Development of a metabolomic risk score for exposure to traffic-related air pollution: A multi-cohort study.

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required.

Human Milk Composition Is Associated with Maternal Body Mass Index in a Cross-Sectional, Untargeted Metabolomics Analysis of Human Milk from Guatemalan Mothers.

Background: Maternal overweight and obesity has been associated with poor lactation performance including delayed lactogenesis and reduced duration. However, the effect on human milk composition is less well understood. Objectives: We evaluated the relationship of maternal BMI on the human milk metabolome among Guatemalan mothers. Methods: We used data from 75 Guatemalan mothers who participated in the Household Air Pollution Intervention Network trial. Maternal BMI was measured between 9 and <20 weeks of gestation. Milk samples were collected at a single time point using aseptic collection from one breast at 6 mo postpartum and analyzed using high-resolution mass spectrometry. A cross-sectional untargeted high-resolution metabolomics analysis was performed by coupling hydrophilic interaction liquid chromatography (HILIC) and reverse phase C18 chromatography with mass spectrometry. Metabolic features associated with maternal BMI were determined by a metabolome-wide association study (MWAS), adjusting for baseline maternal age, education, and dietary diversity, and perturbations in metabolic pathways were identified by pathway enrichment analysis. Results: The mean age of participants at baseline was 23.62 ± 3.81 y, and mean BMI was 24.27 ± 4.22 kg/m2. Of the total metabolic features detected by HILIC column (19,199 features) and by C18 column (11,594 features), BMI was associated with 1026 HILIC and 500 C18 features. Enriched pathways represented amino acid metabolism, galactose metabolism, and xenobiotic metabolic metabolism. However, no significant features were identified after adjusting for multiple comparisons using the Benjamini-Hochberg false discovery rate procedure (FDRBH < 0.2). Conclusions: Findings from this untargeted MWAS indicate that maternal BMI is associated with metabolic perturbations of galactose metabolism, xenobiotic metabolism, and xenobiotic metabolism by cytochrome p450 and biosynthesis of amino acid pathways. Significant metabolic pathway alterations detected in human milk were associated with energy metabolism-related pathways including carbohydrate and amino acid metabolism.This trial was registered at clinicaltrials.gov as NCT02944682.

Protein S-palmitoylation enhances profibrotic signaling in response to cadmium.

Cadmium (Cd) is a naturally occurring, toxic environmental metal found in foods. Humans do not have an efficient mechanism for Cd elimination; thus, Cd burden in humans increases with age. Cell and mouse studies show that Cd burden from low environmental levels of exposure impacts lung cell metabolism, proliferation signaling and cell growth as part of disease-promoting profibrotic responses in the lungs. Prior integrative analysis of metabolomics and transcriptomics identified the zDHHC11 transcript as a central functional hub in response to Cd dose. zDHHC11 encodes a protein S-palmitoyltransferase, but no evidence is available for effects of Cd on protein S-palmitoylation. In the present research, we studied palmitoylation changes in response to Cd and found increased protein S-palmitoylation in human lung fibroblasts that was inhibited by 2-bromopalmitate (2-BP), an irreversible palmitoyltransferase inhibitor. Mass spectrometry-based proteomics showed palmitoylation of proteins involved in divalent metal transport and in fibrotic signaling. Mechanistic studies showed that 2-BP inhibited palmitoylation of divalent metal ion transporter ZIP14 and also inhibited cellular Cd uptake. Transcription analyses showed that Cd stimulated transforming growth factor (TGF)-ß1 and ß3 expression within 8 h and lung fibrotic markers α-smooth muscle actin, matrix metalloproteinase-2, and collagen 1α1 gene expression and that these effects were blocked by 2-BP. Because 2-BP also blocked palmitoylation of proteins controlled by TGFß1, these results show that palmitoylation impacts Cd-dependent fibrotic signaling both by enhancing cellular Cd accumulation and by supporting post-translational processing of TGFß1-dependent proteins.

Maternal and newborn metabolomic changes associated with urinary polycyclic aromatic hydrocarbon metabolite concentrations at delivery: an untargeted approach.

