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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.

BACKGROUND & AIMS:The enhanced liver fibrosis (ELF) test has been proposed for the non-invasive assessment of advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). We performed a systematic review to estimate the accuracy of this test against biopsy. METHODS:In this systematic review, we searched MEDLINE, Embase, Web of Science and the Cochrane Library for studies that included patients with NAFLD and that used both liver biopsy (as the reference standard) and the ELF test. Two authors independently screened the references, extracted the data and assessed the quality of included studies. Due to the variation in reported thresholds, we used a multiple thresholds random effects model for meta-analysis (diagmeta R-package). RESULTS:The meta-analysis of 11 studies reporting advanced fibrosis and 5 studies reporting significant fibrosis showed that the ELF test had a sensitivity of >0.90 for excluding fibrosis at a threshold of 7.7. However, as a diagnostic test at high thresholds, the test only achieved specificity and positive predictive value >0.80 in very high prevalence settings (>50%). To achieve a specificity of 0.90 for advanced and significant fibrosis, thresholds of 10.18 (sensitivity: 0.57) and 9.86 (sensitivity: 0.55) were required, respectively. CONCLUSION:The ELF test showed high sensitivity but limited specificity to exclude advanced and significant fibrosis at low cut-offs. The diagnostic performance of the test at higher thresholds was found to be more limited in low-prevalence settings. We conclude that clinicians should carefully consider the likely disease prevalence in their practice setting and adopt suitable test thresholds to achieve the desired performance. LAY SUMMARY:The enhanced liver fibrosis test has been suggested as a non-invasive blood test to aid the diagnosis of severe liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). Our study results showed that the test has a high negative predictive value, especially in populations with low disease prevalence (likely encountered in primary care); so, it can exclude advanced fibrosis in patients with NAFLD. However, when prevalence is low, the positive predictive value of the enhanced liver fibrosis test is low, suggesting that additional strategies may be needed to make a positive diagnosis in such settings.

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.

Background & Aims Serum microRNA (miRNA) levels are known to change in non-alcoholic fatty liver disease (NAFLD) and may serve as useful biomarkers. This study aimed to profile miRNAs comprehensively at all NAFLD stages. Methods We profiled 2,083 serum miRNAs in a discovery cohort (183 cases with NAFLD representing the complete NAFLD spectrum and 10 population controls). miRNA libraries generated by HTG EdgeSeq were sequenced by Illumina NextSeq. Selected serum miRNAs were profiled in 372 additional cases with NAFLD and 15 population controls by quantitative reverse transcriptase PCR. Results Levels of 275 miRNAs differed between cases and population controls. Fewer differences were seen within individual NAFLD stages, but miR-193a-5p consistently showed increased levels in all comparisons. Relative to NAFL/non-alcoholic steatohepatitis (NASH) with mild fibrosis (stage 0/1), 3 miRNAs (miR-193a-5p, miR-378d, and miR378d) were increased in cases with NASH and clinically significant fibrosis (stages 2–4), 7 (miR193a-5p, miR-378d, miR-378e, miR-320b, miR-320c, miR-320d, and miR-320e) increased in cases with NAFLD activity score (NAS) 5–8 compared with lower NAS, and 3 (miR-193a-5p, miR-378d, and miR-378e) increased but 1 (miR-19b-3p) decreased in steatosis, activity, and fibrosis (SAF) activity score 2–4 compared with lower SAF activity. The significant findings for miR-193a-5p were replicated in the additional cohort with NAFLD. Studies in Hep G2 cells showed that following palmitic acid treatment, miR-193a-5p expression decreased significantly. Gene targets for miR-193a-5p were investigated in liver RNAseq data for a case subgroup (n = 80); liver GPX8 levels correlated positively with serum miR-193a-5p. Conclusions Serum miR-193a-5p levels correlate strongly with NAFLD activity grade and fibrosis stage. MiR-193a-5p may have a role in the hepatic response to oxidative stress and is a potential clinically tractable circulating biomarker for progressive NAFLD. Lay summary MicroRNAs (miRNAs) are small pieces of nucleic acid that may turn expression of genes on or off. These molecules can be detected in the blood circulation, and their levels in blood may change in liver disease including non-alcoholic fatty liver disease (NAFLD). To see if we could detect specific miRNA associated with advanced stages of NAFLD, we carried out miRNA sequencing in a group of 183 patients with NAFLD of varying severity together with 10 population controls. We found that a number of miRNAs showed changes, mainly increases, in serum levels but that 1 particular miRNA miR-193a-5p consistently increased. We confirmed this increase in a second group of cases with NAFLD. Measuring this miRNA in a blood sample may be a useful way to determine whether a patient has advanced NAFLD without an invasive liver biopsy., Graphical abstract, Highlights • Serum miRNA was sequenced in 183 NAFLD cases of varying severity and 10 population controls. • Plasma levels of miR-193a-5p were significantly increased in patients with advanced fibrosis, high NAS scores, or high SAF scores. • Other miRNAs including miR378d and miR378e were also significantly increased in certain comparisons. • The findings for miR-193a-5p were replicated in a cohort of 372 additional NAFLD cases.

Background & aims: Recent experimental models and epidemiological studies suggest that specific environmental contaminants (ECs) contribute to the initiation and pathology of nonalcoholic fatty liver disease (NAFLD). However, the underlying mechanisms linking EC exposure with NAFLD remain poorly understood and there is no data on their impact on the human liver metabolome. Herein, we hypothesized that exposure to ECs, particularly perfluorinated alkyl substances (PFAS), impacts liver metabolism, specifically bile acid metabolism. Methods: In a well-characterized human NAFLD cohort of 105 individuals, we investigated the effects of EC exposure on liver metabolism. We characterized the liver (via biopsy) and circulating metabolomes using 4 mass spectrometry-based analytical platforms, and measured PFAS and other ECs in serum. We subsequently compared these results with an exposure study in a PPARa-humanized mouse model. Results: PFAS exposure appears associated with perturbation of key hepatic metabolic pathways previously found altered in NAFLD, particularly those related to bile acid and lipid metabolism. We identified stronger associations between the liver metabolome, chemical exposure and NAFLD-associated clinical variables (liver fat content, HOMA-IR), in females than males. Specifically, we observed PFAS-associated upregulation of bile acids, triacylglycerols and ceramides, and association between chemical exposure and dysregulated glucose metabolism in females. The murine exposure study further corroborated our findings, vis-a-vis a sex-specific association between PFAS exposure and NAFLD-associated lipid changes. Conclusions: Females may be more sensitive to the harmful impacts of PFAS. Lipid-related changes subsequent to PFAS exposure may be secondary to the interplay between PFAS and bile acid metabolism. Lay summary: There is increasing evidence that specific environmental contaminants, such as perfluorinated alkyl substances (PFAS), contribute to the progression of non-alcoholic fatty liver disease (NAFLD). However, it is poorly understood how these chemicals impact human liver metabolism. Here we show that human exposure to PFAS impacts metabolic processes associated with NAFLD, and that the effect is different in females and males. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver.

