Metabolomic assessment of exposure to near-highway ultrafine particles

Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution

BACKGROUND

Substantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.

OBJECTIVES

We examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.

METHODS

A cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.

RESULTS

Subjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.

CONCLUSIONS

We identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.

Air Pollution and Adverse Pregnancy and Birth Outcomes: Mediation Analysis Using Metabolomic Profiles

PURPOSE OF REVIEW

Review how to use metabolomic profiling in causal mediation analysis to assess epidemiological evidence for air pollution impacts on birth outcomes.

RECENT FINDINGS

Maternal exposures to air pollutants have been associated with pregnancy complications and adverse pregnancy and birth outcomes. Causal mediation analysis enables us to estimate direct and indirect effects on outcomes (i.e., effect decomposition), elucidating causal mechanisms or effect pathways. Maternal metabolites and metabolic pathways are perturbed by air pollution exposures may lead to adverse pregnancy and birth outcomes, thus they can be considered mediators in the causal pathways. Metabolomic markers have been used to explain the biological mechanisms linking air pollution and respiratory function, and of arsenic exposure and birth weight. However, mediation analysis of metabolomic markers has not been used to assess air pollution effects on adverse birth outcomes. In this article, we describe the assumptions and applications of mediation analysis using metabolomic markers that elucidate the potential mechanisms of the effects of air pollution on adverse pregnancy and birth outcomes. The hypothesis of mediation along specified pathways can be assessed within the structural causal modeling framework. For causal inferences, several assumptions that go beyond the data-including no uncontrolled confounding-need to be made to justify the effect decomposition. Nevertheless, studies that integrate metabolomic information in causal mediation analysis may greatly improve our understanding of the effects of ambient air pollution on adverse pregnancy and birth outcomes as they allow us to suggest and test hypotheses about underlying biological mechanisms in studies of pregnant women.

Increasing cardiopulmonary effects of ultrafine particles at relatively low fine particle concentrations

Ultrafine particles (UFPs) are of concern because of their high pulmonary deposition efficiency. However, present control measures are generally targeted at fine particles (PM_2.5), with little effect on UFPs. The health effects of UFPs at different PM_2.5 concentrations may provide a basic for controlling UFPs but remain unclear in polluted areas. School children spend the majority of their time in the classrooms. This study investigated the different short-term effects of indoor UFPs on school children in Beijing, China when indoor PM_2.5 concentrations exceeded or satisfied the recently published Chinese standard for indoor PM_2.5. Cardiopulmonary functions of 48 school children, of whom 46 completed, were measured three times. Indoor PM_2.5 and UFPs were monitored in classrooms on weekdays. Measurements were separated into two groups according to the abovementioned standard. Mixed-effect models were used to explore the health effects of the air pollutants. Generally, UFP-associated effects on children's cardiopulmonary function persisted even at relatively low PM_2.5 concentrations, especially on heart rate variability indices. The risks associated with high PM_2.5 concentrations are well-known, but the effects of UFPs on children's cardiopulmonary function deserve more attention even when PM_2.5 has been controlled. UFP control and standard setting should therefore be considered.

Metabolomic signatures of the long-term exposure to air pollution and temperature

BACKGROUND

Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.

OBJECTIVES

We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.

METHODS

We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.

RESULTS

Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.

CONCLUSIONS

Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

A metabolomic study of cervical dystonia

INTRODUCTION

Cervical dystonia is the most common of the adult-onset focal dystonias. Most cases are idiopathic. The current view is that cervical dystonia may be caused by some combination of genetic and environmental factors. Genetic contributions have been studied extensively, but there are few studies of other factors. We conducted an exploratory metabolomics analysis of cervical dystonia to identify potentially abnormal metabolites or altered biological pathways.

METHODS

Plasma samples from 100 cases with idiopathic cervical dystonia and 100 controls were compared using liquid chromatography coupled with mass spectrometry-based metabolomics.

RESULTS

A total of 7346 metabolic features remained after quality control, and up to 289 demonstrated significant differences between cases and controls, depending on statistical criteria chosen. Pathway analysis revealed 9 biological processes to be significantly associated at p < 0.05, 5 pathways were related to carbohydrate metabolism, 3 pathways were related to lipid metabolism.

CONCLUSION

This is the first large scale metabolomics study for any type of dystonia. The results may provide potential novel insights into the biology of cervical dystonia.

