Ambient air pollution and survival in childhood cancer: A nationwide survival analysis.

BACKGROUND: Particulate matter consisting of fine particles measuring 2.5 microns or less in diameter (PM2.5), a component of air pollution, has been linked to adverse health outcomes. The objective of this study was to assess the association between ambient PM2.5 exposure and survival in children with cancer in the United States. METHODS: Individuals aged birth to 19 years who were diagnosed with cancer between January 1, 2004, and December 31, 2019, were selected from the National Cancer Database. The association between the annual PM2.5 level at the patient's zip code of residence at the time of diagnosis and overall survival was evaluated using time-varying Cox proportional hazards models (crude and adjusted for diagnosis year and age). To address concerns that exposure to air pollution is correlated with other social determinants of health, the authors tested the association between PM2.5 levels and survival among sociodemographic subgroups. RESULTS: Of the 172,550 patients included, 27,456 (15.9%) resided in areas with annual PM2.5 concentrations above the US Environmental Protection Agency (EPA) annual PM2.5 standard of 12 µg/m3. Residing in these high-pollution areas was associated with worse overall survival (adjusted hazard ratio [aHR], 1.06; 95% confidence interval [CI], 1.012-1.10). Similarly, when PM2.5 was evaluated as a linear measure, each unit increase in PM2.5 exposure was associated with worse survival (aHR, 1.011; CI, 1.005-1.017). Exposure to PM2.5 at levels above the EPA standards was also significantly associated with worse overall survival among sociodemographic subgroups. CONCLUSIONS: Exposure to PM2.5 was significantly associated with worse overall survival among children with cancer, even at levels below EPA air quality standards. These results underscore the importance of setting appropriate air quality standards to protect the health of this sensitive population. PLAIN LANGUAGE SUMMARY: The authors investigated how living in areas with high air pollution (defined as particulate matter consisting of fine particles measuring 2.5 microns or less in diameter; PM2.5) affects the overall survival of children with cancer in the United States. The results indicated that children living in areas with higher PM2.5 levels, and even at levels below prior and current US Environmental Protection Agency standards, had lower survival rates than children living in areas with lower levels of PM2.5. This finding emphasizes the need for stricter air quality standards to better protect children, particularly those with serious health conditions like childhood cancer.

Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies.

BACKGROUND: A better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention. METHODS: We included 623 matched case-control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini-Hochberg method was used to correct for multiple comparisons. RESULTS: Sphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways. CONCLUSIONS: This is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.

Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life.

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

The associations between pre-conception urinary phthalate concentrations, the serum metabolome, and live birth among women undergoing assisted reproduction.

BACKGROUND: Phthalates are ubiquitous endocrine disruptors. Past studies have shown an association between higher preconception urinary concentrations of phthalate metabolites and lower fertility in women; however, the biological mechanisms remain unclear. Our exploratory study aimed to understand the metabolites and pathways associated with maternal preconception phthalate exposure and examine if any may underline the association between phthalate exposure and live birth using untargeted metabolomics. METHODS: Participants (n = 183) were part of the Environment and Reproductive Health (EARTH) study, a prospective cohort that followed women undergoing in vitro fertilization (IVF) at the Massachusetts General Hospital Fertility Center (2005-2016). On the same day, women provided a serum sample during controlled ovarian stimulation, which was analyzed for metabolomics using liquid chromatography coupled with high-resolution mass spectrometry and two chromatography columns, and a urine sample, which was analyzed for 11 phthalate metabolites using targeted approaches. We used multivariable generalized linear models to identified metabolic features associated with urinary phthalate metabolite concentrations and live birth, followed by enriched pathway analysis. We then used a meet-in-the-middle approach to identify overlapping pathways and features. RESULTS: Metabolic pathway enrichment analysis revealed 43 pathways in the C18 negative and 32 pathways in the HILIC positive columns that were significantly associated (p < 0.05) with at least one of the 11 urinary phthalate metabolites or molar sum of di-2-ethylhexyl phthalate metabolites. Lipid, amino acid, and carbohydrate metabolism were the most common pathways associated with phthalate exposure. Five pathways, tryptophan metabolism, tyrosine metabolism, biopterin metabolism, carnitine shuttle, and vitamin B6 metabolism, were also identified as being associated with at least one phthalate metabolite and live birth following IVF. CONCLUSION: Our study provides further insight into the metabolites and metabolomics pathways, including amino acid, lipid, and vitamin metabolism that may underlie the observed associations between phthalate exposures and lower fertility in women.

