| 1. |
- Hylén, Ulrika, 1977-, et al.
(author)
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Potential Transdiagnostic Lipid Mediators of Inflammatory Activity in Individuals With Serious Mental Illness
- 2021
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In: Frontiers in Psychiatry. - : Frontiers Media S.A.. - 1664-0640. ; 12
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Journal article (peer-reviewed)abstract
- Mental disorders are heterogeneous and psychiatric comorbidities are common. Previous studies have suggested a link between inflammation and mental disorders. This link can manifest as increased levels of proinflammatory mediators in circulation and as signs of neuroinflammation. Furthermore, there is strong evidence that individuals suffering from psychiatric disorders have increased risk of developing metabolic comorbidities. Our group has previously shown that, in a cohort of low-functioning individuals with serious mental disorders, there is increased expression of genes associated with the NLRP3 inflammasome, a known sensor of metabolic perturbations, as well as increased levels of IL-1-family cytokines. In the current study, we set out to explore the interplay between disease-specific changes in lipid metabolism and known markers of inflammation. To this end, we performed mass spectrometry-based lipidomic analysis of plasma samples from low-functioning individuals with serious mental disorders (n = 39) and matched healthy controls (n = 39). By identifying non-spurious immune-lipid associations, we derived a partial correlation network of inflammatory markers and molecular lipids. We identified levels of lipids as being altered between individuals with serious mental disorders and controls, showing associations between lipids and inflammatory mediators, e.g., osteopontin and IL-1 receptor antagonist. These results indicate that, in low-functioning individuals with serious mental disorders, changes in specific lipids associate with immune mediators that are known to affect neuroinflammatory diseases.
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| 2. |
- Hyötyläinen, Tuulia, 1971-, et al.
(author)
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In utero exposures to perfluoroalkyl substances and the human fetal liver metabolome in Scotland : a cross-sectional study
- 2024
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In: The Lancet Planetary Health. - : Elsevier. - 2542-5196. ; 8:1, s. e5-e17
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Journal article (peer-reviewed)abstract
- BACKGROUND: Perfluoroalkyl and polyfluoroalkyl substances are classed as endocrine disrupting compounds but continue to be used in many products such as firefighting foams, flame retardants, utensil coatings, and waterproofing of food packaging. Perfluoroalkyl exposure aberrantly modulates lipid, metabolite, and bile acid levels, increasing susceptibility to onset and severity of metabolic diseases, such as diabetes and metabolic dysfunction-associated steatotic liver disease. To date, most studies in humans have focused on perfluoroalkyl-exposure effects in adults. In this study we aimed to show if perfluoroalkyls are present in the human fetal liver and if they have metabolic consequences for the human fetus.METHODS: In this cross-sectional study, human fetal livers from elective termination of pregnancies at the Aberdeen Pregnancy Counselling Service, Aberdeen, UK, were analysed by both targeted (bile acids and perfluoroalkyl substances) and combined targeted and untargeted (lipids and polar metabolites) mass spectrometry based metabolomic analyses, as well as with RNA-Seq. Only fetuses from normally progressing pregnancies (determined at ultrasound scan before termination), terminated for non-medical reasons, from women older than 16 years, fluent in English, and between 11 and 21 weeks of gestation were collected. Women exhibiting considerable emotional distress or whose fetuses had anomalies identified at ultrasound scan were excluded. Stringent bioinformatic and statistical methods such as partial correlation network analysis, linear regression, and pathway analysis were applied to this data to investigate the association of perfluoroalkyl exposure with hepatic metabolic pathways.FINDINGS: Fetuses included in this study were collected between Dec 2, 2004, and Oct 27, 2014. 78 fetuses were included in the study: all 78 fetuses were included in the metabolomics analysis (40 female and 38 male) and 57 fetuses were included in the RNA-Seq analysis (28 female and 29 male). Metabolites associated with perfluoroalkyl were identified in the fetal liver and these varied with gestational age. Conjugated bile acids were markedly positively associated with fetal age. 23 amino acids, fatty acids, and sugar derivatives in fetal livers were inversely associated with perfluoroalkyl exposure, and the bile acid glycolithocholic acid was markedly positively associated with all quantified perfluoroalkyl. Furthermore, 7α-hydroxy-4-cholesten-3-one, a marker of bile acid synthesis rate, was strongly positively associated with perfluoroalkyl levels and was detectable as early as gestational week 12.INTERPRETATION: Our study shows direct evidence for the in utero effects of perfluoroalkyl exposure on specific key hepatic products. Our results provide evidence that perfluoroalkyl exposure, with potential future consequences, manifests in the human fetus as early as the first trimester of gestation. Furthermore, the profiles of metabolic changes resemble those observed in perinatal perfluoroalkyl exposures. Such exposures are already linked with susceptibility, initiation, progression, and exacerbation of a wide range of metabolic diseases.
