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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.
Subject(s)
Air Pollutants , Feces , Metabolome , Feces/chemistry , Female , Pregnancy , Humans , Prenatal Exposure Delayed Effects/metabolism , Infant , Air Pollution , Male , Environmental Exposure , Child, PreschoolABSTRACT
BACKGROUND: In mechanistic and preliminary human studies, prenatal exposure to per- and polyfluoroalkyl substances (PFAS) is associated with oxidative stress, a potential contributor to maternal liver disease. Bilirubin is an endogenous antioxidant abundant in the liver that may serve as a physiological modulator of oxidative stress in pregnant people. Hence, our objective was to estimate the association between repeated measures of PFAS and bilirubin during pregnancy. METHODS: The study population included 332 participants in the Atlanta African American Maternal-Child Cohort between 2014 and 2020. Serum samples were collected up to two times (early pregnancy: 6-18 gestational weeks; late pregnancy: 21-36 gestational weeks) for the measurement of perfluorohexane sulfonate (PFHxS), perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and total bilirubin. We analyzed single PFAS with linear mixed effect regression and a mixture of the four PFAS with quantile g-computation. Models were repeated with a multiplicative interaction term to explore effect modification by study visit. RESULTS: Overall, PFHxS was positively associated with bilirubin (ß = 0.08, 95 % CI = 0.01, 0.15). We also found during late pregnancy, there was a positive association of PFHxS and the PFAS mixture with bilirubin (ß = 0.12, 95 % CI = 0.02, 0.22; ψ = 0.19, 95 % CI = 0.03, 0.34, respectively). Finally, study visit modified the PFOA-bilirubin association (interaction p-value = 0.09), which was greater during early pregnancy (ß = 0.08, 95 % CI = 0.01, 0.15). CONCLUSION: In a prospective cohort of pregnant African Americans, an increase in PFOA, PFHxS, and the PFAS mixture was associated with an increase in bilirubin. Our results suggest that, depending on pregnancy stage, prenatal PFAS exposure disrupts the maternal liver antioxidant capacity.
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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.
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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.
Subject(s)
Lung Neoplasms , Metabolomics , Humans , Lung Neoplasms/blood , Lung Neoplasms/prevention & control , Lung Neoplasms/epidemiology , Lung Neoplasms/diagnosis , Male , Female , Metabolomics/methods , Case-Control Studies , Middle Aged , Aged , Sphingomyelins/bloodABSTRACT
Background: Maternal overweight and obesity has been associated with poor lactation performance including delayed lactogenesis and reduced duration. However, the effect on human milk composition is less well understood. Objectives: We evaluated the relationship of maternal BMI on the human milk metabolome among Guatemalan mothers. Methods: We used data from 75 Guatemalan mothers who participated in the Household Air Pollution Intervention Network trial. Maternal BMI was measured between 9 and <20 weeks of gestation. Milk samples were collected at a single time point using aseptic collection from one breast at 6 mo postpartum and analyzed using high-resolution mass spectrometry. A cross-sectional untargeted high-resolution metabolomics analysis was performed by coupling hydrophilic interaction liquid chromatography (HILIC) and reverse phase C18 chromatography with mass spectrometry. Metabolic features associated with maternal BMI were determined by a metabolome-wide association study (MWAS), adjusting for baseline maternal age, education, and dietary diversity, and perturbations in metabolic pathways were identified by pathway enrichment analysis. Results: The mean age of participants at baseline was 23.62 ± 3.81 y, and mean BMI was 24.27 ± 4.22 kg/m2. Of the total metabolic features detected by HILIC column (19,199 features) and by C18 column (11,594 features), BMI was associated with 1026 HILIC and 500 C18 features. Enriched pathways represented amino acid metabolism, galactose metabolism, and xenobiotic metabolic metabolism. However, no significant features were identified after adjusting for multiple comparisons using the Benjamini-Hochberg false discovery rate procedure (FDRBH < 0.2). Conclusions: Findings from this untargeted MWAS indicate that maternal BMI is associated with metabolic perturbations of galactose metabolism, xenobiotic metabolism, and xenobiotic metabolism by cytochrome p450 and biosynthesis of amino acid pathways. Significant metabolic pathway alterations detected in human milk were associated with energy metabolism-related pathways including carbohydrate and amino acid metabolism.This trial was registered at clinicaltrials.gov as NCT02944682.