Toxicity of airborne particles-established evidence, knowledge gaps and emerging areas of importance

Epidemiological research has taught us a great deal about the health effects of airborne particulate matter (PM), particularly cardiorespiratory effects of combustion-related particles. This has been matched by toxicological research to define underlying mechanistic pathways. To keep abreast of the substantial challenges that air pollution continues to throw at us requires yet more strides to be achieved. For example, being aware of the most toxic components/sources and having a definitive idea of the range of associated disease outcomes. This review discusses approaches designed to close some of these knowledge gaps. These include a focus on particles arising from non-exhaust PM at the roadside and microplastics-both of which are becoming more relevant in the light of a shift in PM composition in response to global pressure to reduce combustion emissions. The application of hypothesis-free approaches in both mechanistic studies and epidemiology in unveiling unexpected relationships and generating novel insights is also discussed. Previous work, strengthening the evidence for both the adverse effects and benefits of intervention tell us that the sooner we act to close knowledge gaps, increase awareness and develop creative solutions, the sooner we can reduce the public health burden attributable to these complex and insidious environmental pollutants. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Use of Integrative Interactomics for Improvement of Farm Animal Health and Welfare: An Example with Fescue Toxicosis

Rapid scientific advances are increasing our understanding of the way complex biological interactions integrate to maintain homeostatic balance and how seemingly small, localized perturbations can lead to systemic effects. The ‘omics movement, alongside increased throughput resulting from statistical and computational advances, has transformed our understanding of disease mechanisms and the multi-dimensional interaction between environmental stressors and host physiology through data integration into multi-dimensional analyses, i.e., integrative interactomics. This review focuses on the use of high-throughput technologies in farm animal research, including health- and toxicology-related papers. Although limited, we highlight recent animal agriculture-centered reports from the integrative multi-‘omics movement. We provide an example with fescue toxicosis, an economically costly disease affecting grazing livestock, and describe how integrative interactomics can be applied to a disease with a complex pathophysiology in the pursuit of novel treatment and management approaches. We outline how ‘omics techniques have been used thus far to understand fescue toxicosis pathophysiology, lay out a framework for the fescue toxicosis integrome, identify some challenges we foresee, and offer possible means for addressing these challenges. Finally, we briefly discuss how the example with fescue toxicosis could be used for other agriculturally important animal health and welfare problems.

Metabolomics profiling of tobacco exposure in children with cystic fibrosis

BACKGROUND

Inflammation is integral to early disease progression in children with CF. The effect of modifiable environmental factors on infection and inflammation in persons with CF is poorly understood. Our prior studies determined that secondhand smoke exposure (SHSe) is highly prevalent in young children with CF. SHSe is associated with increased inflammation, heightened bacterial burden, and worsened clinical outcomes. However, the specific metabolite and signaling pathways that regulate responses to SHSe in CF are relatively unknown.

METHODS

High-resolution metabolomics was performed on plasma samples from infants (n = 25) and children (n = 40) with CF compared to non-CF controls (n = 15). CF groups were stratified according to infant or child age and SHSe status.

RESULTS

Global metabolomic profiles segregated by age and SHSe status. SHSe in CF was associated with changes in pathways related to steroid biosynthesis, fatty acid metabolism, cysteine metabolism, and oxidative stress. CF infants with SHSe demonstrated enrichment for altered metabolite localization to the small intestine, liver, and striatum. CF children with SHSe demonstrated metabolite enrichment for organs/tissues associated with oxidative stress including mitochondria, peroxisomes, and the endoplasmic reticulum. In a confirmatory analysis, SHSe was associated with changes in biomarkers of oxidative stress and cellular adhesion including MMP-9, MPO, and ICAM-1.

CONCLUSIONS

SHSe in young children and infants with CF is associated with altered global metabolomics profiles and specific biochemical pathways, including enhanced oxidative stress. SHSe remains an important but understudied modifiable variable in early CF disease.

Macronutrient, Energy, and Bile Acid Metabolism Pathways Altered Following a Physiological Meal Challenge, Relative to Fasting, among Guatemalan Adults

BACKGROUND

The healthy human metabolome, including its physiological responses after meal consumption, remains incompletely understood. One major research gap is the limited literature assessing how human metabolomic profiles differ between fasting and postprandial states after physiological challenges.

OBJECTIVES

Our study objective was to evaluate alterations in high-resolution metabolomic profiles following a standardized meal challenge, relative to fasting, in Guatemalan adults.

