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Ecotoxicology and Public Health
Cross-Sectional Associations between Prenatal Per- and Poly-Fluoroalkyl Substances and Bioactive Lipids in Three Environmental Influences on Child Health Outcomes (ECHO) CohortsClick to copy article linkArticle link copied!
- Himal SutharHimal SutharDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United StatesMore by Himal Suthar
- Tomás ManeaTomás ManeaDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United StatesMore by Tomás Manea
- Dominic PakDominic PakDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United StatesMore by Dominic Pak
- Megan WoodburyMegan WoodburyDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United StatesMore by Megan Woodbury
- Stephanie M. EickStephanie M. EickGangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, Georgia 30322, United StatesMore by Stephanie M. Eick
- Amber CatheyAmber CatheyDepartment of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, United StatesMore by Amber Cathey
- Deborah J. WatkinsDeborah J. WatkinsDepartment of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, United StatesMore by Deborah J. Watkins
- Rita S. StrakovskyRita S. StrakovskyInstitute for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United StatesDepartment of Food Sciences and Human Nutrition, Michigan State University, East Lansing, Michigan 48824, United StatesMore by Rita S. Strakovsky
- Brad A. RyvaBrad A. RyvaInstitute for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United StatesDepartment of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan 48824, United StatesCollege of Osteopathic Medicine, Michigan State University, East Lansing, Michigan 48824, United StatesMore by Brad A. Ryva
- Subramaniam PennathurSubramaniam PennathurDepartment of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, Michigan 48824, United StatesDepartment of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan 48109, United StatesMore by Subramaniam Pennathur
- Lixia ZengLixia ZengDepartment of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, Michigan 48824, United StatesMore by Lixia Zeng
- David Weller
- June-Soo ParkJune-Soo ParkEnvironmental Chemistry Laboratory, Department of Toxic Substances Control, California Environmental Protection Agency, Berkeley, California 94710, United StatesMore by June-Soo Park
- Sabrina SmithSabrina SmithEnvironmental Chemistry Laboratory, Department of Toxic Substances Control, California Environmental Protection Agency, Berkeley, California 94710, United StatesMore by Sabrina Smith
- Erin DeMiccoErin DeMiccoProgram on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, California 94143, United StatesMore by Erin DeMicco
- Amy PadulaAmy PadulaProgram on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, California 94143, United StatesMore by Amy Padula
- Rebecca C. FryRebecca C. FryDepartment of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, Gillings School of Global Public Health, Chapel Hill, North Carolina 27599, United StatesMore by Rebecca C. Fry
- Bhramar MukherjeeBhramar MukherjeeDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, United StatesMore by Bhramar Mukherjee
- Andrea AguiarAndrea AguiarBeckman Institute for Advanced Science and Technology, University of Illinois Urbana−Champaign, Champaign, Illinois 61801, United StatesDepartment of Comparative Biosciences, University of Illinois Urbana−Champaign, Champaign, Illinois 61802, United StatesMore by Andrea Aguiar
- Sarah Dee GeigerSarah Dee GeigerDepartment of Comparative Biosciences, University of Illinois Urbana−Champaign, Champaign, Illinois 61802, United StatesDepartment of Kinesiology and Community Health, University of Illinois at Urbana−Champaign, Champaign, Illinois 61801, United StatesMore by Sarah Dee Geiger
- Shukhan NgShukhan NgDepartment of Comparative Biosciences, University of Illinois Urbana−Champaign, Champaign, Illinois 61802, United StatesMore by Shukhan Ng
- Gredia Huerta-MontanezGredia Huerta-MontanezDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United StatesMore by Gredia Huerta-Montanez
- Carmen Vélez-VegaCarmen Vélez-VegaDepartment of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia 30606, United StatesMore by Carmen Vélez-Vega
- Zaira RosarioZaira RosarioUniversity of Puerto Rico Graduate School of Public Health, San Juan, Puerto Rico 00935, United StatesMore by Zaira Rosario
- Jose F. CorderoJose F. CorderoDepartment of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia 30606, United StatesMore by Jose F. Cordero
- Emily ZimmermanEmily ZimmermanDepartment of Communication Sciences and Disorders, Northeastern University, Boston, Massachusetts 02115, United StatesMore by Emily Zimmerman
- Tracey J. WoodruffTracey J. WoodruffProgram on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, California 94143, United StatesMore by Tracey J. Woodruff
- Rachel Morello-FroschRachel Morello-FroschProgram on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, California 94143, United StatesDepartment of Environmental Science, Policy and Management and School of Public Health, University of California, Berkeley, Berkeley, California 94720, United StatesMore by Rachel Morello-Frosch
- Susan L. SchantzSusan L. SchantzBeckman Institute for Advanced Science and Technology, University of Illinois Urbana−Champaign, Champaign, Illinois 61801, United StatesDepartment of Comparative Biosciences, University of Illinois Urbana−Champaign, Champaign, Illinois 61802, United StatesMore by Susan L. Schantz
- John D. MeekerJohn D. MeekerDepartment of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, United StatesMore by John D. Meeker
- Akram N. AlshawabkehAkram N. AlshawabkehDepartment of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United StatesMore by Akram N. Alshawabkeh
- Max T. Aung*Max T. Aung*University of Southern California, Keck School of Medicine, Department of Population and Public Health Sciences, SSB 225R, 1845 N Soto St., Los Angeles, California 90032, United States. Email: [email protected]Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United StatesMore by Max T. Aung
Environmental Science & Technology
Cite this: Environ. Sci. Technol. 2024, 58, 19, 8264–8277
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Abstract
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Prenatal per- and poly-fluoroalkyl substances (PFAS) exposure may influence gestational outcomes through bioactive lipids─metabolic and inflammation pathway indicators. We estimated associations between prenatal PFAS exposure and bioactive lipids, measuring 12 serum PFAS and 50 plasma bioactive lipids in 414 pregnant women (median 17.4 weeks’ gestation) from three Environmental influences on Child Health Outcomes Program cohorts. Pairwise association estimates across cohorts were obtained through linear mixed models and meta-analysis, adjusting the former for false discovery rates. Associations between the PFAS mixture and bioactive lipids were estimated using quantile g-computation. Pairwise analyses revealed bioactive lipid levels associated with PFDeA, PFNA, PFOA, and PFUdA (p < 0.05) across three enzymatic pathways (cyclooxygenase, cytochrome p450, lipoxygenase) in at least one combined cohort analysis, and PFOA and PFUdA (q < 0.2) in one linear mixed model. The strongest signature revealed doubling in PFOA corresponding with PGD2 (cyclooxygenase pathway; +24.3%, 95% CI: 7.3–43.9%) in the combined cohort. Mixture analysis revealed nine positive associations across all pathways with the PFAS mixture, the strongest signature indicating a quartile increase in the PFAS mixture associated with PGD2 (+34%, 95% CI: 8–66%), primarily driven by PFOS. Bioactive lipids emerged as prenatal PFAS exposure biomarkers, deepening insights into PFAS’ influence on pregnancy outcomes.
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License Summary*
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Attribution (BY): Credit must be given to the creator.
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License Summary*
You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below:
Creative Commons (CC): This is a Creative Commons license.
Attribution (BY): Credit must be given to the creator.
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Copyright © 2024 The Authors. Published by American Chemical Society
Synopsis
Exposure to per- and poly-fluoroalkyl substances (PFAS), ubiquitous in consumer and industrial products, was revealed to be associated with elevated levels of bioactive lipids across three enzymatic pathways in pregnant women.
1. Introduction
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Widespread environmental contamination of per- and poly-fluoroalkyl substances (PFAS) poses a major public health concern. Human exposure to PFAS can occur through ingestion of contaminated food and water, and inhalation of indoor air contaminated by consumer products. (1) Biomonitoring in the National Health and Nutrition Examination Study (NHANES) has reported over 98% detection of PFAS compounds in serum of U.S. residents. (2) PFAS metabolism and excretion is slow due to their carbon–fluorine bonds, with in vivo half-lives spanning from several months to years. (3) Increasing experimental and epidemiological evidence indicates adverse health effects attributable to PFAS exposure, including kidney dysfunction, hormone disruption, and liver, reproductive, and developmental toxicity. (4) Biomonitoring of PFAS in NHANES and the Environmental influences on Child Health Outcomes (ECHO) Program indicates moderate correlation between individual compounds, highlighting the need to consider PFAS as a mixture to evaluate cumulative health effects and ameliorate residual confounding. (5,6)
PFAS exposures during pregnancy, a sensitive period of the life course, have been identified as potential risk factors for adverse birth outcomes and pregnancy complications. One systematic review of prenatal PFAS exposures identified select compounds associated with increased odds of preterm birth and miscarriage. (7) There is also evidence indicating disparities in associations between PFAS exposure in women and chronic health outcomes, with one study revealing that Black women (median age 49) had higher risk of developing hypertension compared to White women. (8) Our team also identified increased depressive symptoms associated with higher PFAS exposure among immigrant pregnant women compared to U.S. born counterparts (median age 34) in the Chemicals in Our Bodies cohort. (9) Widespread evidence of human exposure, coupled with associated health effects, warrants detailed investigation into the intermediate mechanisms of PFAS toxicity to inform risk assessment and develop potential interventions.
Bioactive lipids, including polyunsaturated fatty acids such as arachidonic acid, are metabolized by conserved families of enzymes (e.g., cytochrome p450s, lipoxygenases, and cyclooxygenases) yielding secondary eicosanoid metabolites with important downstream physiological functions. (10) Eicosanoids partly regulate inflammation and influence cardiovascular and renal function, and perturbations in circulating eicosanoids are potential biomarkers of adverse pregnancy outcomes. (11−13) In a metabolomic study in Atlanta, Georgia, lipid metabolism pathways were associated with gestational age at birth, including linoleic acid, a bioactive lipid compound. (14) We have also shown in a previous LIFECODES cohort study that higher concentrations of several eicosanoid metabolites derived from the cytochrome p450, lipoxygenase, and cyclooxygenase enzymes were associated with increased risk of spontaneous preterm birth. (15) Another study in the LIFECODES cohort identified higher concentrations of eicosanoid metabolites from the cytochrome p450 and lipoxygenase pathways associated with greater risk of being born small for gestational age. (16)
PFAS have been found to be associated with changes to several biological pathways, including metabolism of bioactive lipids, amino acids, and xenobiotic detoxification. (17) This is corroborated by experimental studies indicating that PFAS interfere with cytochrome p450 signaling, critical for cellular metabolism. (18,19) PFAS also interfere with homeostasis of intracellular calcium gradients, impacting calcium-dependent enzymatic activity and altering systemic bioactive lipid profiles. (20) Evidence that PFAS are linked to whole pathways of lipid metabolism provides an impetus for deeper investigation of targeted lipid metabolites associated with PFAS, particularly during pregnancy.
The objective of this study was to quantify maternal PFAS exposures and bioactive lipids during pregnancy and estimate the individual and cumulative associations of PFAS with these biomarkers. There is a need for modern epidemiology studies to integrate greater racial, socioeconomic, and geographic diversity to better inform risk estimation across historically marginalized communities. Thus, our current study utilized a diverse sample across three birth cohorts in the ECHO Program. Our study hypothesized that higher concentrations of PFAS are associated with increased eicosanoid metabolite concentrations based on previous studies indicating that higher concentrations of these biomarkers are associated with adverse birth outcomes.
2. Methods
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2.1. Study Populations
The ECHO Program integrates diverse sample populations into a large cohort to advance research of how environmental factors from preconception through childhood influence child health and development. (21) To support this program goal, this study integrates data across three ECHO samples (Table 1): Chemicals in Our Bodies (CiOB), Illinois Kids Development Study (IKIDS), and the ECHO-PROTECT cohort. (22,23) These three sample populations were selected due to having rich data on PFAS, targeted lipid biomarkers, and neurodevelopment measures as part of the Opportunities and Infrastructure Fund. The samples utilize demographic diversity across the U.S. and serve as a foundation to expand measurements in future studies across additional ECHO samples. This approach has been applied in previous studies within the ECHO program with robust sensitivity analyses to account for different cohort characteristics. (24,25)
Table 1. Demographic Profile of CiOB, IKIDS, and ECHO-PROTECT Cohorts
| cohort | ||||||
|---|---|---|---|---|---|---|
| characteristic | overall | CiOB, N = 73a | IKIDS, N = 287a | ECHO-PROTECT, N = 54a | p-valueb | |
| mother’s Race | <0.001 | |||||
| non-Hispanic white | 253 (62%) | 34 (47%) | 219 (78%) | 0 | ||
| black | 19 (4.6%) | - | 14 (5.0%) | 0 | ||
| Asian | 48 (11.7%) | 14 (19%) | 34 (12%) | 0 | ||
| Hispanic | 78 (19%) | 17 (23%) | 7 (2.5%) | 54 (100%) | ||
| other | 11 (2.7%) | - | 8 (2.8%) | 0 | ||
| missing | 5 | 0 | 5 | 0 | ||
| maternal age (years) | 31.8 (28.8, 34.5) | 33.1 (29.9, 36.0) | 31.8 (29.1, 34.3) | 28.0 (24.0, 33.0) | <0.001 | |
| missing | 6 | 1 | 0 | 5 | ||
| maternal education | <0.001 | |||||
| <HS | 11 (2.7%) | - | - | - | ||
| HS/GED/some college | 77 (19%) | 16 (22%) | 39 (14%) | 22 (45%) | ||
| Bachelors | 142 (35%) | 15 (21%) | 111 (39%) | 16 (33%) | ||
| Graduate | 179 (44%) | 37 (51%) | 135 (47%) | 7 (14%) | ||
| missing | 5 | 0 | 0 | 5 | ||
| prepregnancy BMI (kg/m2) | 25 (22, 29) | 24 (22, 27) | 25 (22, 30) | 25 (21, 29) | 0.2 | |
| missing | 20 | 11 | 1 | 8 | ||
| parity | <0.001 | |||||
| 0 | 191 (47%) | 35 (51%) | 156 (54%) | 0 (0%) | ||
| 1 or more | 214 (53%) | 34 (49%) | 131 (46%) | 49 (100%) | ||
| missing | 9 | 4 | 0 | 5 | ||
| maternal household Income | <0.001 | |||||
| <$50,000 | 110 (28%) | 18 (26%) | 52 (18%) | 40 (93%) | ||
| $50,000–$99,999 | 145 (36%) | 6 (9%) | 137 (48%) | - | ||
| >$100,000 | 143 (36%) | 45 (65%) | 97 (34%) | - | ||
| missing | 16 | 4 | 1 | 11 | ||
| gestational age at visit (weeks) | 17.4 (16.6, 18.9) | 23.1 (19.7, 25.7) | 17.0 (16.4, 17.7) | 25.7 (24.4, 27.9) | <0.001 | |
| missing | 10 | 0 | 0 | 10 | ||
a
n (%), cells with counts ≤5 have been masked; median (IQR).
b
Kruskal–Wallis rank sum test; Pearson’s Chi-squared test
The CiOB cohort participants are based in San Francisco, CA, and were recruited during the second trimester of pregnancy from three University of California San Francisco hospitals. Women included in the CiOB cohort had to be ≥18 years of age, primarily speak English or Spanish, and have a singleton pregnancy. The IKIDS cohort participants were recruited between 10 and 14 weeks gestation from two obstetric clinics in Champaign-Urbana, Illinois. Women included in the IKIDS cohort had to be between 18 and 40 years of age, have English fluency, have a singleton pregnancy, be ≤15 weeks gestation at enrollment, not have a child already in the IKIDS cohort, reside within a 30 min drive from the University of Illinois Urbana-Campaign (UIUC) campus, and plan to remain in the area through the child’s first birthday. The ECHO-PROTECT cohort participants were recruited before 20 weeks’ gestation from two hospitals and five clinics in the Northern Karst aquifer region in Puerto Rico. Enrollment of the cohort began in 2011 and is ongoing. Inclusion criteria for the women in this cohort included being between 18 and 40 years of age, residing in the Northern Karst aquifer region, not having used oral contraceptives three months prepregnancy, not having undergone in vitro fertilization, and having no major pre-existing conditions. Detailed information on study recruitment and data collection per cohort has been previously described. (22,23) Participants in each cohort provided written informed consent for inclusion in this study, and local institutional review boards per cohort reviewed and approved study protocols. Sample sizes for each cohort are described in greater detail below, and the flow diagram for selection of the final analytical data set used in statistical analyses is illustrated in Supplemental Figure 1.
2.2. PFAS Exposure Assessment
In the CiOB (n = 73, median 23 weeks’ gestation at sample collection) and IKIDS (n = 287, median 17 weeks’ gestation at sample collection) cohorts, 12 PFAS compounds were quantified in maternal serum during pregnancy: perfluorononanoic acid (PFNA), perfluoroheptanoic acid (PFHpA), perfluorodecanoic acid (PFDeA), perfluorododecanoic acid (PFDoA), perfluorooctanoic acid (PFOA), perfluorooctanesulfonamide (PFOSA), 2-(N-methyl-perfluorooctane sulfonamido) acetic acid (Me-PFOSA-AcOH), 2-(N-ethyl-perfluorooctane sulfonamido) acetic acid (Et-PFOSA-AcOH), perfluoroundecanoic acid (PFUdA), perfluorohexanesulfonate (PFHxS), perfluorooctanesulfonic acid (PFOS), and perfluorobutanesulfonic acid (PFBS). After sample collection, serum was frozen at −80 °C. Samples were processed at the Environmental Chemical Laboratory at the California Department of Toxic Substances Control using a previously described analytical protocol. (26) PFAS quantification was achieved using internal standards per serum sample and an automated online solid phase extraction method coupled to liquid chromatography and tandem mass spectrometry. The limits of detection for individual PFAS compounds were equal to three times the standard deviation of the blank negative control sample. (26) In each batch of serum PFAS analyses, analytes were quantified using a constructed calibration, and calibration curve regression coefficients (R2) of 0.98 to 0.99 were obtained. We utilized in-house quality control materials that were prepared by spiking a known amount of PFAS compounds in blank bovine serum at low and high levels, 4 samples each, achieving over 90% recovery and coefficient of variation (CV%) values ranging from 5.2 to 14.1. There was also a QC/QA effort to evaluate the interlaboratory comparison. Standard reference materials (SRM 1958) were utilized from the National Institute of Standards and Technology (Gaithersburg, MD), and quality control samples spiked with known PFAS concentrations were from the United States Centers for Disease Control and Prevention as reference materials. Blank samples of bovine serum (Hyclone/GE Healthcare LifeSciences) were also processed for each sample batch, and no PFAS were detected above their respective limit of detection in these blank samples.
Maternal serum samples from the ECHO-PROTECT cohort (n = 54, median 26 weeks’ gestation at sample collection) were used to quantify nine PFAS compounds (Table 1). After sample collection, serum was frozen at −80 °C and processed at NSF International (Ann Arbor, MI). PFAS quantification was also performed by liquid chromatography and tandem mass spectrometry, simulating the Centers for Disease Control and Prevention’s poly-fluoroalkyl chemicals laboratory procedure method No: 6304.1. Standards of known purity and identity were used during preparation of calibration, quality control, and internal standards, with a minimum of 5 standards for each compound of interest. The validated analyte calibration curve correlation coefficient (R2) ranges were ≥0.996. The method accuracy (% nominal concentration) and precision (% relative standard deviation [RSD]) were determined through six replicate analyses of analytes spiked at three different concentrations in pooled human serum across validation runs on three separate days (n = 18), reflecting the intraday and interday variability of the assay. Calibration checks were conducted after every 10 samples. The accuracy (% nominal concentration) range across all analytes was 95.1–103% with the precision (%RSD) range for the serum quality control samples across all analytes being 2.3–16%.
Method detection limits for all PFAS measured in each cohort are reported in Supplemental Table 1. For samples with values below the limit of detection, we used machine-read values (if reported) or concentrations imputed using the limit of detection divided by the square root of 2. (27) Of the PFAS compounds measured, we selected to analyze those with a detection rate of ≥70%, highlighted in Supplemental Table 1 by cohort.
2.3. Bioactive Lipids Assay
Maternal plasma samples were used to quantify a targeted panel of 50 bioactive lipids (Supplemental Table 2) in the CiOB (n = 73, median 24 weeks’ gestation at sample collection), IKIDS (n = 287, median 17 weeks’ gestation at sample collection), and PROTECT (n = 54, median 26 weeks’ gestation at sample collection) cohorts. For ECHO-PROTECT and CiOB cohorts, plasma was collected using ethylenediaminetetraacetic acid plasma tubes and temporarily stored at +4 °C for less than 4 h. Blood was subsequently centrifuged for 20 min and stored at −80 °C. Women in the IKIDS cohort provided a fasted (10 to 12 h) blood sample collected in green-top sodium heparin tubes, which were kept at room temperature for 2 h prior to processing and centrifuged at room temperature for 20 min. The resulting plasma was aliquoted immediately into cryovials for storage at −80 °C. The targeted bioactive lipids panel consisted of five parent fatty acid compounds and 45 eicosanoid metabolites derived from three enzymatic groups (lipoxygenases, cytochrome p450s, and cyclooxygenases), and full names and abbreviations are documented in Supplemental Table 2. Quantification of bioactive lipid concentrations was achieved using a 6490 Triple Quadrupole mass spectrometer (Agilent, New Castle, DE), where the mass spectrometer was set to a targeted multiple reaction monitoring mode and individual biomarkers were identified based on metabolite-specific fragmentation and retention time. Limits of detection were not calculated across individual instrument analysis cycles, and all measured bioactive lipids had machine-read values. Further information on instrumental parameters and quality control/assurance have been previously documented. (28) Briefly, we conducted sequential dilution of each internal standard in duplicate to establish linearity and estimate the coefficient of variation (CV) of the measurements at various concentrations. CV values for a majority (86%) of bioactive lipids were <40% indicating modest levels of variability, and hence measurements are of high confidence and likely highly reproducible. Six bioactive lipids (13,14-D-PGJ2, PGD3, PGE3, BCPGE2, BCPGE1, 9-oxoODE) were at the threshold of limit of detection potentially accounting for the higher CV/variability observed (65 to 112%); higher sensitivity methods may enhance reproducibility of these analytes. We ran a pool of study samples at the beginning of each batch and after each 12 samples during mass spectrometry to assess drift in measurements over time and the batch-to-batch variability.
2.4. Statistical Analyses
We utilized a conceptual model and directed an acyclic graph of the relationships between PFAS and bioactive lipids (Supplemental Figure 2) to inform our statistical analyses. We tabulated distributions of key covariates from our conceptual model for each cohort in our study. Spearman correlations were estimated between all high-detect (i.e., ≥70% of observations exceeding minimum level of detection in cohort) PFAS compounds and bioactive lipids within each cohort. Combined cohort correlations were not conducted due to differences in high-detect PFAS across cohorts. Based on which PFAS were highly detected in each cohort (Supplemental Table 1), associations were estimated in combined cohort samples with two (CiOB and IKIDS) or three cohorts (CiOB, IKIDS, and ECHO-PROTECT) using linear mixed effect regressions (random intercept for cohort) and meta-analyses. Significance was evaluated at a level of α ≤ 0.05. Associations between PFAS mixtures and bioactive lipids were estimated using quantile g-computation in the combined IKIDS and CiOB cohort. (29) Analyses are described in detail below and were performed with R (version 4.3.0).