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| 3. |
- Sen, Partho, 1983-, et al.
(author)
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Exposure to environmental contaminants is associated with altered hepatic lipid metabolism in non-alcoholic fatty liver disease
- 2022
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 76:2, s. 283-293
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Journal article (peer-reviewed)abstract
- Background & aims: Recent experimental models and epidemiological studies suggest that specific environmental contaminants (ECs) contribute to the initiation and pathology of non-alcoholic 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-à-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.
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| 4. |
- Alves, Marina Amaral, et al.
(author)
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Systems biology approaches to study lipidomes in health and disease
- 2021
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In: Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids. - : Elsevier. - 1388-1981 .- 1879-2618. ; 1866:2
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Research review (peer-reviewed)abstract
- 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.
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| 5. |
- Fart, Frida, 1992-, et al.
(author)
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Perfluoroalkyl substances are increased in patients with late-onset ulcerative colitis and induce intestinal barrier defects ex vivo in murine intestinal tissue
- 2021
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In: Scandinavian Journal of Gastroenterology. - : Taylor & Francis. - 0036-5521 .- 1502-7708. ; 56:11, s. 1286-1295
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Journal article (peer-reviewed)abstract
- BACKGROUND: Environmental factors are strongly implicated in late-onset of inflammatory bowel disease. Here, we investigate whether high levels of perfluoroalkyl substances are associated with (1) late-onset inflammatory bowel disease, and (2) disturbances of the bile acid pool. We further explore the effect of the specific perfluoroalkyl substance perfluorooctanoic acid on intestinal barrier function in murine tissue.METHODS: Serum levels of perfluoroalkyl substances and bile acids were assessed by ultra-performance liquid chromatography coupled to a triple-quadrupole mass spectrometer in matched samples from patients with ulcerative colitis (n = 20) and Crohn's disease (n = 20) diagnosed at the age of ≥55 years. Age and sex-matched blood donors (n = 20), were used as healthy controls. Ex vivo Ussing chamber experiments were performed to assess the effect of perfluorooctanoic acid on ileal and colonic murine tissue (n = 9).RESULTS: The total amount of perfluoroalkyl substances was significantly increased in patients with ulcerative colitis compared to healthy controls and patients with Crohn's disease (p < .05). Ex vivo exposure to perfluorooctanoic acid induced a significantly altered ileal and colonic barrier function. The distribution of bile acids, as well as the correlation pattern between (1) perfluoroalkyl substances and (2) bile acids, differed between patient and control groups.DISCUSSION: Our results demonstrate that perfluoroalkyl substances levels are increased in patients with late-onset ulcerative colitis and may contribute to the disease by inducing a dysfunctional intestinal barrier.
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| 6. |
- McGlinchey, Aidan J, 1984-, et al.
(author)
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Metabolic signatures across the full spectrum of non-alcoholic fatty liver disease
- 2022
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In: JHEP Reports. - : Elsevier. - 2589-5559. ; 4:5
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Journal article (peer-reviewed)abstract
- Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a progressive liver disease with potentially severe complications including cirrhosis and hepatocellular carcinoma. Previously, we have identified circulating lipid signatures associating with liver fat content and non-alcoholic steatohepatitis (NASH). Here, we develop a metabolomic map across the NAFLD spectrum, defining interconnected metabolic signatures of steatosis (non-alcoholic fatty liver, NASH, and fibrosis).Methods: We performed mass spectrometry analysis of molecular lipids and polar metabolites in serum samples from the European NAFLD Registry patients (n = 627), representing the full spectrum of NAFLD. Using various univariate, multivariate, and machine learning statistical approaches, we interrogated metabolites across 3 clinical perspectives: steatosis, NASH, and fibrosis.Results: Following generation of the NAFLD metabolic network, we identify 15 metabolites unique to steatosis, 18 to NASH, and 15 to fibrosis, with 27 common to all. We identified that progression from F2 to F3 fibrosis coincides with a key pathophysiological transition point in disease natural history, with n = 73 metabolites altered.Conclusions: Analysis of circulating metabolites provides important insights into the metabolic changes during NAFLD progression, revealing metabolic signatures across the NAFLD spectrum and features that are specific to NAFL, NASH, and fibrosis. The F2-F3 transition marks a critical metabolic transition point in NAFLD pathogenesis, with the data pointing to the pathophysiological importance of metabolic stress and specifically oxidative stress.Clinical Trials registration: The study is registered at Clinicaltrials.gov (NCT04442334).Lay summary: Non-alcoholic fatty liver disease is characterised by the build-up of fat in the liver, which progresses to liver dysfunction, scarring, and irreversible liver failure, and is markedly increasing in its prevalence worldwide. Here, we measured lipids and other small molecules (metabolites) in the blood with the aim of providing a comprehensive molecular overview of fat build-up, liver fibrosis, and diagnosed severity. We identify a key metabolic 'watershed' in the progression of liver damage, separating severe disease from mild, and show that specific lipid and metabolite profiles can help distinguish and/or define these cases.