METHODS

We studied 123 Guatemalan adults without obesity, hypertension, diabetes, metabolic syndrome, or comorbidities. Every participant received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein) and provided blood samples while fasting and at 2 h postprandial. Plasma samples were assayed by high-resolution metabolomics with dual-column LC [C18 (negative electrospray ionization), hydrophilic interaction LC (HILIC, positive electrospray ionization)] coupled to ultra-high-resolution MS. Associations between metabolomic features and the meal challenge timepoint were assessed in feature-by-feature multivariable linear mixed regression models. Two algorithms (mummichog, gene set enrichment analysis) were used for pathway analysis, and P values were combined by the Fisher method.

RESULTS

Among participants (62.6% male, median age 43.0 y), 1130 features (C18: 777; HILIC: 353) differed between fasting and postprandial states (all false discovery rate-adjusted q < 0.05). Based on differing C18 features, top pathways included: tricarboxylic acid cycle (TCA), primary bile acid biosynthesis, and linoleic acid metabolism (all Pcombined < 0.05). Mass spectral features included: taurine and cholic acid in primary bile acid biosynthesis; and fumaric acid, malic acid, and citric acid in the TCA. HILIC features that differed in the meal challenge reflected linoleic acid metabolism (Pcombined < 0.05).

CONCLUSIONS

Energy, macronutrient, and bile acid metabolism pathways were responsive to a standardized meal challenge in adults without cardiometabolic diseases. Our findings reflect metabolic flexibility in disease-free individuals.

Hepatic fat is a stronger correlate of key clinical and molecular abnormalities than visceral and abdominal subcutaneous fat in youth

INTRODUCTION

Body fat distribution is strongly associated with cardiometabolic disease (CMD), but the relative importance of hepatic fat as an underlying driver remains unclear. Here, we applied a systems biology approach to compare the clinical and molecular subnetworks that correlate with hepatic fat, visceral fat, and abdominal subcutaneous fat distribution.

RESEARCH DESIGN AND METHODS

This was a cross-sectional sub-study of 283 children/adolescents (7-19 years) from the Yale Pediatric NAFLD Cohort. Untargeted, high-resolution metabolomics (HRM) was performed on plasma and combined with existing clinical variables including hepatic and abdominal fat measured by MRI. Integrative network analysis was coupled with pathway enrichment analysis and multivariable linear regression (MLR) to examine which metabolites and clinical variables associated with each fat depot.

RESULTS

The data divided into four communities of correlated variables (|r|>0.15, p<0.05) after integrative network analysis. In the largest community, hepatic fat was associated with eight clinical biomarkers, including measures of insulin resistance and dyslipidemia, and 878 metabolite features that were enriched predominantly in amino acid (AA) and lipid pathways in pathway enrichment analysis (p<0.05). Key metabolites associated with hepatic fat included branched-chain AAs (valine and isoleucine/leucine), aromatic AAs (tyrosine and tryptophan), serine, glycine, alanine, and pyruvate, as well as several acylcarnitines and glycerophospholipids (all q<0.05 in MLR adjusted for covariates). The other communities detected in integrative network analysis consisted of abdominal visceral, superficial subcutaneous, and deep subcutaneous fats, but no clinical variables, fewer metabolite features (280, 312, and 74, respectively), and limited findings in pathway analysis.

CONCLUSIONS

These data-driven findings show a stronger association of hepatic fat with key CMD risk factors compared with abdominal fats. The molecular network identified using HRM that associated with hepatic fat provides insight into potential mechanisms underlying the hepatic fat-insulin resistance interface in youth.

Untargeted Metabolomics Screen of Mid-pregnancy Maternal Serum and Autism in Offspring

