Association between Fine Particulate Matter Exposure and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease among a Cognitively Healthy Population-Based Cohort.

BACKGROUND: Epidemiological evidence suggests air pollution adversely affects cognition and increases the risk of Alzheimer's disease (AD), but little is known about the biological effects of fine particulate matter (PM2.5, particulate matter with aerodynamic diameter ≤2.5µm) on early predictors of future disease risk. OBJECTIVES: We investigated the association between 1-, 3-, and 5-y exposure to ambient and traffic-related PM2.5 and cerebrospinal fluid (CSF) biomarkers of AD. METHODS: We conducted a cross-sectional analysis using data from 1,113 cognitively healthy adults (45-75 y of age) from the Emory Healthy Brain Study in Georgia in the United States. CSF biomarker concentrations of Aß42, tTau, and pTau, were collected at enrollment (2016-2020) and analyzed with the Roche Elecsys system. Annual ambient and traffic-related residential PM2.5 concentrations were estimated at a 1-km and 250-m resolution, respectively, and computed for each participant's geocoded address, using three exposure time periods based on specimen collection date. Associations between PM2.5 and CSF biomarker concentrations, considering continuous and dichotomous (dichotomized at clinical cutoffs) outcomes, were estimated with multiple linear/logistic regression, respectively, controlling for potential confounders (age, gender, race, ethnicity, body mass index, and neighborhood socioeconomic status). RESULTS: Interquartile range (IQR; IQR=0.845) increases in 1-y [ß:-0.101; 95% confidence interval (CI): -0.18, -0.02] and 3-y (ß:-0.078; 95% CI: -0.15, -0.00) ambient PM2.5 exposures were negatively associated with Aß42 CSF concentrations. Associations between ambient PM2.5 and Aß42 were similar for 5-y estimates (ß:-0.076; 95% CI: -0.160, 0.005). Dichotomized CSF variables revealed similar associations between ambient PM2.5 and Aß42. Associations with traffic-related PM2.5 were similar but not significant. Associations between PM2.5 exposures and tTau, pTau tTau/Aß42, or pTau/Aß42 levels were mainly null. CONCLUSION: In our study, consistent trends were found between 1-y PM2.5 exposure and decreased CSF Aß42, which suggests an accumulation of amyloid plaques in the brain and an increased risk of developing AD. https://doi.org/10.1289/EHP13503.

Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and associations with hypertensive disorders of pregnancy in the Atlanta African American Maternal-Child cohort.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are man-made chemicals that are slow to break down in the environment and widely detected in humans. Epidemiological evidence suggests that prenatal exposure to perfluorooctanoic acid (PFOA), a legacy PFAS, is linked to gestational hypertension and preeclampsia. However, the relationship between other PFAS, which are structurally similar, and these outcomes remains largely understudied, despite biologic plausibility. Here, we examined associations between serum PFAS mixtures in relation to hypertensive disorders of pregnancy within a birth cohort of African Americans. METHODS: Participants in the present study were enrolled in the Atlanta African American Maternal-Child cohort between 2014 and 2020 (n = 513). Serum samples collected between 8 and 14 weeks gestation were analyzed for four PFAS. Logistic regression was used to assess associations between individual natural log transformed PFAS and specific hypertensive disorders of pregnancy (preeclampsia, gestational hypertension), while quantile g-computation was used to estimate mixture effects. Preeclampsia and gestational hypertension were treated as separate outcomes in individual models. All models were adjusted for maternal education, maternal age, early pregnancy body mass index, parity, and any alcohol, tobacco, or marijuana use. RESULTS: The geometric mean of PFOS and PFHxS was slightly lower among those with preeclampsia relative to those without a hypertensive disorder (e.g., geometric mean for PFOS was 1.89 and 1.94, respectively). Serum concentrations of PFAS were not strongly associated with gestational hypertension or preeclampsia in single pollutant or mixture models. For example, using quantile g-computation, a simultaneous one quartile increase in all PFAS was not associated with odds of gestational hypertension (odds ratio = 0.86, 95% CI = 0.60, 1.23), relative to those without a hypertensive disorder of pregnancy. CONCLUSIONS: In this birth cohort of African Americans, there was no association between serum PFAS measured in early pregnancy and hypertensive disorders of pregnancy, which may be reflective of the fairly low PFAS levels in our study population.

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.

Association of PM2.5 Exposure and Alzheimer Disease Pathology in Brain Bank Donors-Effect Modification by APOE Genotype.