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| 7. |
- McGlinchey, Aidan J, 1984-, et al.
(author)
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Metabolomics approaches to identify biomarkers of nonalcoholic fatty liver disease
- 2020
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 73:Suppl. 1, s. S438-S438
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Journal article (other academic/artistic)abstract
- 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 proposed interactions in our NAFLD data from the EPoS cohort, along with our proposed biomarkers for various disease outcomes, as put forward by our current machine learning analyses.Conclusion: Our findings suggest that dysregulation of lipid metabolism in progressive stages of NAFLD is reflected in circulation and may thus hold diagnostic value as well as offer new insights about the NAFLD pathogenesis. Using this cohort as a proof-of-concept, we demonstrate current progress in tuning the accuracy of neural network and random forest approaches with a view to predicting various subtypes of NAFLD patient using a minimal set of lipidomic and metabolic markers. A detailed network-based picture emerges between lipids, polar metabolites and clinical variables. Lipidomic/metabolomic markers may provide an alternative method of NAFLD patient classification and risk stratification to guide therapy.
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| 8. |
- McGlinchey, Aidan J, 1984-, et al.
(author)
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Prenatal exposure to perfluoroalkyl substances modulates neonatal serum phospholipids, increasing risk of type 1 diabetes
- 2020
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In: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 143
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Journal article (peer-reviewed)abstract
- 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.
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| 9. |
- McGlinchey, Aidan J, 1984-, et al.
(author)
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The Metabolomics of Non-Alcoholic Fatty Liver Disease : Of Networks and Biomarkers
- 2021
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 75:Suppl. 2, s. S579-S580
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Journal article (other academic/artistic)abstract
- 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 and fibrosis in NAFLD. Our novel overview network revealsas sociations between specific LCs and clinical variables, such as TGs (LC3), and a subgroup of TGs of lowest and highest carbon numbers (LC9) along with PC (O)s (LC7) positively associating with NAFLD score and fibrosis. Conversely, LPCs (LC4), particularly sphingomyelins (SMs, LC6), negatively associated with these variables. Many other metabolites changing across NAFLD stages beg further discussion.Conclusion: In addition to generation of a novel metabolomic network of NAFLD, we demonstrate feasibility of lipidomic and metabolomic data to classify NAFLD patients’fibrosis grades (median AUC: 0.765), competitive with gold-standard clinical variables (age, BMI, sex, diabetes, liver AST/ALT, platelet count) (median AUC: 0.778). These biomarkers are being taken forward (LITMUS project) to develop clinical testing.
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| 10. |
- Mehmood, Arfa, et al.
(author)
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Systematic evaluation of differential splicing tools for RNA-seq studies
- 2020
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In: Briefings in Bioinformatics. - : Oxford University Press. - 1467-5463 .- 1477-4054. ; 21:6, s. 2052-2065
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Journal article (peer-reviewed)abstract
- Differential splicing (DS) is a post-transcriptional biological process with critical, wide-ranging effects on a plethora of cellular activities and disease processes. To date, a number of computational approaches have been developed to identify and quantify differentially spliced genes from RNA-seq data, but a comprehensive intercomparison and appraisal of these approaches is currently lacking. In this study, we systematically evaluated 10 DS analysis tools for consistency and reproducibility, precision, recall and false discovery rate, agreement upon reported differentially spliced genes and functional enrichment. The tools were selected to represent the three different methodological categories: exon-based (DEXSeq, edgeR, JunctionSeq, limma), isoform-based (cuffdiff2, DiffSplice) and event-based methods (dSpliceType, MAJIQ, rMATS, SUPPA). Overall, all the exon-based methods and two event-based methods (MAJIQ and rMATS) scored well on the selected measures. Of the 10 tools tested, the exon-based methods performed generally better than the isoform-based and event-based methods. However, overall, the different data analysis tools performed strikingly differently across different data sets or numbers of samples.
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| 11. |
- Oresic, Matej, 1967-, et al.
(author)
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Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health
- 2020
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In: Metabolites. - : MDPI. - 2218-1989 .- 2218-1989. ; 10:11
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Research review (peer-reviewed)abstract
- Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the "chemical exposome" (exposures to environmental chemicals), affect the host's metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.
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| 12. |
- Sen, Partho, 1983-, et al.