ObjectiveGut microbial products are involved in regulation of host metabolism. In human and experimental studies, we explored the potential role of hippurate, a hepatic phase 2 conjugation product of microbial benzoate, as a marker and mediator of metabolic health.DesignIn 271 middle-aged non-diabetic Danish individuals, who were stratified on habitual dietary intake, we applied 1H-nuclear magnetic resonance (NMR) spectroscopy of urine samples and shotgun-sequencing-based metagenomics of the gut microbiome to explore links between the urine level of hippurate, measures of the gut microbiome, dietary fat and markers of metabolic health. In mechanistic experiments with chronic subcutaneous infusion of hippurate to high-fat-diet-fed obese mice, we tested for causality between hippurate and metabolic phenotypes.ResultsIn the human study, we showed that urine hippurate positively associates with microbial gene richness and functional modules for microbial benzoate biosynthetic pathways, one of which is less prevalent in the Bacteroides 2 enterotype compared with Ruminococcaceae or Prevotella enterotypes. Through dietary stratification, we identify a subset of study participants consuming a diet rich in saturated fat in which urine hippurate concentration, independently of gene richness, accounts for links with metabolic health. In the high-fat-fed mice experiments, we demonstrate causality through chronic infusion of hippurate (20 nmol/day) resulting in improved glucose tolerance and enhanced insulin secretion.ConclusionOur human and experimental studies show that a high urine hippurate concentration is a general marker of metabolic health, and in the context of obesity induced by high-fat diets, hippurate contributes to metabolic improvements, highlighting its potential as a mediator of metabolic health.

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.

International audience; Knowledge about in vivo effects of human circulating C-6 hydroxylated bile acids (BAs), also called muricholic acids, is sparse. It is unsettled if the gut microbiome might contribute to their biosynthesis. Here, we measured a range of serum BAs and related them to markers of human metabolic health and the gut microbiome. We examined 283 non-obese and obese Danish adults from the MetaHit study. Fasting concentrations of serum BAs were quantified using ultra-performance liquid chromatographytandem mass-spectrometry. The gut microbiome was characterized with shotgun metagenomic sequencing and genome-scale metabolic modeling. We find that tauro-and glycohyocholic acid correlated inversely with body mass index (P = 4.1e-03, P = 1.9e-05, respectively), waist circumference (P = 0.017, P = 1.1e-04, respectively), body fat percentage (P = 2.5e-03, P = 2.3e-06, respectively), insulin resistance (P = 0.051, P = 4.6e-4, respectively), fasting concentrations of triglycerides (P = 0.06, P = 9.2e-4, respectively) and leptin (P = 0.067, P = 9.2e-4). Tauro-and glycohyocholic acids, and tauroa-muricholic acid were directly linked with a distinct gut microbial community primarily composed of Clostridia species (P = 0.037, P = 0.013, P = 0.027, respectively). We conclude that serum conjugated C-6-hydroxylated BAs associate with measures of human metabolic health and gut communities of Clostridia species. The findings merit preclinical interventions and human feasibility studies to explore the therapeutic potential of these BAs in obesity and type 2 diabetes. Bile acids (BAs) are a class of steroids produced from cholesterol in the liver where they are conjugated with either glycine or taurine and released into the bile. These primary BAs, which in humans predominantly comprise of cholic acid (CA) and chenodeoxycholic acid (CDCA) are absorbed by different intestinal bacteria, and conjugates of glycine or taurine are removed with subsequent alteration of hydroxyl groups to form secondary BAs 1. BAs emulsify dietary fats in the small intestine and facilitate their absorption 1,2. At the terminal ileum, the majority of BAs are absorbed by the apical sodium dependent BA transporters and enter the hepatic portal circulation. In total, about 95% of BAs are reabsorbed into intestinal enterocytes, whilst > 5% of BAs enter the systemic circulation and act on multiple organs throughout the body via several types of receptors 3. The most prominent of these are the farnesoid X receptor (FXR) and the Takeda G protein-coupled membrane receptor 5 (TGR5) which are expressed in a variety of peripheral tissues 4-7. Through these receptors, BAs regulate biological processes such as immunity, neuroprotection, metabolism, and energy expenditure 8-12 .

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.

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 ...

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

International audience; The mechanisms that drive nonalcoholic fatty liver disease (NAFLD) remain incompletely understood. This large multicenter study characterized the transcriptional changes that occur in liver tissue across the NAFLD spectrum as disease progresses to cirrhosis to identify potential circulating markers. We performed high-throughput RNA sequencing on a discovery cohort comprising histologically characterized NAFLD samples from 206 patients. Unsupervised clustering stratified NAFLD on the basis of disease activity and fibrosis stage with differences in age, aspartate aminotransferase (AST), type 2 diabetes mellitus, and carriage of PNPLA3 rs738409 , a genetic variant associated with NAFLD. Relative to early disease, we consistently identified 25 differentially expressed genes as fibrosing steatohepatitis progressed through stages F2 to F4. This 25-gene signature was independently validated by logistic modeling in a separate replication cohort ( n = 175), and an integrative analysis with publicly available single-cell RNA sequencing data elucidated the likely relative contribution of specific intrahepatic cell populations. Translating these findings to the protein level, SomaScan analysis in more than 300 NAFLD serum samples confirmed that circulating concentrations of proteins AKR1B10 and GDF15 were strongly associated with disease activity and fibrosis stage. Supporting the biological plausibility of these data, in vitro functional studies determined that endoplasmic reticulum stress up-regulated expression of AKR1B10 , GDF15 , and PDGFA , whereas GDF15 supplementation tempered the inflammatory response in macrophages upon lipid loading and lipopolysaccharide stimulation. This study provides insights into the pathophysiology of progressive fibrosing steatohepatitis, and proof of principle that transcriptomic changes represent potentially tractable and clinically relevant markers of disease progression.