2.4.1. Combined Cohort Analysis
Linear mixed effects models were utilized to test combined cohort pairwise associations between all sampled bioactive lipids and common high-detection PFAS, using natural log-transformed lipid levels as outcomes and natural log-transformed PFAS levels as exposures. These linear mixed effects models included a random intercept for the cohort to partly ameliorate bias from different laboratory analyses of PFAS, heterogeneity in demographic characteristics between cohorts, and differences in PFAS and bioactive lipid concentrations between cohorts. All effect estimates were transformed to enhance interpretability and represent a percent change in a given bioactive lipid corresponding to a doubling (or 100% increase) of individual PFAS (exact transformation executed: (2β – 1)*100). Unadjusted and adjusted random intercept models were generated for all three cohorts by using PFAS common to all three cohorts: PFNA and PFOS (Supplemental Table 1), and when combining the CiOB and IKIDS cohorts, using the natural log-transformed high-detect PFAS common to those two cohorts as exposures (Supplemental Table 1). Adjusted models included variables selected a priori based on our previous investigation of PFAS and biomarkers of lipid peroxidation and oxidative stress. (30) The covariates included in the adjusted models were maternal age, education, prepregnancy BMI, parity, and gestational age at sampling of bioactive lipids. Maternal education was specifically included due to its establishment as a proxy for social and economic resources, (31) and its associations with both PFAS concentrations during pregnancy (32) and metabolic perturbations. (33) To evaluate the appropriateness of utilizing a priori confounders, we estimated associations between the covariates and PFAS and bioactive lipids (Supplemental Tables 4–6). In the CiOB and IKIDS cohorts, all covariates had a significant association with at least one PFAS and one bioactive lipid using a p-value threshold of 0.10; in the ECHO-PROTECT cohort, maternal age and maternal education were significantly associated with at least one PFAS and one bioactive lipid, using a p-value threshold of 0.15 due to limited sample size and power in this cohort. Missing observations for the covariates were omitted from the adjusted models. Q-values were calculated for all pairwise models to control for false discovery rates, (34) and, to test for nonlinear associations between PFAS and bioactive lipid levels, we conducted a sensitivity analysis treating quartiles of log-transformed PFAS levels as exposures in our linear mixed effect models.
2.4.2. Meta-Analysis
Each cohort in our study has heterogeneous demographic features and varying exposure levels of PFAS. Thus, to recognize cohort-specific exposure response functions, we estimated pairwise effect estimates for PFAS and bioactive lipids from each individual cohort using linear regression, adjusted for the same covariates modeled in the combined cohort analysis except for ECHO-PROTECT, which excluded parity due to 0% variance within the cohort. We combined these effect estimates by meta-analysis using the METAL method, (35) yielding overall effect estimates and p values for pairwise associations between individual bioactive lipids and common high-detect PFAS. Meta-analysis was implemented for all three cohort-specific models, and for the IKIDS and CiOB cohort-specific models. Interpretation of cohort-specific effect estimates was treated as a sensitivity analysis to evaluate consistencies in combined cohort and meta-analysis and reported in the Supporting Information.
2.4.3. PFAS Mixtures Analysis
To address the study goal of estimating the cumulative effect of multiple PFAS on bioactive lipids, we used quantile g-computation, (29) a generalization of the weighted quantile sum (WQS) regression method (36,37) which does not assume directional homogeneity of the exposures’ effects on the outcome. This method outputs an unbiased estimate of the effect on a particular bioactive lipid associated with simultaneously increasing all PFAS exposures by one quartile. Quantile g-computation was implemented in the combined CiOB and IKIDS sample to measure the mixtures effect of log-transformed high-detect PFAS common to both the CiOB and IKIDS cohorts (Et-PFOSA-AcOH, PFDEA, PFHxS, PFNA, PFOA, PFOS, and PFUDA; Supplemental Table 1) on all log-transformed bioactive lipids, controlling for the same covariates included in the adjusted combined CiOB and IKIDS random intercept model. The cohort itself was included as an additional fixed effect covariate to account for any between-cohort differences. (30) To assess the robustness of our main results with respect to our selected covariates, we conducted a vibration analysis of the primary effect estimate, obtaining β coefficients when including all possible combinations of four out of the five of our covariates in our main quantile g-computation model. To assess the effect of missingness in covariates (Table 1) on our main effect estimate, we conducted another vibration analysis, performing multiple imputation on the CiOB and IKIDS combined sample using 10 iterations and comparing the outputted β coefficients to that of our main quantile g-computation model. The resulting β coefficients from both vibration analyses were evaluated based on significance and whether they were in the 95% confidence interval of our main results.
3. Results
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3.1. Descriptive Statistics
Table 1 shows the distribution of demographics and gestational age at plasma collection for bioactive lipids across all three cohorts. White women represented the largest group in CiOB (47%) and IKIDS (78%), and ECHO-PROTECT had only Hispanic women (100%). Women in CiOB were the oldest (median 33 years), followed by IKIDS (median 32 years), and ECHO-PROTECT (median 28 years; p < 0.01). Women in IKIDS had the highest educational attainment, with 86% having completed a bachelor’s or graduate degree, followed by CiOB (72%), and ECHO-PROTECT (47%; p < 0.01). All mothers in ECHO-PROTECT reported having at least one previous birth─higher than CiOB (49%) and IKIDS (46%; p < 0.01). The annual household income for women in CiOB was the highest with 65% reporting annual household incomes of ≥$100,000, then women in IKIDS (34%), while 93% of women in ECHO-PROTECT reported a household income <$50,000 (p < 0.01). Income was not adjusted for local cost of living or median salary. Prepregnancy BMI was similar across all three cohorts (median 24 kg/m2 in CIOB and 25 kg/m2 in IKIDS and ECHO-PROTECT, p = 0.2).
Distributions of PFAS in our sample and in the 2011–2018 NHANES cycle sampling adult women of reproductive age and bioactive lipids by cohort are reported in Supplemental Tables 1 and 3, respectively. Among the high-detect PFAS common to all three cohorts, PFNA (median 0.20 ng/mL) and PFOS (median 1.78 ng/mL) concentrations were the lowest in the ECHO-PROTECT cohort (p < 0.01), while the CiOB cohort had the highest median concentration of PFNA (0.53 ng/mL), and the IKIDS cohort had the highest median concentration of PFOS (3.27 ng/mL). Among the high-detect PFAS common to only the CiOB and IKIDS cohorts, the greatest differences were observed for PFUdA (median 0.18 ng/mL in CiOB and median 0.06 ng/mL in IKIDS; p < 0.01) and PFHxS (median 0.55 ng/mL in CiOB and median 0.76 ng/mL in IKIDS; p = 0.02). There were differences in the interquartile range of PFAS levels in our sample and those in the NHANES sample for PFNA, PFHpA, PFHxS, and PFBS. Among the bioactive lipids, we observed the greatest difference across cohorts for linoleic acid concentrations (median 668 μMol/L in CiOB, 1185 μMol/L in IKIDS, and 102 μMol/L in ECHO-PROTECT; p < 0.01) and 20-carboxy arachidonic acid (CAA) concentrations (median 185 nMol/L in CiOB, 302 nMol/L in IKIDS, and 74 nMol/L in ECHO-PROTECT; p < 0.01).
3.2. Within-Cohort Correlations
Within-cohort Spearman correlations between bioactive lipids and PFAS are shown in Supplemental Figure 3A for the CiOB cohort, in Supplemental Figure 3B for the IKIDS cohort, and in Supplemental Figure 3C for the ECHO-PROTECT cohort. In the CiOB cohort, correlation coefficients between bioactive lipids and PFAS ranged between −0.31 and 0.38, with the strongest negative correlation between DHA and PFOS, and the strongest positive correlation between 13S-HODE and PFUDA. For bioactive lipids in the CiOB cohort, correlation coefficients ranged from −0.47 (16-HETE and 13-oxoODE) to 1 (12(13)-EpoME and 13S-HODE), while correlation coefficients for PFAS were between −0.08 (PFDeA and Et-PFOSA-AcOH) and 0.81 (PFNA and PFOA). In the IKIDS cohort, correlation coefficients between bioactive lipids and PFAS ranged between −0.14 and 0.22, with the strongest negative correlation between 15-HETE and PFHxS, and the strongest positive correlation between arachidonic acid and PFNA. Correlation coefficients for bioactive lipids in the IKIDS cohort were between −0.75 (13,14-D-PGJ2 and 18-HETE) and 0.89 (9S-HODE and 13S-HODE), and between 0.05 (PFOA and Me-PFOSA-AcOH) and 0.75 (PFNA and PFOA) for PFAS. In the ECHO-PROTECT cohort, correlation coefficients between bioactive lipids and PFAS ranged between −0.37 and 0.32, with the strongest negative correlation between 9,10-DiHOME and PFNA, and the strongest positive correlation between 13,14-D-PGJ2 and PFNA. Bioactive lipid correlation coefficients within the ECHO-PROTECT cohort were between −0.59 (PGA2 and 11-HETE) and 0.8 (9(10)-EpoME and 12(13)-EpoME), and the correlation coefficients between PFNA and PFOS in the ECHO-PROTECT cohort was 0.57.
3.3. Pairwise Associations between Individual PFAS and Bioactive Lipids
The majority of significant associations observed in at least one of the four combined models were positive. All coefficients representing the pairwise associations between bioactive lipids and PFAS from the adjusted random intercept models and meta-analyses are presented in a heatmap (Figure 1) as the effect per doubling of PFAS concentration. Additional output of these models, including exact p values and standard errors can be found in Supplemental Tables 7–10.
Figure 1
Figure 1. Heatmap of β estimates corresponding to percentage change in bioactive lipids as a result of doubling log-transformed PFAS for adjusted joint analyses and meta-analyses run on adjusted within-cohort models. The magnitude of effect estimates in each cell in the heatmap corresponds to the intensity of the color band in the legend. Nonsignificant values (p > .05) are marked with black “X”. Sample sizes range from 343 to 383 (see Supplemental Tables 7, 8, 9, and 10 for exact pairwise sample sizes).
In the cyclooxygenase pathway, 15 significant associations between bioactive lipids and PFAS were observed in at least one of the four combined cohort models. The association between BCPGE1 and PFNA was significant in all four models (doubling effect in PFNA range of 7.2–12.8% increase in BCPGE1 across models). The associations between 9-oxoODE and PFNA (doubling effect in PFNA range 1.6–2.4% decrease in 9-oxoODE), PGD2 and PFOS (doubling effect in PFOS range 11.3–11.9% increase in PGD2), and PGD3 and PFOS (doubling effect in PFOS range 6.8–11.5% increase in PGD3) were significant in three models.
In the cytochrome p450 pathway, no significant associations were found common to all four models; however, there were significant positive associations between 14(15)-EET and PFDeA (doubling effect range 4.6–6.4%) and between 8(9)-EET and Me-PFOSA-AcOH (doubling effect range 4.0–5.4%) observed in the CiOB and IKIDS random intercept model and in the meta-analysis integrating effect estimates from CiOB and IKIDS cohorts.
Within the lipoxygenase pathway, significant positive associations were observed between 12-oxoETE and PFOS (doubling effect range 4.9–8.2%) and 15-oxETE and PFOS (doubling effect range 7.0–10.4%) across all four models.
Among the parent compounds, significant positive associations were observed for arachidonic acid and PFNA (doubling effect range 6.0–10.9%) and arachidonic acid and PFOS (doubling effect range 5.5–9.7%) across all four models.
We explored multiple testing comparison adjustments in the linear mixed effects models (Supplemental Tables 7 and 8). While none were below a threshold of 0.1 in the two-cohort or three-cohort models, there were seven PFAS and bioactive lipid pairs (PGD2 and PFOA; PGD3 and PFUdA; 13,14DHK-PGF2a* and PFUdA; 12-oxoETE and PFUdA; 15-oxoETE and PFUdA; 15-oxoETE and PFOS; arachidonic acid and PFOS) below the 0.2 threshold in the two-cohort linear mixed effect models. Our sensitivity analysis of within-cohort pairwise associations can be found in Supplemental Tables 11–16. While individual cohort analyses are underpowered to detect associations, directions of pairwise associations between individual cohorts and combined cohorts were largely consistent. Quartile analyses of the 3-cohort linear mixed effect models revealed that while certain quartiles of log-transformed PFAS may drive the overall direction of association, there is no substantial evidence of nonlinear associations (Supplemental Table 17). Quartile analyses of the two-cohort linear mixed effect models are suggestive of nonlinear relationships between PFOA and PGD2 and 13,14-PGJ2 (Supplemental Table 18).
3.4. PFAS Mixture Associations
Quantile g-computation utilizing the CiOB and IKIDS cohorts indicated that simultaneously increasing all log-transformed PFAS in the mixture (PFNA, PFDeA, PFoA, Me-PFOSA, PFUdA, PFHxS, and PFOS) by one quartile corresponded to increases in BCPGE1, PGD2, and PGD3 (cyclooxygenase pathway); 12,13-DiHOME and 5(6)-EET (cytochrome p450 pathway); 12-oxoETE, 15-oxoETE, and 5-HETE (lipoxygenase pathway); and the arachidonic acid parent compound. The largest increase in the cyclooxygenase pathway was observed in PGD2 (34% increase, 95% CI [8%, 66%]), with decomposition of the effect estimate indicating that PFOS exhibited the greatest positive weight to the overall mixture effect among other PFAS compounds (Supplemental Table 19). In the cytochrome p450 pathway, the largest increase associated with a simultaneous one quartile increase in all PFAS in the mixture was in 5(6)-EET (31% increase, 95% CI [4%, 64%]), with PFHxS contributing most to this increase. The largest increase in the lipoxygenase pathway was observed in 15-oxoETE (15% increase, 95% CI [2%, 29%]), with PFOS having the largest contribution. In the parent compounds, arachidonic acid had a 16% increase (95% CI [4%, 29%]), driven predominantly by PFOS. No significant decreases in bioactive lipids were observed. These effects are visualized in Figure 2 and reported in detail in Supplemental Table 19. Our vibration analyses assessing the robustness of our covariate selection and degree to which our models were affected by missingness in covariate data did not yield any effect estimates that were outside of the 95% CI of our main model (Supplemental Tables 20–21).
Figure 2
Figure 2. Forest plot of quantile g-computation effect estimates in the combined cohort analysis with IKIDS and CIOB cohorts (N = 343), showing of β estimates corresponding to percentage change in bioactive lipids associated with a simultaneous 1-quartile increase in all log-transformed PFAS. Model adjusted for maternal age, maternal education, prepregnancy BMI, parity, gestational age at visit, and cohort.
4. Discussion
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4.1. Summary of Findings across Statistical Approaches
In the present study, we estimated associations between PFAS and bioactive lipids in single pollutant and mixture models, utilizing cohort stratified analyses, combined cohort analyses, and meta-analyses. Combined cohort analyses and meta-analyses identified mostly positive associations of PFAS with parent fatty acid compounds and their secondary eicosanoid metabolites derived from the lipoxygenase, cytochrome p450, and cyclooxygenase pathways. Mixtures analysis using quantile g-computation revealed that the PFAS mixture exhibited positive associations with bioactive lipids across all three enzymatic pathways, and with the exception of 12(13)-DiHOME, at least one individual PFAS was associated with these bioactive lipids in the single pollutant models for either combined cohort analyses or meta-analyses. Largely consistent results between mixtures analysis and pairwise associations strengthen confidence in targeted bioactive lipids as potential mechanistic biomarkers of PFAS exposure, providing insight into addressing the health effects of PFAS as an entire class. Although our estimated associations are susceptible to false-positive associations, our findings allow for the prioritization of pairs of PFAS and bioactive lipids for future hypothesis testing and replication in independent samples.
4.2. Biological Context of Associations in Bioactive Lipid Enzymatic Pathways
The physiological implications of our findings vary by the metabolic pathway investigated. We observed the strongest positive effect between the PFAS mixture and cyclooxygenase-derived PGD2, which was consistent with individual PFAS compound analyses for PFDeA, PFOA, and PFOS in the CiOB and IKIDS meta-analyses. Systemic inflammation and oxidative stress are both antecedent physiological states conferring risk of adverse pregnancy outcomes such as spontaneous preterm birth and preeclampsia. (38,39) Cyclooxygenases have been implicated in promoting inflammation through the production of prostaglandins (40) and prostaglandin production is sensitive to reactive oxygen species and oxidative stress imbalances. (41) Existing literature indicates that cyclooxygenases are important for regulating reproductive health and fetal development; animal models have found that deficiencies in the genes encoding these enzymes cause altered implantation, increased mortality, and impaired organ development in offspring. (42) Animal studies indicate that disruptions in cyclooxygenase function and prostaglandin synthesis can also lead to altered neurodevelopment and behavior (43,44)─a previous study in an experimental rat model found that the PGD2 signaling pathway is involved in neuroinflammation, and induction of this pathway results in neurodegenerative pathologies. (45) Evidence from experimental mechanistic studies, combined with our findings that PFAS are linked to altered eicosanoid concentrations within the cyclooxygenase pathway, highlights this pathway as a potential mediator between PFAS and adverse pregnancy outcomes.
We observed that the PFAS mixture was associated with two cytochrome p450-derived eicosanoids: 12,13-DiHOME and 5(6)-EET. Cytochrome p450 enzymes have varied regulatory roles, including biosynthesis of endogenous hormones, detoxification of xenobiotics, and cellular metabolism. (19) In vitro experiments indicate that multiple PFAS compounds can directly interfere and inhibit cytochrome p450 activity. (18) 12,13-DiHOME has been classified as an oxylipin derived from linoleic acid, and is involved with inflammation, endocrine signaling, and adipogenesis. (46,47) In a previous case-control study by our team on the LIFECODES cohort using the same bioactive lipids panel measured (median 26 weeks’ gestation) in this present study, we reported that 12,13-DiHOME was associated with increased risk of spontaneous preterm birth (ncases = 31, ncontrols = 115). (15) Further, placental 5(6)-EET has been detected at higher levels in preeclamptic women compared to controls, linking 5(6)-EET to regulation pathways associated with preeclampsia. (48,49) Additionally, a study of 146 adult women reported that single nucleotide polymorphisms of cytochrome p450 genes amplified cancer risk attributable to PFAS exposures. (50) While bioactive lipids were not measured in that study, this is a consistent biological inference based on their findings of increased breast cancer risk in association with higher PFOS and PFOA and polymorphisms in cytochrome p450 genes. Based on these previous studies, PFAS potentially interferes directly with cytochrome p450 activity and subsequent eicosanoid metabolite concentrations, and there may be gene and environment interactions. To disentangle these different contributions of PFAS’ effects on lipid metabolism, future studies can consider integrating PFAS, eicosanoids, genotypes, and maternal health outcomes.
Lipoxygenases are calcium-dependent enzymes that catalyze the formation of hydroperoxides from polyunsaturated fatty acids and have been associated with several adverse health outcomes including asthma, skin disorders, and cancers. (51) We observed that the PFAS mixture was associated with higher levels of the lipoxygenase-derived eicosanoids 12-oxoETE, 15-oxoETE, and 5-HETE, which may be biomarkers for metabolic and cardiovascular disorders. 12-oxoETE has been linked to diabetic macular edema (52) and experimental models indicate that 15-oxoETE may influence atherosclerosis. (12) Additionally, our previous study in the LIFECODES cohort identified higher levels of 12-oxoETE and 5-HETE associated with spontaneous preterm birth. (15) Our present study findings showing that increases in 12-oxoETE and 15-oxoETE were associated with increased PFAS exposure further align with previous experimental evidence showing that PFAS can interfere with intracellular calcium gradients, influencing the catalytic activity of lipoxygenases. (20) Therefore, future studies should continue to investigate this pathway as a mechanistic link between PFAS exposure and adverse maternal and child health outcomes.
We observed differences in bioactive lipid compound distributions between individual cohorts, possibly driven by variation in genetic makeup of the populations caused by heterogeneous ethnic composition of the cohorts, (53) or differences in environmental exposures of the cohorts due to diet. (54) Among the parent polyunsaturated fatty acids, the PFAS mixture was associated with increased concentrations of arachidonic acid. These findings align with the positive signatures that we observed for the secondary eicosanoid metabolites described above derived from these parent compounds. Our reported findings can be partially contextualized with previous metabolomics studies linking PFAS-induced effects to lipid metabolism. One metabolomics study investigated a mixture of six common PFAS (PFOS, PFHxS, PFHpS, PFOA, PFNA, and PFDA) in children and adolescents (n = 137) based in Los Angeles, CA, and observed positive associations of the mixture with arachidonic acid and linoleic acid. (55) Another study of 267 maternal-newborn dyads in Atlanta, GA reported that maternal PFAS exposures were associated with newborn metabolomic signatures for bioactive lipid metabolism including leukotrienes, cytochrome p450 pathway, and linoleic acid. (14) Our findings align with existing evidence of the deleterious effects of PFAS exposure on pregnancy outcomes, as prenatal/perinatal PFAS exposure has been associated with multiple adverse birth outcomes including preterm birth, (7) miscarriage, and maternal depression. (9) Thus, our study underscores the importance of applying targeted metabolomics approaches to investigate the role of lipid metabolism as a potential intermediate mechanism of PFAS exposure on maternal and early child health outcomes.
4.3. Implications for Public Health Policy and Practice
In a 2022 report, the National Academies of Science, Engineering, and Mathematics systematically reviewed human health literature on PFAS and produced decision making guideline recommendations for PFAS testing and clinical follow-up, (8) including screening for hypertensive disorders and lipid panel measures for individuals with serum or plasma PFAS concentrations above 2 ng/mL. (56) Findings from our present study contextualize these clinical care approaches by providing more granular details on specific prenatal lipid metabolite and PFAS exposure associations. While the bioactive lipids measured in our study have not yet been tested as routine biomarkers in clinical care settings, our findings aid in advancing the foundation for future precision health considerations, as more advanced lipid biomarkers become scalable and tested for clinical utility.
4.4. Strengths and Limitations
Our study has notable strengths. First is the diversity of our study population, which included individuals from three distinct geographies, exhibiting heterogeneity across demographics, socioeconomic status, and PFAS exposures. Second, we will discuss our statistical approach. We performed combined cohort analysis utilizing two methods (linear mixed effects models and meta-analysis) and a mixtures analysis using quantile g-computation to assess cumulative associations with PFAS mixtures. The combination of methods applied and the consistency in results across methods strengthens the inference in identified associations. Third, our selection of outcomes was a targeted assay of bioactive lipids not previously tested for associations with PFAS. This targeted assay directly complements existing studies utilizing nontargeted metabolomics by deepening knowledge of specific lipid metabolite features to contextualize larger biological pathways and processes observed in past studies. Combined, this resulted in a robust investigation, with corroboration of our key findings both within our study and with previous literature.
Our study also has limitations to consider. First is the cross-sectional nature of data collection, as serum PFAS and plasma bioactive lipids were measured during the same visit. Single time point assessment is more susceptible to measurement error and reverse causation than longitudinal studies. Because of their long half-lives, PFAS measures may be relatively stable during pregnancy; however, researchers may consider longitudinal designs to more effectively assess spatiotemporal relationships and causal mechanisms driving the observed associations. Additionally, some confounding variables (e.g., maternal education and parity) were heterogeneous across cohorts. There are also potential unmeasured confounders that we did not model in the present study including dietary intake which is known to influence both PFAS and bioactive lipid concentrations; for example, fish and dairy consumption has been linked to increased PFAS levels in humans and is a source of fatty acids including arachidonic acid. (57−59) Future studies may benefit from considering this confounder via a comprehensive assessment of dietary intake. It is also possible that intermediate underlying metabolic factors such as liver disease or type 2 diabetes are affected by PFAS exposure, (60,61) which in turn could influence lipid metabolism. (62,63) Therefore, future studies may consider more complex causal pathways to disentangle the contribution of the underlying maternal metabolic factors in the relationship between PFAS and bioactive lipids. Regarding statistical approaches, we recognize that there are alternatives for analyzing chemical mixtures in health studies. Our study focused on cumulative PFAS mixture associations; however, future studies may consider high-order interactions across multiple exposure variables, latent clustering of correlated exposure variables, or dimension reduction through risk scores based on sources of exposures. We are likely underestimating the effect of PFAS as a whole class, as our study evaluated 12 serum PFAS compounds, and there are thousands of PFAS compounds that humans may be exposed to, especially given the presence of newer replacement and short-chained PFAS compounds. (64) Future studies should consider nontargeted exposomic approaches to contextualize how associations observed in our study might be influenced by the detection of these PFAS not measured in our study. (65) Despite this limitation, we highlight the importance of these 12 PFAS compounds being detected at relatively high rates in existing biomonitoring studies─and some are targets for near-term regulation, as the Environmental Protection Agency proposed establishing limits on 6 of the PFAS in our sample (PFOA, PFOS, PFNA, PFHxS, and PFBS) due to their high presence in drinking water in the US. (65) Limited sample size and detection rates of PFAS in the ECHO-PROTECT cohort reduced our ability to examine differences in associations between Hispanic and White women exposed to PFAS. Finally, we have documented associations between other classes of endocrine-disrupting chemicals (e.g., phthalates, phenols, and parabens) and prenatal bioactive in the LIFECODES cohort (N = 173). (66) It is possible that these chemicals are correlated with prenatal PFAS exposures, contributing to residual confounding and potential interactions and influencing the effects of PFAS on maternal bioactive lipid profiles. Therefore, future investigations should consider broader chemical mixture analyses with bioactive lipids and pregnancy outcomes.