INTRODUCTION: Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse human health outcomes. To explore the plausible associations between maternal PAH exposure and maternal/newborn metabolomic outcomes, we conducted a cross-sectional study among 75 pregnant people from Cincinnati, Ohio. METHOD: We quantified 8 monohydroxylated PAH metabolites in maternal urine samples collected at delivery. We then used an untargeted high-resolution mass spectrometry approach to examine alterations in the maternal (n = 72) and newborn (n = 63) serum metabolome associated with PAH metabolites. Associations between individual maternal urinary PAH metabolites and maternal/newborn metabolome were assessed using linear regression adjusted for maternal and newborn factors while accounting for multiple testing with the Benjamini-Hochberg method. We then conducted functional analysis to identify potential biological pathways. RESULTS: Our results from the metabolome-wide associations (MWAS) indicated that an average of 1% newborn metabolome features and 2% maternal metabolome features were associated with maternal urinary PAH metabolites. Individual PAH metabolite concentrations in maternal urine were associated with maternal/newborn metabolome related to metabolism of vitamins, amino acids, fatty acids, lipids, carbohydrates, nucleotides, energy, xenobiotics, glycan, and organic compounds. CONCLUSION: In this cross-sectional study, we identified associations between urinary PAH concentrations during late pregnancy and metabolic features associated with several metabolic pathways among pregnant women and newborns. Further studies are needed to explore the mediating role of the metabolome in the relationship between PAHs and adverse pregnancy outcomes.

Characterizing substrate utilization during the fasted state using plasma high-resolution metabolomics.

OBJECTIVES: High-resolution metabolomics enables global assessment of metabolites and molecular pathways underlying physiologic processes, including substrate utilization during the fasted state. The clinical index for substrate utilization, respiratory exchange ratio (RER), is measured via indirect calorimetry. The aim of this pilot study was to use metabolomics to identify metabolic pathways and plasma metabolites associated with substrate utilization in healthy, fasted adults. METHODS: This cross-sectional study included 33 adults (mean age 27.7 ± 4.9 y, mean body mass index 24.8 ± 4 kg/m2). Participants underwent indirect calorimetry to determine resting RER after an overnight fast. Untargeted metabolomics was performed on fasted plasma samples using dual-column liquid chromatography and ultra-high-resolution mass spectrometry. Linear regression and pathway enrichment analyses identified pathways and metabolites associated with substrate utilization measured with indirect calorimetry. RESULTS: RER was significantly associated with 1389 metabolites enriched within 13 metabolic pathways (P < 0.05). Lipid-related findings included general pathways, such as fatty acid activation, and specific pathways, such as C21-steroid hormone biosynthesis and metabolism, butyrate metabolism, and carnitine shuttle. Amino acid pathways included those central to metabolism, such as glucogenic amino acids, and pathways needed to maintain reduction-oxidation reactions, such as methionine and cysteine metabolism. Galactose and pyrimidine metabolism were also associated with RER (all P < 0.05). CONCLUSIONS: The fasting plasma metabolome reflects the diverse macronutrient pathways involved in carbohydrate, amino acid, and lipid metabolism during the fasted state in healthy adults. Future studies should consider the utility of metabolomics to profile individual nutrient requirements and compare findings reported here to clinical populations.

Exposome epidemiology for suspect environmental chemical exposures during pregnancy linked to subsequent breast cancer diagnosis.

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry of pregnancy cohort biospecimens in the Child Health and Development Studies to test for associations with breast cancer identified via the California Cancer Registry. Second and third trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both second and third trimesters to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol, linked to variations in amino acid and nucleotide pathways in second trimester and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in third trimester. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

Antagonistic Interactions in Mitochondria ROS Signaling Responses to Manganese.

Antagonistic interaction refers to opposing beneficial and adverse signaling by a single agent. Understanding opposing signaling is important because pathologic outcomes can result from adverse causative agents or the failure of beneficial mechanisms. To test for opposing responses at a systems level, we used a transcriptome-metabolome-wide association study (TMWAS) with the rationale that metabolite changes provide a phenotypic readout of gene expression, and gene expression provides a phenotypic readout of signaling metabolites. We incorporated measures of mitochondrial oxidative stress (mtOx) and oxygen consumption rate (mtOCR) with TMWAS of cells with varied manganese (Mn) concentration and found that adverse neuroinflammatory signaling and fatty acid metabolism were connected to mtOx, while beneficial ion transport and neurotransmitter metabolism were connected to mtOCR. Each community contained opposing transcriptome-metabolome interactions, which were linked to biologic functions. The results show that antagonistic interaction is a generalized cell systems response to mitochondrial ROS signaling.

