Project description:Benzene is a recognized hematotoxin and leukemogen; however, its mechanism of action in humans remain unclear. To provide insight into the processes underlying benzene hematotoxicity, we performed high-resolution metabolomic profiling of plasma collected from a cross-sectional study of 33 healthy workers exposed to benzene (median 8-h time-weighted average exposure; 20 ppma), and 25 unexposed controls in Shanghai, China. Metabolic features associated with benzene were identified using a metabolome-wide association study (MWAS) that tested for the relationship between feature intensity and benzene exposure. MWAS identified 478 mass spectral features associated with benzene exposure at false discovery rate < 20%. Comparison to a list of 13 known benzene metabolites and metabolites predicted using a multi-component biotransformation algorithm showed five metabolites were detected, which included the known metabolites phenol and benzene diolepoxide. Metabolic pathway enrichment identified 41 pathways associated with benzene exposure, with altered pathways including carnitine shuttle, fatty acid metabolism, sulfur amino acid metabolism, glycolysis, gluconeogenesis and branched chain amino acid metabolism. These results suggest disruption to fatty acid uptake, energy metabolism and increased oxidative stress, and point towards pathways related to mitochondrial dysfunction, which has previously been linked to benzene exposure in animal models and human studies. Taken together, these results suggest benzene exposure is associated with disruption of mitochondrial pathways, and provide promising, systems biology biomarkers for risk assessment of benzene-induced hematotoxicity in humans.
Project description:BackgroundExposure to disinfection by-products (DBPs) in drinking water and chlorinated swimming pools are associated with adverse health outcomes, but biological mechanisms remain poorly understood.ObjectivesEvaluate short-term changes in metabolic profiles in response to DBP exposure while swimming in a chlorinated pool.Materials and methodsThe PISCINA-II study (EXPOsOMICS project) includes 60 volunteers swimming 40min in an indoor pool. Levels of most common DBPs were measured in water and in exhaled breath before and after swimming. Blood samples, collected before and 2h after swimming, were used for metabolic profiling by liquid-chromatography coupled to high-resolution mass-spectrometry. Metabolome-wide association between DBP exposures and each metabolic feature was evaluated using multivariate normal (MVN) models. Sensitivity analyses and compound annotation were conducted.ResultsExposure levels of all DBPs in exhaled breath were higher after the experiment. A total of 6,471 metabolic features were detected and 293 features were associated with at least one DBP in exhaled breath following Bonferroni correction. A total of 333 metabolic features were associated to at least one DBP measured in water or urine. Uptake of DBPs and physical activity were strongly correlated and mutual adjustment reduced the number of statistically significant associations. From the 293 features, 20 could be identified corresponding to 13 metabolites including compounds in the tryptophan metabolism pathway.ConclusionOur study identified numerous molecular changes following a swim in a chlorinated pool. While we could not explicitly evaluate which experiment-related factors induced these associations, molecular characterization highlighted metabolic features associated with exposure changes during swimming.
Project description:The underlying mechanisms linking physical activity to better health are not fully understood. Here we examined the associations between physical activity and small circulatory molecules, the metabolome, to highlight relevant biological pathways. We examined plasma metabolites associated with self-reported physical activity among 2217 participants from the Airwave Health Monitoring Study. Metabolic profiling was conducted using the mass spectrometry-based Metabolon platform (LC/GC-MS), measuring 828 known metabolites. We replicated our findings in an independent subset of the study (n = 2971) using untargeted LC-MS. Mendelian randomisation was carried out to investigate potential causal associations between physical activity, body mass index, and metabolites. Higher vigorous physical activity was associated (P < 0.05/828 = 6.03 × 10-5) with circulatory levels of 28 metabolites adjusted for age, sex and body mass index. The association was inverse for glutamate and diacylglycerol lipids, and direct for 3-4-hydroxyphenyllactate, phenyl lactate (PLA), alpha-hydroxy isovalerate, tiglylcarnitine, alpha-hydroxyisocaproate, 2-hydroxy-3-methylvalerate, isobutyrylcarnitine, imidazole lactate, methionine sulfone, indole lactate, plasmalogen lipids, pristanate and fumarate. In the replication panel, we found 23 untargeted LC-MS features annotated to the identified metabolites, for which we found nominal associations with the same direction of effect for three features annotated to 1-(1-enyl-palmitoyl)-2-oleoyl-GPC (P-16:0/18:1), 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2), 1-stearoyl-2-dihomo-linolenoyl-GPC (18:0/20:3n3 or 6). Using Mendelian randomisation, we showed a potential causal relationship between body mass index and three identified metabolites. Circulatory metabolites are associated with physical activity and may play a role in mediating its health effects.