BACKGROUND AND OBJECTIVES: Fine particulate matter (PM2.5) exposure has been found to be associated with Alzheimer disease (AD) and is hypothesized to cause inflammation and oxidative stress in the brain, contributing to neuropathology. The APOE gene, a major genetic risk factor of AD, has been hypothesized to modify the association between PM2.5 and AD. However, little prior research exists to support these hypotheses. This study investigates the association between traffic-related PM2.5 and AD hallmark pathology, including effect modification by APOE genotype, in an autopsy cohort. METHODS: A cross-sectional study was conducted using brain tissue donors enrolled in the Emory Goizueta AD Research Center who died before 2020 (n = 224). Donors were assessed for AD pathology including the Braak stage, Consortium to Establish a Registry for AD (CERAD) score, and combined AD neuropathologic change (ABC) score. Traffic-related PM2.5 concentrations were modeled for the metro-Atlanta area during 2002-2019 with a spatial resolution of 200-250 m. One-year, 3-year, and 5-year average PM2.5 concentrations before death were matched to participants' home address. We assessed the association between traffic-related PM2.5 and AD hallmark pathology and effect modification by APOE genotype, using adjusted ordinal logistic regression models. RESULTS: Among the 224 participants, the mean age of death was 76 years, and 57% had at least 1 APOE ε4 copy. Traffic-related PM2.5 was significantly associated with the CERAD score for the 1-year exposure window (odds ratio [OR] 1.92; 95% CI 1.12-3.30) and the 3-year exposure window (OR 1.87; 95% CI 1.01-3.17). PM2.5 was also associated with higher Braak stage and ABC score albeit nonsignificantly. The strongest associations between PM2.5 and neuropathology markers were among those without APOE ε4 alleles (e.g., for the CERAD score and 1-year exposure window, OR 2.31; 95% CI 1.36-3.94), though interaction between PM2.5 and APOE genotype was not statistically significant. DISCUSSION: Our study found traffic-related PM2.5 exposure was associated with the CERAD score in an autopsy cohort, contributing to epidemiologic evidence that PM2.5 affects ß-amyloid deposition in the brain. This association was particularly strong among donors without APOE ε4 alleles. Future studies should further investigate the biological mechanisms behind this association.

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.

Phthalate exposure increases interferon-γ during pregnancy: The Atlanta African American Maternal-Child Cohort.

BACKGROUND: The immune system undergoes unique adaptations during pregnancy and is particularly sensitive to environmental chemicals, such as phthalates, which are associated with acute and chronic inflammatory medical conditions. However, current knowledge of how phthalate exposures are associated with systemic inflammation in pregnant people is limited by cross-sectional study designs and single chemical models. Our objective was to estimate the association between repeated measures of prenatal phthalate exposures, examined individually and collectively, and a panel of clinical inflammatory biomarkers. METHODS: In the Atlanta African American Maternal-Child Cohort, biospecimens were collected at mean 11 and 26 weeks gestation (N = 126). Concentrations of eight urinary phthalate metabolites and five serum inflammatory biomarkers, including CRP, IFN-γ, IL-6, IL-10, and TNF-α, were measured. Linear mixed effect regression and quantile g-computation models were used to estimate the associations for single phthalates and their exposure mixture, respectively. RESULTS: Participants who self-reported any use of alcohol, tobacco, or marijuana in the month prior to pregnancy had increased MEP, MBP, MiBP, and CRP, relative to those with no substance use. IFN-γ was elevated in response to MECPP (% change = 17.35, 95 % confidence interval [CI] = 0.32, 32.27), MEHHP (% change = 12.75, 95 % CI = 2.22, 24.36), MEOHP (% change = 11.63, 95 % CI = 1.21, 23.12), and their parent phthalate, ΣDEHP (% change = 15.03, 95 % CI = 0.28, 31.94). The phthalate mixture was also associated with an increase in IFN-γ (% change = 15.03, 95 % CI = 6.18, 24.61). CONCLUSIONS: Our findings suggest DEHP metabolites induce systemic inflammation during pregnancy. The pro-inflammatory cytokine IFN-γ may play an important role in the relationship between prenatal phthalate exposures and adverse pregnancy outcomes.

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.

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.

Assessing Metabolic Differences Associated with Exposure to Polybrominated Biphenyl and Polychlorinated Biphenyls in the Michigan PBB Registry.