Untargeted, High-Resolution Metabolomics in Pediatric Eosinophilic Esophagitis.

BACKGROUND/OBJECTIVES: Eosinophilic esophagitis (EoE) is an inflammatory disease of unclear etiology. The aim of this study was to use untargeted plasma metabolomics to identify metabolic pathway alterations associated with EoE to better understand the pathophysiology. METHODS: This prospective, case-control study included 72 children, aged 1-17 years, undergoing clinically indicated upper endoscopy (14 diagnosed with EoE and 58 controls). Fasting plasma samples were analyzed for metabolomics by high-resolution dual-chromatography mass spectrometry. Analysis was performed on sex-matched groups at a 2:1 ratio. Significant differences among the plasma metabolite features between children with and without EoE were determined using multivariate regression analysis and were annotated with a network-based algorithm. Subsequent pathway enrichment analysis was performed. RESULTS: Patients with EoE had a higher proportion of atopic disease (85.7% vs 50%, P = 0.019) and any allergies (100% vs 57.1%, P = 0.0005). Analysis of the dual chromatography features resulted in a total of 918 metabolites that differentiated EoE and controls. Glycerophospholipid metabolism was significantly enriched with the greatest number of differentiating metabolites and overall pathway enrichment ( P < 0.01). Multiple amino and fatty acid pathways including linoleic acid were also enriched, as well as pyridoxine metabolism ( P < 0.01). CONCLUSIONS: In this pilot study, we found differences in metabolites involved in glycerophospholipid and inflammation pathways in pediatric patients with EoE using untargeted metabolomics, as well as overlap with amino acid metabolome alterations found in atopic disease.

Longitudinal profiles of the fecal metabolome during the first 2 years of life.

During the first 2 years of life, the infant gut microbiome is rapidly developing, and gut bacteria may impact host health through the production of metabolites that can have systemic effects. Thus, the fecal metabolome represents a functional readout of gut bacteria. Despite the important role that fecal metabolites may play in infant health, the development of the infant fecal metabolome has not yet been thoroughly characterized using frequent, repeated sampling during the first 2 years of life. Here, we described the development of the fecal metabolome in a cohort of 101 Latino infants with data collected at 1-, 6-, 12-, 18-, and 24-months of age. We showed that the fecal metabolome is highly conserved across time and highly personalized, with metabolic profiles being largely driven by intra-individual variability. Finally, we also identified several novel metabolites and metabolic pathways that changed significantly with infant age, such as valerobetaine and amino acid metabolism, among others.

MaHPIC malaria systems biology data from Plasmodium cynomolgi sporozoite longitudinal infections in macaques.

Plasmodium cynomolgi causes zoonotic malarial infections in Southeast Asia and this parasite species is important as a model for Plasmodium vivax and Plasmodium ovale. Each of these species produces hypnozoites in the liver, which can cause relapsing infections in the blood. Here we present methods and data generated from iterative longitudinal systems biology infection experiments designed and performed by the Malaria Host-Pathogen Interaction Center (MaHPIC) to delve deeper into the biology, pathogenesis, and immune responses of P. cynomolgi in the Macaca mulatta host. Infections were initiated by sporozoite inoculation. Blood and bone marrow samples were collected at defined timepoints for biological and computational experiments and integrative analyses revolving around primary illness, relapse illness, and subsequent disease and immune response patterns. Parasitological, clinical, haematological, immune response, and -omic datasets (transcriptomics, proteomics, metabolomics, and lipidomics) including metadata and computational results have been deposited in public repositories. The scope and depth of these datasets are unprecedented in studies of malaria, and they are projected to be a F.A.I.R., reliable data resource for decades.

Metabolomics profiling in acute liver transplant rejection in a pediatric population.

Pediatric liver transplantation rejection affects 20% of children. Currently, liver biopsy, expensive and invasive, is the best method of diagnosis. Discovery and validation of clinical biomarkers from blood or other biospecimens would improve clinical care. For this study, stored plasma samples were utilized from two cross-sectional cohorts of liver transplant patients at Children's Healthcare of Atlanta. High resolution metabolic profiling was completed using established methods. Children with (n = 18) or without (n = 25) acute cellular rejection were included in the analysis (n = 43 total). The mean age of these racially diverse cohorts ranged from 12.6 years in the rejection group and 13.6 years in the no rejection group. Linear regression provided 510 significantly differentiating metabolites between groups, and OPLS-DA showed 145 metabolites with VIP > 2. A total of 95 overlapping significant metabolites between OPLS-DA and linear regression analyses were detected. Pathway analysis (p < 0.05) showed bile acid biosynthesis and tryptophan metabolism as the top two differentiating pathways. Network analysis also identified tryptophan and clustered with liver enzymes and steroid use. We conclude metabolic profiling of plasma from children with acute liver transplant rejection demonstrates > 500 significant metabolites. This result suggests that development of a non-invasive biomarker-based test is possible for rejection screening.

