMI2 Joint Undertaking [115974]; European Federation of Pharmaceutical Industries and Associations with JDRF; H2020 Program ERA PerMed JTC 2018 Call (VR) [2018-05619]

This review focuses on the recent findings from lipidomics studies as related to nutrition and health research.Several lipidomics studies have investigated malnutrition, including both under- and overnutrition. Focus has been both on the early-life nutrition as well as on the impact of overfeeding later in life. Multiple studies have investigated the impact of different macronutrients in lipidome on human health, demonstrating that overfeeding with saturated fat is metabolically more harmful than overfeeding with polyunsaturated fat or carbohydrate-rich food. Diet rich in saturated fat increases the lipotoxic lipids, such as ceramides and saturated fatty-acyl-containing triacylglycerols, increasing also the low-density lipoprotein aggregation rate. In contrast, diet rich in polyunsaturated fatty acids, such as n-3 fatty acids, decreases the triacylglycerol levels, although some individuals are poor responders to n-3 supplementation.The results highlight the benefits of lipidomics in clinical nutrition research, also providing an opportunity for personalized nutrition. An area of increasing interest is the interplay of diet, gut microbiome, and metabolome, and how they together impact individuals' responses to nutritional challenges.

Aims Cardiac injury and remodelling are associated with the rearrangement of cardiac lipids. Glycosphingolipids are membrane lipids that are important for cellular structure and function, and cardiac dysfunction is a characteristic of rare monogenic diseases with defects in glycosphingolipid synthesis and turnover. However, it is not known how cardiac glycosphingolipids regulate cellular processes in the heart. The aim of this study is to determine the role of cardiac glycosphingolipids in heart function. Methods and results Using human myocardial biopsies, we showed that the glycosphingolipids glucosylceramide and lactosylceramide are present at very low levels in non-ischaemic human heart with normal function and are elevated during remodelling. Similar results were observed in mouse models of cardiac remodelling. We also generated mice with cardiomyocyte-specific deficiency in Ugcg, the gene encoding glucosylceramide synthase (hUgcg–/– mice). In 9- to 10-week-old hUgcg–/– mice, contractile capacity in response to dobutamine stress was reduced. Older hUgcg–/– mice developed severe heart failure and left ventricular dilatation even under baseline conditions and died prematurely. Using RNA-seq and cell culture models, we showed defective endolysosomal retrograde trafficking and autophagy in Ugcg-deficient cardiomyocytes. We also showed that responsiveness to β-adrenergic stimulation was reduced in cardiomyocytes from hUgcg–/– mice and that Ugcg knockdown suppressed the internalization and trafficking of β1-adrenergic receptors. Conclusions Our findings suggest that cardiac glycosphingolipids are required to maintain β-adrenergic signalling and contractile capacity in cardiomyocytes and to preserve normal heart function., Graphical Abstract Cardiac glycosphingolipids are required to maintain β-adrenergic signaling and contractile capacity in cardiomyocytes and to preserve normal heart function.

Current evidence suggests that chemical exposure alters gut microbiota composition, with higher exposure to environmental chemicals being associated with reduced microbiome diversity. However, not much is known about the impact of per- and polyfluoroalkyl substances (PFAS) on gut bacteria. Here we set out to identify the gut bacterial species that associate with chemical exposure before (maternal) and after (maternal, infant) birth in a mother-infant series. Paired blood and stool samples were collected from mother-infant dyads (n = 30) in a longitudinal setting. PFAS were quantified in maternal blood to examine their associations with the microbial compositions (determined by shotgun metagenomic sequencing) in mothers and infants. High maternal exposure to PFAS was persistently associated with increased abundance ofMethanobrevibacter smithiiin maternal stool. Among individual PFAS compounds, PFOS and PFHpS showed the strongest connection withM. smithii. However, maternal PFAS exposure associated only weakly with the infant microbiome. Our findings suggest that PFAS exposure contributes to the modulation of the adult gut microbiome composition.