Data Availability
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The R-script used for the present study is found in the Supporting Information. Select deidentified data from the ECHO Program are available through NICHD’s Data and Specimen Hub (DASH). Information on study data not available on DASH, such as some Indigenous data sets, can be found on the ECHO study DASH webpage.
Supporting Information
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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c00094.
Flow diagram of final sample selection across CiOB, IKIDS, and PROTECT cohorts; directed acyclic graph of the relationships between maternal per- and poly-fluoroalkyl substances and bioactive lipids; correlation matrices of bioactive lipids and high-detect PFAS in the study cohorts (Appendix A. Supplementary Figures S1–S3) (PDF)
PFAS Detection Rates and Distributions Across Cohorts; Bioactive lipids sampled from maternal plasma; Bioactive Lipid Distribution Across Cohorts; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the CiOB Cohort; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the IKIDS Cohort; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the ECHO-PROTECT Cohort; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for random intercept model across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for random intercept model across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for meta-analysis across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for meta-analysis across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for CiOB within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for CiOB within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for IKIDS within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for IKIDS within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for PROTECT within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for PROTECT within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates Corresponding to Percentage Change in Bioactive Lipids associated with a 1-Quartile increase in log-transformed PFAS relative to first quartile for random intercept model across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates Corresponding to Percentage Change in Bioactive Lipids associated with a 1-Quartile increase in log-transformed PFAS relative to first quartile for random intercept model across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; Quantile g-computation β Estimates Corresponding to Percentage Change in Bioactive Lipids as a Result of Simultaneous 1-Quartile Increase in All Log-Transformed PFAS, Model adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit, and Cohort; Comparison of Mixture Effects between Main Quantile G-Computation Results and Sensitivity Analysis Performing Stepwise Inclusion of Covariates; Comparison of Mixture Effects between Main Quantile G-Computation Results and Sensitivity Analysis Performing Multiple Imputation Supplementary data to this article can be found online (Appendix B. Supplementary Tables S1–S22) (XLSX)
ECHO OIF PFAS Lipids R Script (TXT)
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Author Information
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- Max T. Aung - Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United States;
https://orcid.org/0000-0001-5541-5447;
- Stephanie M. Eick - Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, Georgia 30322, United States;https://orcid.org/0000-0001-6695-3291
- Subramaniam Pennathur - Department of Internal Medicine-Nephrology, University of Michigan, Ann Arbor, Michigan 48824, United States; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan 48109, United States;https://orcid.org/0000-0003-3628-6883
- June-Soo Park - Environmental Chemistry Laboratory, Department of Toxic Substances Control, California Environmental Protection Agency, Berkeley, California 94710, United States;https://orcid.org/0009-0005-2177-4405
- Tracey J. Woodruff - Program on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, California 94143, United States;https://orcid.org/0000-0003-3622-1297
Funding acquisition (M.T.A., A.A., J.D.M., J.F.C., R.M.-F., T.J.W., S.L.S., A.N.A.); Conceptualization (M.T.A., H.S., A.N.A.); Data curation (E.D., S.N., M.W., S.M.E., A.C., S.P., L.Z., J.-S.P., D.W., S.S., A.A., S.D.G., T.J.W., R.M.-F., S.L.S., J.D.M., A.N.A., M.T.A., H.S.); Formal analysis (H.S.); Investigation (H.S., M.T.A.); Methodology (H.S., M.T.A., S.M.E.); Literature review (T.M., D.P., H.S., B.A.R., M.T.A.); Writing─original draft (H.S., M.T.A.); Writing─reviewing and editing (H.S., T.M., D.P., M.W., S.M.E., A.C., D.J.W., R.S.S., B.A.R., S.P., L.Z., D.W., J.-S.P., S.S., E.D., A.P., R.C.F., B.M., A.A., S.D.G., S.N., G.H.-M., C.V.-V., Z.R., J.F.C., E.Z., T.J.W., R.M.-F., S.L.S., J.D.M., A.N.A., M.T.A.).
Research reported in this publication was supported by the Environmental Influences on Child Health Outcomes (ECHO) Program, Office of the Director, National Institutes of Health (NIH), under award numbers U2COD023375 (Coordinating Center), U24OD023382 (Data Analysis Center), U24OD023319 with co-funding from the Office of Behavioral and Social Science Research (Pro-Core), U2COD023375 (Opportunities and Infrastructure Fund), UH3OD023251 (Alshawabkeh), UH3OD023272 (Schantz and Woodruff). This work was additionally supported by the Children’s Environmental Health and Disease Prevention Research Center (grant numbers ES022848 and RD83543401), the Molecular Phenotyping and Metabolomics Core, Michigan Nutrition and Obesity Center (5P30DK089503), US Environmental Protection Agency (grant number RD83543301), National Institute of Environmental Health Sciences (NIEHS; grant numbers P42ES017198, P50ES026049, P01ES022841, P30ES019776, P30ES030284, and P30ES007048). M.T.A. and S.M.E. were also supported in part by the JPB Foundation Environmental Health Fellows Program. The content of this study is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Acknowledgments
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The authors thank their Environmental Influences on Child Health Outcomes (ECHO) colleagues; the medical, nursing, and program staff; and the children and families participating in the ECHO cohorts. Furthermore, they acknowledge the contribution of the following ECHO program collaborators: ECHO Components─Coordinating Center: Duke Clinical Research Institute, Durham, North Carolina: Smith PB, Newby LK; Data Analysis Center: Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland: Jacobson LP; Research Triangle Institute, Durham, North Carolina: Catellier DJ; Person-Reported Outcomes Core: Northwestern University, Evanston, Illinois: Gershon R, Cella D.
References
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- 1Sunderland, E. M.; Hu, X. C.; Dassuncao, C.; Tokranov, A. K.; Wagner, C. C.; Allen, J. G. A Review of the Pathways of Human Exposure to Poly-and Perfluoroalkyl Substances (PFASs) and Present Understanding of Health Effects. J. Exposure Sci. Environ. Epidemiol. 2019, 29 (2), 131– 147, DOI: 10.1038/s41370-018-0094-1Google Scholar1https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXitlShu7jO&md5=1e8b317874a0ca47788c824343630818A review of the pathways of human exposure to poly- and perfluoroalkyl substances (PFASs) and present understanding of health effectsSunderland, Elsie M.; Hu, Xindi C.; Dassuncao, Clifton; Tokranov, Andrea K.; Wagner, Charlotte C.; Allen, Joseph G.Journal of Exposure Science & Environmental Epidemiology (2019), 29 (2), 131-147CODEN: JESEBS; ISSN:1559-0631. (Nature Research)A review. Here, we review present understanding of sources and trends in human exposure to poly- and perfluoroalkyl substances (PFASs) and epidemiol. evidence for impacts on cancer, immune function, metabolic outcomes, and neurodevelopment. More than 4000 PFASs have been manufd. by humans and hundreds have been detected in environmental samples. Direct exposures due to use in products can be quickly phased out by shifts in chem. prodn. but exposures driven by PFAS accumulation in the ocean and marine food chains and contamination of groundwater persist over long timescales. Serum concns. of legacy PFASs in humans are declining globally but total exposures to newer PFASs and precursor compds. have not been well characterized. Human exposures to legacy PFASs from seafood and drinking water are stable or increasing in many regions, suggesting obsd. declines reflect phase-outs in legacy PFAS use in consumer products. Many regions globally are continuing to discover PFAS contaminated sites from aq. film forming foam (AFFF) use, particularly next to airports and military bases. Exposures from food packaging and indoor environments are uncertain due to a rapidly changing chem. landscape where legacy PFASs have been replaced by diverse precursors and custom mols. that are difficult to detect. Multiple studies find significant assocns. between PFAS exposure and adverse immune outcomes in children. Dyslipidemia is the strongest metabolic outcome assocd. with PFAS exposure. Evidence for cancer is limited to manufg. locations with extremely high exposures and insufficient data are available to characterize impacts of PFAS exposures on neurodevelopment. Preliminary evidence suggests significant health effects assocd. with exposures to emerging PFASs. Lessons learned from legacy PFASs indicate that limited data should not be used as a justification to delay risk mitigation actions for replacement PFASs.
- 2Calafat, A. M.; Wong, L.-Y.; Kuklenyik, Z.; Reidy, J. A.; Needham, L. L. Polyfluoroalkyl Chemicals in the US Population: Data from the National Health and Nutrition Examination Survey (NHANES) 2003–2004 and Comparisons with NHANES 1999–2000. Environ. Health Perspect. 2007, 115 (11), 1596– 1602, DOI: 10.1289/ehp.10598Google Scholar2https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtl2ns7%252FK&md5=2f97144423bc80ba1be402249b11722dPolyfluoroalkyl chemicals in the U.S. population: data from the National Health and Nutrition Examination Survey 2003-2004 and comparisons with NHANES 1999-2000Calafat, Antonia M.; Wong, Lee-Yang; Kuklenyik, Zsuzsanna; Reidy, John A.; Needham, Larry L.Environmental Health Perspectives (2007), 115 (11), 1596-1602CODEN: EVHPAZ; ISSN:0091-6765. (U. S. Department of Health and Human Services, Public Health Services)Polyfluoroalkyl chems. (PFCs) have been used since the 1950s in numerous com. applications. Exposure of the general U.S. population to PFCs is widespread. Since 2002, the manufg. practices for PFCs in the United States have changed considerably. We aimed to assess exposure to perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and eight other PFCs in a representative 2003-2004 sample of the general U.S. population ≥ 12 years of age and to det. whether serum concns. have changed since the 1999-2000 National Health and Nutrition Examn. Survey (NHANES). By using automated solid-phase extn. coupled to isotope diln.-high-performance liq. chromatog.-tandem mass spectrometry, we analyzed 2094 serum samples collected from NHANES 2003-2004 participants. We detected PFOS, PFOA, PFHxS, and PFNA in >98% of the samples. Concns. differed by race/ethnicity and sex. Geometric mean concns. were significantly lower (approx. 32% for PFOS, 25% for PFOA, 10% for PFHxS) and higher (100%, PFNA) than the concns. reported in NHANES 1999-2000 (p < 0.001). In the general U.S. population in 2003-2004, PFOS, PFOA, PFHxS, and PFNA serum concns. were measurable in each demog. population group studied. Geometric mean concns. of PFOS, PFOA, and PFHxS in 2003-2004 were lower than in 1999-2000. The apparent redns. in concns. of PFOS, PFOA, and PFHxS most likely are related to discontinuation in 2002 of industrial prodn. by electrochem. fluorination of PFOS and related perfluorooctanesulfonyl fluoride compds.
- 3Chiu, W. A.; Lynch, M. T.; Lay, C. R.; Antezana, A.; Malek, P.; Sokolinski, S.; Rogers, R. D. Bayesian Estimation of Human Population Toxicokinetics of PFOA, PFOS, PFHxS, and PFNA from Studies of Contaminated Drinking Water. Environ. Health Perspect. 2022, 130 (12), 127001 DOI: 10.1289/EHP10103Google ScholarThere is no corresponding record for this reference.
- 4Fenton, S. E.; Ducatman, A.; Boobis, A.; DeWitt, J. C.; Lau, C.; Ng, C.; Smith, J. S.; Roberts, S. M. Per-and Polyfluoroalkyl Substance Toxicity and Human Health Review: Current State of Knowledge and Strategies for Informing Future Research. Environ. Toxicol. Chem. 2021, 40 (3), 606– 630, DOI: 10.1002/etc.4890Google Scholar4https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXisV2nurjE&md5=8d69f30fc5484e9a25bcca83eb7ad2e0Per- and Polyfluoroalkyl Substance Toxicity and Human Health Review: Current State of Knowledge and Strategies for Informing Future ResearchFenton, Suzanne E.; Ducatman, Alan; Boobis, Alan; DeWitt, Jamie C.; Lau, Christopher; Ng, Carla; Smith, James S.; Roberts, Stephen M.Environmental Toxicology and Chemistry (2021), 40 (3), 606-630CODEN: ETOCDK; ISSN:0730-7268. (Wiley-Blackwell)Reports of environmental and human health impacts of per- and polyfluoroalkyl substances (PFAS) have greatly increased in the peer-reviewed literature. The goals of the present review are to assess the state of the science regarding toxicol. effects of PFAS and to develop strategies for advancing knowledge on the health effects of this large family of chems. Currently, much of the toxicity data available for PFAS are for a handful of chems., primarily legacy PFAS such as perfluorooctanoic acid and perfluorooctane sulfonate. Epidemiol. studies have revealed assocns. between exposure to specific PFAS and a variety of health effects, including altered immune and thyroid function, liver disease, lipid and insulin dysregulation, kidney disease, adverse reproductive and developmental outcomes, and cancer. Concordance with exptl. animal data exists for many of these effects. However, information on modes of action and adverse outcome pathways must be expanded, and profound differences in PFAS toxicokinetic properties must be considered in understanding differences in responses between the sexes and among species and life stages. With many health effects noted for a relatively few example compds. and hundreds of other PFAS in commerce lacking toxicity data, more contemporary and high-throughput approaches such as read-across, mol. dynamics, and protein modeling are proposed to accelerate the development of toxicity information on emerging and legacy PFAS, individually and as mixts. In addn., an appropriate degree of precaution, given what is already known from the PFAS examples noted, may be needed to protect human health. Environ Toxicol Chem 2020;00:1-25. 2020 SETAC.
- 5Calafat, A. M.; Wong, L.-Y.; Kuklenyik, Z.; Reidy, J. A.; Needham, L. L. Polyfluoroalkyl Chemicals in the U.S. Population: Data from the National Health and Nutrition Examination Survey (NHANES) 2003–2004 and Comparisons with NHANES 1999–2000. Environ. Health Perspect. 2007, 115 (11), 1596– 1602, DOI: 10.1289/ehp.10598Google Scholar5https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtl2ns7%252FK&md5=2f97144423bc80ba1be402249b11722dPolyfluoroalkyl chemicals in the U.S. population: data from the National Health and Nutrition Examination Survey 2003-2004 and comparisons with NHANES 1999-2000Calafat, Antonia M.; Wong, Lee-Yang; Kuklenyik, Zsuzsanna; Reidy, John A.; Needham, Larry L.Environmental Health Perspectives (2007), 115 (11), 1596-1602CODEN: EVHPAZ; ISSN:0091-6765. (U. S. Department of Health and Human Services, Public Health Services)Polyfluoroalkyl chems. (PFCs) have been used since the 1950s in numerous com. applications. Exposure of the general U.S. population to PFCs is widespread. Since 2002, the manufg. practices for PFCs in the United States have changed considerably. We aimed to assess exposure to perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and eight other PFCs in a representative 2003-2004 sample of the general U.S. population ≥ 12 years of age and to det. whether serum concns. have changed since the 1999-2000 National Health and Nutrition Examn. Survey (NHANES). By using automated solid-phase extn. coupled to isotope diln.-high-performance liq. chromatog.-tandem mass spectrometry, we analyzed 2094 serum samples collected from NHANES 2003-2004 participants. We detected PFOS, PFOA, PFHxS, and PFNA in >98% of the samples. Concns. differed by race/ethnicity and sex. Geometric mean concns. were significantly lower (approx. 32% for PFOS, 25% for PFOA, 10% for PFHxS) and higher (100%, PFNA) than the concns. reported in NHANES 1999-2000 (p < 0.001). In the general U.S. population in 2003-2004, PFOS, PFOA, PFHxS, and PFNA serum concns. were measurable in each demog. population group studied. Geometric mean concns. of PFOS, PFOA, and PFHxS in 2003-2004 were lower than in 1999-2000. The apparent redns. in concns. of PFOS, PFOA, and PFHxS most likely are related to discontinuation in 2002 of industrial prodn. by electrochem. fluorination of PFOS and related perfluorooctanesulfonyl fluoride compds.
- 6Padula, A. M.; Ning, X.; Bakre, S.; Barrett, E. S.; Bastain, T.; Bennett, D. H.; Bloom, M. S.; Breton, C. V.; Dunlop, A. L.; Eick, S. M.; Ferrara, A.; Fleisch, A.; Geiger, S.; Goin, D. E.; Kannan, K.; Karagas, M. R.; Korrick, S.; Meeker, J. D.; Morello-Frosch, R.; O’Connor, T. G.; Oken, E.; Robinson, M.; Romano, M. E.; Schantz, S. L.; Schmidt, R. J.; Starling, A. P.; Zhu, Y.; Hamra, G. B.; Woodruff, T. J.; the program collaborators for Environmental influences on Child Health Outcomes Birth Outcomes in Relation to Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Stress in the Environmental Influences on Child Health Outcomes (ECHO) Program. Environ. Health Perspect. 2023, 131 (3), 037006 DOI: 10.1289/EHP10723Google ScholarThere is no corresponding record for this reference.
- 7Gao, X.; Ni, W.; Zhu, S.; Wu, Y.; Cui, Y.; Ma, J.; Liu, Y.; Qiao, J.; Ye, Y.; Yang, P.; Liu, C.; Zeng, F. Per- and Polyfluoroalkyl Substances Exposure during Pregnancy and Adverse Pregnancy and Birth Outcomes: A Systematic Review and Meta-Analysis. Environ. Res. 2021, 201, 111632 DOI: 10.1016/j.envres.2021.111632Google Scholar7https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhsF2mur3N&md5=3e02f9d52e4fb6342f5f2e188d24ead4Per- and polyfluoroalkyl substances exposure during pregnancy and adverse pregnancy and birth outcomes: A systematic review and meta-analysisGao, Xuping; Ni, Wanze; Zhu, Sui; Wu, Yanxin; Cui, Yunfeng; Ma, Junrong; Liu, Yanhua; Qiao, Jinlong; Ye, Yanbin; Yang, Pan; Liu, Chaoqun; Zeng, FangfangEnvironmental Research (2021), 201 (), 111632CODEN: ENVRAL; ISSN:0013-9351. (Elsevier Inc.)Exposure to per- and polyfluoroalkyl substances (PFAS) during pregnancy has been suggested to be assocd. with adverse pregnancy and birth outcomes; however, the findings have been inconsistent. We aimed to conduct a systematic review and meta-anal. to provide an overview of these assocns. The online databases PubMed, EMBASE and Web of Science were searched comprehensively for eligible studies from inception to Feb. 2021. Odds ratios (ORs) and 95% confidence intervals (CIs) were pooled using random- or fixed-effects models, and dose-response meta-analyses were also conducted when possible. A total of 29 studies (32,905 participants) were included. The pooled results demonstrated that perfluorooctane sulfonate (PFOS) exposure during pregnancy was linearly assocd. with increased preterm birth risk (pooled OR per 1-ng/mL increase: 1.01, 95% CIs: 1.00-1.02, P = 0.009) and perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) exposure showed inverted U-shaped assocns. with preterm birth risk (P values for the nonlinear trend: 0.025 and 0.030). Pos. assocns. were also obsd. for exposure to perfluorodecanoate (PFDA) and miscarriage (pooled OR per 1-ng/mL increase: 1.87, 95% CIs: 1.15-3.03) and PFOS and preeclampsia (pooled OR per 1-log increase: 1.27, 95% CIs: 1.06-1.51), whereas exposure to perfluoroundecanoate (PFUnDA) was inversely assocd. with preeclampsia risk (pooled OR per 1-log increase: 0.81, 95% CIs: 0.71-0.93). Based on individual evidence, detrimental effects were obsd. between PFDA exposure and small for gestational age and between PFOA and PFOS and intrauterine growth restriction. No significant assocns. were found between pregnancy PFAS exposure and other adverse pregnancy outcomes (i.e., gestational diabetes mellitus, pregnancy-induced hypertension, low birth wt., and large and small for gestational age). Our findings indicated that PFOS, PFOA and PFNA exposure during pregnancy might be assocd. with increased preterm birth risk and that PFAS exposure might be assocd. with the risk of miscarriage and preeclampsia. Due to the limited evidence obtained for most assocns., addnl. studies are required to confirm these findings.
- 8Ding, N.; Karvonen-Gutierrez, C. A.; Zota, A. R.; Mukherjee, B.; Harlow, S. D.; Park, S. K. The Role of Exposure to Per- and Polyfluoroalkyl Substances in Racial/Ethnic Disparities in Hypertension: Results from the Study of Women’s Health across the Nation. Environ. Res. 2023, 227, 115813 DOI: 10.1016/j.envres.2023.115813Google ScholarThere is no corresponding record for this reference.
- 9Aung, M. T.; Eick, S. M.; Padula, A. M.; Smith, S.; Park, J.-S.; DeMicco, E.; Woodruff, T. J.; Morello-Frosch, R. Maternal Per- and Poly-Fluoroalkyl Substances Exposures Associated with Higher Depressive Symptom Scores among Immigrant Women in the Chemicals in Our Bodies Cohort in San Francisco. Environ. Int. 2023, 172, 107758 DOI: 10.1016/j.envint.2023.107758Google Scholar9https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXhvVCqs78%253D&md5=ad2fcb8172e7bc57190fa3c36bb39904Maternal per- and poly-fluoroalkyl substances exposures associated with higher depressive symptom scores among immigrant women in the Chemicals in Our Bodies cohort in San FranciscoAung, Max T.; Eick, Stephanie M.; Padula, Amy M.; Smith, Sabrina; Park, June-Soo; DeMicco, Erin; Woodruff, Tracey J.; Morello-Frosch, RachelEnvironment International (2023), 172 (), 107758CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)Exposure to per- and poly-fluoroalkyl substances (PFAS) remains an important public health issue due to widespread detection and persistence in environmental media, slow metab. in humans, and influences on physiol. processes such as neurol. signaling. Maternal depression is highly prevalent during pregnancy and postpartum and is potentially sensitive to PFAS. The health risks assocd. with PFAS may be further amplified in historically marginalized communities, including immigrants. Evaluate maternal concns. of PFAS in assocn. with depression scores during pregnancy and whether effects differ between US born and immigrant women. Our study sample included 282 US born and 235 immigrant pregnant women enrolled in the Chems. in Our Bodies prospective birth cohort based in San Francisco, CA. We measured 12 PFAS in serum samples collected in the second trimester and depressive symptom scores were assessed using the Center for Epidemiol. Studies Depression Scale. Assocns. were estd. using linear regression, adjusting for maternal age, education, pre-pregnancy body mass index, and parity. Assocns. with a PFAS mixt. were estd. using quantile g-computation. In adjusted linear regression models, a twofold increase in two PFAS was assocd. with higher depression scores in the overall sample, and this assocn. persisted only among immigrant women β [95% confidence interval]: perfluorooctane sulfonic acid (2.7 [0.7-4.7]) and methyl-perfluorooctane sulfonamide acetic acid (2.9 [1.2-4.7]). Quantile g-computation indicated that simultaneously increasing all PFAS in the mixt. by one quartile was assocd. with increased depressive symptoms among immigrant women (mean change per quartile increase = 1.12 [0.002, 2.3]), and assocns. were stronger compared to US born women (mean change per quartile increase = 0.09 [-1.0, 0.8]). Findings provide new evidence that PFAS are assocd. with higher depression symptoms among immigrant women during pregnancy. Results can inform efforts to address environmental factors that may affect depression among US immigrants.