Background & Aims\ud \ud The I148M variant in PNPLA3 is the major genetic risk factor for non‐alcoholic fatty liver disease (NAFLD). The liver is enriched with polyunsaturated triglycerides (PUFA‐TGs) in PNPLA3‐I148M carriers. Gene expression data indicate that PNPLA3 is liver‐specific in humans, but whether it functions in adipose tissue (AT) is unknown. We investigated whether PNPLA3‐I148M modifies AT metabolism in human NAFLD.\ud Methods\ud \ud Profiling of the AT lipidome and fasting serum non‐esterified fatty acid (NEFA) composition was conducted in 125 volunteers (PNPLA3 148MM/MI, n = 63; PNPLA3 148II, n = 62). AT fatty acid composition was determined in 50 volunteers homozygous for the variant (PNPLA3 148MM, n = 25) or lacking the variant (PNPLA3 148II, n = 25). Whole‐body insulin sensitivity of lipolysis was determined using [2H5]glycerol, and PNPLA3 mRNA and protein levels were measured in subcutaneous AT and liver biopsies in a subset of the volunteers.\ud Results\ud \ud PUFA‐TGs were significantly increased in AT in carriers versus non‐carriers of PNPLA3‐I148M. The variant did not alter the rate of lipolysis or the composition of fasting serum NEFAs. PNPLA3 mRNA was 33‐fold higher in the liver than in AT (P < .0001). In contrast, PNPLA3 protein levels per tissue protein were three‐fold higher in AT than the liver (P < .0001) and nine‐fold higher when related to whole‐body AT and liver tissue masses (P < .0001).\ud Conclusions\ud \ud Contrary to previous assumptions, PNPLA3 is highly abundant in AT. PNPLA3‐I148M locally remodels AT TGs to become polyunsaturated as it does in the liver, without affecting lipolysis or composition of serum NEFAs. Changes in AT metabolism do not contribute to NAFLD in PNPLA3‐I148M carriers.

Patients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic comorbidities. There is an unmet public health need to identify individuals with psychotic disorders who have a high risk of rapid weight gain and who are at risk of developing metabolic complications. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 healthy controls (CTR), 44 first-episode psychosis (FEP) patients, and 22 individuals at clinical high risk (CHR) for psychosis, from 2 study centers (Turku, Finland and London, UK). Baseline serum samples were analyzed using lipidomics, and body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols (TGs) 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 2 TGs (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 comorbidities.

We call upon the research community to standardize efforts to use daily self-reported data about COVID-19 symptoms in the response to the pandemic and to form a collaborative consortium to maximize global gain while protecting participant privacy.

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

Activation of pregnane X receptor (PXR) elevates circulating 4β-hydroxycholesterol (4βHC), an agonist of liver X receptor (LXR). PXR may also regulate 25-hydroxycholesterol and 27-hydroxycholesterol. Our aim was to elucidate the roles of PXR and oxysterols in the regulation of cholesterol transporters. We measured oxysterols in serum of volunteers dosed with PXR agonist rifampicin 600 mg/day versus placebo for a week and analyzed the expression of cholesterol transporters in mononuclear cells. The effect of 4βHC on the transport of cholesterol and the expression of cholesterol transporters was studied in human primary monocyte-derived macrophages and foam cells in vitro. The expression of cholesterol transporters was measured also in rat tissues after dosing with a PXR agonist. The levels of 4βHC were elevated, while 25-hydroxycholesterol and 27-hydroxycholesterol remained unchanged in volunteers dosed with rifampicin. The expression of ATP binding cassette transporter A1 (ABCA1) was induced in human mononuclear cells in vivo. The influx of cholesterol was repressed by 4βHC, as was the expression of influx transporter lectin-like oxidized LDL receptor-1 in vitro. The cholesterol efflux and the expression of efflux transporters ABCA1 and ABCG1 were induced. The expression of inducible degrader of the LDL receptor was induced. In rats, PXR agonist increased circulating 4βHC and expression of LXR targets in peripheral tissues, especially ABCA1 and ABCG1 in heart. In conclusion, PXR activation-elevated 4βHC is a signaling molecule that represses cholesterol influx and induces efflux. The PXR-4βHC-LXR pathway could link the hepatic xenobiotic exposure and the regulation of cholesterol transport in peripheral tissues.

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

OBJECTIVESCeliac disease (CD) is a systemic immune-mediated disorder with increased frequency in the developed countries over the last decades implicating the potential causal role of various environmental triggers in addition to gluten. Herein, we apply determination of perfluorinated alkyl substances (PFAS) and combine the results with the determination of bile acids (BAs) and molecular lipids, with the aim to elucidate the impact of prenatal exposure on risk of progression to CD in a prospective series of children prior the first exposure to gluten (at birth and at 3 months of age).METHODSWe analyzed PFAS, BAs and lipidomic profiles in 76 plasma samples at birth and at 3 months of age in the Type 1 Diabetes Prediction and Prevention (DIPP) study (n=17 progressors to CD, n=16 healthy controls, HCs).RESULTSPlasma PFAS levels showed a significant inverse association with the age of CD diagnosis in infants who later progressed to the disease. Associations between BAs and triacylglycerols (TGs) showed different patterns already at birth in CD progressors, indicative of different absorption of lipids in these infants.DISCUSSIONPFAS exposure may modulate lipid and BA metabolism, and the impact is different in the infants who develop CD later in life, in comparison to HCs. The results indicate more efficient uptake of PFAS in such infants. Higher PFAS exposure during prenatal and early life may accelerate the progression to CD in the genetically predisposed children.Study HighlightsWHAT IS KNOWNSeveral observational studies have implicated a role of early life environmental triggers other than gluten in the development of CD. This is supported by the findings showing dysregulation of lipids already prior to the first introduction of gluten.WHAT IS NEW HEREWe show that prenatal exposure to perfluorinated compounds is associated with changes in the lipid metabolism, most likely through the bile acids, and that a high exposure during prenatal and early life may accelerate the progression to CD in the genetically predisposed children.TRANSLATIONAL IMPACTExposure to environmental chemicals may impact the rate of progression to CD and should be assessed as a potential risk factor of CD in larger clinical cohort settings.

The effects of gut microbiota on the central nervous system, along its possible role in mental disorders, have received increasing attention. Here we investigated differences in fecal microbiota between 28 patients with first-episode psychosis (FEP) and 16 healthy matched controls and explored whether such differences were associated with response after up to 12 months of treatment. Numbers of Lactobacillus group bacteria were elevated in FEP-patients and significantly correlated with severity along different symptom domains. A subgroup of FEP patients with the strongest microbiota differences also showed poorer response after up to 12 months of treatment. The present findings support the involvement of microbiota alterations in psychotic illness and may provide the basis for exploring the benefit of their modulation on treatment response and remission. (C) 2017 Elsevier B.V. All rights reserved.