BACKGROUND: Polybrominated biphenyls (PBB) and polychlorinated biphenyls (PCB) are persistent organic pollutants with potential endocrine-disrupting effects linked to adverse health outcomes. OBJECTIVES: In this study, we utilize high-resolution metabolomics (HRM) to identify internal exposure and biological responses underlying PCB and multigenerational PBB exposure for participants enrolled in the Michigan PBB Registry. METHODS: HRM profiling was conducted on plasma samples collected from 2013 to 2014 from a subset of participants enrolled in the Michigan PBB Registry, including 369 directly exposed individuals (F0) who were alive when PBB mixtures were accidentally introduced into the food chain and 129 participants exposed to PBB in utero or through breastfeeding, if applicable (F1). Metabolome-wide association studies were performed for PBB-153 separately for each generation and ΣPCB (PCB-118, PCB-138, PCB-153, and PCB-180) in the two generations combined, as both had direct PCB exposure. Metabolite and metabolic pathway alterations were evaluated following a well-established untargeted HRM workflow. RESULTS: Mean levels were 1.75 ng/mL [standard deviation (SD): 13.9] for PBB-153 and 1.04 ng/mL (SD: 0.788) for ΣPCB. Sixty-two and 26 metabolic features were significantly associated with PBB-153 in F0 and F1 [false discovery rate (FDR) p<0.2], respectively. There were 2,861 features associated with ΣPCB (FDR p<0.2). Metabolic pathway enrichment analysis using a bioinformatics tool revealed perturbations associated with ΣPCB in numerous oxidative stress and inflammation pathways (e.g., carnitine shuttle, glycosphingolipid, and vitamin B9 metabolism). Metabolic perturbations associated with PBB-153 in F0 were related to oxidative stress (e.g., pentose phosphate and vitamin C metabolism) and in F1 were related to energy production (e.g., pyrimidine, amino sugars, and lysine metabolism). Using authentic chemical standards, we confirmed the chemical identity of 29 metabolites associated with ΣPCB levels (level 1 evidence). CONCLUSIONS: Our results demonstrate that serum PBB-153 is associated with alterations in inflammation and oxidative stress-related pathways, which differed when stratified by generation. We also found that ΣPCB was associated with the downregulation of important neurotransmitters, serotonin, and 4-aminobutanoate. These findings provide novel insights for future investigations of molecular mechanisms underlying PBB and PCB exposure on health. https://doi.org/10.1289/EHP12657.

The impact of heat exposures on biomarkers of AKI and plasma metabolome among agricultural and non-agricultural workers.

BACKGROUND: Agricultural workers are consistently exposed to elevated heat exposures and vulnerable to acute kidney injury. The underlying pathophysiology and detailed molecular mechanisms of AKI among agricultural workers, and the disproportionate burden of HRI and heat stress exposure are not well understood, especially at the level of cellular metabolism. OBJECTIVE: The aim of this study was to examine the impact of heat exposures on renal biomarkers and on the human metabolome via untargeted high-resolution metabolomics among agricultural and non-agricultural workers. METHODS: Blood and urine samples were collected pre- and post-work shift from 63 agricultural workers and 27 non- agricultural workers. We evaluated pre- and post-work shift renal biomarkers and completed untargeted metabolomics using high-resolution mass spectrometry with liquid chromatography. Metabolome-wide association studies (MWAS) models identified the metabolic features differentially expressed between agricultural workers and non-agricultural workers. RESULTS: Median values of pre-shift creatinine and osteopontin (p < 0.05) were higher for agricultural workers than non-agricultural workers. Metabolic pathway enrichment analyses revealed 27 diverse pathways differed between agricultural workers and non-agricultural workers (p < 0.05) including TCA cycle and urea cycle, carbohydrate metabolism, histidine metabolism and evidence for altered microbiome shikimate pathway. CONCLUSION: This is the first investigation on the metabolic pathways that are affected among agricultural workers who are exposed to heat compared to non-heat exposed workers. This study shows extensive responses of central metabolic systems to heat exposures that impact human health.

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.

Dietaryindex: A User-Friendly and Versatile R Package for Standardizing Dietary Pattern Analysis in Epidemiological and Clinical Studies.