- 10Yuan, Z.-X.; Majchrzak-Hong, S.; Keyes, G. S.; Iadarola, M. J.; Mannes, A. J.; Ramsden, C. E. Lipidomic Profiling of Targeted Oxylipins with Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry. Anal. Bioanal. Chem. 2018, 410 (23), 6009– 6029, DOI: 10.1007/s00216-018-1222-4Google Scholar10https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhsVGhtLzI&md5=0ff3e0bdc0752714db02a8af9ce08b24Lipidomic profiling of targeted oxylipins with ultra-performance liquid chromatography-tandem mass spectrometryYuan, Zhi-Xin; Majchrzak-Hong, Sharon; Keyes, Gregory S.; Iadarola, Michael J.; Mannes, Andrew J.; Ramsden, Christopher E.Analytical and Bioanalytical Chemistry (2018), 410 (23), 6009-6029CODEN: ABCNBP; ISSN:1618-2642. (Springer)Oxylipins are bioactive mediators that play diverse roles in (patho)physiol. The authors developed a sensitive and selective ultra-performance liq. chromatog.-tandem mass spectrometry (UPLC-MS/MS) method for the simultaneous profiling of 57 targeted oxylipins derived from five major n-6 and n-3 polyunsatd. fatty acids (PUFAs) that serve as oxylipin precursors, including linoleic (LA), arachidonic (AA), alpha-linolenic (ALA), eicosapentaenoic (EPA), and docosahexaenoic (DHA) acids. The targeted oxylipin panel provides broad coverage of lipid mediators and pathway markers generated from cyclooxygenases, lipoxygenases, cytochrome P 450 epoxygenases/hydroxylases, and non-enzymic oxidn. pathways. The method is based on combination of protein pptn. and solid-phase extn. (SPE) for sample prepn., followed by UPLC-MS/MS. This is the first methodol. to incorporate four hydroxy-epoxy-octadecenoic acids and four keto-epoxy-octadecenoic acids into an oxylipin profiling network. The novel method achieves excellent resoln. and allows in-depth anal. of isomeric and isobaric species of oxylipin exts. in biol. samples. The method was quant. characterized in human plasma with good linearity (R = 0.990-0.999), acceptable reproducibility (relative std. deviation < 20% for the majority of analytes), accuracy (67.8 to 129.3%) for all analytes, and recovery (66.8-121.2%) for all analytes except 5,6-EET. Ion enhancement effects for 28% of the analytes in tested concns. were obsd. in plasma, but were reproducible with relative std. deviation < 17.2%. Basal levels of targeted oxylipins detd. in plasma and serum are in agreement with those previously reported in literature. The method has been successfully applied in clin. and preclin. studies.
- 11Eek, P.; Järving, R.; Järving, I.; Gilbert, N. C.; Newcomer, M. E.; Samel, N. Structure of a Calcium-Dependent 11R-Lipoxygenase Suggests a Mechanism for Ca2+ Regulation. J. Biol. Chem. 2012, 287 (26), 22377– 22386, DOI: 10.1074/jbc.M112.343285Google Scholar11https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XptVWqsro%253D&md5=64649cbb4f2c28aa75b9830c40c810cdStructure of a Calcium-dependent 11R-Lipoxygenase Suggests a Mechanism for Ca2+ RegulationEek, Priit; Jaerving, Reet; Jaerving, Ivar; Gilbert, Nathaniel C.; Newcomer, Marcia E.; Samel, NigulasJournal of Biological Chemistry (2012), 287 (26), 22377-22386CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Lipoxygenases (LOXs) are a key part of several signaling pathways that lead to inflammation and cancer. Yet, the mechanisms of substrate binding and allosteric regulation by the various LOX isoforms remain speculative. Here we report the 2.47-Å resoln. crystal structure of the arachidonate 11R-LOX from Gersemia fruticosa, which sheds new light on the mechanism of LOX catalysis. Our crystallog. and mutational studies suggest that the aliph. tail of the fatty acid is bound in a hydrophobic pocket with two potential entrances. We speculate that LOXs share a common T-shaped substrate channel architecture that gives rise to the varying positional specificities. A general allosteric mechanism is proposed for transmitting the activity-inducing effect of calcium binding from the membrane-targeting PLAT (polycystin-1/lipoxygenase/α-toxin) domain to the active site via a conserved π-cation bridge.
- 12Ma, G.; Pan, B.; Ren, S.; Guo, C.; Guo, Y.; Wei, L.; Zheng, L.; Chen, B. 15-Oxoeicosatetraenoic Acid Mediates Monocyte Adhesion to Endothelial Cell. Lipids Health Dis. 2017, 16 (1), 137 DOI: 10.1186/s12944-017-0518-2Google ScholarThere is no corresponding record for this reference.
- 13Patel, N. S. A.; Cuzzocrea, S.; Chatterjee, P. K.; Di Paola, R.; Sautebin, L.; Britti, D.; Thiemermann, C. Reduction of Renal Ischemia-Reperfusion Injury in 5-Lipoxygenase Knockout Mice and by the 5-Lipoxygenase Inhibitor Zileuton. Mol. Pharmacol. 2004, 66 (2), 220– 227, DOI: 10.1124/mol.66.2.220Google ScholarThere is no corresponding record for this reference.
- 14Taibl, K. R.; Dunlop, A. L.; Barr, D. B.; Li, Y.-Y.; Eick, S. M.; Kannan, K.; Ryan, P. B.; Schroder, M.; Rushing, B.; Fennell, T.; Chang, C.-J.; Tan, Y.; Marsit, C. J.; Jones, D. P.; Liang, D. Newborn Metabolomic Signatures of Maternal Per- and Polyfluoroalkyl Substance Exposure and Reduced Length of Gestation. Nat. Commun. 2023, 14, 3120 DOI: 10.1038/s41467-023-38710-3Google ScholarThere is no corresponding record for this reference.
- 15Aung, M. T.; Yu, Y.; Ferguson, K. K.; Cantonwine, D. E.; Zeng, L.; McElrath, T. F.; Pennathur, S.; Mukherjee, B.; Meeker, J. D. Prediction and Associations of Preterm Birth and Its Subtypes with Eicosanoid Enzymatic Pathways and Inflammatory Markers. Sci. Rep. 2019, 9 (1), 17049 DOI: 10.1038/s41598-019-53448-zGoogle ScholarThere is no corresponding record for this reference.
- 16Welch, B. M.; Keil, A. P.; van ‘t Erve, T. J.; Deterding, L. J.; Williams, J. G.; Lih, F. B.; Cantonwine, D. E.; McElrath, T. F.; Ferguson, K. K. Longitudinal Profiles of Plasma Eicosanoids during Pregnancy and Size for Gestational Age at Delivery: A Nested Case-Control Study. PLoS Med. 2020, 17 (8), e1003271 DOI: 10.1371/journal.pmed.1003271Google ScholarThere is no corresponding record for this reference.
- 17Guo, P.; Furnary, T.; Vasiliou, V.; Yan, Q.; Nyhan, K.; Jones, D. P.; Johnson, C. H.; Liew, Z. Non-Targeted Metabolomics and Associations with per- and Polyfluoroalkyl Substances (PFAS) Exposure in Humans: A Scoping Review. Environ. Int. 2022, 162, 107159 DOI: 10.1016/j.envint.2022.107159Google Scholar17https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XovF2ksLw%253D&md5=a39339bcf099e1441056110e3e896e5eNon-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping reviewGuo, Pengfei; Furnary, Tristan; Vasiliou, Vasilis; Yan, Qi; Nyhan, Kate; Jones, Dean P.; Johnson, Caroline H.; Liew, ZeyanEnvironment International (2022), 162 (), 107159CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)A review. To summarize the application of non-targeted metabolomics in epidemiol. studies that assessed metabolite and metabolic pathway alterations assocd. with per- and polyfluoroalkyl substances (PFAS) exposure. Eleven human studies published before Apr. 1st, 2021 were identified through database searches (PubMed, Dimensions, Web of Science Core Collection, Embase, Scopus), and citation chaining (Citationchaser). The sample sizes of these studies ranged from 40 to 965, involving children and adolescents (n = 3), non-pregnant adults (n = 5), or pregnant women (n = 3). High-resoln. liq. chromatog.-mass spectrometry was the primary anal. platform to measure both PFAS and metabolome. PFAS were measured in either plasma (n = 6) or serum (n = 5), while metabolomic profiles were assessed using plasma (n = 6), serum (n = 4), or urine (n = 1). Four types of PFAS (perfluorooctane sulfonate (n = 11), perfluorooctanoic acid (n = 10), perfluorohexane sulfonate (n = 9), perfluorononanoic acid (n = 5)) and PFAS mixts. (n = 7) were the most studied. We found that alterations to tryptophan metab. and the urea cycle were most reported PFAS-assocd. metabolomic signatures. Numerous lipid metabolites were also suggested to be assocd. with PFAS exposure, esp. key metabolites in glycerophospholipid metab. which is crit. for biol. membrane functions, and fatty acids and carnitines which are relevant to the energy supply pathway of fatty acid oxidn. Other important metabolome changes reported included the tricarboxylic acid (TCA) cycle regarding energy generation, and purine and pyrimidine metab. in cellular energy systems. There is growing interest in using non-targeted metabolomics to study the human physiol. changes assocd. with PFAS exposure. Multiple PFAS were reported to be assocd. with alterations in amino acid and lipid metab., but these results are driven by one predominant type of pathway anal. thus require further confirmation. Standardizing research methods and reporting are recommended to facilitate result comparison. Future studies should consider potential differences in study methodol., use of prospective design, and influence from confounding bias and measurement errors.
- 18Hvizdak, M.; Kandel, S. E.; Work, H. M.; Gracey, E. G.; McCullough, R. L.; Lampe, J. N. Per- and Polyfluoroalkyl Substances (PFAS) Inhibit Cytochrome P450 CYP3A7 through Direct Coordination to the Heme Iron and Water Displacement. J. Inorg. Biochem. 2023, 240, 112120 DOI: 10.1016/j.jinorgbio.2023.112120Google ScholarThere is no corresponding record for this reference.
- 19Zanger, U. M.; Schwab, M. Cytochrome P450 Enzymes in Drug Metabolism: Regulation of Gene Expression, Enzyme Activities, and Impact of Genetic Variation. Pharm. Ther. 2013, 138 (1), 103– 141, DOI: 10.1016/j.pharmthera.2012.12.007Google ScholarThere is no corresponding record for this reference.
- 20Cao, Y.; Ng, C. Absorption, Distribution, and Toxicity of per- and Polyfluoroalkyl Substances (PFAS) in the Brain: A Review. Environ. Sci. Process Impacts 2021, 23 (11), 1623– 1640, DOI: 10.1039/D1EM00228GGoogle Scholar20https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhvF2isrvF&md5=10fe32a2c1557e7b0a93d92c02183219Absorption, distribution, and toxicity of per- and polyfluoroalkyl substances (PFAS) in the brain: a reviewCao, Yuexin; Ng, CarlaEnvironmental Science: Processes & Impacts (2021), 23 (11), 1623-1640CODEN: ESPICZ; ISSN:2050-7895. (Royal Society of Chemistry)A review. Per- and polyfluoroalkyl substances (PFAS) are a class of synthetic chems. colloquially known as "forever chems." because of their high persistence. PFAS have been detected in the blood, liver, kidney, heart, muscle and brain of various species. Although brain is not a dominant tissue for PFAS accumulation compared to blood and liver, adverse effects of PFAS on brain functions have been identified. Here, we review studies related to the absorption, accumulation, distribution and toxicity of PFAS in the brain. We summarize evidence on two potential mechanisms of PFAS entering the brain: initiating blood-brain barrier (BBB) disassembly through disrupting tight junctions and relying on transporters located at the BBB. PFAS with diverse structures and properties enter and accumulate in the brain with varying efficiencies. Compared to long-chain PFAS, short-chain PFAS may not cross cerebral barriers effectively. According to biomonitoring studies and PFAS exposure expts., PFAS can accumulate in the brain of humans and wildlife species. With respect to the distribution of PFAS in specific brain regions, the brain stem, hippocampus, hypothalamus, pons/medulla and thalamus are dominant for PFAS accumulation. The accumulation and distribution of PFAS in the brain may lead to toxic effects in the central nervous system (CNS), including PFAS-induced behavioral and cognitive disorders. The specific mechanisms underlying such PFAS-induced neurotoxicity remain to be explored, but two major potential mechanisms based on current understanding are PFAS effects on calcium homeostasis and neurotransmitter alterations in neurons. Based on the information available about PFAS uptake, accumulation, distribution and impacts on the brain, PFAS have the potential to enter and accumulate in the brain at varying levels. The balance of existing studies shows there is some indication of risk in animals, while the human evidence is mixed and warrants further scrutiny.
- 21Knapp, E. A.; Kress, A. M.; Parker, C. B.; Page, G. P.; McArthur, K.; Gachigi, K. K.; Alshawabkeh, A. N.; Aschner, J. L.; Bastain, T. M.; Breton, C. V.; Bendixsen, C. G.; Brennan, P. A.; Bush, N. R.; Buss, C.; Camargo, Carlos A., Jr.; Catellier, D.; Cordero, J. F.; Croen, L.; Dabelea, D.; Deoni, S.; D’Sa, V.; Duarte, C. S.; Dunlop, A. L.; Elliott, A. J.; Farzan, S. F.; Ferrara, A.; Ganiban, J. M.; Gern, J. E.; Giardino, A. P.; Towe-Goodman, N. R.; Gold, D. R.; Habre, R.; Hamra, G. B.; Hartert, T.; Herbstman, J. B.; Hertz-Picciotto, I.; Hipwell, A. E.; Karagas, M. R.; Karr, C. J.; Keenan, K.; Kerver, J. M.; Koinis-Mitchell, D.; Lau, B.; Lester, B. M.; Leve, L. D.; Leventhal, B.; LeWinn, K. Z.; Lewis, J.; Litonjua, A. A.; Lyall, K.; Madan, J. C.; McEvoy, C. T.; McGrath, M.; Meeker, J. D.; Miller, R. L.; Morello-Frosch, R.; Neiderhiser, J. M.; O’Connor, T. G.; Oken, E.; O’Shea, M.; Paneth, N.; Porucznik, C. A.; Sathyanarayana, S.; Schantz, S. L.; Spindel, E. R.; Stanford, J. B.; Stroustrup, A.; Teitelbaum, S. L.; Trasande, L.; Volk, H.; Wadhwa, P. D.; Weiss, S. T.; Woodruff, T. J.; Wright, R. J.; Zhao, Q.; Jacobson, L. P.; Influences on Child Health Outcomes, on behalf of program collaborators for Environmental The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort. Am. J. Epidemiol. 2023, 192 (8), 1249– 1263, DOI: 10.1093/aje/kwad071Google ScholarThere is no corresponding record for this reference.
- 22Eick, S. M.; Enright, E. A.; Geiger, S. D.; Dzwilewski, K. L. C.; DeMicco, E.; Smith, S.; Park, J.-S.; Aguiar, A.; Woodruff, T. J.; Morello-Frosch, R.; Schantz, S. L. Associations of Maternal Stress, Prenatal Exposure to Per- and Polyfluoroalkyl Substances (PFAS), and Demographic Risk Factors with Birth Outcomes and Offspring Neurodevelopment: An Overview of the ECHO.CA.IL Prospective Birth Cohorts. Int. J. Environ. Res. Public Health 2021, 18 (2), 742, DOI: 10.3390/ijerph18020742Google ScholarThere is no corresponding record for this reference.
- 23Ferguson, K. K.; Rosario, Z.; McElrath, T. F.; Vélez Vega, C.; Cordero, J. F.; Alshawabkeh, A.; Meeker, J. D. Demographic Risk Factors for Adverse Birth Outcomes in Puerto Rico in the PROTECT Cohort. PLoS One 2019, 14 (6), e0217770 DOI: 10.1371/journal.pone.0217770Google ScholarThere is no corresponding record for this reference.
- 24Eick, S. M.; Geiger, S. D.; Alshawabkeh, A.; Aung, M.; Barrett, E.; Bush, N. R.; Cordero, J. F.; Ferguson, K. K.; Meeker, J. D.; Milne, G. L.; Nguyen, R. H. N.; Padula, A. M.; Sathyanarayana, S.; Welch, B. M.; Schantz, S. L.; Woodruff, T. J.; Morello-Frosch, R. Associations between Social, Biologic, and Behavioral Factors and Biomarkers of Oxidative Stress during Pregnancy: Findings from Four ECHO Cohorts. Sci. Total Environ. 2022, 835, 155596 DOI: 10.1016/j.scitotenv.2022.155596Google ScholarThere is no corresponding record for this reference.
- 25Eick, S. M.; Geiger, S. D.; Alshawabkeh, A.; Aung, M.; Barrett, E. S.; Bush, N.; Carroll, K. N.; Cordero, J. F.; Goin, D. E.; Ferguson, K. K.; Kahn, L. G.; Liang, D.; Meeker, J. D.; Milne, G. L.; Nguyen, R. H. N.; Padula, A. M.; Sathyanarayana, S.; Taibl, K. R.; Schantz, S. L.; Woodruff, T. J.; Morello-Frosch, R. Urinary Oxidative Stress Biomarkers Are Associated with Preterm Birth: An Environmental Influences on Child Health Outcomes Program Study. Am. J. Obstet. Gynecol. 2023, 228 (5), 576.e1– 576.e22, DOI: 10.1016/j.ajog.2022.11.1282Google ScholarThere is no corresponding record for this reference.
- 26Morello-Frosch, R.; Cushing, L. J.; Jesdale, B. M.; Schwartz, J. M.; Guo, W.; Guo, T.; Wang, M.; Harwani, S.; Petropoulou, S.-S. E.; Duong, W.; Park, J.-S.; Petreas, M.; Gajek, R.; Alvaran, J.; She, J.; Dobraca, D.; Das, R.; Woodruff, T. J. Environmental Chemicals in an Urban Population of Pregnant Women and Their Newborns from San Francisco. Environ. Sci. Technol. 2016, 50 (22), 12464– 12472, DOI: 10.1021/acs.est.6b03492Google Scholar26https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhs1SmtLjI&md5=59075dbb94c6c595a6145ca685274e8aEnvironmental Chemicals in an Urban Population of Pregnant Women and Their Newborns from San FranciscoMorello-Frosch, Rachel; Cushing, Lara J.; Jesdale, Bill M.; Schwartz, Jackie M.; Guo, Weihong; Guo, Tan; Wang, Miaomiao; Harwani, Suhash; Petropoulou, Syrago-Styliani E.; Duong, Wendy; Park, June-Soo; Petreas, Myrto; Gajek, Ryszard; Alvaran, Josephine; She, Jianwen; Dobraca, Dina; Das, Rupali; Woodruff, Tracey J.Environmental Science & Technology (2016), 50 (22), 12464-12472CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)In-utero exposure to environmental pollutants may increase the risk of adverse health effects. Concns. of 59 potentially harmful chems. (polychlorinated biphenyls [PCB], organochlorine pesticides [OCP], polybrominated di-Ph ethers [PBDE], hydroxylated PBDE [OH-PBDE], perfluorinated compds. [PFC]) were measured in 77 maternal and 65 paired umbilical cord blood serum samples collected in San Francisco, California, 2010-2011, and whole blood metal concns. Consistent with previous studies, evidence was found that Hg and lower-brominated PBDE concns. were often higher in umbilical cord blood or serum vs. maternal samples (median cord:maternal ratio >1); for most PFC and Pb, cord blood or serum concns. were generally less than or equal to their maternal pair (median cord:maternal ratio ≤1). Results showed evidence that several PCB and OCP also often had higher concns. in cord vs. maternal serum (median cord:maternal ratio >1) when concns. were assessed on a lipid-adjusted basis. Results suggested that for many chems., fetuses may experience higher exposure than their mothers, and highlighted the need to characterize potential health risks and inform policies to reduce exposure sources.
- 27Hornung, R. W.; Reed, L. D. Estimation of Average Concentration in the Presence of Nondetectable Values. Appl. Occup. Environ. Hyg. 1990, 5 (1), 46– 51, DOI: 10.1080/1047322X.1990.10389587Google Scholar27https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXltVyitr4%253D&md5=b254033f29a8e9b299fef9c92200cd06Estimation of average concentration in the presence of nondetectable valuesHornung, Richard W.; Reed, Laurence D.Applied Occupational and Environmental Hygiene (1990), 5 (1), 46-51CODEN: AOEHE9; ISSN:1047-322X.To est. the av. concn. of a particular contaminant during some period of time, a certain proportion of the collected samples is often reported to be below the limit of detection. The statistical terminol. for these results is censored data, i.e., nonzero values which cannot be measured but are known to be below some threshold. Samples taken over time are assumed to follow a lognormal distribution. Given this assumption, several techniques are presented for estn. of the av. concn. from data contg. nondetectable values. The techniques proposed include three methods of estn. with a left-censored lognormal distribution: a max. likelihood statistical method and two methods involving the limit of detection. Each method is evaluated using computer simulation with respect to the bias assocd. with estn. of the mean and std. deviation. The max. likelihood method produced unbiased ests. of both the mean and std. deviation under a variety of conditions. However, this method is somewhat complex and involves laborious calcns. and use of tables. Two simpler alternatives involve the substitution of L/2 and a new proposal of L/√‾2 for each nondetectable value, where L = the limit of detection. The new method provided more accurate estn. of the mean and std. deviation than the L/2 method when the data are not highly skewed. The L/2 method should be used when the data are highly skewed (geometric std. deviation ≥3.0 or greater).
- 28Afshinnia, F.; Zeng, L.; Byun, J.; Wernisch, S.; Deo, R.; Chen, J.; Hamm, L.; Miller, E. R.; Rhee, E. P.; Fischer, M. J.; Sharma, K.; Feldman, H. I.; Michailidis, G.; Pennathur, S.; CRIC Study Investigators Elevated Lipoxygenase and Cytochrome P450 Products Predict Progression of Chronic Kidney Disease. Nephrol., Dial., Transplant. 2020, 35 (2), 303– 312, DOI: 10.1093/ndt/gfy232Google ScholarThere is no corresponding record for this reference.
- 29Keil, A. P.; Buckley, J. P.; O’Brien, K. M.; Ferguson, K. K.; Zhao, S.; White, A. J. A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures. Environ. Health Perspect. 2020, 128 (4), 047004 DOI: 10.1289/EHP5838Google Scholar29https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38zhslKqtw%253D%253D&md5=c667f3704295f9d3d52e4de297c594deA Quantile-Based g-Computation Approach to Addressing the Effects of Exposure MixturesKeil Alexander P; Keil Alexander P; O'Brien Katie M; Ferguson Kelly K; White Alexandra J; Buckley Jessie P; Buckley Jessie P; Zhao ShanshanEnvironmental health perspectives (2020), 128 (4), 47004 ISSN:.BACKGROUND: Exposure mixtures frequently occur in data across many domains, particularly in the fields of environmental and nutritional epidemiology. Various strategies have arisen to answer questions about exposure mixtures, including methods such as weighted quantile sum (WQS) regression that estimate a joint effect of the mixture components. OBJECTIVES: We demonstrate a new approach to estimating the joint effects of a mixture: quantile g-computation. This approach combines the inferential simplicity of WQS regression with the flexibility of g-computation, a method of causal effect estimation. We use simulations to examine whether quantile g-computation and WQS regression can accurately and precisely estimate the effects of mixtures in a variety of common scenarios. METHODS: We examine the bias, confidence interval (CI) coverage, and bias-variance tradeoff of quantile g-computation and WQS regression and how these quantities are impacted by the presence of noncausal exposures, exposure correlation, unmeasured confounding, and nonlinearity of exposure effects. RESULTS: Quantile g-computation, unlike WQS regression, allows inference on mixture effects that is unbiased with appropriate CI coverage at sample sizes typically encountered in epidemiologic studies and when the assumptions of WQS regression are not met. Further, WQS regression can magnify bias from unmeasured confounding that might occur if important components of the mixture are omitted from the analysis. DISCUSSION: Unlike inferential approaches that examine the effects of individual exposures while holding other exposures constant, methods like quantile g-computation that can estimate the effect of a mixture are essential for understanding the effects of potential public health actions that act on exposure sources. Our approach may serve to help bridge gaps between epidemiologic analysis and interventions such as regulations on industrial emissions or mining processes, dietary changes, or consumer behavioral changes that act on multiple exposures simultaneously. https://doi.org/10.1289/EHP5838.