Aims/hypothesis Previous metabolomics studies suggest that type 1 diabetes is preceded by specific metabolic disturbances. The aim of this study was to investigate whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children who later develop pancreatic beta cell autoimmunity or overt type 1 diabetes. Methods In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who (1) progressed to type 1 diabetes (PT1D, n = 34), (2) seroconverted to ≥1 islet autoantibody without progressing to type 1 diabetes (P1Ab, n = 27) or (3) remained autoantibody negative during follow-up (CTRL, n = 10). Results During the first year of life, levels of most lipids and polar metabolites were lower in the PT1D and P1Ab groups compared with the CTRL group. Pathway over-representation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were over-represented in PT1D. Genome-scale metabolic models of PBMCs during type 1 diabetes progression were developed by using publicly available transcriptomics data and constrained with metabolomics data from our study. Metabolic modelling confirmed altered ceramide pathways, known to play an important role in immune regulation, as specifically associated with type 1 diabetes progression. Conclusions/interpretation Our data suggest that systemic dysregulation of lipid metabolism, as observed in plasma, may impact the metabolism and function of immune cells during progression to overt type 1 diabetes. Data availability The GEMs for PBMCs have been submitted to BioModels (www.ebi.ac.uk/biomodels/), under accession number MODEL1905270001. The metabolomics datasets and the clinical metadata generated in this study were submitted to MetaboLights (https://www.ebi.ac.uk/metabolights/), under accession number MTBLS1015.

Bipolar disorder (BD) is a mood disorder characterized by the occurrence of depressive episodes alternating with episodes of elevated mood (known as mania). There is also an increased risk of other medical comorbidities.This work uses a systems biology approach to compare BD treated patients with healthy controls (HCs), integrating proteomics and metabolomics data using partial correlation analysis in order to observe the interactions between altered proteins and metabolites, as well as proposing a potential metabolic signature panel for the disease.Data integration between proteomics and metabolomics was performed using GC-MS data and label-free proteomics from the same individuals (N = 13; 5 BD, 8 HC) using generalized canonical correlation analysis and partial correlation analysis, and then building a correlation network between metabolites and proteins. Ridge-logistic regression models were developed to stratify between BD and HC groups using an extended metabolomics dataset (N = 28; 14 BD, 14 HC), applying a recursive feature elimination for the optimal selection of the metabolites.Network analysis demonstrated links between proteins and metabolites, pointing to possible alterations in hemostasis of BD patients. Ridge-logistic regression model indicated a molecular signature comprising 9 metabolites, with an area under the receiver operating characteristic curve (AUROC) of 0.833 (95% CI 0.817-0.914).From our results, we conclude that several metabolic processes are related to BD, which can be considered as a multi-system disorder. We also demonstrate the feasibility of partial correlation analysis for integration of proteomics and metabolomics data in a case-control study setting.

Current evidence suggests that the composition of infant formula (IF) affects the gut microbiome, intestinal function, and immune responses during infancy. However, the impact of IF on circulating lipid profiles in infants is still poorly understood. The objectives of this study were to (1) investigate how extensively hydrolyzed IF impacts serum lipidome compared to conventional formula and (2) to associate changes in circulatory lipids with gastrointestinal biomarkers including intestinal permeability.In a randomized, double-blind controlled nutritional intervention study (Concentrations of sphingomyelins were higher in the HF group as compared to the RF group. Triacylglycerols (TGs) containing saturated and monounsaturated fatty acyl chains were found in higher levels in the HF group at 3 months, but downregulated at 9 and 12 months of age. LM ratio was lower in the HF group at 9 months of age. In the RF group, the LM ratio was positively associated with ether-linked lipids. Such an association was, however, not observed in the HF group.Our study suggests that HF intervention changes the circulating lipidome, including those lipids previously found to be associated with progression to islet autoimmunity or overt T1D.[Clinicaltrials.gov], identifier [NCT01735123].