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OBJECTIVE: This longitudinal study evaluated renal function and acute kidney injury (AKI) over time in U.S. agricultural workers. METHODS: We followed Florida agricultural workers from January 2020 to August 2022, collecting blood and urine pre- and post-workday during 5 visits. RESULTS: Pre-workday eGFR function in all participants was lower in summers but relatively consistent over time. In participants who worked almost exclusively in fernery operations (piece-rate compensation), we observed a high incidence of post-workday AKI in 2020 (21%) that increased to 43% by the end of the study. In comparison, 11% of nursery workers (hourly compensation) had AKI, and this rate was fairly stable. CONCLUSION: AKI risk over time differs according to the type of agricultural work. Piece rate workers who are incentivized to forgo rest breaks and hydration to earn higher wages demonstrate steadily increasing rates of AKI.
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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.
Subject(s)
Live Birth , Metabolome , Phthalic Acids , Humans , Phthalic Acids/urine , Phthalic Acids/blood , Female , Adult , Metabolome/drug effects , Prospective Studies , Environmental Pollutants/urine , Environmental Pollutants/blood , Pregnancy , Endocrine Disruptors/urine , Endocrine Disruptors/blood , Maternal Exposure , MassachusettsABSTRACT
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.
Subject(s)
Black or African American , Environmental Pollutants , Fluorocarbons , Hypertension, Pregnancy-Induced , Maternal Exposure , Humans , Female , Fluorocarbons/blood , Pregnancy , Black or African American/statistics & numerical data , Adult , Hypertension, Pregnancy-Induced/epidemiology , Hypertension, Pregnancy-Induced/blood , Maternal Exposure/statistics & numerical data , Environmental Pollutants/blood , Cohort Studies , Caprylates/blood , Georgia/epidemiology , Young Adult , Prenatal Exposure Delayed Effects , Pre-Eclampsia/blood , Pre-Eclampsia/epidemiology , Alkanesulfonic Acids/bloodABSTRACT
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.
Subject(s)
Air Pollutants , Air Pollution , Alzheimer Disease , Adult , Humans , United States , Particulate Matter/analysis , Air Pollutants/analysis , Alzheimer Disease/epidemiology , Cross-Sectional Studies , Environmental Exposure/analysis , Air Pollution/analysis , Biomarkers/analysisABSTRACT
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.
Subject(s)
Alzheimer Disease , Humans , Aged , Alzheimer Disease/genetics , Alzheimer Disease/pathology , Apolipoprotein E4/genetics , Cross-Sectional Studies , Genotype , Brain/pathology , Apolipoproteins E/geneticsABSTRACT
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.
Subject(s)
Alzheimer Disease , DNA Methylation , Humans , Alzheimer Disease/genetics , Neuroinflammatory Diseases , Particulate Matter/adverse effects , BrainABSTRACT
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.
Subject(s)
Chlorpyrifos , Insecticides , Male , Pregnancy , Child , Humans , Female , Chlorpyrifos/urine , Insecticides/urine , Thailand , Farmers , Environmental Exposure , Maternal ExposureABSTRACT
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.
Subject(s)
Lysine , Metabolomics , Child , Female , Pregnancy , Humans , Child, Preschool , Body Mass Index , Reproducibility of Results , Linear ModelsABSTRACT
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.
Subject(s)
Environmental Pollutants , Phthalic Acids , Pregnancy , Female , Humans , Interferon-gamma , Black or African American , Cross-Sectional Studies , Phthalic Acids/metabolism , Biomarkers , Inflammation , Environmental ExposureABSTRACT
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.
Subject(s)
Polybrominated Biphenyls , Polychlorinated Biphenyls , Female , Humans , Polychlorinated Biphenyls/toxicity , Polybrominated Biphenyls/toxicity , Michigan , Registries , InflammationABSTRACT
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.
Subject(s)
Black or African American , Environmental Pollutants , Fluorocarbons , Pregnancy , Prenatal Exposure Delayed Effects , Female , Humans , Pregnancy/metabolism , Alkanesulfonic Acids , Environmental Pollutants/toxicity , Fetus/metabolism , Fluorocarbons/toxicity , Placenta/metabolism , Georgia , MetabolomicsABSTRACT
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.
Subject(s)
Follicular Fluid , Infertility , Female , Humans , Follicular Fluid/metabolism , Prospective Studies , Infertility/metabolism , Ovulation Induction/methods , Estradiol , Metabolome , Fatty Acids , Vitamins/metabolism , Lipids , Oocytes/metabolism , Fertilization in VitroABSTRACT
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.
Subject(s)
Acute Kidney Injury , Farmers , Humans , Metabolome , Metabolomics , BiomarkersABSTRACT
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).