- 30Taibl, K. R.; Schantz, S.; Aung, M. T.; Padula, A.; Geiger, S.; Smith, S.; Park, J.-S.; Milne, G. L.; Robinson, J. F.; Woodruff, T. J.; Morello-Frosch, R.; Eick, S. M. Associations of Per- and Polyfluoroalkyl Substances (PFAS) and Their Mixture with Oxidative Stress Biomarkers during Pregnancy. Environ. Int. 2022, 169, 107541 DOI: 10.1016/j.envint.2022.107541Google Scholar30https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38Xis1GnurnN&md5=427961af0e3b2575dcc83c2cc8ec8b8dAssociations of per- and polyfluoroalkyl substances (PFAS) and their mixture with oxidative stress biomarkers during pregnancyTaibl, Kaitlin R.; Schantz, Susan; Aung, Max T.; Padula, Amy; Geiger, Sarah; Smith, Sabrina; Park, June-Soo; Milne, Ginger L.; Robinson, Joshua F.; Woodruff, Tracey J.; Morello-Frosch, Rachel; Eick, Stephanie M.Environment International (2022), 169 (), 107541CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)Oxidative stress from excess reactive oxygen species (ROS) is a hypothesized contributor to preterm birth. Per- and polyfluoroalkyl substances (PFAS) exposure is reported to generate ROS in lab. settings, and is linked to adverse birth outcomes globally. However, to our knowledge, the relationship between PFAS and oxidative stress has not been examd. in the context of human pregnancy. To investigate the assocns. between prenatal PFAS exposure and oxidative stress biomarkers among pregnant people. Our analytic sample included 428 participants enrolled in the Illinois Kids Development Study and Chems. In Our Bodies prospective birth cohorts between 2014 and 2019. Twelve PFAS were measured in second trimester serum. We focused on seven PFAS that were detected in >65 % of participants. Urinary levels of 8-isoprostane-prostaglandin-F2α, prostaglandin-F2α, 2,3-dinor-8-iso-PGF2α, and 2,3-dinor-5,6-dihydro-8-iso-PGF2α were measured in the second and third trimesters as biomarkers of oxidative stress. We fit linear mixed-effects models to est. individual assocns. between PFAS and oxidative stress biomarkers. We used quantile g-computation and Bayesian kernel machine regression (BKMR) to assess assocns. between the PFAS mixt. and averaged oxidative stress biomarkers. Linear mixed-effects models showed that an interquartile range increase in perfluorooctane sulfonic acid (PFOS) was assocd. with an increase in 8-isoprostane-prostaglandin-F2α (β = 0.10, 95 % confidence interval = 0, 0.20). In both quantile g-computation and BKMR, and across all oxidative stress biomarkers, PFOS contributed the most to the overall mixt. effect. The six remaining PFAS were not significantly assocd. with changes in oxidative stress biomarkers. Our study is the first to investigate the relationship between PFAS exposure and biomarkers of oxidative stress during human pregnancy. We found that PFOS was assocd. with elevated levels of oxidative stress, which is consistent with prior work in animal models and cell lines. Future research is needed to understand how prenatal PFAS exposure and maternal oxidative stress may affect fetal development.
- 31Braveman, P. A.; Cubbin, C.; Egerter, S.; Chideya, S.; Marchi, K. S.; Metzler, M.; Posner, S. Socioeconomic Status in Health ResearchOne Size Does Not Fit All. JAMA 2005, 294 (22), 2879– 2888, DOI: 10.1001/jama.294.22.2879Google ScholarThere is no corresponding record for this reference.
- 32McAdam, J.; Bell, E. M. Determinants of Maternal and Neonatal PFAS Concentrations: A Review. Environ. Health 2023, 22 (1), 41 DOI: 10.1186/s12940-023-00992-xGoogle Scholar32https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXpsl2it7k%253D&md5=226c3078c19e0c4f720233db4d2da5d1Determinants of maternal and neonatal PFAS concentrations: a reviewMcAdam, Jordan; Bell, Erin M.Environmental Health (London, United Kingdom) (2023), 22 (1), 41CODEN: EHAGAB; ISSN:1476-069X. (BioMed Central Ltd.)A review. Per- and polyfluoroalkyl substances (PFAS) are used for their properties such as stain and water resistance. The substances have been assocd. with adverse health outcomes in both pregnant mothers and infants, including pre-eclampsia and low birthweight. A growing body of research suggests that PFAS are transferred from mother to fetus through the placenta, leading to in utero exposure. A systematic review was performed using the PubMed database to search for studies evaluating determinants of PFAS concns. in blood matrixes of pregnant mothers and neonates shortly after birth. Studies were included in this review if an observational study design was utilized, exposure to at least one PFAS analyte was measured, PFAS were measured in maternal or neonatal matrixes, at least one determinant of PFAS concns. was assessed, and results such as beta ests. were provided. We identified 35 studies for inclusion in the review and evaluated the PFAS and determinant relationships among the factors collected in these studies. Parity, breastfeeding history, maternal race and country of origin, and household income had the strongest and most consistent evidence to support their roles as determinants of certain PFAS concns. in pregnant mothers. Reported study findings on smoking status, alc. consumption, and pre-pregnancy body mass index (BMI) suggest that these factors are not important determinants of PFAS concns. in pregnant mothers or neonates. Further study into informative factors such as consumer product use, detailed dietary information, and consumed water sources as potential determinants of maternal or neonatal PFAS concns. is needed. Research on determinants of maternal or neonatal PFAS concns. is crit. to est. past PFAS exposure, build improved exposure models, and further our understanding on dose-response relationships, which can influence epidemiol. studies and risk assessment evaluations. Given the potential for adverse outcomes in pregnant mothers and neonates exposed to PFAS, it is important to identify and understand determinants of maternal and neonatal PFAS concns. to better implement public health interventions in these populations.
- 33Stephens, C. R.; Easton, J. F.; Robles-Cabrera, A.; Fossion, R.; de la Cruz, L.; Martínez-Tapia, R.; Barajas-Martínez, A.; Hernández-Chávez, A.; López-Rivera, J. A.; Rivera, A. L. The Impact of Education and Age on Metabolic Disorders. Front. Public Health 2020, 8, 180, DOI: 10.3389/fpubh.2020.00180Google ScholarThere is no corresponding record for this reference.
- 34Storey, J. D.; Bass, A. J.; Dabney, A.; Robinson, D.; Warnes, G. Qvalue: Q-Value Estimation for False Discovery Rate Control, 2023. http://github.com/jdstorey/qvalue.Google ScholarThere is no corresponding record for this reference.
- 35Willer, C. J.; Li, Y.; Abecasis, G. R. METAL: Fast and Efficient Meta-Analysis of Genomewide Association Scans. Bioinformatics 2010, 26 (17), 2190– 2191, DOI: 10.1093/bioinformatics/btq340Google Scholar35https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtVGru73F&md5=d377a9f6119f912e83bef351aa8909afMETAL: fast and efficient meta-analysis of genomewide association scansWiller, Cristen J.; Li, Yun; Abecasis, Goncalo R.Bioinformatics (2010), 26 (17), 2190-2191CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)METAL provides a computationally efficient tool for meta-anal. of genome-wide assocn. scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: [email protected].
- 36Carrico, C.; Gennings, C.; Wheeler, D. C.; Factor-Litvak, P. Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting. J. Agric. Biol. Environ. Stat. 2015, 20 (1), 100– 120, DOI: 10.1007/s13253-014-0180-3Google Scholar36https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3crns1Gnsg%253D%253D&md5=3c9738d976b0c9791be0aeec9f342225Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis SettingCarrico Caroline; Gennings Chris; Wheeler David C; Factor-Litvak PamJournal of agricultural, biological, and environmental statistics (2015), 20 (1), 100-120 ISSN:1085-7117.In risk evaluation, the effect of mixtures of environmental chemicals on a common adverse outcome is of interest. However, due to the high dimensionality and inherent correlations among chemicals that occur together, the traditional methods (e.g. ordinary or logistic regression) suffer from collinearity and variance inflation, and shrinkage methods have limitations in selecting among correlated components. We propose a weighted quantile sum (WQS) approach to estimating a body burden index, which identifies "bad actors" in a set of highly correlated environmental chemicals. We evaluate and characterize the accuracy of WQS regression in variable selection through extensive simulation studies through sensitivity and specificity (i.e., ability of the WQS method to select the bad actors correctly and not incorrect ones). We demonstrate the improvement in accuracy this method provides over traditional ordinary regression and shrinkage methods (lasso, adaptive lasso, and elastic net). Results from simulations demonstrate that WQS regression is accurate under some environmentally relevant conditions, but its accuracy decreases for a fixed correlation pattern as the association with a response variable diminishes. Nonzero weights (i.e., weights exceeding a selection threshold parameter) may be used to identify bad actors; however, components within a cluster of highly correlated active components tend to have lower weights, with the sum of their weights representative of the set.
- 37Czarnota, J.; Gennings, C.; Wheeler, D. C. Assessment of Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk. Cancer Inf. 2015, 14s2 (Suppl 2), CIN-S17295 DOI: 10.4137/CIN.S17295Google ScholarThere is no corresponding record for this reference.
- 38Ferguson, K. K.; Chin, H. B. Environmental Chemicals and Preterm Birth: Biological Mechanisms and the State of the Science. Curr. Epidemiol. Rep. 2017, 4 (1), 56– 71, DOI: 10.1007/s40471-017-0099-7Google ScholarThere is no corresponding record for this reference.
- 39Gomez-Lopez, N.; Galaz, J.; Miller, D.; Farias-Jofre, M.; Liu, Z.; Arenas-Hernandez, M.; Garcia-Flores, V.; Shaffer, Z.; Greenberg, J. M.; Theis, K. R.; Romero, R. The Immunobiology of Preterm Labor and Birth: Intra-Amniotic Inflammation or Breakdown of Maternal-Fetal Homeostasis. Reproduction 2022, 164 (2), R11– R45, DOI: 10.1530/REP-22-0046Google ScholarThere is no corresponding record for this reference.
- 40Ricciotti, E.; FitzGerald, G. A. Prostaglandins and Inflammation. Arterioscler., Thromb., Vasc. Biol. 2011, 31 (5), 986– 1000, DOI: 10.1161/ATVBAHA.110.207449Google Scholar40https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvFantbs%253D&md5=1e08aa9b4ac193f0f433dd121a6b5340Prostaglandins and InflammationRicciotti, Emanuela; FitzGerald, Garret A.Arteriosclerosis, Thrombosis, and Vascular Biology (2011), 31 (5), 986-1000CODEN: ATVBFA; ISSN:1079-5642. (Lippincott Williams & Wilkins)A review. Prostaglandins are lipid autacoids derived from arachidonic acid. They both sustain homeostatic functions and mediate pathogenic mechanisms, including the inflammatory response. They are generated from arachidonate by the action of cyclooxygenase isoenzymes, and their biosynthesis is blocked by nonsteroidal antiinflammatory drugs, including those selective for inhibition of cyclooxygenase-2. Despite the clin. efficacy of nonsteroidal antiinflammatory drugs, prostaglandins may function in both the promotion and resoln. of inflammation. This review summarizes insights into the mechanisms of prostaglandin generation and the roles of individual mediators and their receptors in modulating the inflammatory response. Prostaglandin biol. has potential clin. relevance for atherosclerosis, the response to vascular injury and aortic aneurysm.
- 41Burdon, C.; Mann, C.; Cindrova-Davies, T.; Ferguson-Smith, A. C.; Burton, G. J. Oxidative Stress and the Induction of Cyclooxygenase Enzymes and Apoptosis in the Murine Placenta. Placenta 2007, 28 (7), 724– 733, DOI: 10.1016/j.placenta.2006.12.001Google ScholarThere is no corresponding record for this reference.
- 42Xu, Y.; Wang, Q.; Cook, T. J.; Knipp, G. T. Effect of Placental Fatty Acid Metabolism and Regulation by Peroxisome Proliferator Activated Receptor on Pregnancy and Fetal Outcomes. J. Pharm. Sci. 2007, 96 (10), 2582– 2606, DOI: 10.1002/jps.20973Google ScholarThere is no corresponding record for this reference.
- 43Davis-Bruno, K.; Tassinari, M. S. Essential Fatty Acid Supplementation of DHA and ARA and Effects on Neurodevelopment across Animal Species: A Review of the Literature. Birth Defects Res., Part B 2011, 92 (3), 240– 250, DOI: 10.1002/bdrb.20311Google ScholarThere is no corresponding record for this reference.
- 44Wong, C. T.; Bestard-Lorigados, I.; Crawford, D. A. Autism-Related Behaviors in the Cyclooxygenase-2-Deficient Mouse Model. Genes Brain Behav. 2019, 18 (1), e12506 DOI: 10.1111/gbb.12506Google ScholarThere is no corresponding record for this reference.
- 45Corwin, C.; Nikolopoulou, A.; Pan, A. L.; Nunez-Santos, M.; Vallabhajosula, S.; Serrano, P.; Babich, J.; Figueiredo-Pereira, M. E. Prostaglandin D2/J2 Signaling Pathway in a Rat Model of Neuroinflammation Displaying Progressive Parkinsonian-like Pathology: Potential Novel Therapeutic Targets. J. Neuroinflammation 2018, 15, 272 DOI: 10.1186/s12974-018-1305-3Google ScholarThere is no corresponding record for this reference.
- 46Hildreth, K.; Kodani, S. D.; Hammock, B. D.; Zhao, L. Cytochrome P450-Derived Linoleic Acid Metabolites EpOMEs and DiHOMEs: A Review of Recent Studies. J. Nutr. Biochem. 2020, 86, 108484 DOI: 10.1016/j.jnutbio.2020.108484Google Scholar46https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhvV2mtLrJ&md5=617ddc14fc8ae82adf742a96ac858586Cytochrome P450-derived linoleic acid metabolites EpOMEs and DiHOMEs: a review of recent studiesHildreth, Kelsey; Kodani, Sean D.; Hammock, Bruce D.; Zhao, LingJournal of Nutritional Biochemistry (2020), 86 (), 108484CODEN: JNBIEL; ISSN:0955-2863. (Elsevier Inc.)A review. Linoleic acid (LA) is the most abundant polyunsatd. fatty acid found in the Western diet. Cytochrome P 450-derived LA metabolites 9,10-epoxyoctadecenoic acid (9,10-EpOME), 12,13-epoxyoctadecenoic acid (12,13-EpOME), 9,10-dihydroxy-12Z-octadecenoic acid (9,10-DiHOME) and 12,13-dihydroxy-9Z-octadecenoic acid (12,13-DiHOME) have been studied for their assocn. with various disease states and biol. functions. Previous studies of the EpOMEs and DiHOMEs have focused on their roles in cytotoxic processes, primarily in the inhibition of the neutrophil respiratory burst. More recent research has suggested the DiHOMEs may be important lipid mediators in pain perception, altered immune response and brown adipose tissue activation by cold and exercise. The purpose of this review is to summarize the current understanding of the physiol. and pathophysiol. roles and modes of action of the EpOMEs and DiHOMEs in health and disease.
- 47Macêdo, A. P. A.; Muñoz, V. R.; Cintra, D. E.; Pauli, J. R. 12,13-diHOME as a New Therapeutic Target for Metabolic Diseases. Life Sci. 2022, 290, 120229 DOI: 10.1016/j.lfs.2021.120229Google ScholarThere is no corresponding record for this reference.
- 48Dalle Vedove, F.; Fava, C.; Jiang, H.; Zanconato, G.; Quilley, J.; Brunelli, M.; Guglielmi, V.; Vattemi, G.; Minuz, P. Increased Epoxyeicosatrienoic Acids and Reduced Soluble Epoxide Hydrolase Expression in the Preeclamptic Placenta. J. Hypertens. 2016, 34 (7), 1364– 1370, DOI: 10.1097/HJH.0000000000000942Google ScholarThere is no corresponding record for this reference.
- 49Herse, F.; LaMarca, B.; Hubel, C. A.; Kaartokallio, T.; Lokki, A. I.; Ekholm, E.; Laivuori, H.; Gauster, M.; Huppertz, B.; Sugulle, M.; Ryan, M. J.; Novotny, S.; Brewer, J.; Park, J.-K.; Kacik, M.; Hoyer, J.; Verlohren, S.; Wallukat, G.; Rothe, M.; Luft, F. C.; Muller, D. N.; Schunck, W.-H.; Staff, A. C.; Dechend, R. Cytochrome P450 Subfamily 2J Polypeptide 2 Expression and Circulating Epoxyeicosatrienoic Metabolites in Preeclampsia. Circulation 2012, 126 (25), 2990– 2999, DOI: 10.1161/CIRCULATIONAHA.112.127340Google ScholarThere is no corresponding record for this reference.
- 50Ghisari, M.; Eiberg, H.; Long, M.; Bonefeld-Jørgensen, E. C. Polymorphisms in Phase I and Phase II Genes and Breast Cancer Risk and Relations to Persistent Organic Pollutant Exposure: A Case–Control Study in Inuit Women. Environ. Health 2014, 13, 19 DOI: 10.1186/1476-069X-13-19Google ScholarThere is no corresponding record for this reference.
- 51Mashima, R.; Okuyama, T. The Role of Lipoxygenases in Pathophysiology; New Insights and Future Perspectives. Redox Biol. 2015, 6, 297– 310, DOI: 10.1016/j.redox.2015.08.006Google Scholar51https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlSnt7fJ&md5=4ef4d8e6e8db03f70dacaebd5c086277The role of lipoxygenases in pathophysiology; new insights and future perspectivesMashima, Ryuichi; Okuyama, TorayukiRedox Biology (2015), 6 (), 297-310CODEN: RBEIB3; ISSN:2213-2317. (Elsevier B.V.)Lipoxygenases (LOXs) are dioxygenases that catalyze the formation of corresponding hydroperoxides from polyunsatd. fatty acids such as linoleic acid and arachidonic acid. LOX enzymes are expressed in immune, epithelial, and tumor cells that display a variety of physiol. functions, including inflammation, skin disorder, and tumorigenesis. In the humans and mice, six LOX isoforms have been known. 15-LOX, a prototypical enzyme originally found in reticulocytes shares the similarity of amino acid sequence as well as the biochem. property to plant LOX enzymes. 15-LOX-2, which is expressed in epithelial cells and leukocytes, has different substrate specificity in the humans and mice, therefore, the role of them in mammals has not been established. 12-LOX is an isoform expressed in epithelial cells and myeloid cells including platelets. Many mutations in this isoform are found in epithelial cancers, suggesting a potential link between 12-LOX and tumorigenesis. 12R-LOX can be found in the epithelial cells of the skin. Defects in this gene result in ichthyosis, a cutaneous disorder characterized by pathophysiol. dried skin due to abnormal loss of water from its epithelial cell layer. Similarly, eLOX-3, which is also expressed in the skin epithelial cells acting downstream 12R-LOX, is another causative factor for ichthyosis. 5-LOX is a distinct isoform playing an important role in asthma and inflammation. This isoform causes the constriction of bronchioles in response to cysteinyl leukotrienes such as LTC4, thus leading to asthma. It also induces neutrophilic inflammation by its recruitment in response to LTB4. Importantly, 5-LOX activity is strictly regulated by 5-LOX activating protein (FLAP) though the distribution of 5-LOX in the nucleus. Currently, pharmacol. drugs targeting FLAP are actively developing. This review summarized these functions of LOX enzymes under pathophysiol. conditions in mammals.
- 52Rhee, S. Y.; Jung, E. S.; Suh, D. H.; Jeong, S. J.; Kim, K.; Chon, S.; Yu, S.-Y.; Woo, J.-T.; Lee, C. H. Plasma Amino Acids and Oxylipins as Potential Multi-Biomarkers for Predicting Diabetic Macular Edema. Sci. Rep. 2021, 11, 9727 DOI: 10.1038/s41598-021-88104-yGoogle ScholarThere is no corresponding record for this reference.
- 53Sergeant, S.; Hugenschmidt, C. E.; Rudock, M. E.; Ziegler, J. T.; Ivester, P.; Ainsworth, H. C.; Vaidya, D.; Case, L. D.; Langefeld, C. D.; Freedman, B. I.; Bowden, D. W.; Mathias, R. A.; Chilton, F. H. Differences in Arachidonic Acid Levels and Fatty Acid Desaturase (FADS) Gene Variants in African Americans and European Americans with Diabetes or the Metabolic Syndrome. Br. J. Nutr. 2012, 107 (4), 547– 555, DOI: 10.1017/S0007114511003230Google ScholarThere is no corresponding record for this reference.
- 54Saadatian-Elahi, M.; Slimani, N.; Chajès, V.; Jenab, M.; Goudable, J.; Biessy, C.; Ferrari, P.; Byrnes, G.; Autier, P.; Peeters, P. H. M.; Ocké, M.; Bueno de Mesquita, B.; Johansson, I.; Hallmans, G.; Manjer, J.; Wirfält, E.; González, C. A.; Navarro, C.; Martinez, C.; Amiano, P.; Suárez, L. R.; Ardanaz, E.; Tjønneland, A.; Halkjaer, J.; Overvad, K.; Jakobsen, M. U.; Berrino, F.; Pala, V.; Palli, D.; Tumino, R.; Vineis, P.; Santucci de Magistris, M.; Spencer, E. A.; Crowe, F. L.; Bingham, S.; Khaw, K.-T.; Linseisen, J.; Rohrmann, S.; Boeing, H.; Noethlings, U.; Olsen, K. S.; Skeie, G.; Lund, E.; Trichopoulou, A.; Oustoglou, E.; Clavel-Chapelon, F.; Riboli, E. Plasma Phospholipid Fatty Acid Profiles and Their Association with Food Intakes: Results from a Cross-Sectional Study within the European Prospective Investigation into Cancer and Nutrition. Am. J. Clin. Nutr. 2009, 89 (1), 331– 346, DOI: 10.3945/ajcn.2008.26834Google ScholarThere is no corresponding record for this reference.
- 55Goodrich, J. A.; Walker, D. I.; He, J.; Lin, X.; Baumert, B. O.; Hu, X.; Alderete, T. L.; Chen, Z.; Valvi, D.; Fuentes, Z. C.; Rock, S.; Wang, H.; Berhane, K.; Gilliland, F. D.; Goran, M. I.; Jones, D. P.; Conti, D. V.; Chatzi, L. Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study. Environ. Health Perspect. 2023, 131 (2), 027005 DOI: 10.1289/EHP11372Google ScholarThere is no corresponding record for this reference.
- 56Guidance on PFAS Exposure, Testing, and Clinical Follow-Up; National Academies Press: Washington, D.C., 2022 DOI: 10.17226/26156 .Google ScholarThere is no corresponding record for this reference.