Funder: European Commission, BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) is a progressive liver disease with potentially severe complications including cirrhosis and hepatocellular carcinoma. Previously, we have identified circulating lipid signatures associating with liver fat content and non-alcoholic steatohepatitis (NASH). Here, we develop a metabolomic map across the NAFLD spectrum, defining interconnected metabolic signatures of steatosis (non-alcoholic fatty liver, NASH, and fibrosis). METHODS: We performed mass spectrometry analysis of molecular lipids and polar metabolites in serum samples from the European NAFLD Registry patients (n = 627), representing the full spectrum of NAFLD. Using various univariate, multivariate, and machine learning statistical approaches, we interrogated metabolites across 3 clinical perspectives: steatosis, NASH, and fibrosis. RESULTS: Following generation of the NAFLD metabolic network, we identify 15 metabolites unique to steatosis, 18 to NASH, and 15 to fibrosis, with 27 common to all. We identified that progression from F2 to F3 fibrosis coincides with a key pathophysiological transition point in disease natural history, with n = 73 metabolites altered. CONCLUSIONS: Analysis of circulating metabolites provides important insights into the metabolic changes during NAFLD progression, revealing metabolic signatures across the NAFLD spectrum and features that are specific to NAFL, NASH, and fibrosis. The F2-F3 transition marks a critical metabolic transition point in NAFLD pathogenesis, with the data pointing to the pathophysiological importance of metabolic stress and specifically oxidative stress. CLINICAL TRIALS REGISTRATION: The study is registered at Clinicaltrials.gov (NCT04442334). LAY SUMMARY: Non-alcoholic fatty liver disease is characterised by the build-up of fat in the liver, which progresses to liver dysfunction, scarring, and irreversible liver failure, and is markedly increasing in its prevalence worldwide. Here, we measured lipids and other small molecules (metabolites) in the blood with the aim of providing a comprehensive molecular overview of fat build-up, liver fibrosis, and diagnosed severity. We identify a key metabolic 'watershed' in the progression of liver damage, separating severe disease from mild, and show that specific lipid and metabolite profiles can help distinguish and/or define these cases.

Previous studies suggest that the human gut microbiome is dysregulated in islet autoimmunity, preceding the clinical onset of type 1 diabetes (T1D). The microbiota of the gut plays an important role in the regulation of bile acid (BA) metabolism. However, not much is known about the regulation of BAs during progression to T1D. Here, we analyzed BAs in a longitudinal series of serum (n= 333) and stool (n= 304) samples, collected at 3, 6, 12, 18, 24 and 36 months of age, from children who developed a single islet autoantibody (P1Ab), multiple islet autoantibodies (P2Ab), and controls (CTRs) who remained autoantibody (AAb) negative during the follow-up. In addition, we analyzed the stool microbiome by shotgun metagenomics in a subgroup of these children (n=111). Factor analysis showed that age had the strongest impact on BA and microbiome profiles. We found that, at an early age, the systemic BA (including taurine and glycine conjugates) and microbial secondary BA pathways were altered in the P2Ab group as compared to the P1Ab or CTR groups. Our findings thus suggest that dysregulated BA metabolism in early life may contribute to the risk and pathogenesis of T1D.

Environmental factors are strongly implicated in late-onset of inflammatory bowel disease. Here, we investigate whether high levels of perfluoroalkyl substances are associated with (1) late-onset inflammatory bowel disease, and (2) disturbances of the bile acid pool. We further explore the effect of the specific perfluoroalkyl substance perfluorooctanoic acid on intestinal barrier function in murine tissue.Serum levels of perfluoroalkyl substances and bile acids were assessed by ultra-performance liquid chromatography coupled to a triple-quadrupole mass spectrometer in matched samples from patients with ulcerative colitis (The total amount of perfluoroalkyl substances was significantly increased in patients with ulcerative colitis compared to healthy controls and patients with Crohn's disease (Our results demonstrate that perfluoroalkyl substances levels are increased in patients with late-onset ulcerative colitis and may contribute to the disease by inducing a dysfunctional intestinal barrier.