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility.

Background The identification of early biomarkers of psychotic experiences (PEs) is of interest because early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study of Parents and Children cohort. Methods Plasma of 115 children (12 years of age) who were first identified as experiencing PEs at 18 years of age (48 cases and 67 controls) were assessed through integrated and targeted lipidomics and semitargeted proteomics approaches. We assessed the lipids, lysophosphatidylcholines (n = 11) and phosphatidylcholines (n = 61), and the protein members of the coagulation pathway (n = 22) and integrated these data with complement pathway protein data already available on these subjects. Results Twelve phosphatidylcholines, four lysophosphatidylcholines, and the coagulation protein plasminogen were altered between the control and PEs groups after correction for multiple comparisons. Lipidomic and proteomic datasets were integrated into a multivariate network displaying a strong relationship between most lipids that were significantly associated with PEs and plasminogen. Finally, an unsupervised clustering approach identified four different clusters, with one of the clusters presenting the highest case-control ratio (p < .01) and associated with a higher concentration of smaller low-density lipoprotein cholesterol particles. Conclusions Our findings indicate that the lipidome and proteome of subjects who report PEs at 18 years of age are already altered at 12 years of age, indicating that metabolic dysregulation may contribute to an early vulnerability to PEs and suggesting crosstalk between these lysophosphatidylcholines, phosphatidylcholines, and coagulation and complement proteins.

BackgroundSeveral small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities and complications. Here, we report the development and validation of a novel, quantitative, analytical method for use in the diabetes clinic. This method enables the determination of a selected panel of 36 metabolite biomarkers from human plasma.MethodsBased on a review of the literature and our own data, we selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings.ResultsWe validated the method in terms of limit of (a) detection (LOD), (b) limit of quantitation (LOQ), (c) linearity (R2), (d) linear range, and (e) intra- and inter-day repeatability of each metabolite. The method’s performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes were associated with macro-albuminuria. Additionally, specific bile acids were associated with kidney function, anti-hypertensive medication, statin medication and clinical lipid measurements.ConclusionsThe developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.

Previous metabolomics studies suggest that type 1 diabetes (T1D) is preceded by specific metabolic disturbances. Here we asked whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children later developing pancreaticβ-cell autoimmunity or overt T1D. In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who either (1) progressed to T1D (PT1D, n=34), (2) seroconverted to ≥1 islet autoantibody without progressing to T1D (P1Ab, n=27), or (3) remained autoantibody negative during follow-up (CTRL, n=10). During the first year of life, levels of most lipids and polar metabolites were lower in PT1D and P1Ab, versus CTRLs. Pathway overrepresentation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were overrepresented in PT1D. Genome-scale metabolic models of PBMCs in T1D progression were developed using available transcriptomics data and constrained with metabolomics data from our study. Metabolic modeling confirmed altered ceramide pathways as specifically associated with T1D progression.

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

openaire: EC/H2020/634413/EU//EPoS | openaire: EC/H2020/777377/EU//LITMUS The common patatin-like phospholipase domain-containing protein 3 (PNPLA3) variant I148M predisposes to nonalcoholic liver disease but not its metabolic sequelae. We compared the handling of labeled polyunsaturated fatty acids (PUFAs) and saturated fatty acids (SFA) in vivo in humans and in cells harboring different PNPLA3 genotypes. In 148M homozygous individuals, triglycerides (TGs) in very low-density lipoproteins (VLDL) were depleted of PUFAs both under fasting and postprandial conditions compared with 148I homozygotes, and the PUFA/SFA ratio in VLDL-TGs was lower relative to the chylomicron precursor pool. In human PNPLA3-148M and PNPLA3-KO cells, PUFA but not SFA incorporation into TGs was increased at the expense of phosphatidylcholines, and under lipolytic conditions, PUFA-containing diacylglycerols (DAGs) accumulated compared with PNPLA3-148I cells. Polyunsaturated TGs were increased, while phosphatidylcholines (PCs) were decreased in the human liver in 148M homozygous individuals as compared with 148I homozygotes. We conclude that human PNPLA3-I148M is a loss-of-function allele that remodels liver TGs in a polyunsaturated direction by impairing hydrolysis/transacylation of PUFAs from DAGs to feed phosphatidylcholine synthesis.

Previous studies suggest that children who progress to type 1 diabetes (T1D) later in life already have an altered serum lipid molecular profile at birth. Here, we compared cord blood lipidome across the three study groups: children who progressed to T1D (PT1D, n = 30), children who developed at least one islet autoantibody but did not progress to T1D during the follow-up (P1Ab, n = 33), and their age-matched controls (CTR, n = 38). We found that phospholipids, specifically sphingomyelins, were lower in T1D progressors when compared to P1Ab and the CTR. Cholesterol esters remained higher in PT1D when compared to other groups. A signature comprising five lipids was predictive of the risk of progression to T1D, with an area under the receiver operating characteristic curve (AUROC) of 0.83. Our findings provide further evidence that the lipidomic profiles of newborn infants who progress to T1D later in life are different from lipidomic profiles in P1Ab and CTR.

There is growing interest in the metabolic interplay between the gut microbiome and host metabolism. Taxonomic and functional profiling of the gut microbiome by next-generation sequencing (NGS) has unveiled substantial richness and diversity. However, the mechanisms underlying interactions between diet, gut microbiome and host metabolism are still poorly understood. Genome-scale metabolic modeling (GSMM) is an emerging approach that has been increasingly applied to infer diet⁻microbiome, microbe⁻microbe and host⁻microbe interactions under physiological conditions. GSMM can, for example, be applied to estimate the metabolic capabilities of microbes in the gut. Here, we discuss how meta-omics datasets such as shotgun metagenomics, can be processed and integrated to develop large-scale, condition-specific, personalized microbiota models in healthy and disease states. Furthermore, we summarize various tools and resources available for metagenomic data processing and GSMM, highlighting the experimental approaches needed to validate the model predictions.