- 57EFSA Panel on Contaminants in the Food Chain (CONTAM); Knutsen, H. K.; Alexander, J.; Barregård, L.; Bignami, M.; Brüschweiler, B.; Ceccatelli, S.; Cottrill, B.; Dinovi, M.; Edler, L.; Grasl-Kraupp, B.; Hogstrand, C.; Hoogenboom, L. R.; Nebbia, C. S.; Oswald, I. P.; Petersen, A.; Rose, M.; Roudot, A.-C.; Vleminckx, C.; Vollmer, G.; Wallace, H.; Bodin, L.; Cravedi, J.-P.; Halldorsson, T. I.; Haug, L. S.; Johansson, N.; van Loveren, H.; Gergelova, P.; Mackay, K.; Levorato, S.; van Manen, M.; Schwerdtle, T. Risk to Human Health Related to the Presence of Perfluorooctane Sulfonic Acid and Perfluorooctanoic Acid in Food. EFSA J. 2018, 16 (12), e05194 DOI: 10.2903/j.efsa.2018.5194Google ScholarThere is no corresponding record for this reference.
- 58Christensen, K. Y.; Raymond, M.; Blackowicz, M.; Liu, Y.; Thompson, B. A.; Anderson, H. A.; Turyk, M. Perfluoroalkyl Substances and Fish Consumption. Environ. Res. 2017, 154, 145– 151, DOI: 10.1016/j.envres.2016.12.032Google Scholar58https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXmsV2ktA%253D%253D&md5=a3e61934bdd38e79583b9deda2165f32Perfluoroalkyl substances and fish consumptionChristensen, Krista Y.; Raymond, Michelle; Blackowicz, Michael; Liu, Yangyang; Thompson, Brooke A.; Anderson, Henry A.; Turyk, MaryEnvironmental Research (2017), 154 (), 145-151CODEN: ENVRAL; ISSN:0013-9351. (Elsevier)Perfluoroalkyl substances (PFAS) are an emerging class of contaminants. Certain PFAS are regulated or voluntarily limited due to concern about environmental persistence and adverse health effects, including thyroid disease and dyslipidemia. The major source of PFAS exposure in the general population is thought to be consumption of seafood. In this anal. we examine PFAS levels and their determinants, as well as assocns. between PFAS levels and self-reported fish and shellfish consumption, using a representative sample of the U.S. population. Data on PFAS levels and self-reported fish consumption over the past 30 days were collected from the 2007-2008, 2009-2010, 2011-2012, and 2013-2014 cycles of the National Health and Nutrition Examn. Survey. Twelve different PFAS were measured in serum samples from participants. Ordinary least squares regression models were used to identify factors (demog. characteristics and fish consumption habits) assocd. with serum PFAS concns. Addnl. models were further adjusted for other potential exposures including military service and consumption of ready-to-eat and fast foods. Seven PFAS were detected in at least 30% of participants and were examd. in subsequent analyses (PFDA, PFOA, PFOS, PFHxS, MPAH, PFNA, PFUA). The PFAS with the highest concns. were PFOS, followed by PFOA, PFHxS and PFNA (medians of 8.3, 2.7, 1.5 and 1.0 ng/mL). Fish consumption was generally low, with a median of 1.2 fish meals and 0.14 shellfish meals, reported over the past 30 days. After adjusting for demog. characteristics, total fish consumption was assocd. with reduced MPAH, and with elevated PFDE, PFNA and PFuDA. Shellfish consumption was assocd. with elevations of all PFAS examd. except MPAH. Certain specific fish and shellfish types were also assocd. with specific PFAS. Adjustment for addnl. exposure variables resulted in little to no change in effect ests. for seafood variables. PFAS are emerging contaminants with widespread exposure, persistence, and potential for adverse health effects. In the general population, fish and shellfish consumption are assocd. with PFAS levels, which may indicate an avenue for education and outreach.
- 59Chen, B.; McClements, D. J.; Decker, E. A. Design of Foods with Bioactive Lipids for Improved Health. Annu. Rev. Food Sci. Technol. 2013, 4, 35– 56, DOI: 10.1146/annurev-food-032112-135808Google ScholarThere is no corresponding record for this reference.
- 60Zhang, X.; Zhao, L.; Ducatman, A.; Deng, C.; von Stackelberg, K. E.; Danford, C. J.; Zhang, X. Association of Per- and Polyfluoroalkyl Substance Exposure with Fatty Liver Disease Risk in US Adults. JHEP Rep. 2023, 5 (5), 100694 DOI: 10.1016/j.jhepr.2023.100694Google ScholarThere is no corresponding record for this reference.
- 61Roth, K.; Petriello, M. C. Exposure to Per- and Polyfluoroalkyl Substances (PFAS) and Type 2 Diabetes Risk. Front. Endocrinol. 2022, 13, 965384 DOI: 10.3389/fendo.2022.965384Google ScholarThere is no corresponding record for this reference.
- 62Athyros, V. G.; Doumas, M.; Imprialos, K. P.; Stavropoulos, K.; Georgianou, E.; Katsimardou, A.; Karagiannis, A. Diabetes and Lipid Metabolism. Hormones 2018, 17 (1), 61– 67, DOI: 10.1007/s42000-018-0014-8Google ScholarThere is no corresponding record for this reference.
- 63Paul, B.; Lewinska, M.; Andersen, J. B. Lipid Alterations in Chronic Liver Disease and Liver Cancer. JHEP Rep. 2022, 4 (6), 100479 DOI: 10.1016/j.jhepr.2022.100479Google ScholarThere is no corresponding record for this reference.
- 64Zheng, G.; Eick, S. M.; Salamova, A. Elevated Levels of Ultrashort- and Short-Chain Perfluoroalkyl Acids in US Homes and People. Environ. Sci. Technol. 2023, 57 (42), 15782– 15793, DOI: 10.1021/acs.est.2c06715Google Scholar64https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXitVynur3E&md5=026693b740aa19df2ee504d87deaceb7Elevated Levels of Ultrashort- and Short-Chain Perfluoroalkyl Acids in US Homes and PeopleZheng, Guomao; Eick, Stephanie M.; Salamova, AminaEnvironmental Science & Technology (2023), 57 (42), 15782-15793CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)Per- and polyfluoroalkyl substances (PFAS) make up a large group of fluorinated org. compds. extensively used in consumer products and industrial applications. Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), the two perfluoroalkyl acids (PFAAs) with 8 carbons in their structure, were phased out on a global scale because of their high environmental persistence and toxicity. As a result, shorter-chain PFAAs with \<8 carbons in their structure are being used as their replacements and are now widely detected in the environment, raising concerns about their effects on the environment and human health. In this study, 47 PFAAs and their precursors were measured in paired samples of dust and drinking water collected from residential homes in Indiana, United States, and in blood and urine samples collected from the residents of these homes. Ultrashort- (with 2 or 3 carbons [C2-C3]) and short-chain (with 4-7 carbons [C4-C7]) PFAAs were the most abundant in all four matrixes and constituted on av. 69-100% of the total PFAA concns. Specifically, trifluoroacetic acid (TFA, C2) and perfluoropropanoic acid (PFPrA, C3) were the predominant PFAA congeners in most of the samples. Significant pos. correlations (n = 81; r = 0.23-0.42; p < 0.05) were found between TFA, perfluorobutanoic acid (PFBA, C4) and perfluoroheptanoic acid (PFHpA, C7) concns. in dust or water and those in serum, suggesting dust ingestion and/or drinking water consumption as important exposure pathways for these compds. This study demonstrates that ultrashort- and short-chain PFAAs are now abundant in the indoor environment and in people and warrants further research on potential adverse health effects of these exposures.
- 65Gao, P. The Exposome in the Era of One Health. Environ. Sci. Technol. 2021, 55 (5), 2790– 2799, DOI: 10.1021/acs.est.0c07033Google Scholar65https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXmsFCgug%253D%253D&md5=45813c73d5ec6a42624653c25b42ca21The exposome in the era of One HealthGao, PengEnvironmental Science & Technology (2021), 55 (5), 2790-2799CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)A review. Current studies on environmental chem. mainly focus on a single stressor or single group of stressors, which does not reflect the multiple stressors in the dynamic exposome the authors are facing. Similarly, current studies on environmental toxicol. mostly target humans, animals, or the environment sep., which are inadequate to solve the grand challenge of multiple receptors in One Health. Though chem., biol., and phys. stressors all pose health threats, the susceptibilities of different organisms are different. As such, significant relationships and interactions of the chem., biol., and phys. stressors in the environment and their holistic environmental and biol. consequences remain unclear. Fortunately, the rapid developments in various techniques, as well as the concepts of multistressors in the exposome and multireceptor in One Health provide the possibilities to understand the authors' environment better. Since the combined stressor is location-specific and mixt. toxicity is species-specific, more comprehensive frameworks to guide risk assessment and environmental treatment are urgently needed. Here, three conceptual frameworks to categorize unknown stressors, spatially visualize the riskiest stressors, and investigate the combined effects of multiple stressors across multiple species within the concepts of the exposome and One Health are proposed for the first time.
- 66Aung, M. T.; Yu, Y.; Ferguson, K. K.; Cantonwine, D. E.; Zeng, L.; McElrath, T. F.; Pennathur, S.; Mukherjee, B.; Meeker, J. D. Cross-Sectional Estimation of Endogenous Biomarker Associations with Prenatal Phenols, Phthalates, Metals, and Polycyclic Aromatic Hydrocarbons in Single-Pollutant and Mixtures Analysis Approaches. Environ. Health Perspect. 2021, 129 (3), 037007 DOI: 10.1289/EHP7396Google ScholarThere is no corresponding record for this reference.
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Abstract
Figure 1
Figure 1. Heatmap of β estimates corresponding to percentage change in bioactive lipids as a result of doubling log-transformed PFAS for adjusted joint analyses and meta-analyses run on adjusted within-cohort models. The magnitude of effect estimates in each cell in the heatmap corresponds to the intensity of the color band in the legend. Nonsignificant values (p > .05) are marked with black “X”. Sample sizes range from 343 to 383 (see Supplemental Tables 7, 8, 9, and 10 for exact pairwise sample sizes).
Figure 2
Figure 2. Forest plot of quantile g-computation effect estimates in the combined cohort analysis with IKIDS and CIOB cohorts (N = 343), showing of β estimates corresponding to percentage change in bioactive lipids associated with a simultaneous 1-quartile increase in all log-transformed PFAS. Model adjusted for maternal age, maternal education, prepregnancy BMI, parity, gestational age at visit, and cohort.
References
This article references 66 other publications.
- 1Sunderland, E. M.; Hu, X. C.; Dassuncao, C.; Tokranov, A. K.; Wagner, C. C.; Allen, J. G. A Review of the Pathways of Human Exposure to Poly-and Perfluoroalkyl Substances (PFASs) and Present Understanding of Health Effects. J. Exposure Sci. Environ. Epidemiol. 2019, 29 (2), 131– 147, DOI: 10.1038/s41370-018-0094-11https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXitlShu7jO&md5=1e8b317874a0ca47788c824343630818A review of the pathways of human exposure to poly- and perfluoroalkyl substances (PFASs) and present understanding of health effectsSunderland, Elsie M.; Hu, Xindi C.; Dassuncao, Clifton; Tokranov, Andrea K.; Wagner, Charlotte C.; Allen, Joseph G.Journal of Exposure Science & Environmental Epidemiology (2019), 29 (2), 131-147CODEN: JESEBS; ISSN:1559-0631. (Nature Research)A review. Here, we review present understanding of sources and trends in human exposure to poly- and perfluoroalkyl substances (PFASs) and epidemiol. evidence for impacts on cancer, immune function, metabolic outcomes, and neurodevelopment. More than 4000 PFASs have been manufd. by humans and hundreds have been detected in environmental samples. Direct exposures due to use in products can be quickly phased out by shifts in chem. prodn. but exposures driven by PFAS accumulation in the ocean and marine food chains and contamination of groundwater persist over long timescales. Serum concns. of legacy PFASs in humans are declining globally but total exposures to newer PFASs and precursor compds. have not been well characterized. Human exposures to legacy PFASs from seafood and drinking water are stable or increasing in many regions, suggesting obsd. declines reflect phase-outs in legacy PFAS use in consumer products. Many regions globally are continuing to discover PFAS contaminated sites from aq. film forming foam (AFFF) use, particularly next to airports and military bases. Exposures from food packaging and indoor environments are uncertain due to a rapidly changing chem. landscape where legacy PFASs have been replaced by diverse precursors and custom mols. that are difficult to detect. Multiple studies find significant assocns. between PFAS exposure and adverse immune outcomes in children. Dyslipidemia is the strongest metabolic outcome assocd. with PFAS exposure. Evidence for cancer is limited to manufg. locations with extremely high exposures and insufficient data are available to characterize impacts of PFAS exposures on neurodevelopment. Preliminary evidence suggests significant health effects assocd. with exposures to emerging PFASs. Lessons learned from legacy PFASs indicate that limited data should not be used as a justification to delay risk mitigation actions for replacement PFASs.
- 2Calafat, A. M.; Wong, L.-Y.; Kuklenyik, Z.; Reidy, J. A.; Needham, L. L. Polyfluoroalkyl Chemicals in the US Population: Data from the National Health and Nutrition Examination Survey (NHANES) 2003–2004 and Comparisons with NHANES 1999–2000. Environ. Health Perspect. 2007, 115 (11), 1596– 1602, DOI: 10.1289/ehp.105982https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtl2ns7%252FK&md5=2f97144423bc80ba1be402249b11722dPolyfluoroalkyl chemicals in the U.S. population: data from the National Health and Nutrition Examination Survey 2003-2004 and comparisons with NHANES 1999-2000Calafat, Antonia M.; Wong, Lee-Yang; Kuklenyik, Zsuzsanna; Reidy, John A.; Needham, Larry L.Environmental Health Perspectives (2007), 115 (11), 1596-1602CODEN: EVHPAZ; ISSN:0091-6765. (U. S. Department of Health and Human Services, Public Health Services)Polyfluoroalkyl chems. (PFCs) have been used since the 1950s in numerous com. applications. Exposure of the general U.S. population to PFCs is widespread. Since 2002, the manufg. practices for PFCs in the United States have changed considerably. We aimed to assess exposure to perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and eight other PFCs in a representative 2003-2004 sample of the general U.S. population ≥ 12 years of age and to det. whether serum concns. have changed since the 1999-2000 National Health and Nutrition Examn. Survey (NHANES). By using automated solid-phase extn. coupled to isotope diln.-high-performance liq. chromatog.-tandem mass spectrometry, we analyzed 2094 serum samples collected from NHANES 2003-2004 participants. We detected PFOS, PFOA, PFHxS, and PFNA in >98% of the samples. Concns. differed by race/ethnicity and sex. Geometric mean concns. were significantly lower (approx. 32% for PFOS, 25% for PFOA, 10% for PFHxS) and higher (100%, PFNA) than the concns. reported in NHANES 1999-2000 (p < 0.001). In the general U.S. population in 2003-2004, PFOS, PFOA, PFHxS, and PFNA serum concns. were measurable in each demog. population group studied. Geometric mean concns. of PFOS, PFOA, and PFHxS in 2003-2004 were lower than in 1999-2000. The apparent redns. in concns. of PFOS, PFOA, and PFHxS most likely are related to discontinuation in 2002 of industrial prodn. by electrochem. fluorination of PFOS and related perfluorooctanesulfonyl fluoride compds.
- 3Chiu, W. A.; Lynch, M. T.; Lay, C. R.; Antezana, A.; Malek, P.; Sokolinski, S.; Rogers, R. D. Bayesian Estimation of Human Population Toxicokinetics of PFOA, PFOS, PFHxS, and PFNA from Studies of Contaminated Drinking Water. Environ. Health Perspect. 2022, 130 (12), 127001 DOI: 10.1289/EHP10103There is no corresponding record for this reference.
- 4Fenton, S. E.; Ducatman, A.; Boobis, A.; DeWitt, J. C.; Lau, C.; Ng, C.; Smith, J. S.; Roberts, S. M. Per-and Polyfluoroalkyl Substance Toxicity and Human Health Review: Current State of Knowledge and Strategies for Informing Future Research. Environ. Toxicol. Chem. 2021, 40 (3), 606– 630, DOI: 10.1002/etc.48904https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXisV2nurjE&md5=8d69f30fc5484e9a25bcca83eb7ad2e0Per- and Polyfluoroalkyl Substance Toxicity and Human Health Review: Current State of Knowledge and Strategies for Informing Future ResearchFenton, Suzanne E.; Ducatman, Alan; Boobis, Alan; DeWitt, Jamie C.; Lau, Christopher; Ng, Carla; Smith, James S.; Roberts, Stephen M.Environmental Toxicology and Chemistry (2021), 40 (3), 606-630CODEN: ETOCDK; ISSN:0730-7268. (Wiley-Blackwell)Reports of environmental and human health impacts of per- and polyfluoroalkyl substances (PFAS) have greatly increased in the peer-reviewed literature. The goals of the present review are to assess the state of the science regarding toxicol. effects of PFAS and to develop strategies for advancing knowledge on the health effects of this large family of chems. Currently, much of the toxicity data available for PFAS are for a handful of chems., primarily legacy PFAS such as perfluorooctanoic acid and perfluorooctane sulfonate. Epidemiol. studies have revealed assocns. between exposure to specific PFAS and a variety of health effects, including altered immune and thyroid function, liver disease, lipid and insulin dysregulation, kidney disease, adverse reproductive and developmental outcomes, and cancer. Concordance with exptl. animal data exists for many of these effects. However, information on modes of action and adverse outcome pathways must be expanded, and profound differences in PFAS toxicokinetic properties must be considered in understanding differences in responses between the sexes and among species and life stages. With many health effects noted for a relatively few example compds. and hundreds of other PFAS in commerce lacking toxicity data, more contemporary and high-throughput approaches such as read-across, mol. dynamics, and protein modeling are proposed to accelerate the development of toxicity information on emerging and legacy PFAS, individually and as mixts. In addn., an appropriate degree of precaution, given what is already known from the PFAS examples noted, may be needed to protect human health. Environ Toxicol Chem 2020;00:1-25. 2020 SETAC.
- 5Calafat, A. M.; Wong, L.-Y.; Kuklenyik, Z.; Reidy, J. A.; Needham, L. L. Polyfluoroalkyl Chemicals in the U.S. Population: Data from the National Health and Nutrition Examination Survey (NHANES) 2003–2004 and Comparisons with NHANES 1999–2000. Environ. Health Perspect. 2007, 115 (11), 1596– 1602, DOI: 10.1289/ehp.105985https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtl2ns7%252FK&md5=2f97144423bc80ba1be402249b11722dPolyfluoroalkyl chemicals in the U.S. population: data from the National Health and Nutrition Examination Survey 2003-2004 and comparisons with NHANES 1999-2000Calafat, Antonia M.; Wong, Lee-Yang; Kuklenyik, Zsuzsanna; Reidy, John A.; Needham, Larry L.Environmental Health Perspectives (2007), 115 (11), 1596-1602CODEN: EVHPAZ; ISSN:0091-6765. (U. S. Department of Health and Human Services, Public Health Services)Polyfluoroalkyl chems. (PFCs) have been used since the 1950s in numerous com. applications. Exposure of the general U.S. population to PFCs is widespread. Since 2002, the manufg. practices for PFCs in the United States have changed considerably. We aimed to assess exposure to perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and eight other PFCs in a representative 2003-2004 sample of the general U.S. population ≥ 12 years of age and to det. whether serum concns. have changed since the 1999-2000 National Health and Nutrition Examn. Survey (NHANES). By using automated solid-phase extn. coupled to isotope diln.-high-performance liq. chromatog.-tandem mass spectrometry, we analyzed 2094 serum samples collected from NHANES 2003-2004 participants. We detected PFOS, PFOA, PFHxS, and PFNA in >98% of the samples. Concns. differed by race/ethnicity and sex. Geometric mean concns. were significantly lower (approx. 32% for PFOS, 25% for PFOA, 10% for PFHxS) and higher (100%, PFNA) than the concns. reported in NHANES 1999-2000 (p < 0.001). In the general U.S. population in 2003-2004, PFOS, PFOA, PFHxS, and PFNA serum concns. were measurable in each demog. population group studied. Geometric mean concns. of PFOS, PFOA, and PFHxS in 2003-2004 were lower than in 1999-2000. The apparent redns. in concns. of PFOS, PFOA, and PFHxS most likely are related to discontinuation in 2002 of industrial prodn. by electrochem. fluorination of PFOS and related perfluorooctanesulfonyl fluoride compds.
- 6Padula, A. M.; Ning, X.; Bakre, S.; Barrett, E. S.; Bastain, T.; Bennett, D. H.; Bloom, M. S.; Breton, C. V.; Dunlop, A. L.; Eick, S. M.; Ferrara, A.; Fleisch, A.; Geiger, S.; Goin, D. E.; Kannan, K.; Karagas, M. R.; Korrick, S.; Meeker, J. D.; Morello-Frosch, R.; O’Connor, T. G.; Oken, E.; Robinson, M.; Romano, M. E.; Schantz, S. L.; Schmidt, R. J.; Starling, A. P.; Zhu, Y.; Hamra, G. B.; Woodruff, T. J.; the program collaborators for Environmental influences on Child Health Outcomes Birth Outcomes in Relation to Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Stress in the Environmental Influences on Child Health Outcomes (ECHO) Program. Environ. Health Perspect. 2023, 131 (3), 037006 DOI: 10.1289/EHP10723There is no corresponding record for this reference.
- 7Gao, X.; Ni, W.; Zhu, S.; Wu, Y.; Cui, Y.; Ma, J.; Liu, Y.; Qiao, J.; Ye, Y.; Yang, P.; Liu, C.; Zeng, F. Per- and Polyfluoroalkyl Substances Exposure during Pregnancy and Adverse Pregnancy and Birth Outcomes: A Systematic Review and Meta-Analysis. Environ. Res. 2021, 201, 111632 DOI: 10.1016/j.envres.2021.1116327https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhsF2mur3N&md5=3e02f9d52e4fb6342f5f2e188d24ead4Per- and polyfluoroalkyl substances exposure during pregnancy and adverse pregnancy and birth outcomes: A systematic review and meta-analysisGao, Xuping; Ni, Wanze; Zhu, Sui; Wu, Yanxin; Cui, Yunfeng; Ma, Junrong; Liu, Yanhua; Qiao, Jinlong; Ye, Yanbin; Yang, Pan; Liu, Chaoqun; Zeng, FangfangEnvironmental Research (2021), 201 (), 111632CODEN: ENVRAL; ISSN:0013-9351. (Elsevier Inc.)Exposure to per- and polyfluoroalkyl substances (PFAS) during pregnancy has been suggested to be assocd. with adverse pregnancy and birth outcomes; however, the findings have been inconsistent. We aimed to conduct a systematic review and meta-anal. to provide an overview of these assocns. The online databases PubMed, EMBASE and Web of Science were searched comprehensively for eligible studies from inception to Feb. 2021. Odds ratios (ORs) and 95% confidence intervals (CIs) were pooled using random- or fixed-effects models, and dose-response meta-analyses were also conducted when possible. A total of 29 studies (32,905 participants) were included. The pooled results demonstrated that perfluorooctane sulfonate (PFOS) exposure during pregnancy was linearly assocd. with increased preterm birth risk (pooled OR per 1-ng/mL increase: 1.01, 95% CIs: 1.00-1.02, P = 0.009) and perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) exposure showed inverted U-shaped assocns. with preterm birth risk (P values for the nonlinear trend: 0.025 and 0.030). Pos. assocns. were also obsd. for exposure to perfluorodecanoate (PFDA) and miscarriage (pooled OR per 1-ng/mL increase: 1.87, 95% CIs: 1.15-3.03) and PFOS and preeclampsia (pooled OR per 1-log increase: 1.27, 95% CIs: 1.06-1.51), whereas exposure to perfluoroundecanoate (PFUnDA) was inversely assocd. with preeclampsia risk (pooled OR per 1-log increase: 0.81, 95% CIs: 0.71-0.93). Based on individual evidence, detrimental effects were obsd. between PFDA exposure and small for gestational age and between PFOA and PFOS and intrauterine growth restriction. No significant assocns. were found between pregnancy PFAS exposure and other adverse pregnancy outcomes (i.e., gestational diabetes mellitus, pregnancy-induced hypertension, low birth wt., and large and small for gestational age). Our findings indicated that PFOS, PFOA and PFNA exposure during pregnancy might be assocd. with increased preterm birth risk and that PFAS exposure might be assocd. with the risk of miscarriage and preeclampsia. Due to the limited evidence obtained for most assocns., addnl. studies are required to confirm these findings.