Discovering pathophysiologic networks in a blood-based approach may help to generate valuable tools for early treatment or preventive measures in autism. To date targeted or untargeted metabolomics approaches to identify metabolic features and pathways affecting fetal neurodevelopment have rarely been applied to pregnancy samples, that is, an early period potentially relevant for the development of autism spectrum disorders (ASD). We conducted a population-based study relying on autism diagnoses retrieved from California Department of Developmental Services record. After linking cases to and sampling controls from birth certificates, we retrieved stored maternal mid-pregnancy serum samples collected as part of the California Prenatal Screening Program from the California Biobank for children born 2004 to 2010 in the central valley of California. We retrieved serum for 52 mothers whose children developed autism and 62 population controls originally selected from all eligible children matched by birth year and child's sex. Also, we required that these mothers were relatively low or unexposed to air pollution and select pesticides during early pregnancy. We identified differences in metabolite levels in several metabolic pathways, including glycosphingolipid biosynthesis and metabolism, N-glycan and pyrimidine metabolism, bile acid pathways and, importantly, C21-steroid hormone biosynthesis and metabolism. Disturbances in these pathways have been shown to be relevant for neurodevelopment in rare genetic syndromes or implicated in previous studies of autism. This study provides new insight into maternal mid-pregnancy metabolic features possibly related to the development of autism and an incentive to explore whether these pathways and metabolites are useful for early diagnosis, treatment, or prevention. LAY SUMMARY: This study found that in mid-pregnancy the blood of mothers who give birth to a child that develops autism has some characteristic features that are different from those of blood samples taken from control mothers. These features are related to biologic mechanisms that can affect fetal brain development. In the future, these insights may help identify biomarkers for early autism diagnosis and treatment or preventive measures. Autism Res 2020, 13: 1258-1269. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Tryptophan catabolism reflects disease activity in human tuberculosis

There is limited understanding of the role of host metabolism in the pathophysiology of human tuberculosis (TB). Using high-resolution metabolomics with an unbiased approach to metabolic pathway analysis, we discovered that the tryptophan pathway is highly regulated throughout the spectrum of TB infection and disease. This regulation is characterized by increased catabolism of tryptophan to kynurenine, which was evident not only in active TB disease but also in latent TB infection (LTBI). Further, we found that tryptophan catabolism is reversed with effective treatment of both active TB disease and LTBI in a manner commensurate with bacterial clearance. Persons with active TB and LTBI also exhibited increased expression of indoleamine 2,3-dioxygenase-1 (IDO-1), suggesting IDO-1 mediates observed increases in tryptophan catabolism. Together, these data indicate IDO-1-mediated tryptophan catabolism is highly preserved in the human response to Mycobacterium tuberculosis and could be a target for biomarker development as well as host-directed therapies.

Perfluoroalkyl substances and severity of nonalcoholic fatty liver in Children: An untargeted metabolomics approach

BACKGROUND

Toxicant-associated steatohepatitis has been described in adults but less is known regarding the role of toxicants in liver disease of children. Perfluoroalkyl substances (PFAS) cause hepatic steatosis in rodents, but few previous studies have examined PFAS effects on severity of liver injury in children.

OBJECTIVES

We aimed to examine the relationship of PFAS to histologic severity of nonalcoholic fatty liver disease (NAFLD) in children.

METHODS

Seventy-four children with physician-diagnosed NAFLD were recruited from Children's Healthcare of Atlanta between 2007 and 2015. Biopsy-based liver histological features were scored for steatosis, lobular and portal inflammation, ballooning, and fibrosis. Plasma concentrations of perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonic acid (PFHxS), and untargeted plasma metabolomic profiling, were determined using liquid chromatography with high-resolution mass spectrometry. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with PFAS. A structural integrated analysis was applied to identify latent clusters of children with more severe form of NAFLD based on their PFAS levels and metabolite pattern.

RESULTS

Patients were 7-19 years old, mostly boys (71%), Hispanic (51%), and obese (85%). The odds of having nonalcoholic steatohepatitis (NASH), compared to children with steatosis alone, was significantly increased with each interquartile range (IQR) increase of PFOS (OR: 3.32, 95% CI: 1.40-7.87) and PFHxS (OR: 4.18, 95% CI: 1.64-10.7). Each IQR increase of PFHxS was associated with increased odds for liver fibrosis (OR: 4.44, 95% CI: 1.34-14.8), lobular inflammation (OR: 2.87, 95% CI: 1.12-7.31), and higher NAFLD activity score (β coefficient 0.46; 95% CI: 0.03, 0.89). A novel integrative analysis identified a cluster of children with NASH, characterized by increased PFAS levels and altered metabolite patterns including higher plasma levels of phosphoethanolamine, tyrosine, phenylalanine, aspartate and creatine, and decreased plasma levels of betaine.

CONCLUSIONS

Ηigher PFAS exposure was associated with more severe disease in children with NAFLD. PFAS may be an important toxicant contributing to NAFLD progression; however larger, longitudinal studies are warranted to confirm these findings.