Lipids have many important biological roles, such as energy storage sources, structural components of plasma membranes and as intermediates in metabolic and signaling pathways. Lipid metabolism is under tight homeostatic control, exhibiting spatial and dynamic complexity at multiple levels. Consequently, lipid-related disturbances play important roles in the pathogenesis of most of the common diseases. Lipidomics, defined as the study of lipidomes in biological systems, has emerged as a rapidly-growing field. Due to the chemical and functional diversity of lipids, the application of a systems biology approach is essential if one is to address lipid functionality at different physiological levels. In parallel with analytical advances to measure lipids in biological matrices, the field of computational lipidomics has been rapidly advancing, enabling modeling of lipidomes in their pathway, spatial and dynamic contexts. This review focuses on recent progress in systems biology approaches to study lipids in health and disease, with specific emphasis on methodological advances and biomedical applications.

Background & Aims: Recent data in mice have identified de novo ceramide synthesis as the key mediator of hepatic insulin resistance (IR) that in humans characterizes increases in liver fat due to IR ('Metabolic NAFLD' but not that due to the I148M gene variant in PNPLA3 ('PNPLA3 NAFLD'). We determined which bioactive lipids co-segregate with IR in the human liver. Methods: Liver lipidome was profiled in liver biopsies from 125 subjects that were divided into equally sized groups based on median HOMA-IR ('High and Low HOMA-IR', n = 62 and n = 63) or PNPLA3 genotype (PNPIA3(148MM/MI), n = 61 vs. PNPLA3(148II), n = 64). The subjects were also divided into 4 groups who had either IR, the I148M gene variant, both of the risk factors or neither. Results: Steatosis and NASH prevalence were similarly increased in 'High HOMA-IR' and PNPLA3(148MM/MI) groups compared to their respective control groups. The 'High HOMA-IR' but not the PNPLA3(148MM/MI) group had features of IR. The liver in 'High HOMA-IR' vs. low HOMA-IR' was markedly enriched in saturated and monounsaturated triacylglycerols and free fatty acids, dihydroceramides (markers of de novo ceramide synthesis) and ceramides. Markers of other ceramide synthetic pathways were unchanged. In PNPLA3(148MM/MI) vs. PNPLA3(148II), the increase in liver fat was due to polyunsaturated triacylglycerols while other lipids were unchanged. Similar changes were observed when data were analyzed using the 4 subgroups. Conclusions: Similar increases in liver fat and NASH are associated with a metabolically harmful saturated, ceramide-enriched liver lipidome in 'Metabolic NAFLD' but not in 'PNPLA3 NAFLD'. This difference may explain why metabolic but not PNPLA3 NAFLD increases the risk of type 2 diabetes and cardiovascular disease. (C) 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Aims The aim of this study was to investigate the longitudinal plasma metabolic profiles in healthy infants and the potential association with breastfeeding duration and islet autoantibodies predictive of type 1 diabetes. Method Up to four longitudinal plasma samples from age 3 months from case children who developed islet autoimmunity (n = 29) and autoantibody-negative control children (n = 29) with the HLA DR4-DQ8/DR3-DQ2 genotype were analyzed using two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer for detection of small polar metabolites. Results Plasma metabolite levels were found to depend strongly on age, with fold changes varying up to 50% from age 3 to 24 months (p

Traumatic brain injury (TBI) is a major cause of death and disability worldwide, especially in children and young adults. TBI is an example of a medical condition where there are still major lacks in diagnostics and outcome prediction. Here we apply comprehensive metabolic profiling of serum samples from TBI patients and controls in two independent cohorts. The discovery study included 144 TBI patients, with the samples taken at the time of hospitalization. The patients were diagnosed as severe (sTBI; n = 22), moderate (moTBI; n = 14) or mild TBI (mTBI; n = 108) according to Glasgow Coma Scale. The control group (n = 28) comprised of acute orthopedic non-brain injuries. The validation study included sTBI (n = 23), moTBI (n = 7), mTBI (n = 37) patients and controls (n = 27). We show that two medium-chain fatty acids (decanoic and octanoic acids) and sugar derivatives including 2,3-bisphosphoglyceric acid are strongly associated with severity of TBI, and most of them are also detected at high concentrations in brain microdialysates of TBI patients. Based on metabolite concentrations from TBI patients at the time of hospitalization, an algorithm was developed that accurately predicted the patient outcomes (AUC = 0.84 in validation cohort). Addition of the metabolites to the established clinical model (CRASH), comprising clinical and computed tomography data, significantly improved prediction of patient outcomes. The identified ‘TBI metabotype’ in serum, that may be indicative of disrupted blood-brain barrier, of protective physiological response and altered metabolism due to head trauma, offers a new avenue for the development of diagnostic and prognostic markers of broad spectrum of TBIs., Graphical Abstract Image 1, Highlights • The study reports that serum metabolites are sensitive to severity of TBI as well as predict the patient outcomes. • The findings are indicative of disruption in blood brain barrier and of protective response and altered TBI metabolism. • Metabolites significantly improved the prediction of patient outcomes when added to the established clinical model. Traumatic brain injury (TBI) is an example of a medical condition where there are still major lacks in diagnostics, outcome prediction, and the therapy development. Since the blood-brain barrier prevents diffusion of most water-soluble molecules with molecular mass over 500 Da, here we hypothesized that circulating small molecules (metabolites) are a potential source of TBI markers. Based on serum metabolomic studies in two independent cohorts, we found that metabolites are sensitive to severity of TBI as well as predict the patient outcomes. The findings of this study may pave the way for new diagnostic tools for TBI.

Background Lysinuric protein intolerance (LPI [MIM 222700]) is an aminoaciduria with defective transport of cationic amino acids in epithelial cells in the small intestine and proximal kidney tubules due to mutations in the SLC7A7 gene. LPI is characterized by protein malnutrition, failure to thrive and hyperammonemia. Many patients also suffer from combined hyperlipidemia and chronic kidney disease (CKD) with an unknown etiology. Methods Here, we studied the plasma metabolomes of the Finnish LPI patients (n = 26) and healthy control individuals (n = 19) using a targeted platform for analysis of amino acids as well as two analytical platforms with comprehensive coverage of molecular lipids and polar metabolites. Results Our results demonstrated that LPI patients have a dichotomy of amino acid profiles, with both decreased essential and increased non-essential amino acids. Altered levels of metabolites participating in pathways such as sugar, energy, amino acid and lipid metabolism were observed. Furthermore, of these metabolites, myo-inositol, threonic acid, 2,5-furandicarboxylic acid, galactaric acid, 4-hydroxyphenylacetic acid, indole-3-acetic acid and beta-aminoisobutyric acid associated significantly (P < 0.001) with the CKD status. Lipid analysis showed reduced levels of phosphatidylcholines and elevated levels of triacylglycerols, of which long-chain triacylglycerols associated (P