- 8Ding, N.; Karvonen-Gutierrez, C. A.; Zota, A. R.; Mukherjee, B.; Harlow, S. D.; Park, S. K. The Role of Exposure to Per- and Polyfluoroalkyl Substances in Racial/Ethnic Disparities in Hypertension: Results from the Study of Women’s Health across the Nation. Environ. Res. 2023, 227, 115813 DOI: 10.1016/j.envres.2023.115813There is no corresponding record for this reference.
- 9Aung, M. T.; Eick, S. M.; Padula, A. M.; Smith, S.; Park, J.-S.; DeMicco, E.; Woodruff, T. J.; Morello-Frosch, R. Maternal Per- and Poly-Fluoroalkyl Substances Exposures Associated with Higher Depressive Symptom Scores among Immigrant Women in the Chemicals in Our Bodies Cohort in San Francisco. Environ. Int. 2023, 172, 107758 DOI: 10.1016/j.envint.2023.1077589https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXhvVCqs78%253D&md5=ad2fcb8172e7bc57190fa3c36bb39904Maternal per- and poly-fluoroalkyl substances exposures associated with higher depressive symptom scores among immigrant women in the Chemicals in Our Bodies cohort in San FranciscoAung, Max T.; Eick, Stephanie M.; Padula, Amy M.; Smith, Sabrina; Park, June-Soo; DeMicco, Erin; Woodruff, Tracey J.; Morello-Frosch, RachelEnvironment International (2023), 172 (), 107758CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)Exposure to per- and poly-fluoroalkyl substances (PFAS) remains an important public health issue due to widespread detection and persistence in environmental media, slow metab. in humans, and influences on physiol. processes such as neurol. signaling. Maternal depression is highly prevalent during pregnancy and postpartum and is potentially sensitive to PFAS. The health risks assocd. with PFAS may be further amplified in historically marginalized communities, including immigrants. Evaluate maternal concns. of PFAS in assocn. with depression scores during pregnancy and whether effects differ between US born and immigrant women. Our study sample included 282 US born and 235 immigrant pregnant women enrolled in the Chems. in Our Bodies prospective birth cohort based in San Francisco, CA. We measured 12 PFAS in serum samples collected in the second trimester and depressive symptom scores were assessed using the Center for Epidemiol. Studies Depression Scale. Assocns. were estd. using linear regression, adjusting for maternal age, education, pre-pregnancy body mass index, and parity. Assocns. with a PFAS mixt. were estd. using quantile g-computation. In adjusted linear regression models, a twofold increase in two PFAS was assocd. with higher depression scores in the overall sample, and this assocn. persisted only among immigrant women β [95% confidence interval]: perfluorooctane sulfonic acid (2.7 [0.7-4.7]) and methyl-perfluorooctane sulfonamide acetic acid (2.9 [1.2-4.7]). Quantile g-computation indicated that simultaneously increasing all PFAS in the mixt. by one quartile was assocd. with increased depressive symptoms among immigrant women (mean change per quartile increase = 1.12 [0.002, 2.3]), and assocns. were stronger compared to US born women (mean change per quartile increase = 0.09 [-1.0, 0.8]). Findings provide new evidence that PFAS are assocd. with higher depression symptoms among immigrant women during pregnancy. Results can inform efforts to address environmental factors that may affect depression among US immigrants.
- 10Yuan, Z.-X.; Majchrzak-Hong, S.; Keyes, G. S.; Iadarola, M. J.; Mannes, A. J.; Ramsden, C. E. Lipidomic Profiling of Targeted Oxylipins with Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry. Anal. Bioanal. Chem. 2018, 410 (23), 6009– 6029, DOI: 10.1007/s00216-018-1222-410https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhsVGhtLzI&md5=0ff3e0bdc0752714db02a8af9ce08b24Lipidomic profiling of targeted oxylipins with ultra-performance liquid chromatography-tandem mass spectrometryYuan, Zhi-Xin; Majchrzak-Hong, Sharon; Keyes, Gregory S.; Iadarola, Michael J.; Mannes, Andrew J.; Ramsden, Christopher E.Analytical and Bioanalytical Chemistry (2018), 410 (23), 6009-6029CODEN: ABCNBP; ISSN:1618-2642. (Springer)Oxylipins are bioactive mediators that play diverse roles in (patho)physiol. The authors developed a sensitive and selective ultra-performance liq. chromatog.-tandem mass spectrometry (UPLC-MS/MS) method for the simultaneous profiling of 57 targeted oxylipins derived from five major n-6 and n-3 polyunsatd. fatty acids (PUFAs) that serve as oxylipin precursors, including linoleic (LA), arachidonic (AA), alpha-linolenic (ALA), eicosapentaenoic (EPA), and docosahexaenoic (DHA) acids. The targeted oxylipin panel provides broad coverage of lipid mediators and pathway markers generated from cyclooxygenases, lipoxygenases, cytochrome P 450 epoxygenases/hydroxylases, and non-enzymic oxidn. pathways. The method is based on combination of protein pptn. and solid-phase extn. (SPE) for sample prepn., followed by UPLC-MS/MS. This is the first methodol. to incorporate four hydroxy-epoxy-octadecenoic acids and four keto-epoxy-octadecenoic acids into an oxylipin profiling network. The novel method achieves excellent resoln. and allows in-depth anal. of isomeric and isobaric species of oxylipin exts. in biol. samples. The method was quant. characterized in human plasma with good linearity (R = 0.990-0.999), acceptable reproducibility (relative std. deviation < 20% for the majority of analytes), accuracy (67.8 to 129.3%) for all analytes, and recovery (66.8-121.2%) for all analytes except 5,6-EET. Ion enhancement effects for 28% of the analytes in tested concns. were obsd. in plasma, but were reproducible with relative std. deviation < 17.2%. Basal levels of targeted oxylipins detd. in plasma and serum are in agreement with those previously reported in literature. The method has been successfully applied in clin. and preclin. studies.
- 11Eek, P.; Järving, R.; Järving, I.; Gilbert, N. C.; Newcomer, M. E.; Samel, N. Structure of a Calcium-Dependent 11R-Lipoxygenase Suggests a Mechanism for Ca2+ Regulation. J. Biol. Chem. 2012, 287 (26), 22377– 22386, DOI: 10.1074/jbc.M112.34328511https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XptVWqsro%253D&md5=64649cbb4f2c28aa75b9830c40c810cdStructure of a Calcium-dependent 11R-Lipoxygenase Suggests a Mechanism for Ca2+ RegulationEek, Priit; Jaerving, Reet; Jaerving, Ivar; Gilbert, Nathaniel C.; Newcomer, Marcia E.; Samel, NigulasJournal of Biological Chemistry (2012), 287 (26), 22377-22386CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)Lipoxygenases (LOXs) are a key part of several signaling pathways that lead to inflammation and cancer. Yet, the mechanisms of substrate binding and allosteric regulation by the various LOX isoforms remain speculative. Here we report the 2.47-Å resoln. crystal structure of the arachidonate 11R-LOX from Gersemia fruticosa, which sheds new light on the mechanism of LOX catalysis. Our crystallog. and mutational studies suggest that the aliph. tail of the fatty acid is bound in a hydrophobic pocket with two potential entrances. We speculate that LOXs share a common T-shaped substrate channel architecture that gives rise to the varying positional specificities. A general allosteric mechanism is proposed for transmitting the activity-inducing effect of calcium binding from the membrane-targeting PLAT (polycystin-1/lipoxygenase/α-toxin) domain to the active site via a conserved π-cation bridge.
- 12Ma, G.; Pan, B.; Ren, S.; Guo, C.; Guo, Y.; Wei, L.; Zheng, L.; Chen, B. 15-Oxoeicosatetraenoic Acid Mediates Monocyte Adhesion to Endothelial Cell. Lipids Health Dis. 2017, 16 (1), 137 DOI: 10.1186/s12944-017-0518-2There is no corresponding record for this reference.
- 13Patel, N. S. A.; Cuzzocrea, S.; Chatterjee, P. K.; Di Paola, R.; Sautebin, L.; Britti, D.; Thiemermann, C. Reduction of Renal Ischemia-Reperfusion Injury in 5-Lipoxygenase Knockout Mice and by the 5-Lipoxygenase Inhibitor Zileuton. Mol. Pharmacol. 2004, 66 (2), 220– 227, DOI: 10.1124/mol.66.2.220There is no corresponding record for this reference.
- 14Taibl, K. R.; Dunlop, A. L.; Barr, D. B.; Li, Y.-Y.; Eick, S. M.; Kannan, K.; Ryan, P. B.; Schroder, M.; Rushing, B.; Fennell, T.; Chang, C.-J.; Tan, Y.; Marsit, C. J.; Jones, D. P.; Liang, D. Newborn Metabolomic Signatures of Maternal Per- and Polyfluoroalkyl Substance Exposure and Reduced Length of Gestation. Nat. Commun. 2023, 14, 3120 DOI: 10.1038/s41467-023-38710-3There is no corresponding record for this reference.
- 15Aung, M. T.; Yu, Y.; Ferguson, K. K.; Cantonwine, D. E.; Zeng, L.; McElrath, T. F.; Pennathur, S.; Mukherjee, B.; Meeker, J. D. Prediction and Associations of Preterm Birth and Its Subtypes with Eicosanoid Enzymatic Pathways and Inflammatory Markers. Sci. Rep. 2019, 9 (1), 17049 DOI: 10.1038/s41598-019-53448-zThere is no corresponding record for this reference.
- 16Welch, B. M.; Keil, A. P.; van ‘t Erve, T. J.; Deterding, L. J.; Williams, J. G.; Lih, F. B.; Cantonwine, D. E.; McElrath, T. F.; Ferguson, K. K. Longitudinal Profiles of Plasma Eicosanoids during Pregnancy and Size for Gestational Age at Delivery: A Nested Case-Control Study. PLoS Med. 2020, 17 (8), e1003271 DOI: 10.1371/journal.pmed.1003271There is no corresponding record for this reference.
- 17Guo, P.; Furnary, T.; Vasiliou, V.; Yan, Q.; Nyhan, K.; Jones, D. P.; Johnson, C. H.; Liew, Z. Non-Targeted Metabolomics and Associations with per- and Polyfluoroalkyl Substances (PFAS) Exposure in Humans: A Scoping Review. Environ. Int. 2022, 162, 107159 DOI: 10.1016/j.envint.2022.10715917https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XovF2ksLw%253D&md5=a39339bcf099e1441056110e3e896e5eNon-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping reviewGuo, Pengfei; Furnary, Tristan; Vasiliou, Vasilis; Yan, Qi; Nyhan, Kate; Jones, Dean P.; Johnson, Caroline H.; Liew, ZeyanEnvironment International (2022), 162 (), 107159CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)A review. To summarize the application of non-targeted metabolomics in epidemiol. studies that assessed metabolite and metabolic pathway alterations assocd. with per- and polyfluoroalkyl substances (PFAS) exposure. Eleven human studies published before Apr. 1st, 2021 were identified through database searches (PubMed, Dimensions, Web of Science Core Collection, Embase, Scopus), and citation chaining (Citationchaser). The sample sizes of these studies ranged from 40 to 965, involving children and adolescents (n = 3), non-pregnant adults (n = 5), or pregnant women (n = 3). High-resoln. liq. chromatog.-mass spectrometry was the primary anal. platform to measure both PFAS and metabolome. PFAS were measured in either plasma (n = 6) or serum (n = 5), while metabolomic profiles were assessed using plasma (n = 6), serum (n = 4), or urine (n = 1). Four types of PFAS (perfluorooctane sulfonate (n = 11), perfluorooctanoic acid (n = 10), perfluorohexane sulfonate (n = 9), perfluorononanoic acid (n = 5)) and PFAS mixts. (n = 7) were the most studied. We found that alterations to tryptophan metab. and the urea cycle were most reported PFAS-assocd. metabolomic signatures. Numerous lipid metabolites were also suggested to be assocd. with PFAS exposure, esp. key metabolites in glycerophospholipid metab. which is crit. for biol. membrane functions, and fatty acids and carnitines which are relevant to the energy supply pathway of fatty acid oxidn. Other important metabolome changes reported included the tricarboxylic acid (TCA) cycle regarding energy generation, and purine and pyrimidine metab. in cellular energy systems. There is growing interest in using non-targeted metabolomics to study the human physiol. changes assocd. with PFAS exposure. Multiple PFAS were reported to be assocd. with alterations in amino acid and lipid metab., but these results are driven by one predominant type of pathway anal. thus require further confirmation. Standardizing research methods and reporting are recommended to facilitate result comparison. Future studies should consider potential differences in study methodol., use of prospective design, and influence from confounding bias and measurement errors.
- 18Hvizdak, M.; Kandel, S. E.; Work, H. M.; Gracey, E. G.; McCullough, R. L.; Lampe, J. N. Per- and Polyfluoroalkyl Substances (PFAS) Inhibit Cytochrome P450 CYP3A7 through Direct Coordination to the Heme Iron and Water Displacement. J. Inorg. Biochem. 2023, 240, 112120 DOI: 10.1016/j.jinorgbio.2023.112120There is no corresponding record for this reference.
- 19Zanger, U. M.; Schwab, M. Cytochrome P450 Enzymes in Drug Metabolism: Regulation of Gene Expression, Enzyme Activities, and Impact of Genetic Variation. Pharm. Ther. 2013, 138 (1), 103– 141, DOI: 10.1016/j.pharmthera.2012.12.007There is no corresponding record for this reference.
- 20Cao, Y.; Ng, C. Absorption, Distribution, and Toxicity of per- and Polyfluoroalkyl Substances (PFAS) in the Brain: A Review. Environ. Sci. Process Impacts 2021, 23 (11), 1623– 1640, DOI: 10.1039/D1EM00228G20https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXhvF2isrvF&md5=10fe32a2c1557e7b0a93d92c02183219Absorption, distribution, and toxicity of per- and polyfluoroalkyl substances (PFAS) in the brain: a reviewCao, Yuexin; Ng, CarlaEnvironmental Science: Processes & Impacts (2021), 23 (11), 1623-1640CODEN: ESPICZ; ISSN:2050-7895. (Royal Society of Chemistry)A review. Per- and polyfluoroalkyl substances (PFAS) are a class of synthetic chems. colloquially known as "forever chems." because of their high persistence. PFAS have been detected in the blood, liver, kidney, heart, muscle and brain of various species. Although brain is not a dominant tissue for PFAS accumulation compared to blood and liver, adverse effects of PFAS on brain functions have been identified. Here, we review studies related to the absorption, accumulation, distribution and toxicity of PFAS in the brain. We summarize evidence on two potential mechanisms of PFAS entering the brain: initiating blood-brain barrier (BBB) disassembly through disrupting tight junctions and relying on transporters located at the BBB. PFAS with diverse structures and properties enter and accumulate in the brain with varying efficiencies. Compared to long-chain PFAS, short-chain PFAS may not cross cerebral barriers effectively. According to biomonitoring studies and PFAS exposure expts., PFAS can accumulate in the brain of humans and wildlife species. With respect to the distribution of PFAS in specific brain regions, the brain stem, hippocampus, hypothalamus, pons/medulla and thalamus are dominant for PFAS accumulation. The accumulation and distribution of PFAS in the brain may lead to toxic effects in the central nervous system (CNS), including PFAS-induced behavioral and cognitive disorders. The specific mechanisms underlying such PFAS-induced neurotoxicity remain to be explored, but two major potential mechanisms based on current understanding are PFAS effects on calcium homeostasis and neurotransmitter alterations in neurons. Based on the information available about PFAS uptake, accumulation, distribution and impacts on the brain, PFAS have the potential to enter and accumulate in the brain at varying levels. The balance of existing studies shows there is some indication of risk in animals, while the human evidence is mixed and warrants further scrutiny.
- 21Knapp, E. A.; Kress, A. M.; Parker, C. B.; Page, G. P.; McArthur, K.; Gachigi, K. K.; Alshawabkeh, A. N.; Aschner, J. L.; Bastain, T. M.; Breton, C. V.; Bendixsen, C. G.; Brennan, P. A.; Bush, N. R.; Buss, C.; Camargo, Carlos A., Jr.; Catellier, D.; Cordero, J. F.; Croen, L.; Dabelea, D.; Deoni, S.; D’Sa, V.; Duarte, C. S.; Dunlop, A. L.; Elliott, A. J.; Farzan, S. F.; Ferrara, A.; Ganiban, J. M.; Gern, J. E.; Giardino, A. P.; Towe-Goodman, N. R.; Gold, D. R.; Habre, R.; Hamra, G. B.; Hartert, T.; Herbstman, J. B.; Hertz-Picciotto, I.; Hipwell, A. E.; Karagas, M. R.; Karr, C. J.; Keenan, K.; Kerver, J. M.; Koinis-Mitchell, D.; Lau, B.; Lester, B. M.; Leve, L. D.; Leventhal, B.; LeWinn, K. Z.; Lewis, J.; Litonjua, A. A.; Lyall, K.; Madan, J. C.; McEvoy, C. T.; McGrath, M.; Meeker, J. D.; Miller, R. L.; Morello-Frosch, R.; Neiderhiser, J. M.; O’Connor, T. G.; Oken, E.; O’Shea, M.; Paneth, N.; Porucznik, C. A.; Sathyanarayana, S.; Schantz, S. L.; Spindel, E. R.; Stanford, J. B.; Stroustrup, A.; Teitelbaum, S. L.; Trasande, L.; Volk, H.; Wadhwa, P. D.; Weiss, S. T.; Woodruff, T. J.; Wright, R. J.; Zhao, Q.; Jacobson, L. P.; Influences on Child Health Outcomes, on behalf of program collaborators for Environmental The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort. Am. J. Epidemiol. 2023, 192 (8), 1249– 1263, DOI: 10.1093/aje/kwad071There is no corresponding record for this reference.
- 22Eick, S. M.; Enright, E. A.; Geiger, S. D.; Dzwilewski, K. L. C.; DeMicco, E.; Smith, S.; Park, J.-S.; Aguiar, A.; Woodruff, T. J.; Morello-Frosch, R.; Schantz, S. L. Associations of Maternal Stress, Prenatal Exposure to Per- and Polyfluoroalkyl Substances (PFAS), and Demographic Risk Factors with Birth Outcomes and Offspring Neurodevelopment: An Overview of the ECHO.CA.IL Prospective Birth Cohorts. Int. J. Environ. Res. Public Health 2021, 18 (2), 742, DOI: 10.3390/ijerph18020742There is no corresponding record for this reference.
- 23Ferguson, K. K.; Rosario, Z.; McElrath, T. F.; Vélez Vega, C.; Cordero, J. F.; Alshawabkeh, A.; Meeker, J. D. Demographic Risk Factors for Adverse Birth Outcomes in Puerto Rico in the PROTECT Cohort. PLoS One 2019, 14 (6), e0217770 DOI: 10.1371/journal.pone.0217770There is no corresponding record for this reference.
- 24Eick, S. M.; Geiger, S. D.; Alshawabkeh, A.; Aung, M.; Barrett, E.; Bush, N. R.; Cordero, J. F.; Ferguson, K. K.; Meeker, J. D.; Milne, G. L.; Nguyen, R. H. N.; Padula, A. M.; Sathyanarayana, S.; Welch, B. M.; Schantz, S. L.; Woodruff, T. J.; Morello-Frosch, R. Associations between Social, Biologic, and Behavioral Factors and Biomarkers of Oxidative Stress during Pregnancy: Findings from Four ECHO Cohorts. Sci. Total Environ. 2022, 835, 155596 DOI: 10.1016/j.scitotenv.2022.155596There is no corresponding record for this reference.
- 25Eick, S. M.; Geiger, S. D.; Alshawabkeh, A.; Aung, M.; Barrett, E. S.; Bush, N.; Carroll, K. N.; Cordero, J. F.; Goin, D. E.; Ferguson, K. K.; Kahn, L. G.; Liang, D.; Meeker, J. D.; Milne, G. L.; Nguyen, R. H. N.; Padula, A. M.; Sathyanarayana, S.; Taibl, K. R.; Schantz, S. L.; Woodruff, T. J.; Morello-Frosch, R. Urinary Oxidative Stress Biomarkers Are Associated with Preterm Birth: An Environmental Influences on Child Health Outcomes Program Study. Am. J. Obstet. Gynecol. 2023, 228 (5), 576.e1– 576.e22, DOI: 10.1016/j.ajog.2022.11.1282There is no corresponding record for this reference.
- 26Morello-Frosch, R.; Cushing, L. J.; Jesdale, B. M.; Schwartz, J. M.; Guo, W.; Guo, T.; Wang, M.; Harwani, S.; Petropoulou, S.-S. E.; Duong, W.; Park, J.-S.; Petreas, M.; Gajek, R.; Alvaran, J.; She, J.; Dobraca, D.; Das, R.; Woodruff, T. J. Environmental Chemicals in an Urban Population of Pregnant Women and Their Newborns from San Francisco. Environ. Sci. Technol. 2016, 50 (22), 12464– 12472, DOI: 10.1021/acs.est.6b0349226https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhs1SmtLjI&md5=59075dbb94c6c595a6145ca685274e8aEnvironmental Chemicals in an Urban Population of Pregnant Women and Their Newborns from San FranciscoMorello-Frosch, Rachel; Cushing, Lara J.; Jesdale, Bill M.; Schwartz, Jackie M.; Guo, Weihong; Guo, Tan; Wang, Miaomiao; Harwani, Suhash; Petropoulou, Syrago-Styliani E.; Duong, Wendy; Park, June-Soo; Petreas, Myrto; Gajek, Ryszard; Alvaran, Josephine; She, Jianwen; Dobraca, Dina; Das, Rupali; Woodruff, Tracey J.Environmental Science & Technology (2016), 50 (22), 12464-12472CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)In-utero exposure to environmental pollutants may increase the risk of adverse health effects. Concns. of 59 potentially harmful chems. (polychlorinated biphenyls [PCB], organochlorine pesticides [OCP], polybrominated di-Ph ethers [PBDE], hydroxylated PBDE [OH-PBDE], perfluorinated compds. [PFC]) were measured in 77 maternal and 65 paired umbilical cord blood serum samples collected in San Francisco, California, 2010-2011, and whole blood metal concns. Consistent with previous studies, evidence was found that Hg and lower-brominated PBDE concns. were often higher in umbilical cord blood or serum vs. maternal samples (median cord:maternal ratio >1); for most PFC and Pb, cord blood or serum concns. were generally less than or equal to their maternal pair (median cord:maternal ratio ≤1). Results showed evidence that several PCB and OCP also often had higher concns. in cord vs. maternal serum (median cord:maternal ratio >1) when concns. were assessed on a lipid-adjusted basis. Results suggested that for many chems., fetuses may experience higher exposure than their mothers, and highlighted the need to characterize potential health risks and inform policies to reduce exposure sources.