Metabolomic and metallomic profile differences between Veterans and Civilians with Pulmonary Sarcoidosis

Sarcoidosis is a disorder characterized by granulomatous inflammation of unclear etiology. In this study we evaluated whether veterans with sarcoidosis exhibited different plasma metabolomic and metallomic profiles compared with civilians with sarcoidosis. A case control study was performed on veteran and civilian patients with confirmed sarcoidosis. Proton nuclear magnetic resonance spectroscopy (1H NMR), hydrophilic interaction liquid chromatography mass spectrometry (HILIC-MS) and inductively coupled plasma mass spectrometry (ICP-MS) were applied to quantify metabolites and metal elements in plasma samples. Our results revealed that the veterans with sarcoidosis significantly differed from civilians, according to metabolic and metallomics profiles. Moreover, the results showed that veterans with sarcoidosis and veterans with COPD were similar to each other in metabolomics and metallomics profiles. This study suggests the important role of environmental risk factors in the development of different molecular phenotypic responses of sarcoidosis. In addition, this study suggests that sarcoidosis in veterans may be an occupational disease.

The Alzheimer's Disease Exposome

INTRODUCTION

Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants.

RESULTS AND DISCUSSION

We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.

Maternal serum metabolome and traffic-related air pollution exposure in pregnancy

BACKGROUND

Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and neurodevelopmental disorders. By utilizing high-resolution metabolomics (HRM), we investigated perturbations of the maternal serum metabolome in response to traffic-related air pollution to identify biological mechanisms.

METHODS

We retrieved stored mid-pregnancy serum samples from 160 mothers who lived in the Central Valley of California known for high air particulate levels. We estimated prenatal traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 μm) during first-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) to select metabolic features associated with air pollution exposure. Pathway analyses were employed to identify biologic pathways related to air pollution exposure. As potential confounders we included maternal age, maternal race/ethnicity, and maternal education.

RESULTS

In total we extracted 4038 and 4957 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for confounding factors, PLS-DA (Variable Importance in Projection (VIP) ≥2) yielded 181 and 251 metabolic features (HILIC and C18, respectively) that discriminated between the high (n = 98) and low exposed (n = 62). Pathway enrichment analysis for discriminatory features associated with air pollution indicated that in maternal serum oxidative stress and inflammation related pathways were altered, including linoleate, leukotriene, and prostaglandin pathways.

CONCLUSION

The metabolomic features and pathways we found to be associated with air pollution exposure suggest that maternal exposure during pregnancy induces oxidative stress and inflammation pathways previously implicated in pregnancy complications and adverse outcomes.

Development of a Plasma Screening Panel for Pediatric Nonalcoholic Fatty Liver Disease Using Metabolomics

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children, but diagnosis is challenging due to limited availability of noninvasive biomarkers. Machine learning applied to high-resolution metabolomics and clinical phenotype data offers a novel framework for developing a NAFLD screening panel in youth. Here, untargeted metabolomics by liquid chromatography-mass spectrometry was performed on plasma samples from a combined cross-sectional sample of children and adolescents ages 2-25 years old with NAFLD (n = 222) and without NAFLD (n = 337), confirmed by liver biopsy or magnetic resonance imaging. Anthropometrics, blood lipids, liver enzymes, and glucose and insulin metabolism were also assessed. A machine learning approach was applied to the metabolomics and clinical phenotype data sets, which were split into training and test sets, and included dimension reduction, feature selection, and classification model development. The selected metabolite features were the amino acids serine, leucine/isoleucine, and tryptophan; three putatively annotated compounds (dihydrothymine and two phospholipids); and two unknowns. The selected clinical phenotype variables were waist circumference, whole-body insulin sensitivity index (WBISI) based on the oral glucose tolerance test, and blood triglycerides. The highest performing classification model was random forest, which had an area under the receiver operating characteristic curve (AUROC) of 0.94, sensitivity of 73%, and specificity of 97% for detecting NAFLD cases. A second classification model was developed using the homeostasis model assessment of insulin resistance substituted for the WBISI. Similarly, the highest performing classification model was random forest, which had an AUROC of 0.92, sensitivity of 73%, and specificity of 94%. Conclusion: The identified screening panel consisting of both metabolomics and clinical features has promising potential for screening for NAFLD in youth. Further development of this panel and independent validation testing in other cohorts are warranted.