(author)
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Deep learning meets metabolomics : a methodological perspective
- 2021
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In: Briefings in Bioinformatics. - : Oxford University Press. - 1467-5463 .- 1477-4054. ; 22:2, s. 1531-1542
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Research review (peer-reviewed)abstract
- Deep learning (DL), an emerging area of investigation in the fields of machine learning and artificial intelligence, has markedly advanced over the past years. DL techniques are being applied to assist medical professionals and researchers in improving clinical diagnosis, disease prediction and drug discovery. It is expected that DL will help to provide actionable knowledge from a variety of 'big data', including metabolomics data. In this review, we discuss the applicability of DL to metabolomics, while presenting and discussing several examples from recent research. We emphasize the use of DL in tackling bottlenecks in metabolomics data acquisition, processing, metabolite identification, as well as in metabolic phenotyping and biomarker discovery. Finally, we discuss how DL is used in genome-scale metabolic modelling and in interpretation of metabolomics data. The DL-based approaches discussed here may assist computational biologists with the integration, prediction and drawing of statistical inference about biological outcomes, based on metabolomics data.
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| 13. |
- Sen, Partho, 1983-, et al.
(author)
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Genome-scale metabolic modeling of human hepatocytes reveals dysregulation of glycosphingolipid pathways in progressive non-alcoholic fatty liver disease
- 2021
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 75:Suppl. 2, s. S256-S256
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Journal article (other academic/artistic)abstract
- 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.
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| 14. |
- Sen, Parho, et al.
(author)
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Metabolism of human liver on a genome scale in non-alcoholic fatty liver disease
- 2020
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 73:Suppl. 1, s. S671-S672
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Journal article (other academic/artistic)abstract
- Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. By using patient-matched liver transcriptomics and serum metabolomics data from the EPoS European NAFLD Registry cohort, we conducted genome-scale metabolic modeling (GSMM) to dissect hepatic metabolism across the full spectrum of NAFLD, from steatosis (NAFL) to NASH-cirrhosis.Method: We compared the genome-scale metabolic networks across different stages of NAFLD together with healthy controls (HC, n = 10), with the patients divided into three groups: steatosis (n = 60), NASH (n = 139; F0: n = 4, F1 n = 28, F2: n = 53, F3: n = 54) and cirrhosis (n = 14). Based on transcriptomics data obtained from the liver biopsy of the patients enrolled in the European NAFLD Registry, genome-scale metabolic models of the liver were developed and contextualized for these conditions. GSMM, as a scaffold, connects metabolic genes (i.e., enzymes) and metabolic pathways. Moreover, genome-scale networks can be constrained with multi-‘omics’ datasets, and thus connect an organism’s genotype to phenotype.Results: GSMM revealed that similar metabolic functions are perturbed in NAFL and NASH, while additional metabolic processes were regulated in advanced fibrosis/cirrhosis. The primary liver processes such as glycerophospholipid metabolism, chondroitin/heparan sulfate, bile acid and fatty acid biosynthesis and oxidation (carnitine shuttle in mitochondria) were affected. Lipid precursors for VLDL particles were upregulated in NAFL. Integrative analysis of transcriptomics and serum metabolomics data also revealed that several microbial pathways are up-regulated in NAFLD and may contribute to pathogenesis.Conclusion: A GSMM approach has identified common and specific liver metabolic pathways across different stages of NAFLD progression. Data were cross-validated by serum metabolomics, where in addition analysis also revealed that specific microbially-produced metabolites are elevated in NAFLD as compared to controls. These results provide important insights into the changes in hepatic metabolism occurring during NAFLD/NASH pathogenesis.
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| 15. |
- Sen, Partho, 1983-, et al.
(author)
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Quantitative modeling of human liver reveals dysregulation of glycosphingolipid pathways in nonalcoholic fatty liver disease
- 2022
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In: iScience. - : Cell Press. - 2589-0042. ; 25:9
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Journal article (peer-reviewed)abstract
- Nonalcoholic fatty liver disease (NAFLD) is an increasingly prevalent disease that is associated with multiple metabolic disturbances, yet the metabolic pathways underlying its progression are poorly understood. Here, we studied metabolic pathways of the human liver across the full histological spectrum of NAFLD. We analyzed whole liver tissue transcriptomics and serum metabolomics data obtained from a large, prospectively enrolled cohort of 206 histologically characterized patients derived from the European NAFLD Registry and developed genome-scale metabolic models (GEMs) of human hepatocytes at different stages of NAFLD. We 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, we derived GEMs and identified metabolic signatures of three common NAFLD-associated gene variants (PNPLA3, TM6SF2, and HSD17B13). The study demonstrates dysregulated liver metabolic pathways which may contribute to the progression of NAFLD.
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