Project description:Electronic cigarettes (e-cig) are an increasingly popular alternative to traditional smoking but have been in use for too short of a period of time to fully understand health risks. Furthermore, associated health risks are difficult to evaluate because of a large range of flavoring agents and their combinations for use with e-cig. Many flavoring agents are generally regarded as safe but have limited studies for effects on lung. Vanillin, an aromatic aldehyde, is one of the most commonly used flavoring agents in e-cig. Vanillin is electrophilic and can be redox active, with chemical properties expected to interact within biologic systems. Because accumulating lung metabolomics studies have identified metabolic disruptions associated with idiopathic pulmonary fibrosis, asthma and acute respiratory distress syndrome, we used human bronchial epithelial cells (BEAS-2B) with high-resolution metabolomics analysis to determine whether these disease-associated pathways are impacted by vanillin over the range used in e-cig. A metabolome-wide association study showed that vanillin perturbed specific energy, amino acid, antioxidant and sphingolipid pathways previously associated with human disease. Analysis of a small publicly available human dataset showed associations with several of the same pathways. Because vanillin is a common and high-abundance flavorant in e-cig, these results show that vanillin has potential to be mechanistically important in lung diseases and warrants in vivo toxicity testing in the context of e-cig use.
Project description:IntroductionOrganophosphate (OP) insecticides, including chlorpyrifos, have been linked with numerous harmful health effects on maternal and child health. Limited data are available on the biological mechanisms and endogenous pathways underlying the toxicity of chlorpyrifos exposures on pregnancy and birth outcomes. In this study, we measured a urinary chlorpyrifos metabolite and used high-resolution metabolomics (HRM) to identify biological perturbations associated with chlorpyrifos exposure among pregnant women in Thailand, who are disparately exposed to high levels of OP insecticides.MethodsThis study included 50 participants from the Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE). We used liquid chromatography-high resolution mass spectrometry to conduct metabolic profiling on first trimester serum samples collected from participants to evaluate metabolic perturbations in relation to chlorpyrifos exposures. We measured 3,5,6-trichloro-2-pyridinol (TCPy), a specific metabolite of chlorpyrifos and chlorpyrifos-methyl, in first trimester urine samples to assess the levels of exposures. Following an untargeted metabolome-wide association study workflow, we used generalized linear models, pathway enrichment analyses, and chemical annotation to identify significant metabolites and pathways associated with urinary TCPy levels.ResultsIn the 50 SAWASDEE participants, the median urinary TCPy level was 4.36 μg TCPy/g creatinine. In total, 691 unique metabolic features were found significantly associated with TCPy levels (p < 0.05) after controlling for confounding factors. Pathway analysis of metabolic features associated with TCPy indicated perturbations in 24 metabolic pathways, most closely linked to the production of reactive oxygen species and cellular damage. These pathways include tryptophan metabolism, fatty acid oxidation and peroxisome metabolism, cytochromes P450 metabolism, glutathione metabolism, and vitamin B3 metabolism. We confirmed the chemical identities of 25 metabolites associated with TCPy levels, including glutathione, cystine, arachidic acid, itaconate, and nicotinamide adenine dinucleotide.DiscussionThe metabolic perturbations associated with TCPy levels were related to oxidative stress, cellular damage and repair, and systemic inflammation, which could ultimately contribute to health outcomes, including neurodevelopmental deficits in the child. These findings support the future development of sensitive biomarkers to investigate the metabolic underpinnings related to pesticide exposure during pregnancy and to understand its link to adverse outcomes in children.
Project description:Existing air pollution metabolomics studies showed inconsistent results, often limited by small sample size and individual air pollutants effects. We conducted a metabolome-wide association study among 1096 women (68.2 ± 5.7 years) who provided blood samples (1998-2001) within the Cancer Prevention Study-II Nutrition Cohort. Annual average individual exposures to particulate matter, nitrogen dioxide, ozone, sulfur dioxide, and carbon monoxide in the year of blood draw were used. Metabolomics profiling was conducted on serum samples by Metabolon. We evaluated the individual air pollutants effects using multiple linear regression and the mixture effect using quantile g-computation, adjusting for confounders and false discovery rate (FDR). Ninety-five metabolites were significantly associated with at least one air pollutant or mixture (FDR < 0.05). These metabolites were enriched in pathways related to oxidative stress, systemic inflammation, energy metabolism, signals transduction, nucleic acid damage and repair, and xenobiotics. Sixty metabolites were confirmed with level 1 or 2 evidence, among which 21 have been previously linked to air pollution exposure, including taurine, creatinine, and sebacate. Overall, our results replicate prior findings in a large sample and provide novel insights into biological responses to long-term air pollution exposure using mixture analysis.
