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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 measure, Funding agencies:Elucidating Pathways of Steatohepatitis (EPoS) consortium - Horizon 2020634413Innovative Medicines Initiative (IMI2) Program of the European Union 777377EFPIANewcastle NIHR Biomedical Research CentreEuropean NAFLD Registry

Background and aims: Non-alcoholic fatty liver disease (NAFLD), the leading cause of chronic liver disease, affects 25%+ of people worldwide. Detailed understanding of the metabolomics of NAFLD, and non-invasive diagnostic techniques for the stages of NAFLD are unavailable. We identify specific serum molecular lipid signatures to these ends. First, we leverage lipidomic and polar metabolomic data (n = 643) subjects, to produce a clear, meaningful interaction map, linking lipids, metabolites, clinical factors and disease outcomes. We find non-spurious associations therein, as features of interest, and for downstream analysis. Third, NAFLD fibrosis biomarker identification was performed using machine learning, with our candidate lipids/metabolites to be forwarded to a successor project; the LITMUS project, towards clinically-applicable, non-invasive, sensitive and specific classification of NAFLD patients. Method: Serum lipids and polar metabolites were measured by mass spectrometry in the EPoS cohort of patients (n = 176 lipids and n = 36 polar metabolites), combined with clinical data from (n = 643 subjects), followed by model-based clustering, giving 10 lipid clusters (LCs). Correlations were calculated pairwise between (1) all LCs, (2) “input” clinical data (height, weight, BMI, blood platelet count) and (3) outcomes (fibrosis, steatosis, NAS score, etc.). Non-rejection rates (NRRs) were calculated for relationships, remove spurious associations (NRR > 0.4). We project the remaining associations as a network; a novel metabolomic overview NAFLD. ANOVA and Tukey’s Honest Significant Differences (Tukey HSDs) revealed detailed metabolic signatures across NAFLD, fibrosis and steatosis stages. Random forest machine learning was used to classify NAFLD patients: LOW (0-1 fibrosis grade) or HIGH (2–4 fibrosis grade), using individual lipids and metabolites, identifying putative biomarkers. Results: In linewith our previous findings, many lipids associate with steatosis

Osteoarthritis (OA) impacts hundreds of millions of people worldwide, with those affected incurring significant physical and financial burdens. Injuries such as focal defects to the articular surface are a major contributing risk factor for the development of OA. Current cartilage repair strategies are moderately effective at reducing pain but often replace damaged tissue with biomechanically inferior fibrocartilage. Here we describe the development, transcriptomic ontogenetic characterization and quality assessment at the single cell level, as well as the scaled manufacturing of an allogeneic human pluripotent stem cell-derived articular chondrocyte formulation that exhibits long-term functional repair of porcine articular cartilage. These results define a new potential clinical paradigm for articular cartilage repair and mitigation of the associated risk of OA.

Background and aims: Non-alcoholic fatty liver disease (NAFLD) is a spectrum of chronic liver diseases intertwined with the metabolic disorders. The prevalence of NAFLD is rapidly increasing worldwide, while the pathologyand the underlying mechanism driving NAFLD is 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., transition from non-alcoholic 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. Method: We analyzed the whole liver tissue transcriptomic (RNA-Seq)1 and serum metabolomics data obtained from a large 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). Results: Our study identified several metabolic signatures in the liver and blood of these patients, specifically highlighting the alteration of vitamins (A, E) and glycosphingolipids, and their link with complex glycosaminoglycans in advanced fibrosis. Furthermore, by applying genome-scale metabolic modeling, 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,TM6SF2andHSD17B13). Conclusion: The study provides insights into the underlying pathways of the progressive-fibrosing steatohepatitis. Of note, there is a marked dysregulation of the glycosphingolipid metabolism in the liver of the patients with advanced fibrosis.

In the last decade, increasing incidence of type 1 diabetes (T1D) stabilized in Finland, a phenomenon that coincides with tighter regulation of perfluoroalkyl substances (PFAS). Here, we quantified PFAS to examine their effects, during pregnancy, on lipid and immune-related markers of T1D risk in children. In a mother-infant cohort (264 dyads), high PFAS exposure during pregnancy associated with decreased cord serum phospholipids and progression to T1D-associated islet autoantibodies in the offspring. This PFAS-lipid association appears exacerbated by increased human leukocyte antigen-conferred risk of T1D in infants. Exposure to a single PFAS compound or a mixture of organic pollutants in non-obese diabetic mice resulted in a lipid profile characterized by a similar decrease in phospholipids, a marked increase of lithocholic acid, and accelerated insulitis. Our findings suggest that PFAS exposure during pregnancy contributes to risk and pathogenesis of T1D in offspring., Funding Agencies:United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK)1DP3DK094338-01Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research 250114Academy of Finland postdoctoral grant 323171Medical Research Funds, Tampere University Hospital Juvenile Diabetes Research Foundation 2-SRA-2016-341-S-B 2-SRA-2016-289-S-BMedical Research Funds, Helsinki University Hospital