T cell activation, proliferation, and differentiation involve metabolic reprogramming resulting from the interplay of genes, proteins, and metabolites. Here, we aim to understand the metabolic pathways involved in the activation and functional differentiation of human CD4

BackgroundDNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2 % of human CpG sites. To detect such associations outside these regions, we chose the bisulfite sequencing approach.MethodsWe collected and curated all available clinical data on 200 newborn infants; whose umbilical cord blood samples were analyzed with the reduced representation bisulfite sequencing (RRBS) method. A generalized linear mixed effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis.ResultsWe discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models.ConclusionsThe inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. With standard significance thresholds, type 1 error rates were high with both these implementations, across alternative parameter settings and analysis strategies. We conclude that comb-p and RADMeth are convenient methods for the detection of differentially methylated regions, but the statistical significance should either be determined empirically or before the spatial adjustment. Our RRBS data analysis workflow is available inhttps://github.com/EssiLaajala/RRBS_workflow.

The composition of human breast milk is highly variable inter- and intra-individually. Environmental factors are suspected to contribute to such compositional variation, however, their impact on breast milk composition is currently poorly understood. We sought to (1) define the impact of maternal exposure to per- and polyfluoroalkyl substances (PFAS) on lipid composition of human breast milk, and (2) to study the combined impact of maternal PFAS exposure and breast milk lipid composition on the growth of the infants.In a mother-infant study (n = 44) we measured the levels of PFAS and lipids in maternal serum and conducted lipidomics analysis of breast milk collect 2–4 days after the delivery and at 3 months of infant age, by using ultra high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry. Gastrointestinal biomarkers fecal calprotectin and human beta defensin 2 were measured in the stool samples at the age of 3, 6, 9, and 12 months. Maternal diet was studied by a validated food frequency questionnaire. PFAS levels were inversely associated with total lipid levels in the breast milk collected after the delivery. In the high exposure group, the ratio of acylated saturated and polyunsaturated fatty acids in triacylglycerols was increased. Moreover, high exposure to PFAS associated with the altered phospholipid composition, which was indicative of unfavorable increase in the size of milk fat globules. These changes in the milk lipid composition were further associated with slower infant growth and with elevated intestinal inflammatory markers. Our data suggest that the maternal exposure to PFAS impacts the nutritional quality of the breast milk, which, in turn, may have detrimental impact on the health and growth of the children later in life. publishedVersion

Ceramides are bioactive sphingolipids, comprised of sphingosine and a fatty acyl chain. They have been recognized as key mediators of lipotoxicity; a phenomenon where excess fat in adipose tissue l ...

BackgroundChemical composition of human breast milk is highly variable inter- and intra-individually. Environmental factors are suspected to partly explain the compositional variation, however, their impact on breast milk composition is currently poorly understood.ObjectivesWe sought (1) to define the impact of maternal exposure to per- and polyfluoroalkyl substances (PFAS) on lipid composition of human breast milk, and (2) to study the combined impact of maternal PFAS exposure and breast milk lipid composition on the growth of the infants.MethodsIn a mother-infant study (n=44) we measured the levels of PFAS and lipids in maternal serum and conducted lipidomics analysis of breast milk at birth and at 3 months of infant age, by using ultra high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry. Maternal diet was studied by a validated food frequency questionnaire.ResultsPFAS levels were inversely associated with total lipid levels in the breast milk collected at birth. In the high exposure group, the ratio of acylated saturated and polyunsaturated fatty acids in triacylglycerols was increased. Moreover, high exposure to PFAS associated with the altered phospholipid composition, which was indicative of unfavorable increase in the size of milk fat globules. These changes in the milk lipid composition were further associated with slower infant growth and with elevated intestinal inflammatory markers.DiscussionOur data suggest that the maternal exposure to PFAS impacts the nutritional quality of the breast milk, which, in turn, may have detrimental impact on the health and growth of the children later in life.