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; 1,000). 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. Black Carbon was positively associated with the metRS in CHDWB data. While we did not identify significant 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.

Association of prenatal chlorpyrifos exposure with sexually dimorphic differences in anogenital distance among Thai farmworker children.

Organophosphate (OP) insecticides are some of the most abundantly used insecticides, and prenatal exposures have been linked to adverse maternal and child health outcomes. Anogenital distance (AGD) has emerged as an early marker of androgen activity, and later reproductive outcomes, that is sensitive to alteration by environmental chemicals. Here, we examined associations between prenatal exposure to chlorpyrifos, an OP insecticide, with AGD. Pregnant farmworkers were enrolled in the Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE; N = 104) between 2017 and 2019 in Northern Thailand. Concentrations of 3,5,6-trichloro-2-pyridinol (TCPy), a specific metabolite of chlorpyrifos, were measured in composited urine samples obtained from each trimester of pregnancy. AGD was measured at 12 months of age. Sex-specific adjusted linear regression models were used to examine associations between average and trimester-specific TCPy levels and AGD. In adjusted models for females and males, increasing TCPy was consistently associated with a modest, non-significant reduction in AGD. Across both strata of sex, associations were greatest in magnitude for trimester 3 (females: ß = -2.17, 95 % confidence interval (CI) = -4.99, 0.66; males: ß = -3.02, 95 % CI = -6.39, 0.35). In the SAWASDEE study, prenatal chlorpyrifos exposure was not strongly associated with AGD at 12 months of age.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease.

INTRODUCTION: Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association. METHODS: We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs. RESULTS: PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation. DISCUSSION: Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD. HIGHLIGHTS: First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

Metapone: a Bioconductor package for joint pathway testing for untargeted metabolomics data.

MOTIVATION: Testing for pathway enrichment is an important aspect in the analysis of untargeted metabolomics data. Due to the unique characteristics of untargeted metabolomics data, some key issues have not been fully addressed in existing pathway testing algorithms: (i) matching uncertainty between data features and metabolites; (ii) lacking of method to analyze positive mode and negative mode liquid chromatography-mass spectrometry (LC/MS) data simultaneously on the same set of subjects; (iii) the incompleteness of pathways in individual software packages. RESULTS: We developed an innovative R/Bioconductor package: metabolic pathway testing with positive and negative mode data (metapone), which can perform two novel statistical tests that take matching uncertainty into consideration-(i) a weighted gene set enrichment analysis-type test and (ii) a permutation-based weighted hypergeometric test. The package is capable of combining positive- and negative-ion mode results in a single testing scheme. For comprehensiveness, the built-in pathways were manually curated from three sources: Kyoto Encyclopedia of Genes and Genomes, Mummichog and The Small Molecule Pathway Database. AVAILABILITY AND IMPLEMENTATION: The package is available at https://bioconductor.org/packages/devel/bioc/html/metapone.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Childhood Autism-related Outcomes.