Background and Aims: Nonalcoholic fatty liver disease (NAFLD) is a progressive liver disease that is strongly associated with type 2 diabetes. Accurate, non-invasive diagnostic tests to deliniate the different stages: degree of steatosis, grade of nonalcoholic steatohepatitis (NASH) and stage fibrosis represent an unmet medical need. In our previous studies, we successfully identified specific serum molecular lipid signatures which associate with the amount of liver fat as well as with NASH. Here we report underlying associations between clinical data, lipidomic profiles, metabolic profiles and clinical outcomes, including downstream identification of potential biomarkers for various stages of the disease. Method: We leverage several statistical and machine-learning approaches to analyse clinical, lipidomic and metabolomic profiles of individuals from the European Horizon 2020 project: Elucidating Pathways of Steatohepatitis (EPoS). We interrogate data on patients representing the full spectrum of NAFLD/NASH derived from the EPoS European NAFLD Registry (n = 627). We condense the EPoS lipidomic data into lipid clusters and subsequently apply non-rejection-rate-pruned partial correlation network techniques to facilitate network analysis between the datasets of lipidomic, metabolomic and clinical data. For biomarker identification, random forest ensemble classification and neural network machine learning approaches were used to both search for valid disease biomarkers and to assess the relative improvement over clinical-data-only classification versus addition of our lipidomic and metabolomic datasets. Results: We found that steatosis grade was strongly associated with (1) an increase of triglycerides with low carbon number and double bond count as well as (2) a decrease of specific phospholipids, including lysophosphatidylcholines. In addition to the network topology as a result itself, we also present lipid clusters (LCs) of interest to the derived network of propos

The use of a new atmospheric-pressure chemical ionization source for gas chromatography (APGC) coupled with a tandem quadrupole mass spectrometry (MS/MS) system, as an alternative to high-resolution mass spectrometry (HRMS), for the determination of PCDDs/PCDFs is described. The potential of using atmospheric-pressure chemical ionization (APCI) coupled to a tandem quadrupole analyzer has been validated for the identification and quantification of dioxins and furans in different complex matrices. The main advantage of using the APCI source is the soft ionization at atmospheric pressure, which results in very limited fragmentation. APCI mass spectra are dominated by the molecular ion cluster, in contrast with the high energy ionization process under electron ionization (El). The use of the molecular ion as the precursor ion in MS/MS enhances selectivity and, consequently, sensitivity by increasing the signal-to-noise ratios (S/N). For standard solutions of 2,3,7,8-TCDD, injections of 10 fg in the splitless mode on 30- or 60-m-length, 0.25 mm inner diameter (id), and 25 mu m film thickness low-polarity capillary columns (DB5MS type), signal-to-noise (S/N) ratios of >10:1 were routinely obtained. Linearity was achieved in the region (correlation coefficient of r(2) > 0.998) for calibration curves ranging from 100 fg/mu L, to 1000 pg/mu L. The results from a wide variety of complex samples, including certified and standard reference materials and samples from several QA/QC studies, which were previously analyzed by EI HRGC/HRMS, were compared with the results from the APGC/MS/MS system. Results between instruments showed good agreement both in individual congeners and toxic equivalence factors (TEQs). The data show that the use of APGC in combination with MS/MS for the analysis of dioxins has the same potential, in terms of sensitivity and selectivity, as the traditional HEMS instrumentation used for this analysis. However, the APCI/MS/MS system, as a benchtop syst, Funding Agencies:Generalitat Valenciana, as research group of excellence PROMETEO/2009/054Serveis Centrals d'Instrumentacio Cientifica (SCIC) of the University Jaume IChina Scholarship Council 201206400003

Analysis of the brominated flame retardant hexabromocyclododecane (HBCDD) is characterized by the separation of its three predominant diastereomers. This analysis is typically performed using reversed phase liquid chromatography (RPLC) coupled with mass spectrometric (MS) detection with analysis times in the order of 10 minutes or greater. Here we describe a rapid method using supercritical CO2 and methanol to baseline separate the three most abundant HBCDD diastereomers within a three minute run time using a High Strength Silica (HSS) C18 1.8 mu m particle size column. A unique elution order of the alpha-, beta- and gamma-HBCDD diastereomers using supercritical CO2 was observed, and can be used as an orthogonal separation for further confidence in diastereomer identification when used in conjuction with RPLC. A tandem quadrupole mass spectrometer with negative mode electrospray ionization was used for detection, operating in multiple reaction monitoring (MRM) mode. Ionization was enhanced by the addition of a make-up flow, which was introduced to the post-column effluent. Method limit of detection (LOD) and limit of quantification (LOQ) for alpha-, beta- and gamma-HBCDD were based on peak-to-peak signal to noise ratios of greater than 3 or 10, respectively. The LOD for all HBCDD diastereomers as solvent standards was 100 fg on-column, and LOQs 500 fg on-column for alpha- and gamma-HBCDD and 250 fg on-column for beta-HBCDD. In order to test the efficiency of this method, small subsets of complex human serum and whale blubber extracts were analyzed using this method, resulting in positive detections in samples of alpha-HBCDD.