Nonalcoholic fatty liver disease (NAFLD) is a well defined chronic liver diseases closely related with metabolic disorders. The prevalence of NAFLD is rapidly increasing worldwide, while the pathology and the underlying mechanisms driving NAFLD are not fully understood. In NAFLD, a series of metabolic changes takes place in the liver. However, the alteration of the metabolic pathways in the human liver along the progression of NAFLD, i.e., the transition from nonalcoholic steatosis (NAFL) to steatohepatitis (NASH) through cirrhosis remains to be discovered. Here, we sought to examine the metabolic pathways of the human liver across the full histological spectrum of NAFLD. We analyzed the whole liver tissue transcriptomic (RNA-Seq) and serum metabolomics data obtained from a large, prospectively enrolled cohort of histologically characterized patients derived from the European NAFLD Registry (n=206), and developed genome-scale metabolic models (GEMs) of human hepatocytes at different stages of NAFLD. The integrative approach employed in this study has enabled us to understand the regulation of the metabolic pathways of human liver in NAFL, and with progressive NASH-associated fibrosis (F0–F4). Our study identified several metabolic signatures in the liver and blood of these patients, specifically highlighting the alteration of vitamins (A, E) and glycosphingolipids (GSLs), and their link with complex glycosaminoglycans (GAGs) in advanced fibrosis. The study provides insights into the underlying pathways of the progressive fibrosing steatohepatitis. Furthermore, by applying genome-scale metabolic modeling (GSMM), we were able to identify the metabolic differences among carriers of widely validated genetic variants associated with NAFLD / NASH disease severity in three genes (PNPLA3, TM6SF2 and HSD17B13).

Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

T-cells are sentinels of adaptive cell-mediated immune responses. T-cell activation, proliferation and differentiation involves metabolic reprogramming involving the interplay of genes, proteins and metabolites. Here, we aim to understand the metabolic pathways involved in the activation and functional differentiation of human CD4+ T-cell subsets (Th1, Th2, Th17 and iTregs). We combined genome-scale metabolic modeling, gene expression data, targeted and non-targeted lipidomics experiments, together with in vitro gene knockdown experiments and showed that human CD4+ T-cells undergo specific metabolic changes during activation and functional differentiation. In addition, we identified and confirmed the importance of ceramide and glycosphingolipid synthesis pathways in Th17 differentiation and effector functions. Finally, through in vitro gene knockdown experiments, we substantiated the requirement of serine palmitoyl transferase (SPT), a de novo sphingolipid pathway in the expression of proinflammatory cytokine (IL17A and IL17F) by Th17 cells. Our findings may provide a comprehensive resource for identifying CD4+ T-cell-specific targets for their selective manipulation under disease conditions, particularly, diseases characterized by an imbalance of Treg / Th17 cells. Our data also suggest a role for elevated levels of ceramides in conditions comorbid with these diseases, e.g., obesity and insulin resistance.

Aging, obesity, and insulin resistance are associated with low levels of PGC1 alpha and PGC1 beta coactivators and defective mitochondrial function. We studied mice deficient for PGC1 alpha and PGC1 beta [double heterozygous (DH)] to investigate their combined pathogenic contribution. Contrary to our hypothesis, DH mice were leaner, had increased energy dissipation, a pro-thermogenic profile in BAT and WAT, and improved carbohydrate metabolism compared to wild types. WAT showed upregulation of mitochondriogenesis/oxphos machinery upon allelic compensation of PGC1 alpha 4 from the remaining allele. However, DH mice had decreased mitochondrial OXPHOS and biogenesis transcriptomes in mitochondria-rich organs. Despite being metabolically healthy, mitochondrial defects in DH mice impaired muscle fiber remodeling and caused qualitative changes in the hepatic lipidome. Our data evidence first the existence of organ-specific compensatory allostatic mechanisms are robust enough to drive an unexpected phenotype. Second, optimization of adipose tissue bioenergetics is sufficient to maintain a healthy metabolic phenotype despite a broad severe mitochondrial dysfunction in other relevant metabolic organs. Third, the decrease in PGC1s in adipose tissue of obese and diabetic patients is in contrast with the robustness of the compensatory upregulation in the adipose of the DH mice. EC | FP7 | FP7 Health (HEALTH), Grant/Award Number: [HEALTH-F4-2008-223450; RCUK | Medical Research Council (MRC), Grant/Award Number: MC_UU_12012/2 and MC_UU_00014/5; European Commission (EC), Grant/ Award Number: MEIF-CT-2005-023061; Wellcome Trust (Wellcome), Grant/Award Number: 208363/Z/17/Z

Human gut is colonized by a vast number of microbes known as gut microbiota. The microbiota plays a significant role in the maintenance of health and well-being. A dysbiosis in the microbiota has b ...

Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide and is often associated with aspects of metabolic syndrome. Despite its prevalence and the importance of early diagnosis, there is a lack of robustly validated biomarkers for diagnosis, prognosis and monitoring of disease progression in response to a given treatment. In this Review, we provide an overview of the contribution of metabolomics and lipidomics in clinical studies to identify biomarkers associated with NAFLD and nonalcoholic steatohepatitis (NASH). In addition, we highlight the key metabolic pathways in NAFLD and NASH that have been identified by metabolomics and lipidomics approaches and could potentially be used as biomarkers for non-invasive diagnostic tests. Overall, the studies demonstrated alterations in amino acid metabolism and several aspects of lipid metabolism including circulating fatty acids, triglycerides, phospholipids and bile acids. Although we report several studies that identified potential biomarkers, few have been validated.

Deep learning (DL), an emerging area of investigation in the fields of machine learning and artificial intelligence, has markedly advanced over the past years. DL techniques are being applied to assist medical professionals and researchers in improving clinical diagnosis, disease prediction and drug discovery. It is expected that DL will help to provide actionable knowledge from a variety of ‘big data’, including metabolomics data. In this review, we discuss the applicability of DL to metabolomics, while presenting and discussing several examples from recent research. We emphasize the use of DL in tackling bottlenecks in metabolomics data acquisition, processing, metabolite identification, as well as in metabolic phenotyping and biomarker discovery. Finally, we discuss how DL is used in genome-scale metabolic modelling and in interpretation of metabolomics data. The DL-based approaches discussed here may assist computational biologists with the integration, prediction and drawing of statistical inference about biological outcomes, based on metabolomics data.

MARC1 variant rs2642438 increases hepatic phosphatidylcholines and decreases severity of non-alcoholic fatty liver disease in humans

Free fatty acids (FFAs) are key intermediates of lipid metabolism that have a crucial role in many critical biological processes. The specific locations of carbon-carbon double bonds (C═C) in FFAs are often associated with distinct biological functions. Despite the rapid development of analytical techniques, identification of C═C locations in FFAs with more than three C═C bonds in complex biological matrices remains a challenge. Herein, we describe a double derivatization strategy, coupled with shotgun-mass spectrometry (MS), for unambiguous and sensitive determination of a high-coverage C═C bond (from 1 to 6) locations of FFAs. Our approach is based on combination of acetone labeling of C═C bonds and N,N-diethyl-1,2-ethanediamine (DEEA) labeling of carboxyl groups within FFAs. Acetone labeling of C═C bonds via photochemical reaction provides diagnostic ions, specific to C═C locations, and DEEA labeling of carboxyl groups significantly enhances MS response of diagnostic ions, by invoking a readily protonated tertiary amine group on FFA analytes. By exploiting this double derivatization strategy, the assignment of C═C locations of FFAs with more than three C═C bonds was achieved with high sensitivity (limit of quantitation (LOQ) 0.1-1.5 nmol/L). In contrast, such assignments were not possible by acetone labeling alone, because of the low sensitivity of diagnostic ions in negative ionization mode of MS. The applicability of our method was demonstrated by profiling of FFAs, including unsaturated FFA C═C positional isomers, in liver samples from mice with nonalcoholic fatty liver disease (NAFLD) and their lean controls. The study showed that the high-specificity and high-sensitivity method developed here is promising for accurate identification and quantitation of a wide array of FFAs in biological samples.

Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease.In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.