Project description:PurposeTo determine if primary open-angle glaucoma (POAG) patients can be differentiated from controls based on metabolic characteristics.MethodsWe used ultra-high resolution mass spectrometry with C18 liquid chromatography for metabolomic analysis on frozen plasma samples from 72 POAG patients and 72 controls. Metabolome-wide Spearman correlation was performed to select differentially expressed metabolites (DEM) correlated with POAG. We corrected P values for multiple testing using Benjamini and Hochberg false discovery rate (FDR). Hierarchical cluster analysis (HCA) was used to depict the relationship between participants and DEM. Differentially expressed metabolites were matched to the METLIN metabolomics database; both DEM and metabolites significantly correlating with DEM were analyzed using MetaboAnalyst to identify metabolic pathways altered in POAG.ResultsOf the 2440 m/z (mass/charge) features recovered after filtering, 41 differed between POAG cases and controls at FDR = 0.05. Hierarchical cluster analysis revealed these DEM to associate into eight clusters; three of these clusters contained the majority of the DEM and included palmitoylcarnitine, hydroxyergocalciferol, and high-resolution METLIN matches to sphingolipids, other vitamin D-related metabolites, and terpenes. MetaboAnalyst also indicated likely alteration in steroid biosynthesis pathways.ConclusionsGlobal ultrahigh resolution metabolomics emphasized the importance of altered lipid metabolism in POAG. The results suggest specific metabolic processes, such as those involving palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors, may contribute to POAG status and merit more detailed study with targeted methods.
Project description:We report for the first time movement of Correia Repeat Enclosed Elements, through inversion of the element at its chromosomal location. Analysis of Ion Torrent generated genome sequence data from Neisseria gonorrhoeae strain NCCP11945 passaged for 8 weeks in the laboratory under standard conditions and stress conditions revealed a total of 37 inversions: 24 were exclusively seen in the stressed sample; 7 in the control sample; and the remaining 3 were seen in both samples. These inversions have the capability to alter gene expression in N. gonorrhoeae through the previously determined activities of the sequence features of these elements. In addition, the locations of predicted non-coding RNAs were investigated to identify potential associations with CREE. Associations varied between strains, as did the number of each element identified. The analysis indicates a role for CREE in disrupting ancestral regulatory networks, including non-coding RNAs. RNA-Seq was used to examine expression changes related to Correia repeats in the strain
Project description:PurposeTo determine if plasma metabolic profiles can detect differences between patients with neovascular age-related macular degeneration (NVAMD) and similarly-aged controls.MethodsMetabolomic analysis using liquid chromatography with Fourier-transform mass spectrometry (LC-FTMS) was performed on plasma samples from 26 NVAMD patients and 19 controls. Data were collected from mass/charge ratio (m/z) 85 to 850 on a Thermo LTQ-FT mass spectrometer, and metabolic features were extracted using an adaptive processing software package. Both non-transformed and log2 transformed data were corrected using Benjamini and Hochberg False Discovery Rate (FDR) to account for multiple testing. Orthogonal Partial Least Squares-Discriminant Analysis was performed to determine metabolic features that distinguished NVAMD patients from controls. Individual m/z features were matched to the Kyoto Encyclopedia of Genes and Genomes database and the Metlin metabolomics database, and metabolic pathways associated with NVAMD were identified using MetScape.ResultsOf the 1680 total m/z features detected by LC-FTMS, 94 unique m/z features were significantly different between NVAMD patients and controls using FDR (q = 0.05). A comparison of these features to those found with log2 transformed data (n = 132, q = 0.2) revealed 40 features in common, reaffirming the involvement of certain metabolites. Such metabolites included di- and tripeptides, covalently modified amino acids, bile acids, and vitamin D-related metabolites. Correlation analysis revealed associations among certain significant features, and pathway analysis demonstrated broader changes in tyrosine metabolism, sulfur amino acid metabolism, and amino acids related to urea metabolism.ConclusionsThese data suggest that metabolomic analysis can identify a panel of individual metabolites that differ between NVAMD cases and controls. Pathway analysis can assess the involvement of certain metabolic pathways, such as tyrosine and urea metabolism, and can provide further insight into the pathophysiology of AMD.
Project description:IntroductionThe metabolomic changes caused by airborne fine particulate matter (PM2.5) exposure in patients with chronic obstructive pulmonary disease (COPD) remain unclear. The aim of this study was to determine whether it is possible to predict PM2.5-induced acute exacerbation of COPD (AECOPD) using metabolic markers.MethodsThirty-eight patients with COPD diagnosed by the 2018 Global Initiative for Obstructive Lung Disease were selected and divided into high exposure and low exposure groups. Questionnaire data, clinical data, and peripheral blood data were collected from the patients. Targeted metabolomics using liquid chromatography-tandem mass spectrometry was performed on the plasma samples to investigate the metabolic differences between the two groups and its correlation with the risk of acute exacerbation.ResultsMetabolomic analysis identified 311 metabolites in the plasma of patients with COPD, among which 21 metabolites showed significant changes between the two groups, involving seven pathways, including glycerophospholipid, alanine, aspartate, and glutamate metabolism. Among the 21 metabolites, arginine and glycochenodeoxycholic acid were positively associated with AECOPD during the three months of follow-up, with an area under the curve of 72.50% and 67.14%, respectively.DiscussionPM2.5 exposure can lead to changes in multiple metabolic pathways that contribute to the development of AECOPD, and arginine is a bridge between PM2.5 exposure and AECOPD.