Transcriptomic-Metabolomic Profiling in Mouse Lung Tissues Reveals Sex- and Strain-Based Differences.

Omics analyses are commonly used for identifying pathways and genes responsible for physiologic and pathologic processes. Though sex is considered a biological variable in rigorous assessments of pulmonary responses to oxidant exposures, the contribution of the murine strain is largely ignored. This study utilized an unbiased integrated assessment of high-resolution metabolomic profiling and RNA-sequencing to explore sex- and strain-dependent pathways in adult mouse lungs. The results indicated that strain exhibited a greater influence than sex on pathways associated with inflammatory and oxidant/antioxidant responses and that interaction metabolites more closely resembled those identified as differentially expressed by strain. Metabolite analyses revealed that the components of the glutathione antioxidant pathway were different between strains, specifically in the formation of mixed disulfides. Additionally, selenium metabolites such as selenohomocystiene and selenocystathionine were similarly differentially expressed. Transcriptomic analysis revealed similar findings, as evidenced by differences in glutathione peroxidase, peroxiredoxin, and the inflammatory transcription factors RelA and Jun. In summary, an multi-omics integrated approach identified that murine strain disproportionately impacts baseline expression of antioxidant systems in lung tissues. We speculate that strain-dependent differences contribute to discrepant pulmonary responses in preclincal mouse models, with deleterious effects on clinical translation.

Use of high-resolution metabolomics to assess the biological perturbations associated with maternal exposure to Bisphenol A and Bisphenol F among pregnant African American women.

BACKGROUND: Human and animal exposure to bisphenol A (BPA) has been associated with adverse developmental and reproductive effects. The molecular mechanisms by which BPA exposure exerts its effects are not well-understood, even less known about its analogues bisphenol F (BPF). To address these knowledge gaps, we conducted an untargeted metabolome-wide association study (MWAS) to identify metabolic perturbations associated with BPA/BPF exposures in a pregnant African American cohort. METHODS: From a subset of study participants enrolled in the Atlanta African American Maternal-Child cohort, we collected both urine samples, for targeted exposure assessment of BPA (N = 230) and BPF (N = 48), and serum samples, for high-resolution metabolomics (HRM) profiling (N = 230), during early pregnancy (8-14 weeks' gestation). Using an established untargeted HRM workflow consisting of MWAS modeling, pathway enrichment analysis, and chemical annotation and confirmation, we investigated the potential metabolic pathways and features associated with BPA/BPF exposures. RESULTS: The geometric mean creatinine-adjusted concentrations of urinary BPA and BPF were 0.85 ± 2.58 and 0.70 ± 4.71 µg/g creatinine, respectively. After false positive discovery rate correction at 20 % level, 264 and 733 unique metabolic features were significantly associated with urinary BPA and BPF concentrations, representing 10 and 12 metabolic pathways, respectively. Three metabolic pathways, including steroid hormones biosynthesis, lysine and lipoate metabolism, were significantly associated with both BPA and BPF exposure. Using chemical standards, we have confirmed the chemical identity of 16 metabolites significantly associated with BPA or BPF exposure. CONCLUSIONS: Our findings support that exposure to BPA and BPF in pregnant women is associated with the perturbation of aromatic amino acid metabolism, xenobiotics metabolism, steroid biosynthesis, and other amino acid metabolism closely linked to stress responses, inflammation, neural development, reproduction, and weight regulation.

Evaluation of the Use of Saliva Metabolome as a Surrogate of Blood Metabolome in Assessing Internal Exposures to Traffic-Related Air Pollution.

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Integrative interactomics applied to bovine fescue toxicosis.