Patients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic co-morbidities. Identification of individuals with psychotic disorders with a high risk of rapid weight gain, and the associated development of metabolic complications, is an unmet need as regards public health. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 controls (CTR), 44 first-episode psychosis (FEP) patients and 22 individuals at clinical-high-risk (CHR) for psychosis, from two study centers (Turku/Finland and London/UK). Baseline serum samples were analyzed by lipidomics, while body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols with low double bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of two triacylglycerols (TG(48:0) and TG(45:0)), was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60–0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61–0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals, and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic co-morbidities.

A key clinical challenge in the management of individuals at clinical high risk for psychosis (CHR) is that it is difficult to predict their future clinical outcomes. Here, we investigated if the levels of circulating molecular lipids are related to adverse clinical outcomes in this group. Serum lipidomic analysis was performed in 263 CHR individuals and 51 healthy controls (HC), who were then clinically monitored for up to five years. Machine learning was used to identify lipid profiles that discriminated between CHR subjects and HC, and between subgroups of CHR subjects with distinct clinical outcomes. At baseline, compared to HC, CHR subjects (independent of outcome) had higher levels of triacylglycerols (TGs) with a low acyl carbon number and a double bond count, as well as higher levels of lipids in general. CHR subjects who subsequently developed psychosis (n=50) were distinguished from those that did not (n=213) on the basis of lipid profile at baseline, using a model with an AUC = 0.81 (95% CI = 0.69-0.93). CHR subjects who became psychotic had lower levels of ether phospholipids than CHR individuals who did not (p

Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.

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

Summary T cell activation, proliferation, and differentiation involve metabolic reprogramming resulting from the interplay of genes, proteins, and metabolites. Here, we aim to understand the metabolic pathways involved in the activation and functional differentiation of human CD4+ T cell subsets (T helper [Th]1, Th2, Th17, and induced regulatory T [iTreg] cells). Here, we combine genome-scale metabolic modeling, gene expression data, and targeted and non-targeted lipidomics experiments, together with in vitro gene knockdown experiments, and show that human CD4+ T cells undergo specific metabolic changes during activation and functional differentiation. In addition, we confirm the importance of ceramide and glycosphingolipid biosynthesis pathways in Th17 differentiation and effector functions. Through in vitro gene knockdown experiments, we substantiate the requirement of serine palmitoyltransferase (SPT), a de novo sphingolipid pathway in the expression of proinflammatory cytokines (interleukin [IL]-17A and IL17F) by Th17 cells. Our findings provide a comprehensive resource for selective manipulation of CD4+ T cells under disease conditions characterized by an imbalance of Th17/natural Treg (nTreg) cells.

Background: Carriers of the transmembrane 6 superfamily member 2 E167K gene variant (TM6SF2(EK/KK)) have decreased expression of the TM6SF2 gene and increased risk of NAFLD and NASH. Unlike common 'obese/metabolic' NAFLD, these subjects lack hypertriglyceridemia and have lower risk of cardiovascular disease. In animals, phosphatidylcholine (PC) deficiency results in a similar phenotype. PCs surround the core of VLDL consisting of triglycerides (TGs) and cholesteryl-esters (CEs). We determined the effect of the TM6SF2 E167K on these lipids in the human liver and serum and on hepatic gene expression and studied the effect of TM6SF2 knockdown on hepatocyte handling of these lipids. Methods: Liver biopsies were taken from subjects characterized with respect to the TM6SF2 genotype, serum and liver lipidome, gene expression and histology. In vitro, after TM6SF2 knockdown in HuH-7 cells, we compared incorporation of different fatty acids into TGs, CEs, and PCs. Results: The TM6SF2(EK/KK) and TM6SF2EE groups had similar age, gender, BMI and HOMA-IR. Liver TGs and CEs were higher and liver PCs lower in the TM6SF2(EK/KK) than the TM6SF2EE group (p Conclusions: Hepatic lipid synthesis from PUFAs is impaired and could contribute to deficiency in PCs and increased intrahepatic TG in TM6SF2 E167K variant carriers. (C) 2017 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.