BACKGROUND: Epidemiologic evidence linking prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with altered neurodevelopment is inconclusive, and few large studies have focused on autism-related outcomes. We investigated whether blood concentrations of PFAS in pregnancy are associated with child autism-related outcomes. METHODS: We included 10 cohorts from the National Institutes of Health (NIH)-funded Environmental influences on Child Health Outcomes (ECHO) program (n = 1,429). We measured 14 PFAS analytes in maternal blood collected during pregnancy; eight analytes met detection criteria for analysis. We assessed quantitative autism-related traits in children via parent report on the Social Responsiveness Scale (SRS). In multivariable linear models, we examined relationships of each PFAS (natural log-transformed) with SRS scores. We further modeled PFAS as a complex mixture using Bayesian methods and examined modification of these relationships by child sex. RESULTS: Most PFAS in maternal blood were not associated with child SRS T-scores. Perfluorononanoic acid (PFNA) showed the strongest and most consistent association: each 1-unit increase in ln-transformed PFNA was associated with greater autism-related traits (adjusted ß [95% confidence interval (CI)] = 1.5 [-0.1, 3.0]). The summed mixture, which included six PFAS detected in >70% of participants, was not associated with SRS T-scores (adjusted ß [95% highest posterior density interval] = 0.7 [-1.4, 3.0]). We did not observe consistent evidence of sex differences. CONCLUSIONS: Prenatal blood concentrations of PFNA may be associated with modest increases in child autism-related traits. Future work should continue to examine the relationship between exposures to both legacy and emerging PFAS and additional dimensional, quantitative measures of childhood autism-related outcomes.

Serum and follicular fluid metabolome and markers of ovarian stimulation.

STUDY QUESTION: What metabolic pathways and metabolites in the serum and follicular fluid are associated with peak estradiol levels and the number of mature oocytes? SUMMARY ANSWER: In the serum metabolome, mostly fatty acid and amino acid pathways were associated with estradiol levels and mature oocytes while in the follicular fluid metabolome, mostly lipid, vitamin, and hormone pathways were associated with peak estradiol levels and mature oocytes. WHAT IS KNOWN ALREADY: Metabolomics has identified several metabolic pathways and metabolites associated with infertility but limited data are available for ovarian stimulation outcomes. STUDY DESIGN, SIZE, DURATION: A prospective cohort study of women undergoing IVF from 2009 to 2015. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 125 women undergoing a fresh IVF cycle at a fertility clinic in the Northeast United States who provided a serum and follicular fluid sample. Untargeted metabolomics profiling was conducted using liquid chromatography with high-resolution mass spectrometry in two chromatography columns (C18 and hydrophilic interaction chromatography (HILIC)). The main ovarian stimulation outcomes were peak serum estradiol levels and number of mature oocytes. We utilized adjusted generalized linear regression models to identify significant metabolic features. Models were adjusted for age,BMI, initial infertility diagnosis, and ovarian stimulation protocol. We then conducted pathway analysis using mummichog and metabolite annotation using level-1 evidence. MAIN RESULTS AND ROLE OF CHANCE: In the serum metabolome, 480 and 850 features were associated with peak estradiol levels in the C18 and HILIC columns, respectively. Additionally, 437 and 538 features were associated with mature oocytes in the C18 and HILIC columns, respectively. In the follicular fluid metabolome, 752 and 929 features were associated with peak estradiol levels in the C18 and HILIC columns, respectively, Additionally, 993 and 986 features were associated with mature oocytes in the C18 and HILIC columns, respectively. The most common pathways associated with peak estradiol included fatty acids (serum and follicular fluid), hormone (follicular fluid), and lipid pathways (follicular fluid). The most common pathways associated with the number of mature oocytes retrieved included amino acids (serum), fatty acids (serum and follicular fluid), hormone (follicular fluid), and vitamin pathways(follicular fluid). The vitamin D3 pathway had the strongest association with both ovarian stimulation outcomes in the follicularfluid. Four and nine metabolites were identified using level-1 evidence (validated identification) in the serum and follicular fluid metabolomes, respectively. LIMITATIONS, REASONS FOR CAUTION: Our sample was majority White and highly educated and may not be generalizable to thewider population. Additionally, residual confounding is possible and the flushing medium used in the follicular fluid could have diluted our results. WIDER IMPLICATIONS OF THE FINDINGS: The pathways and metabolites identified by our study provide novel insights into the biologicalmechanisms in the serum and follicular fluid that may underlie follicular and oocyte development, which could potentially be used to improve ovarian stimulation outcomes. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the following grants from the National Institute of Environmental Health Sciences (P30-ES019776, R01-ES009718, R01-ES022955, P30-ES000002, R00-ES026648, and T32-ES012870), and National Institute of Diabetes and Digestive and Kidney Diseases (P30DK046200). The authors have no competing interests to disclose. TRIAL REGISTRATION NUMBER: N/A.