BACKGROUND: A healthy Nordic diet is associated with improvements in cardiometabolic risk factors, but the effect on lipidomic profile is not known.OBJECTIVE: The aim was to investigate how a healthy Nordic diet affects the fasting plasma lipidomic profile in subjects with metabolic syndrome.METHODS: Men and women (n = 200) with features of metabolic syndrome [mean age: 55 y; body mass index (in kg/m(2)): 31.6] were randomly assigned to either a healthy Nordic (n = 104) or a control (n = 96) diet for 18 or 24 wk at 6 centers. Of the participants, 156 completed the study with plasma lipidomic measurements. The healthy Nordic diet consisted of whole grains, fruits, vegetables, berries, vegetable oils and margarines, fish, low-fat milk products, and low-fat meat. An average Nordic diet served as the control diet and included low-fiber cereal products, dairy fat-based spreads, regular-fat milk products, and a limited amount of fruits, vegetables, and berries. Lipidomic profiles were measured at baseline, week 12, and the end of the intervention (18 or 24 wk) by using ultraperformance liquid chromatography mass spectrometry. The effects of the diets on the lipid variables were analyzed with linear mixed-effects models. Data from centers with 18- or 24-wk duration were also analyzed separately.RESULTS: Changes in 21 plasma lipids differed significantly between the groups at week 12 (false discovery rate P < 0.05), including increases in plasmalogens and decreases in ceramides in the healthy Nordic diet group compared with the control group. At the end of the study, changes in lipidomic profiles did not differ between the groups. However, when the intervention lasted 24 wk, changes in 8 plasma lipids that had been identified at 12 wk, including plasmalogens, were sustained. There were no differences in changes in plasma lipids between groups with an intervention of 18 wk. By the dietary biomarker score, adherence to diet did not explain the difference in the results related to the duration of the study.CONCLUSIONS: A healthy Nordic diet transiently modified the plasma lipidomic profile, specifically by increasing the concentrations of antioxidative plasmalogens and decreasing insulin resistance-inducing ceramides. This trial was registered at clinicaltrials.gov as NCT00992641.

International audience; We recently presented a three-pronged association study that integrated human intestinal microbiome data derived from shotgun-based sequencing with untargeted serum metabolome data and measures of host physiology. Metabolome and microbiome data are high dimensional, posing a major challenge for data integration. Here, we present a step-by-step computational protocol that details and discusses the dimensionality-reduction techniques used and methods for subsequent integration and interpretation of such heterogeneous types of data. Dimensionality reduction was achieved through a combination of data normalization approaches, binning of co-abundant genes and metabolites, and integration of prior biological knowledge. The use of prior knowledge to overcome functional redundancy across microbiome species is one central advance of our method over available alternative approaches. Applying this framework, other investigators can integrate various '-omics' readouts with variables of host physiology or any other phenotype of interest (e.g., connecting host and microbiome readouts to disease severity or treatment outcome in a clinical cohort) in a three-pronged association analysis to identify potential mechanistic links to be tested in experimental settings. Although we originally developed the framework for a human metabolome-microbiome study, it is generalizable to other organisms and environmental metagenomes, as well as to studies including other -omics domains such as transcriptomics and proteomics. The provided R code runs in similar to 1 h on a standard PC.

Background and AimsCeliac disease (CD) is a chronic enteropathy characterized by an autoimmune reaction in the small intestine in genetically-susceptible individuals. Gluten is the required environmental trigger of clinical CD, but the underlying causes of the autoimmune reaction remain unknown. Herein, we apply lipidomics to elucidate the early events preceding clinical CD in a prospective study of children observed from birth until diagnosis of CD and subsequent introduction of a gluten-free diet.MethodsMass spectrometry–based lipidomics profiling was applied to a longitudinal series of 233 plasma samples from the Type 1 Diabetes Prediction and Prevention (DIPP) study, spanning the period between birth and the introduction of a gluten–free diet following CD diagnosis (n=23 CD progressors, n=23 controls matched for gender, HLA risk, period of birth, and age).Results23 children progressed to CD at a mean age of 4.8 years. They showed increased amounts of triacylglycerols (TGs) of low carbon number and double bond count and a decreased level of phosphatidylcholines by 3 months of age as compared to controls. These differences were exacerbated with age but were not observed at birth. No significant differences were observed in essential (dietary) TGs such as those containing polyunsaturated fatty acids.ConclusionOur findings suggest that abnormal lipid metabolism associated with development of clinical CD may occur prior to the introduction of gluten to the diet. Moreover, our data suggest that the specific TGs found elevated in CD progressors may be due to a host response to compromised intake of essential lipids in the small intestine, requiring de novo lipogenesis.

There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of biomarkers to determine the need for CT and to distinguish among different types of injuries observed. Logistical regression models using metabolite data from the discovery cohort (n = 144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and those with negative findings on head CT. The resultant models were then tested in the validation cohort (n = 66, Cambridge, United Kingdom). The levels of glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein biomarkers in patients with TBI, the model that determined the need for a CT scan validated poorly (area under the curve [AUC] = 0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, three sugar derivatives, and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC = 0.77 in Turku patients and AUC = 0.73 in Cambridge patients). Further, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC = 0.87 in Turku patients and AUC = 0.68 in Cambridge patients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.

Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that children who progressed to islet autoimmunity or overt T1D are characterized by distinct lipidomic signatures, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.

Psychotic disorders are associated with metabolic abnormalities including alterations in glucose and lipid metabolism. A major challenge in the treatment of psychosis is to identify patients with vulnerable metabolic profiles who may be at risk of developing cardiometabolic co-morbidities. It is established that both central and peripheral metabolic organs use lipids to control energy balance and regulate peripheral insulin sensitivity. The endocannabinoid system, implicated in the regulation of glucose and lipid metabolism, has been shown to be dysregulated in psychosis. It is currently unclear how these endocannabinoid abnormalities relate to metabolic changes in psychosis. Here we review recent research in the field of metabolic co-morbidities in psychotic disorders as well as the methods to study them and potential links to the endocannabinoid system. We also describe the bioinformatics platforms developed in the EU project METSY for the investigations of the biological etiology in patients at risk of psychosis and in first episode psychosis patients. The METSY project was established with the aim to identify and evaluate multi-modal peripheral and neuroimaging markers that may be able to predict the onset and prognosis of psychiatric and metabolic symptoms in patients at risk of developing psychosis and first episode psychosis patients. Given the intrinsic complexity and widespread role of lipid metabolism, a systems biology approach which combines molecular, structural and functional neuroimaging methods with detailed metabolic characterisation and multi-variate network analysis is essential in order to identify how lipid dysregulation may contribute to psychotic disorders. A decision support system, integrating clinical, neuropsychological and neuroimaging data, was also developed in order to aid clinical decision making in psychosis. Knowledge of common and specific mechanisms may aid the etiopathogenic understanding of psychotic and metabolic disorders, facilitate early disease detection, aid treatment selection and elucidate new targets for pharmacological treatments.