Bovine fescue toxicosis (FT) is caused by grazing ergot alkaloid-producing endophyte (Epichloë coenophiala)-infected tall fescue. Endophyte's effects on the animal's microbiota and metabolism were investigated recently, but its effects in planta or on the plant-animal interactions have not been considered. We examined multi-compartment microbiota-metabolome perturbations using multi-'omics (16S and ITS2 sequencing, plus untargeted metabolomics) in Angus steers grazing non-toxic (Max-Q) or toxic (E+) tall fescue for 28 days and in E+ plants. E+ altered the plant/animal microbiota, decreasing most ruminal fungi, with mixed effects on rumen bacteria and fecal microbiota. Metabolic perturbations occurred in all matrices, with some plant-animal overlap (e.g., Vitamin B6 metabolism). Integrative interactomics revealed unique E+ network constituents. Only E+ had ruminal solids OTUs within the network and fecal fungal OTUs in E+ had unique taxa (e.g., Anaeromyces). Three E+-unique urinary metabolites that could be potential biomarkers of FT and targeted therapeutically were identified.

Malaria disrupts the rhesus macaque gut microbiome.

Previous studies have suggested that a relationship exists between severity and transmissibility of malaria and variations in the gut microbiome, yet only limited information exists on the temporal dynamics of the gut microbial community during a malarial infection. Here, using a rhesus macaque model of relapsing malaria, we investigate how malaria affects the gut microbiome. In this study, we performed 16S sequencing on DNA isolated from rectal swabs of rhesus macaques over the course of an experimental malarial infection with Plasmodium cynomolgi and analyzed gut bacterial taxa abundance across primary and relapsing infections. We also performed metabolomics on blood plasma from the animals at the same timepoints and investigated changes in metabolic pathways over time. Members of Proteobacteria (family Helicobacteraceae) increased dramatically in relative abundance in the animal's gut microbiome during peak infection while Firmicutes (family Lactobacillaceae and Ruminococcaceae), Bacteroidetes (family Prevotellaceae) and Spirochaetes amongst others decreased compared to baseline levels. Alpha diversity metrics indicated decreased microbiome diversity at the peak of parasitemia, followed by restoration of diversity post-treatment. Comparison with healthy subjects suggested that the rectal microbiome during acute malaria is enriched with commensal bacteria typically found in the healthy animal's mucosa. Significant changes in the tryptophan-kynurenine immunomodulatory pathway were detected at peak infection with P. cynomolgi, a finding that has been described previously in the context of P. vivax infections in humans. During relapses, which have been shown to be associated with less inflammation and clinical severity, we observed minimal disruption to the gut microbiome, despite parasites being present. Altogether, these data suggest that the metabolic shift occurring during acute infection is associated with a concomitant shift in the gut microbiome, which is reversed post-treatment.

Lung metabolome of 1,3-butadiene exposed Collaborative Cross mice reflects metabolic phenotype of human lung cancer.

1,3-Butadiene (BD) exposure is known to cause numerous adverse health effects, including cancer, in animals and humans. BD is metabolized to reactive epoxide intermediates, which are genotoxic, but it is not well know what other effects BD has on cellular metabolism. We examined the effects of exposure to BD on the mouse lung metabolome in the genetically heterogeneous collaborative cross outbred mouse model. Mice were exposed to 3 concentra-tions of BD for 10 days (2, 20, and 200 ppm), and lung tissues were analyzed using high-resolution mass spectrometry-based metabolomics. As compared to controls (0 ppm BD), BD had extensive effects on lung metabolism at all concentrations of exposure, including the lowest concentration of 2 ppm, as reflected by reprogramming of multiple metabolic pathways. Metabolites participating in glycolysis and the tricarboxylic acid cycle were elevated, with 8 out of 10 metabolites demonstrating a 2 to 8-fold increase, including the oncometabolite fumarate. Fatty acid levels, sphingosine, and sphinganine were decreased (2 to 8-fold), and fatty acyl-CoAs were significantly increased (16 to 31-fold), suggesting adjustments in lipid metabolism. Furthermore, metabolites involved in basic amino acid metabolism, steroid hormone metabolism, and nucleic acid metabolism were significantly altered. Overall, these changes mirror the metabolic alterations found in lung cancer cells, suggesting that very low doses of BD induce metabolic adaptations that may prevent or promote adverse health effects such as tumor formation.

An atlas of metallome and metabolome interactions and associations with incident diabetes in the Strong Heart Family Study.