Urinary oxidative stress biomarkers are associated with preterm birth: an Environmental Influences on Child Health Outcomes program study.

BACKGROUND: Preterm birth is the leading cause of infant morbidity and mortality worldwide. Elevated levels of oxidative stress have been associated with an increased risk of delivering before term. However, most studies testing this hypothesis have been conducted in racially and demographically homogenous study populations, which do not reflect the diversity within the United States. OBJECTIVE: We leveraged 4 cohorts participating in the Environmental Influences on Child Health Outcomes Program to conduct the largest study to date examining biomarkers of oxidative stress and preterm birth (N=1916). Furthermore, we hypothesized that elevated oxidative stress would be associated with higher odds of preterm birth, particularly preterm birth of spontaneous origin. STUDY DESIGN: This study was a pooled analysis and meta-analysis of 4 birth cohorts spanning multiple geographic regions in the mainland United States and Puerto Rico (208 preterm births and 1708 full-term births). Of note, 8-iso-prostaglandin-F2α, 2,3-dinor-5,6-dihydro-8-iso-prostaglandin-F2α (F2-IsoP-M; the major 8-iso-prostaglandin-F2α metabolite), and prostaglandin-F2α were measured in urine samples obtained during the second and third trimesters of pregnancy. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals for the associations between averaged biomarker concentrations for each participant and all preterm births, spontaneous preterm births, nonspontaneous preterm births (births of medically indicated or unknown origin), and categories of preterm birth (early, moderate, and late). Individual oxidative stress biomarkers were examined in separate models. RESULTS: Approximately 11% of our analytical sample was born before term. Relative to full-term births, an interquartile range increase in averaged concentrations of F2-IsoP-M was associated with higher odds of all preterm births (odds ratio, 1.29; 95% confidence interval, 1.11-1.51), with a stronger association observed for spontaneous preterm birth (odds ratio, 1.47; 95% confidence interval, 1.16-1.90). An interquartile range increase in averaged concentrations of 8-iso-prostaglandin-F2α was similarly associated with higher odds of all preterm births (odds ratio, 1.19; 95% confidence interval, 0.94-1.50). The results from our meta-analysis were similar to those from the pooled combined cohort analysis. CONCLUSION: Here, oxidative stress, as measured by 8-iso-prostaglandin-F2α, F2-IsoP-M, and prostaglandin-F2α in urine, was associated with increased odds of preterm birth, particularly preterm birth of spontaneous origin and delivery before 34 completed weeks of gestation.

Metabolic Perturbations Associated with an Exposure Mixture of Per- and Polyfluoroalkyl Substances in the Atlanta African American Maternal-Child Cohort.

Prenatal exposure to single chemicals belonging to the per- and polyfluoroalkyl substances (PFAS) family is associated with biological perturbations in the mother, fetus, and placenta, plus adverse health outcomes. Despite our knowledge that humans are exposed to multiple PFAS, the potential joint effects of PFAS on the metabolome remain largely unknown. Here, we leveraged high-resolution metabolomics to identify metabolites and metabolic pathways perturbed by exposure to a PFAS mixture during pregnancy. Targeted assessment of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctanesulfonic acid (PFOS), and perfluorohexanesulfonic acid (PFHxS), along with untargeted metabolomics profiling, were conducted on nonfasting serum samples collected from pregnant African Americans at 6-17 weeks gestation. We estimated the overall mixture effect and partial effects using quantile g-computation and single-chemical effects using linear regression. All models were adjusted for maternal age, education, parity, early pregnancy body mass index, substance use, and gestational weeks at sample collection. Our analytic sample included 268 participants and was socioeconomically diverse, with the majority receiving public health insurance (78%). We observed 13.3% of the detected metabolic features were associated with the PFAS mixture (n = 1705, p < 0.05), which was more than any of the single PFAS chemicals. There was a consistent association with metabolic pathways indicative of systemic inflammation and oxidative stress (e.g., glutathione, histidine, leukotriene, linoleic acid, prostaglandins, and vitamins A, C, D, and E metabolism) across all metabolome-wide association studies. Twenty-six metabolites were validated against authenticated compounds and associated with the PFAS mixture (p < 0.05). Based on quantile g-computation weights, PFNA contributed the most to the overall mixture effect for γ-aminobutyric acid (GABA), tyrosine, and uracil. In one of the first studies of its kind, we demonstrate the feasibility and utility of using methods designed for exposure mixtures in conjunction with metabolomics to assess the potential joint effects of multiple PFAS chemicals on the human metabolome. We identified more pronounced metabolic perturbations associated with the PFAS mixture than for single PFAS chemicals. Taken together, our findings illustrate the potential for integrating environmental mixture analyses and high-throughput metabolomics to elucidate the molecular mechanisms underlying human health.