Background: Few standardized and open-source tools exist for calculating dietary pattern indexes from dietary intake data in epidemiological and clinical studies. Miscalculations of dietary indexes, with suspected erroneous findings, are occasionally noted in the literature. Objective: The primary aim is to develop and validate dietaryindex, a user-friendly and versatile R package that standardizes the calculation of dietary indexes. Methods: Dietaryindex utilizes a two-step process: an initial calculation of serving size for each food and nutrient category, followed by the calculation of individual dietary indexes. It includes generic functions that accept any preprocessed serving sizes of food groups and nutrients, with the standard serving sizes defined according to the methodologies used in well-known prospective cohort studies. For ease of use, dietaryindex also offers one-step functions that directly reference common datasets and tools, including the National Health and Nutrition Examination Survey (NHANES) and Block Food Frequency Questionnaire, eliminating the need for data preprocessing. At least two independent researchers validated the serving size definitions and scoring algorithms of dietaryindex. Results: Dietaryindex can calculate multiple dietary indexes of high interest in research, including Healthy Eating Index (HEI) - 2020, Alternative Healthy Eating Index 2010, Dietary Approaches to Stop Hypertension Index, Alternate Mediterranean Diet Score, Dietary Inflammatory Index, American Cancer Society 2020 dietary index, and Planetary Health Diet Index from the EAT-Lancet Commission. In our validation process, dietaryindex demonstrated full accuracy (100%) in all generic functions with two-decimal rounding precision in comparison to hand-calculated results. Similarly, using NHANES 2017-2018 data and ASA24 and DHQ3 example data, the HEI2015 outputs from dietaryindex aligned (99.95%-100%) with results using the SAS codes from the National Cancer Institute. Conclusions: Dietaryindex is a user-friendly, versatile, and validated informatics tool for standardized dietary index calculations. We have open-sourced all the validation files and codes with detailed tutorials on GitHub (https://github.com/jamesjiadazhan/dietaryindex).

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.

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 fine particulate matter (PM2.5) as 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 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-six 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.

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.

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.

Respiratory Effects of Traffic-Related Air Pollution: A Randomized, Crossover Analysis of Lung Function, Airway Metabolome, and Biomarkers of Airway Injury.

BACKGROUND: Exposure to traffic-related air pollution (TRAP) has been associated with increased risks of respiratory diseases, but the biological mechanisms are not yet fully elucidated. OBJECTIVES: Our aim was to evaluate the respiratory responses and explore potential biological mechanisms of TRAP exposure in a randomized crossover trial. METHODS: We conducted a randomized crossover trial in 56 healthy adults. Each participant was exposed to high- and low-TRAP exposure sessions by walking in a park and down a road with high traffic volume for 4 h in random order. Respiratory symptoms and lung function, including forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), the ratio of FEV1 to FVC, and maximal mid-expiratory flow (MMEF), were measured before and after each exposure session. Markers of 8-isoprostane, tumor necrosis factor-α (TNF-α), and ezrin in exhaled breath condensate (EBC), and surfactant proteins D (SP-D) in serum were also measured. We used linear mixed-effects models to estimate the associations, adjusted for age, sex, body mass index, meteorological condition, and batch (only for biomarkers). Liquid chromatography-mass spectrometry was used to profile the EBC metabolome. Untargeted metabolome-wide association study (MWAS) analysis and pathway enrichment analysis using mummichog were performed to identify critical metabolomic features and pathways associated with TRAP exposure. RESULTS: Participants had two to three times higher exposure to traffic-related air pollutants except for fine particulate matter while walking along the road compared with in the park. Compared with the low-TRAP exposure at the park, high-TRAP exposure at the road was associated with a higher score of respiratory symptoms [2.615 (95% CI: 0.605, 4.626), p=1.2×10-2] and relatively lower lung function indicators [-0.075L (95% CI: -0.138, -0.012), p=2.1×10-2] for FEV1 and -0.190L/s (95% CI: -0.351, -0.029; p=2.4×10-2) for MMEF]. Exposure to TRAP was significantly associated with changes in some, but not all, biomarkers, particularly with a 0.494-ng/mL (95% CI: 0.297, 0.691; p=9.5×10-6) increase for serum SP-D and a 0.123-ng/mL (95% CI: -0.208, -0.037; p=7.2×10-3) decrease for EBC ezrin. Untargeted MWAS analysis revealed that elevated TRAP exposure was significantly associated with perturbations in 23 and 32 metabolic pathways under positive- and negative-ion modes, respectively. These pathways were most related to inflammatory response, oxidative stress, and energy use metabolism. CONCLUSIONS: This study suggests that TRAP exposure might lead to lung function impairment and respiratory symptoms. Possible underlying mechanisms include lung epithelial injury, inflammation, oxidative stress, and energy metabolism disorders. https://doi.org/10.1289/EHP11139.

A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction.

BACKGROUND: Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms. OBJECTIVES: We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research. METHODS: We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer. RESULTS: We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in >70% of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings. CONCLUSIONS: Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.