Metabolomics is a study of small molecules in the body and the associated metabolic pathways and is considered to provide a close link between organism's genotype and phenotype. As with other ‘omics’ techniques, metabolomic analysis generates large-scale and complex datasets. Therefore, various data analysis tools are needed to extract biologically relevant information. The data analysis workflows in metabolomics studies are generally complex and involve several steps. In this chapter, we highlight the concept of metabolomics workflow and discuss the data analysis strategies for metabolomics experiments. We also discuss the available tools that can assist in biological interpretation of metabolomics data. We also present an emerging approach of developing genome-scale metabolic models to study cellular metabolism.

International audience; Nuclear receptor PPARγ affects lipid metabolism in several tissues, but its role in intestinal lipid metabolism has not been explored. As alterations have been observed in the plasma lipid profile of ad libitum fed intestinal epithelium-specific PPARγ knockout mice (iePPARγKO), we submitted these mice to lipid gavage challenges. Within hours after gavage with long chain unsaturated fatty acid (FA)-rich canola oil, the iePPARγKO mice had higher plasma free FA levels and lower gastric inhibitory polypeptide levels than their wild-type (WT) littermates, and altered expression of incretin genes and lipid metabolism-associated genes in the intestinal epithelium. Gavage with the medium chain saturated FA-rich coconut oil did not result in differences between the two genotypes. Furthermore, the iePPARγKO mice did not exhibit defective lipid uptake and stomach emptying; however, their intestinal transit was more rapid than in WT mice. When fed a canola oil-rich diet for 4.5 months, iePPARγKO mice had higher body lean mass than the WT mice. We conclude that intestinal epithelium PPARγ is activated preferentially by long chain unsaturated FAs compared to medium chain saturated FAs. Furthermore, we hypothesize that the iePPARγKO phenotype originates from altered lipid metabolism and release in epithelial cells, as well as changes in intestinal motility.

To critically review current knowledge on the positive and negative predictive value of blood biomarkers for concussion; to illustrate the clinical and biological contexts that help evaluate the use of these markers in sport-related traumatic brain injuries (TBIs).This systematic review was performed in accordance with PRISMA guidelines. We reviewed the measurement, clinical utility, endpoint, and biological significance of blood biomarkers in concussion.A total of 4352 publications were identified. Twenty-six articles relating to blood biomarkers were included in the review. Four common blood biomarkers, namely S100B, tau, neuron-specific enolase (NSE), and glial fibrillary acidic protein (GFAP), were examined. Overall, the studies showed S100B measurement and use, either acutely or at several time points, can distinguish injured from noninjured patients with an uncertain degree of utility in predicting mortality. At present, S100B has largely become an acceptable biomarker of TBI; however, studies have begun to highlight the need to incorporate clinical symptoms instead of S100B concentration in isolation on the basis of inconsistent results and lack of specificity across published studies. Further research is needed to evaluate and validate the use of tau, NSE, and GFAP as a diagnostic aid in the management of concussion and TBI.At present, blood biomarkers have only a limited role in the evaluation and management of concussion. Although several biomarkers of brain injury have been identified, continued research is required. S100B holds promise as the most clinically useful diagnostic biomarker. Blood biomarkers, in combination with other clinical data, such as head computed tomography, would maximize the diagnostic accuracy. The methodological limitations evident in blood biomarker research results in the need for the clinical utility of blood biomarker use in concussion to be further explored.

The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36 cases vs 117 controls) preceeding or coincident with the development of psychotic disorder (PD) at age 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC). Overall, 179 lipids were identified at age 11, with 32 found to be significantly altered between the control and PD groups. Following correction for multiple comparisons, 8 of these lipids remained significant (lysophosphatidlycholines (LPCs) LPC(18:1), LPC(18:2), LPC(20:3); phosphatidlycholines (PCs) PC(32:2; PC(34:2), PC(36:4), PC(0-34-3) and sphingomyelin (SM) SM(d18:1/24:0)), all of which were elevated in the PD group. At age 18, 23 lipids were significantly different between the control and PD groups, although none remained significant following correction for multiple comparisons. In conclusion, the findings indicate that the lipidome is altered in the blood during childhood, long before the development of psychotic disorder. LPCs in particular are elevated in those who develop PD, indicating inflammatory abnormalities and altered phospholipid metabolism. These findings were not found at age 18, suggesting there may be ongoing alterations in the pathophysiological processes from prodrome to onset of PD. European Research Council Health Research Board Wellcome Trust UK Medical Council

Traumatic brain injury (TBI) is a complex disease with a multifaceted pathophysiology. Impairment of energy metabolism is a key component of secondary insults. This phenomenon is a consequence of multiple potential mechanisms including diffusion hypoxia, mitochondrial failure and increased energy needs due to systemic trauma responses, seizures or spreading depolarization. The degree of disturbance in brain metabolism is affected by treatment interventions and reflected in clinical patient outcome. Hence, monitoring of these secondary events in peripheral blood will provide a window into the pathophysiological course of severe TBI. New methods for assessing perturbation of brain metabolism are needed in order to monitor on-going pathophysiological processes and thus facilitate targeted interventions, and predict outcome. Circulating metabolites in peripheral blood may serve as sensitive markers of pathological processes in TBI. The levels of these small molecules in blood are less dependent on the integrity of the blood-brain-barrier and recently characterized glymphatic system, as compared to protein biomarkers. We have recently characterized a specific metabolic profile in serum that is associated with both initial severity and patient outcome of TBI. We found that two medium-chain fatty acids, octanoic and decanoic acids, as well as several sugar derivatives are significantly associated with the severity of TBI. The top ranking peripheral blood metabolites were also highly correlated with their levels in cerebral microdialysates. Based on the metabolite profile upon admission, we have been able to develop a model that accurately predicts patient outcome. Moreover, metabolomics profiling improved the performance of the well-established clinical prognostication model. In this review, we discuss metabolomics profiling in patients with severe TBI. We present arguments in support of the need for further development and validation of circulating biomarkers of cerebral metabolism and for their use in assessing patients with severe TBI.