Association between a Mixture of Per- and Polyfluoroalkyl Substances (PFAS) and Inflammatory Biomarkers in the Atlanta African American Maternal-Child Cohort.

Per- and polyfluoroalkyl substances (PFAS) have been identified as environmental contributors to adverse birth outcomes. One potential mechanistic pathway could be through PFAS-related inflammation and cytokine production. Here, we examined associations between a PFAS mixture and inflammatory biomarkers during early and late pregnancy from participants enrolled in the Atlanta African American Maternal-Child Cohort (N = 425). Serum concentrations of multiple PFAS were detected in >90% samples at 8-14 weeks gestation. Serum concentrations of interferon-γ (IFN-γ), interleukin 6 (IL-6), interleukin 10 (IL-10), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP) were measured at up to two time points (8-14 weeks and 24-30 weeks gestation). The effect of the PFAS mixture on each inflammatory biomarker was examined using quantile g-computation, Bayesian kernel machine regression (BKMR), Bayesian Weighted Sums (BWS), and weighted quantile sum (WQS) regression. Across all models, the PFAS mixture was associated with increased IFN-γ, IL-10, and TNF-α at both time points, with the strongest effects being observed at 24-30 weeks. Using quantile g-computation, increasing concentrations of a PFAS mixture were associated with a 29% (95% confidence interval = 18.0%, 40.7%) increase in TNF-α at 24-30 weeks. Similarly, using BWS, the PFAS mixture was associated with increased TNF-α at 24-30 weeks (summed effect = 0.29, 95% highest posterior density = 0.17, 0.41). The PFAS mixture was also positively associated with TNF-α at 24-30 weeks using BKMR [75th vs 50th percentile: 17.1% (95% credible interval = 7.7%, 27.4%)]. Meanwhile, PFOS was consistently the main drivers of overall mixture effect across four methods. Our findings indicated an increase in prenatal PFAS exposure is associated with an increase in multiple pro-inflammatory cytokines, potentially contributing to adverse pregnancy outcomes.

Exposure to phthalate metabolites, bisphenol A, and psychosocial stress mixtures and pregnancy outcomes in the Atlanta African American maternal-child cohort.