BACKGROUND: Chronic exposure to certain metals plays a role in disease development. Integrating untargeted metabolomics with urinary metallome data may contribute to better understanding the pathophysiology of diseases and complex molecular interactions related to environmental metal exposures. To discover novel associations between urinary metal biomarkers and metabolism networks, we conducted an integrative metallome-metabolome analysis using a panel of urinary metals and untargeted blood metabolomic data from the Strong Heart Family Study (SHFS). METHODS: The SHFS is a prospective family-based cohort study comprised of American Indian men and women recruited in 2001-2003. This nested case-control analysis of 145 participants of which 50 developed incident diabetes at follow up in 2006-2009, included participants with urinary metal and untargeted metabolomic data. Concentrations of 8 creatinine-adjusted urine metals/metalloids [antimony (Sb), cadmium (Cd), lead (Pb), molybdenum (Mo), selenium (Se), tungsten (W), uranium (U) and zinc (Zn)], and 4 arsenic species [inorganic arsenic (iAs), monomethylarsonate (MMA), dimethylarsinate (DMA), and arsenobetaine (AsB)] were measured. Global metabolomics was performed on plasma samples using high-resolution Orbitrap mass spectrometry. We performed an integrative network analysis using xMWAS and a metabolic pathway analysis using Mummichog. RESULTS: 8,810 metabolic features and 12 metal species were included in the integrative network analysis. Most metal species were associated with distinct subsets of metabolites, forming single-metal-multiple-metabolite clusters (|r|>0.28, p-value < 0.001). DMA (clustering with W), iAs (clustering with U), together with Mo and Se showed modest interactions through associations with common metabolites. Pathway enrichment analysis of associated metabolites (|r|>0.17, p-value < 0.1) showed effects in amino acid metabolism (AsB, Sb, Se and U), fatty acid and lipid metabolism (iAs, Mo, W, Sb, Pb, Cd and Zn). In stratified analyses among participants who went on to develop diabetes, iAs and U clustered together through shared metabolites, and both were associated with the phosphatidylinositol phosphate metabolism pathway; metals were also associated with metabolites in energy metabolism (iAs, MMA, DMA, U, W) and xenobiotic degradation and metabolism (DMA, Pb) pathways. CONCLUSION: In this integrative analysis of multiple metals and untargeted metabolomics, results show common associations with fatty acid, energy and amino acid metabolism pathways. Results for individual metabolite associations differed for different metals, indicating that larger populations will be needed to confirm the metal-metal interactions detected here, such as the strong interaction of uranium and inorganic arsenic. Understanding the biochemical networks underlying metabolic homeostasis and their association with exposure to multiple metals may help identify novel biomarkers, pathways of disease, potential signatures of environmental metal exposure.

Environmental chemicals and metabolic disruption in primary and secondary human parathyroid tumors.

BACKGROUND: The incidence of primary hyperparathyroidism has increased 300% in the United States in the past 30 years, and secondary hyperparathyroidism is almost universal in patients with end-stage renal disease. We assessed the presence of environmental chemicals in human hyperplastic parathyroid tumors as possible contributing factors to this increase. METHODS: Cryopreserved hyperplastic parathyroid tumors and normal human parathyroids were analyzed by gas chromatography and liquid chromatography coupled to ultra-high-resolution mass spectrometry, bioinformatics, and biostatistics. RESULTS: Detected environmental chemicals included polychlorinated biphenyls, polybrominated diphenyl ethers, dichloro-diphenyl-trichloroethane derivatives, and other insecticides. A total of 99% had p,p'-dichlorodiphenyldichloroethylene. More than 50% contained other environmental chemicals, and many classified as endocrine disruptors. Polychlorinated biphenyl-28 and polychlorinated biphenyl-49 levels correlated positively with parathyroid tumor mass. Polybrominated diphenyl ether-47 concentrations in tumors were inversely correlated with patients' serum calcium levels. Cellular metabolites in pathways of purine and pyrimidine synthesis and mitochondrial energy production were associated with tumor growth and with p,p'-dichlorodiphenyldichloroethylene in primary hyperparathyroidism tumors. In normal parathyroids, p,p'-dichlorodiphenyldichloroethylene , polychlorinated biphenyl-28, polychlorinated biphenyl-74, and polychlorinated biphenyl-153, but not p,p'-dichlorodiphenyldichloroethylene or polychlorinated biphenyl-49, were detected. CONCLUSION: Environmental chemicals are present in human parathyroid tumors and warrant detailed epidemiologic and mechanistic studies to test for causal links to the growth of human parathyroid tumors.