Summary Thyroid hormones (THs) act in the brain to modulate energy balance. We show that central triiodothyronine (T3) regulates de novo lipogenesis in liver and lipid oxidation in brown adipose tissue (BAT) through the parasympathetic (PSNS) and sympathetic nervous system (SNS), respectively. Central T3 promotes hepatic lipogenesis with parallel stimulation of the thermogenic program in BAT. The action of T3 depends on AMP-activated protein kinase (AMPK)-induced regulation of two signaling pathways in the ventromedial nucleus of the hypothalamus (VMH): decreased ceramide-induced endoplasmic reticulum (ER) stress, which promotes BAT thermogenesis, and increased c-Jun N-terminal kinase (JNK) activation, which controls hepatic lipid metabolism. Of note, ablation of AMPKα1 in steroidogenic factor 1 (SF1) neurons of the VMH fully recapitulated the effect of central T3, pointing to this population in mediating the effect of central THs on metabolism. Overall, these findings uncover the underlying pathways through which central T3 modulates peripheral metabolism., Graphical Abstract, Highlights • Central T3 regulates lipogenesis in liver via the parasympathetic nervous system • Central T3 regulates lipid oxidation in BAT via the sympathetic nervous system • Ablation of AMPK in SF1 neurons of the VMH recapitulates the effects of T3 • Hypothalamic JNK1 and ceramides/ER stress mediate T3 actions on liver and BAT, Martínez-Sánchez et al. show that thyroid hormones act in the hypothalamus to regulate hepatic lipogenesis and brown fat lipid oxidation via the parasympathetic and sympathetic nervous systems. These peripheral effects are orchestrated by two distinct signaling pathways in the VMH, JNK1 and ceramides/ER stress, which are under AMPK control.

International audience; Clinical trials are needed to confirm the association between polyphenol consumption and lower incidence of chronic diseases observed in epidemiological studies. However, a reliable evaluation of polyphenol intake is complicated. An 8-week randomized controlled trial (78 subjects) was performed using two isoenergetic diets differing only for polyphenol contents. Then, urinary phenolic metabolite profiles were analysed using gas-chromatography with mass detection. Phenolic metabolites detected in 24-h-urine were hydroxylated phenolic acids with C1-C3 side chain in the group consuming polyphenol-rich diet. The intake of polyphenol-rich foods increases the excretion of phenolic metabolites in urine providing a profile, which may serve as compliance biomarker of polyphenol-rich diet.

Aims/hypothesis: Not all obese individuals display the metabolic disturbances commonly associated with excess fat accumulation. Mechanisms maintaining this ‘metabolically healthy obesity’ (MHO) are as yet unknown. We aimed to study different fat depots and transcriptional pathways in subcutaneous adipose tissue (SAT) as related to the MHO phenomenon. Methods: Sixteen rare young adult obesity-discordant monozygotic (MZ) twin pairs (intra-pair difference (∆) in BMI ≥3 kg/m2), aged 22.8–35.8 years, were examined for detailed characteristics of metabolic health (subcutaneous, intra-abdominal and liver fat [magnetic resonance imaging/spectroscopy]), OGTT, lipids, adipokines and C-reactive protein (CRP). Affymetrix U133 Plus 2.0 chips were used to analyse transcriptomics pathways related to mitochondrial function and inflammation in SAT. Results: Based on liver fat accumulation, two metabolically different subgroups emerged. In half (8/16) of the pairs (∆weight 17.1 ± 2.0 kg), the obese co-twin had significantly higher liver fat (∆718%), 78% increase in AUC insulin during OGTT and CRP, significantly more disturbance in the lipid profile and greater tendency for hypertension compared with the lean co-twin. In these obese co-twins, SAT expression of mitochondrial oxidative phosphorylation, branched-chain amino acid catabolism, fatty acid oxidation and adipocyte differentiation pathways were downregulated and chronic inflammation upregulated. In the other eight pairs (∆weight 17.4 ± 2.8 kg), the obese co-twin did not differ from the non-obese co-twin in liver fat (∆8%), insulin sensitivity, CRP, lipids, blood pressure or SAT transcriptomics. Conclusions/interpretation: Our results suggest that maintenance of high mitochondrial transcription and lack of inflammation in SAT are associated with low liver fat and MHO., Cited By :56; Export Date: 12 March 2018; ArticleFunding Agencies:Helsinki University Central HospitalBiomedicum HelsinkiJalmari and Rauha Ahokas (KHP)Finnish Medical Foundations Finnish Foundation for Cardiovascular Research Competitive Research Funding of the Pirkanmaa Hospital DistrictAcademy of Finland Centre of Excellence in Complex Disease GeneticsNational Institute of Alcohol Abuse and Alcoholism

The epidemic of obesity imposes unprecedented challenges on human adipose tissue (WAT) storage capacity that may benefit from adaptive mechanisms to maintain adipocyte functionality. Here, we demonstrate that changes in the regulatory feedback set point control of Insig1/SREBP1 represent an adaptive response that preserves WAT lipid homeostasis in obese and insulin-resistant states. In our experiments, we show that Insig1 mRNA expression decreases in WAT from mice with obesity-associated insulin resistance and from morbidly obese humans and in in vitro models of adipocyte insulin resistance. Insig1 downregulation is part of an adaptive response that promotes the maintenance of SREBP1 maturation and facilitates lipogenesis and availability of appropriate levels of fatty acid unsaturation, partially compensating the antilipogenic effect associated with insulin resistance. We describe for the first time the existence of this adaptive mechanism in WAT, which involves Insig1/SREBP1 and preserves the degree of lipid unsaturation under conditions of obesity-induced insulin resistance. These adaptive mechanisms contribute to maintain lipid desaturation through preferential SCD1 regulation and facilitate fat storage in WAT, despite on-going metabolic stress., Funding agencies:MRC Biotechnology and Biological Sciences Research CouncilEuropean Foundation for the Study of DiabetesIntegrative Pharmacology FundFritz Thyssen Foundation fellowship (Germany)National Institute for Health Research

Objective— Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450). Approach and Results— In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the HLA region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 (VCAM1) levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the HLA region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies–identified HDL genes. Conclusions— Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis -expression quantitative trait loci ( cis -eQTL) variants in HLA region to be associated with low HDL-C.