Metabolomics of childhood exposure to perfluoroalkyl substances: a cross-sectional study

INTRODUCTION

Exposure to perfluoroalkyl substances (PFAS), synthetic and persistent chemicals used in commercial and industrial processes, are associated with cardiometabolic dysfunction and related risk factors including reduced birth weight, excess adiposity, and dyslipidemia. Identifying the metabolic changes induced by PFAS exposure could enhance our understanding of biological pathways underlying PFAS toxicity.

OBJECTIVE

To identify metabolic alterations associated with serum concentrations of four PFAS in children using a metabolome-wide association study.

METHODS

We performed untargeted metabolomic profiling by liquid chromatography with ultra-high-resolution mass spectrometry, and separately quantified serum concentrations of perfluorooctanoic acid, perfluorooctanesulfonic acid, perfluorononanoic acid, and perfluorohexanesulfonic acid (PFHxS) for 114 8-year old children from Cincinnati, OH. We evaluated associations between each serum PFAS concentration and 16,097 metabolic features using linear regression adjusted for child age, sex, and race with a false discovery rate < 20%. We annotated PFAS-associated metabolites and conducted pathway enrichment analyses.

RESULTS

Serum PFAS concentrations were associated with metabolic features annotated primarily as lipids and dietary factors. Biological pathways associated with all four PFAS included arginine, proline, aspartate, asparagine, and butanoate metabolism.

CONCLUSIONS

In this cross-sectional study, childhood serum PFAS concentrations were correlated with metabolic pathways related to energy production and catabolism. Future studies should determine whether these pathways mediate associations between PFAS exposure and childhood cardiometabolic health.

Multigenerational metabolic profiling in the Michigan PBB registry

Although polychlorinated biphenyls and polybrominated biphenyls are no longer manufactured the United States, biomonitoring in human populations show that exposure to these pollutants persist in human tissues. The objective of this study was to identify metabolic variations associated with exposure to 2,2'4,4',5,5'-hexabromobiphenyl (PBB-153) and 2,2'4,4',5,5'-hexachlorobiphenyl (PCB-153) in two generations of participants enrolled in the Michigan PBB Registry (http://pbbregistry.emory.edu/). Untargeted, high-resolution metabolomic profiling of plasma collected from 156 individuals was completed using liquid chromatography with high-resolution mass spectrometry. PBB-153 and PCB-153 levels were measured in the same individuals using targeted gas chromatography-tandem mass spectrometry and tested for dose-dependent correlation with the metabolome. Biological response to these exposures were evaluated using identified endogenous metabolites and pathway enrichment. When compared to lipid-adjusted concentrations for adults in the National Health and Nutrition Examination Survey (NHANES) for years 2003-2004, PCB-153 levels were consistent with similarly aged individuals, whereas PBB-153 concentrations were elevated (p<0.0001) in participants enrolled in the Michigan PBB Registry. Metabolic alterations were correlated with PBB-153 and PCB-153 in both generations of participants, and included changes in pathways related to catecholamine metabolism, cellular respiration, essential fatty acids, lipids and polyamine metabolism. These pathways were consistent with pathophysiological changes observed in neurodegenerative disease and included previously identified metabolomic markers of Parkinson's disease. To determine if the metabolic alterations detected in this study are replicated other cohorts, we evaluated correlation of PBB-153 and PCB-153 with plasma fatty acids measured in NHANES. Both pollutants showed similar associations with fatty acids previously linked to PCB exposure. Thus, the results from this study show metabolic alterations correlated with PBB-153 and PCB-153 exposure can be detected in human populations and are consistent with health outcomes previously reported in epidemiological and mechanistic studies.

The metabolome: A key measure for exposome research in epidemiology

PURPOSE OF REVIEW

Application of omics to study human health has created a new era of opportunities for epidemiology research. However, approaches to characterize exogenous health triggers have largely not leveraged advances in analytical platforms and big data. In this review, we highlight the exposome, which is defined as the cumulative measure of exposure and biological responses across a lifetime as a cornerstone for new epidemiology approaches to study complex and preventable human diseases.

RECENT FINDINGS

While no universal approach exists to measure the entirety of the exposome, use of high-resolution mass spectrometry methods provide distinct advantages over traditional biomonitoring and have provided key advances necessary for exposome research. Application to different study designs and recommendations for combining exposome data with novel data analytic frameworks to study complex interactions of multiple stressors are also discussed.

SUMMARY

Even though challenges still need to be addressed, advances in methods to characterize the exposome provide exciting new opportunities for epidemiology to support fundamental discoveries to improve public health.