BACKGROUND: Consumer products are common sources of exposure for phthalates and bisphenol A (BPA), which disrupt the endocrine system. Psychosocial stressors have been shown to amplify the toxic effects of endocrine disruptors but, information is limited among African Americans (AAs), who experience the highest rates of adverse pregnancy outcomes and are often exposed to the highest levels of chemical and non-chemical stressors. We examined the association between an exposure mixture of phthalate metabolites, BPA, and psychosocial stressors with gestational age at delivery and birthweight for gestational age z-scores in pregnant AA women. STUDY DESIGN: Participants were enrolled in the Atlanta African American Maternal-Child Cohort (N = 247). Concentrations of eight phthalate metabolites and BPA were measured in urine samples collected at up to two timepoints during pregnancy (8-14 weeks gestation and 20-32 weeks gestation) and were averaged. Psychosocial stressors were measured using self-reported, validated questionnaires that assessed experiences of discrimination, gendered racial stress, depression, and anxiety. Linear regression was used to estimate individual associations between stress exposures (chemical and psychosocial) and birth outcomes. We leveraged quantile g-computation was used to examine joint effects of chemical and stress exposures on gestational age at delivery (in weeks) and birthweight for gestational age z-scores. RESULTS: A simultaneous increase in all phthalate metabolites and BPA was associated with a moderate reduction in birthweight z-scores (mean change per quartile increase = -0.22, 95% CI = -0.45, 0.0). The association between our exposure mixture and birthweight z-scores became stronger when including psychosocial stressors as additional exposures (mean change per quantile increase = -0.35, 95% CI = -0.61, -0.08). Overall, we found null associations between exposure to chemical and non-chemical stressors with gestational age at delivery. CONCLUSIONS: In a prospective cohort of AA mother-newborn dyads, we observed that increased prenatal exposure to phthalates, BPA, and psychosocial stressors were associated with adverse pregnancy outcomes.

Environmental health perceptions of urban youth from low-income communities: A qualitative photovoice study and framework.

BACKGROUND: Children are amongst the most susceptible groups to environmental exposures, for both immediate and life-course health outcomes. Despite their increased susceptibility, children's knowledge, experiences and voices are understudied. A deeper understanding of children's environmental health perceptions has the potential to better inform policy, develop targeted interventions and improve public health outcomes. METHODS: In this study, our community-academic partnership used the Photovoice research method to examine how urban children from low-income communities perceive environmental influences on their health. Twenty children, ages 10-12, took photographs and participated in focus group interviews regarding their perspectives on how the environment influences their health. RESULTS: Qualitative analyses revealed five major thematic categories: environmental exposures, environmental health sentiments, environmental health outcomes, interest in environmental health and environmental health solutions. We used the findings to develop an environmental health perspective theoretical framework that can inform future work designed to promote the environmental health and well-being of children from low-income communities in urban communities. CONCLUSION: Photovoice enabled children from low-income communities to capture and communicate their environmental health perceptions. These findings have the potential to inform and identify potential targets and opportunities for environmental health interventions and promotion in their communities. PATIENT OR PUBLIC CONTRIBUTION: Partnerships with community-based organizations were central to the present study. By design, these community-based partners were involved in the conduct and procedures of the study.

The Oxidative Potential of Fine Particulate Matter and Biological Perturbations in Human Plasma and Saliva Metabolome.

Particulate oxidative potential may comprise a key health-relevant parameter of particulate matter (PM) toxicity. To identify biological perturbations associated with particulate oxidative potential and examine the underlying molecular mechanisms, we recruited 54 participants from two dormitories near and far from a congested highway in Atlanta, GA. Fine particulate matter oxidative potential ("FPMOP") levels at the dormitories were measured using dithiothreitol assay. Plasma and saliva samples were collected from participants four times for longitudinal high-resolution metabolic profiling. We conducted metabolome-wide association studies to identify metabolic signals with FPMOP. Leukotriene metabolism and galactose metabolism were top pathways associated with ≥5 FPMOP-related indicators in plasma, while vitamin E metabolism and leukotriene metabolism were found associated with most FPMOP indicators in saliva. We observed different patterns of perturbed pathways significantly associated with water-soluble and -insoluble FPMOPs, respectively. We confirmed five metabolites directly associated with FPMOP, including hypoxanthine, histidine, pyruvate, lactate/glyceraldehyde, and azelaic acid, which were implications of perturbations in acute inflammation, nucleic acid damage and repair, and energy perturbation. The unique metabolic signals were specific to FPMOP, but not PM mass, providing initial indication that FPMOP might constitute a more sensitive, health-relevant measure for elucidating etiologies related to PM2.5 exposures.

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.

Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers.

INTRODUCTION: Organophosphate (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. METHODS: This 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. RESULTS: In 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. DISCUSSION: The 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.

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.