- 27Hornung, R. W.; Reed, L. D. Estimation of Average Concentration in the Presence of Nondetectable Values. Appl. Occup. Environ. Hyg. 1990, 5 (1), 46– 51, DOI: 10.1080/1047322X.1990.1038958727https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXltVyitr4%253D&md5=b254033f29a8e9b299fef9c92200cd06Estimation of average concentration in the presence of nondetectable valuesHornung, Richard W.; Reed, Laurence D.Applied Occupational and Environmental Hygiene (1990), 5 (1), 46-51CODEN: AOEHE9; ISSN:1047-322X.To est. the av. concn. of a particular contaminant during some period of time, a certain proportion of the collected samples is often reported to be below the limit of detection. The statistical terminol. for these results is censored data, i.e., nonzero values which cannot be measured but are known to be below some threshold. Samples taken over time are assumed to follow a lognormal distribution. Given this assumption, several techniques are presented for estn. of the av. concn. from data contg. nondetectable values. The techniques proposed include three methods of estn. with a left-censored lognormal distribution: a max. likelihood statistical method and two methods involving the limit of detection. Each method is evaluated using computer simulation with respect to the bias assocd. with estn. of the mean and std. deviation. The max. likelihood method produced unbiased ests. of both the mean and std. deviation under a variety of conditions. However, this method is somewhat complex and involves laborious calcns. and use of tables. Two simpler alternatives involve the substitution of L/2 and a new proposal of L/√‾2 for each nondetectable value, where L = the limit of detection. The new method provided more accurate estn. of the mean and std. deviation than the L/2 method when the data are not highly skewed. The L/2 method should be used when the data are highly skewed (geometric std. deviation ≥3.0 or greater).
- 28Afshinnia, F.; Zeng, L.; Byun, J.; Wernisch, S.; Deo, R.; Chen, J.; Hamm, L.; Miller, E. R.; Rhee, E. P.; Fischer, M. J.; Sharma, K.; Feldman, H. I.; Michailidis, G.; Pennathur, S.; CRIC Study Investigators Elevated Lipoxygenase and Cytochrome P450 Products Predict Progression of Chronic Kidney Disease. Nephrol., Dial., Transplant. 2020, 35 (2), 303– 312, DOI: 10.1093/ndt/gfy232There is no corresponding record for this reference.
- 29Keil, A. P.; Buckley, J. P.; O’Brien, K. M.; Ferguson, K. K.; Zhao, S.; White, A. J. A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures. Environ. Health Perspect. 2020, 128 (4), 047004 DOI: 10.1289/EHP583829https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB38zhslKqtw%253D%253D&md5=c667f3704295f9d3d52e4de297c594deA Quantile-Based g-Computation Approach to Addressing the Effects of Exposure MixturesKeil Alexander P; Keil Alexander P; O'Brien Katie M; Ferguson Kelly K; White Alexandra J; Buckley Jessie P; Buckley Jessie P; Zhao ShanshanEnvironmental health perspectives (2020), 128 (4), 47004 ISSN:.BACKGROUND: Exposure mixtures frequently occur in data across many domains, particularly in the fields of environmental and nutritional epidemiology. Various strategies have arisen to answer questions about exposure mixtures, including methods such as weighted quantile sum (WQS) regression that estimate a joint effect of the mixture components. OBJECTIVES: We demonstrate a new approach to estimating the joint effects of a mixture: quantile g-computation. This approach combines the inferential simplicity of WQS regression with the flexibility of g-computation, a method of causal effect estimation. We use simulations to examine whether quantile g-computation and WQS regression can accurately and precisely estimate the effects of mixtures in a variety of common scenarios. METHODS: We examine the bias, confidence interval (CI) coverage, and bias-variance tradeoff of quantile g-computation and WQS regression and how these quantities are impacted by the presence of noncausal exposures, exposure correlation, unmeasured confounding, and nonlinearity of exposure effects. RESULTS: Quantile g-computation, unlike WQS regression, allows inference on mixture effects that is unbiased with appropriate CI coverage at sample sizes typically encountered in epidemiologic studies and when the assumptions of WQS regression are not met. Further, WQS regression can magnify bias from unmeasured confounding that might occur if important components of the mixture are omitted from the analysis. DISCUSSION: Unlike inferential approaches that examine the effects of individual exposures while holding other exposures constant, methods like quantile g-computation that can estimate the effect of a mixture are essential for understanding the effects of potential public health actions that act on exposure sources. Our approach may serve to help bridge gaps between epidemiologic analysis and interventions such as regulations on industrial emissions or mining processes, dietary changes, or consumer behavioral changes that act on multiple exposures simultaneously. https://doi.org/10.1289/EHP5838.
- 30Taibl, K. R.; Schantz, S.; Aung, M. T.; Padula, A.; Geiger, S.; Smith, S.; Park, J.-S.; Milne, G. L.; Robinson, J. F.; Woodruff, T. J.; Morello-Frosch, R.; Eick, S. M. Associations of Per- and Polyfluoroalkyl Substances (PFAS) and Their Mixture with Oxidative Stress Biomarkers during Pregnancy. Environ. Int. 2022, 169, 107541 DOI: 10.1016/j.envint.2022.10754130https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38Xis1GnurnN&md5=427961af0e3b2575dcc83c2cc8ec8b8dAssociations of per- and polyfluoroalkyl substances (PFAS) and their mixture with oxidative stress biomarkers during pregnancyTaibl, Kaitlin R.; Schantz, Susan; Aung, Max T.; Padula, Amy; Geiger, Sarah; Smith, Sabrina; Park, June-Soo; Milne, Ginger L.; Robinson, Joshua F.; Woodruff, Tracey J.; Morello-Frosch, Rachel; Eick, Stephanie M.Environment International (2022), 169 (), 107541CODEN: ENVIDV; ISSN:0160-4120. (Elsevier Ltd.)Oxidative stress from excess reactive oxygen species (ROS) is a hypothesized contributor to preterm birth. Per- and polyfluoroalkyl substances (PFAS) exposure is reported to generate ROS in lab. settings, and is linked to adverse birth outcomes globally. However, to our knowledge, the relationship between PFAS and oxidative stress has not been examd. in the context of human pregnancy. To investigate the assocns. between prenatal PFAS exposure and oxidative stress biomarkers among pregnant people. Our analytic sample included 428 participants enrolled in the Illinois Kids Development Study and Chems. In Our Bodies prospective birth cohorts between 2014 and 2019. Twelve PFAS were measured in second trimester serum. We focused on seven PFAS that were detected in >65 % of participants. Urinary levels of 8-isoprostane-prostaglandin-F2α, prostaglandin-F2α, 2,3-dinor-8-iso-PGF2α, and 2,3-dinor-5,6-dihydro-8-iso-PGF2α were measured in the second and third trimesters as biomarkers of oxidative stress. We fit linear mixed-effects models to est. individual assocns. between PFAS and oxidative stress biomarkers. We used quantile g-computation and Bayesian kernel machine regression (BKMR) to assess assocns. between the PFAS mixt. and averaged oxidative stress biomarkers. Linear mixed-effects models showed that an interquartile range increase in perfluorooctane sulfonic acid (PFOS) was assocd. with an increase in 8-isoprostane-prostaglandin-F2α (β = 0.10, 95 % confidence interval = 0, 0.20). In both quantile g-computation and BKMR, and across all oxidative stress biomarkers, PFOS contributed the most to the overall mixt. effect. The six remaining PFAS were not significantly assocd. with changes in oxidative stress biomarkers. Our study is the first to investigate the relationship between PFAS exposure and biomarkers of oxidative stress during human pregnancy. We found that PFOS was assocd. with elevated levels of oxidative stress, which is consistent with prior work in animal models and cell lines. Future research is needed to understand how prenatal PFAS exposure and maternal oxidative stress may affect fetal development.
- 31Braveman, P. A.; Cubbin, C.; Egerter, S.; Chideya, S.; Marchi, K. S.; Metzler, M.; Posner, S. Socioeconomic Status in Health ResearchOne Size Does Not Fit All. JAMA 2005, 294 (22), 2879– 2888, DOI: 10.1001/jama.294.22.2879There is no corresponding record for this reference.
- 32McAdam, J.; Bell, E. M. Determinants of Maternal and Neonatal PFAS Concentrations: A Review. Environ. Health 2023, 22 (1), 41 DOI: 10.1186/s12940-023-00992-x32https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXpsl2it7k%253D&md5=226c3078c19e0c4f720233db4d2da5d1Determinants of maternal and neonatal PFAS concentrations: a reviewMcAdam, Jordan; Bell, Erin M.Environmental Health (London, United Kingdom) (2023), 22 (1), 41CODEN: EHAGAB; ISSN:1476-069X. (BioMed Central Ltd.)A review. Per- and polyfluoroalkyl substances (PFAS) are used for their properties such as stain and water resistance. The substances have been assocd. with adverse health outcomes in both pregnant mothers and infants, including pre-eclampsia and low birthweight. A growing body of research suggests that PFAS are transferred from mother to fetus through the placenta, leading to in utero exposure. A systematic review was performed using the PubMed database to search for studies evaluating determinants of PFAS concns. in blood matrixes of pregnant mothers and neonates shortly after birth. Studies were included in this review if an observational study design was utilized, exposure to at least one PFAS analyte was measured, PFAS were measured in maternal or neonatal matrixes, at least one determinant of PFAS concns. was assessed, and results such as beta ests. were provided. We identified 35 studies for inclusion in the review and evaluated the PFAS and determinant relationships among the factors collected in these studies. Parity, breastfeeding history, maternal race and country of origin, and household income had the strongest and most consistent evidence to support their roles as determinants of certain PFAS concns. in pregnant mothers. Reported study findings on smoking status, alc. consumption, and pre-pregnancy body mass index (BMI) suggest that these factors are not important determinants of PFAS concns. in pregnant mothers or neonates. Further study into informative factors such as consumer product use, detailed dietary information, and consumed water sources as potential determinants of maternal or neonatal PFAS concns. is needed. Research on determinants of maternal or neonatal PFAS concns. is crit. to est. past PFAS exposure, build improved exposure models, and further our understanding on dose-response relationships, which can influence epidemiol. studies and risk assessment evaluations. Given the potential for adverse outcomes in pregnant mothers and neonates exposed to PFAS, it is important to identify and understand determinants of maternal and neonatal PFAS concns. to better implement public health interventions in these populations.
- 33Stephens, C. R.; Easton, J. F.; Robles-Cabrera, A.; Fossion, R.; de la Cruz, L.; Martínez-Tapia, R.; Barajas-Martínez, A.; Hernández-Chávez, A.; López-Rivera, J. A.; Rivera, A. L. The Impact of Education and Age on Metabolic Disorders. Front. Public Health 2020, 8, 180, DOI: 10.3389/fpubh.2020.00180There is no corresponding record for this reference.
- 34Storey, J. D.; Bass, A. J.; Dabney, A.; Robinson, D.; Warnes, G. Qvalue: Q-Value Estimation for False Discovery Rate Control, 2023. http://github.com/jdstorey/qvalue.There is no corresponding record for this reference.
- 35Willer, C. J.; Li, Y.; Abecasis, G. R. METAL: Fast and Efficient Meta-Analysis of Genomewide Association Scans. Bioinformatics 2010, 26 (17), 2190– 2191, DOI: 10.1093/bioinformatics/btq34035https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtVGru73F&md5=d377a9f6119f912e83bef351aa8909afMETAL: fast and efficient meta-analysis of genomewide association scansWiller, Cristen J.; Li, Yun; Abecasis, Goncalo R.Bioinformatics (2010), 26 (17), 2190-2191CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)METAL provides a computationally efficient tool for meta-anal. of genome-wide assocn. scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: [email protected].
- 36Carrico, C.; Gennings, C.; Wheeler, D. C.; Factor-Litvak, P. Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting. J. Agric. Biol. Environ. Stat. 2015, 20 (1), 100– 120, DOI: 10.1007/s13253-014-0180-336https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3crns1Gnsg%253D%253D&md5=3c9738d976b0c9791be0aeec9f342225Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis SettingCarrico Caroline; Gennings Chris; Wheeler David C; Factor-Litvak PamJournal of agricultural, biological, and environmental statistics (2015), 20 (1), 100-120 ISSN:1085-7117.In risk evaluation, the effect of mixtures of environmental chemicals on a common adverse outcome is of interest. However, due to the high dimensionality and inherent correlations among chemicals that occur together, the traditional methods (e.g. ordinary or logistic regression) suffer from collinearity and variance inflation, and shrinkage methods have limitations in selecting among correlated components. We propose a weighted quantile sum (WQS) approach to estimating a body burden index, which identifies "bad actors" in a set of highly correlated environmental chemicals. We evaluate and characterize the accuracy of WQS regression in variable selection through extensive simulation studies through sensitivity and specificity (i.e., ability of the WQS method to select the bad actors correctly and not incorrect ones). We demonstrate the improvement in accuracy this method provides over traditional ordinary regression and shrinkage methods (lasso, adaptive lasso, and elastic net). Results from simulations demonstrate that WQS regression is accurate under some environmentally relevant conditions, but its accuracy decreases for a fixed correlation pattern as the association with a response variable diminishes. Nonzero weights (i.e., weights exceeding a selection threshold parameter) may be used to identify bad actors; however, components within a cluster of highly correlated active components tend to have lower weights, with the sum of their weights representative of the set.
- 37Czarnota, J.; Gennings, C.; Wheeler, D. C. Assessment of Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk. Cancer Inf. 2015, 14s2 (Suppl 2), CIN-S17295 DOI: 10.4137/CIN.S17295There is no corresponding record for this reference.
- 38Ferguson, K. K.; Chin, H. B. Environmental Chemicals and Preterm Birth: Biological Mechanisms and the State of the Science. Curr. Epidemiol. Rep. 2017, 4 (1), 56– 71, DOI: 10.1007/s40471-017-0099-7There is no corresponding record for this reference.
- 39Gomez-Lopez, N.; Galaz, J.; Miller, D.; Farias-Jofre, M.; Liu, Z.; Arenas-Hernandez, M.; Garcia-Flores, V.; Shaffer, Z.; Greenberg, J. M.; Theis, K. R.; Romero, R. The Immunobiology of Preterm Labor and Birth: Intra-Amniotic Inflammation or Breakdown of Maternal-Fetal Homeostasis. Reproduction 2022, 164 (2), R11– R45, DOI: 10.1530/REP-22-0046There is no corresponding record for this reference.
- 40Ricciotti, E.; FitzGerald, G. A. Prostaglandins and Inflammation. Arterioscler., Thromb., Vasc. Biol. 2011, 31 (5), 986– 1000, DOI: 10.1161/ATVBAHA.110.20744940https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvFantbs%253D&md5=1e08aa9b4ac193f0f433dd121a6b5340Prostaglandins and InflammationRicciotti, Emanuela; FitzGerald, Garret A.Arteriosclerosis, Thrombosis, and Vascular Biology (2011), 31 (5), 986-1000CODEN: ATVBFA; ISSN:1079-5642. (Lippincott Williams & Wilkins)A review. Prostaglandins are lipid autacoids derived from arachidonic acid. They both sustain homeostatic functions and mediate pathogenic mechanisms, including the inflammatory response. They are generated from arachidonate by the action of cyclooxygenase isoenzymes, and their biosynthesis is blocked by nonsteroidal antiinflammatory drugs, including those selective for inhibition of cyclooxygenase-2. Despite the clin. efficacy of nonsteroidal antiinflammatory drugs, prostaglandins may function in both the promotion and resoln. of inflammation. This review summarizes insights into the mechanisms of prostaglandin generation and the roles of individual mediators and their receptors in modulating the inflammatory response. Prostaglandin biol. has potential clin. relevance for atherosclerosis, the response to vascular injury and aortic aneurysm.
- 41Burdon, C.; Mann, C.; Cindrova-Davies, T.; Ferguson-Smith, A. C.; Burton, G. J. Oxidative Stress and the Induction of Cyclooxygenase Enzymes and Apoptosis in the Murine Placenta. Placenta 2007, 28 (7), 724– 733, DOI: 10.1016/j.placenta.2006.12.001There is no corresponding record for this reference.
- 42Xu, Y.; Wang, Q.; Cook, T. J.; Knipp, G. T. Effect of Placental Fatty Acid Metabolism and Regulation by Peroxisome Proliferator Activated Receptor on Pregnancy and Fetal Outcomes. J. Pharm. Sci. 2007, 96 (10), 2582– 2606, DOI: 10.1002/jps.20973There is no corresponding record for this reference.
- 43Davis-Bruno, K.; Tassinari, M. S. Essential Fatty Acid Supplementation of DHA and ARA and Effects on Neurodevelopment across Animal Species: A Review of the Literature. Birth Defects Res., Part B 2011, 92 (3), 240– 250, DOI: 10.1002/bdrb.20311There is no corresponding record for this reference.
- 44Wong, C. T.; Bestard-Lorigados, I.; Crawford, D. A. Autism-Related Behaviors in the Cyclooxygenase-2-Deficient Mouse Model. Genes Brain Behav. 2019, 18 (1), e12506 DOI: 10.1111/gbb.12506There is no corresponding record for this reference.
- 45Corwin, C.; Nikolopoulou, A.; Pan, A. L.; Nunez-Santos, M.; Vallabhajosula, S.; Serrano, P.; Babich, J.; Figueiredo-Pereira, M. E. Prostaglandin D2/J2 Signaling Pathway in a Rat Model of Neuroinflammation Displaying Progressive Parkinsonian-like Pathology: Potential Novel Therapeutic Targets. J. Neuroinflammation 2018, 15, 272 DOI: 10.1186/s12974-018-1305-3There is no corresponding record for this reference.
- 46Hildreth, K.; Kodani, S. D.; Hammock, B. D.; Zhao, L. Cytochrome P450-Derived Linoleic Acid Metabolites EpOMEs and DiHOMEs: A Review of Recent Studies. J. Nutr. Biochem. 2020, 86, 108484 DOI: 10.1016/j.jnutbio.2020.10848446https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhvV2mtLrJ&md5=617ddc14fc8ae82adf742a96ac858586Cytochrome P450-derived linoleic acid metabolites EpOMEs and DiHOMEs: a review of recent studiesHildreth, Kelsey; Kodani, Sean D.; Hammock, Bruce D.; Zhao, LingJournal of Nutritional Biochemistry (2020), 86 (), 108484CODEN: JNBIEL; ISSN:0955-2863. (Elsevier Inc.)A review. Linoleic acid (LA) is the most abundant polyunsatd. fatty acid found in the Western diet. Cytochrome P 450-derived LA metabolites 9,10-epoxyoctadecenoic acid (9,10-EpOME), 12,13-epoxyoctadecenoic acid (12,13-EpOME), 9,10-dihydroxy-12Z-octadecenoic acid (9,10-DiHOME) and 12,13-dihydroxy-9Z-octadecenoic acid (12,13-DiHOME) have been studied for their assocn. with various disease states and biol. functions. Previous studies of the EpOMEs and DiHOMEs have focused on their roles in cytotoxic processes, primarily in the inhibition of the neutrophil respiratory burst. More recent research has suggested the DiHOMEs may be important lipid mediators in pain perception, altered immune response and brown adipose tissue activation by cold and exercise. The purpose of this review is to summarize the current understanding of the physiol. and pathophysiol. roles and modes of action of the EpOMEs and DiHOMEs in health and disease.
- 47Macêdo, A. P. A.; Muñoz, V. R.; Cintra, D. E.; Pauli, J. R. 12,13-diHOME as a New Therapeutic Target for Metabolic Diseases. Life Sci. 2022, 290, 120229 DOI: 10.1016/j.lfs.2021.120229There is no corresponding record for this reference.
- 48Dalle Vedove, F.; Fava, C.; Jiang, H.; Zanconato, G.; Quilley, J.; Brunelli, M.; Guglielmi, V.; Vattemi, G.; Minuz, P. Increased Epoxyeicosatrienoic Acids and Reduced Soluble Epoxide Hydrolase Expression in the Preeclamptic Placenta. J. Hypertens. 2016, 34 (7), 1364– 1370, DOI: 10.1097/HJH.0000000000000942There is no corresponding record for this reference.
- 49Herse, F.; LaMarca, B.; Hubel, C. A.; Kaartokallio, T.; Lokki, A. I.; Ekholm, E.; Laivuori, H.; Gauster, M.; Huppertz, B.; Sugulle, M.; Ryan, M. J.; Novotny, S.; Brewer, J.; Park, J.-K.; Kacik, M.; Hoyer, J.; Verlohren, S.; Wallukat, G.; Rothe, M.; Luft, F. C.; Muller, D. N.; Schunck, W.-H.; Staff, A. C.; Dechend, R. Cytochrome P450 Subfamily 2J Polypeptide 2 Expression and Circulating Epoxyeicosatrienoic Metabolites in Preeclampsia. Circulation 2012, 126 (25), 2990– 2999, DOI: 10.1161/CIRCULATIONAHA.112.127340There is no corresponding record for this reference.
- 50Ghisari, M.; Eiberg, H.; Long, M.; Bonefeld-Jørgensen, E. C. Polymorphisms in Phase I and Phase II Genes and Breast Cancer Risk and Relations to Persistent Organic Pollutant Exposure: A Case–Control Study in Inuit Women. Environ. Health 2014, 13, 19 DOI: 10.1186/1476-069X-13-19There is no corresponding record for this reference.
- 51Mashima, R.; Okuyama, T. The Role of Lipoxygenases in Pathophysiology; New Insights and Future Perspectives. Redox Biol. 2015, 6, 297– 310, DOI: 10.1016/j.redox.2015.08.00651https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlSnt7fJ&md5=4ef4d8e6e8db03f70dacaebd5c086277The role of lipoxygenases in pathophysiology; new insights and future perspectivesMashima, Ryuichi; Okuyama, TorayukiRedox Biology (2015), 6 (), 297-310CODEN: RBEIB3; ISSN:2213-2317. (Elsevier B.V.)Lipoxygenases (LOXs) are dioxygenases that catalyze the formation of corresponding hydroperoxides from polyunsatd. fatty acids such as linoleic acid and arachidonic acid. LOX enzymes are expressed in immune, epithelial, and tumor cells that display a variety of physiol. functions, including inflammation, skin disorder, and tumorigenesis. In the humans and mice, six LOX isoforms have been known. 15-LOX, a prototypical enzyme originally found in reticulocytes shares the similarity of amino acid sequence as well as the biochem. property to plant LOX enzymes. 15-LOX-2, which is expressed in epithelial cells and leukocytes, has different substrate specificity in the humans and mice, therefore, the role of them in mammals has not been established. 12-LOX is an isoform expressed in epithelial cells and myeloid cells including platelets. Many mutations in this isoform are found in epithelial cancers, suggesting a potential link between 12-LOX and tumorigenesis. 12R-LOX can be found in the epithelial cells of the skin. Defects in this gene result in ichthyosis, a cutaneous disorder characterized by pathophysiol. dried skin due to abnormal loss of water from its epithelial cell layer. Similarly, eLOX-3, which is also expressed in the skin epithelial cells acting downstream 12R-LOX, is another causative factor for ichthyosis. 5-LOX is a distinct isoform playing an important role in asthma and inflammation. This isoform causes the constriction of bronchioles in response to cysteinyl leukotrienes such as LTC4, thus leading to asthma. It also induces neutrophilic inflammation by its recruitment in response to LTB4. Importantly, 5-LOX activity is strictly regulated by 5-LOX activating protein (FLAP) though the distribution of 5-LOX in the nucleus. Currently, pharmacol. drugs targeting FLAP are actively developing. This review summarized these functions of LOX enzymes under pathophysiol. conditions in mammals.
- 52Rhee, S. Y.; Jung, E. S.; Suh, D. H.; Jeong, S. J.; Kim, K.; Chon, S.; Yu, S.-Y.; Woo, J.-T.; Lee, C. H. Plasma Amino Acids and Oxylipins as Potential Multi-Biomarkers for Predicting Diabetic Macular Edema. Sci. Rep. 2021, 11, 9727 DOI: 10.1038/s41598-021-88104-yThere is no corresponding record for this reference.
- 53Sergeant, S.; Hugenschmidt, C. E.; Rudock, M. E.; Ziegler, J. T.; Ivester, P.; Ainsworth, H. C.; Vaidya, D.; Case, L. D.; Langefeld, C. D.; Freedman, B. I.; Bowden, D. W.; Mathias, R. A.; Chilton, F. H. Differences in Arachidonic Acid Levels and Fatty Acid Desaturase (FADS) Gene Variants in African Americans and European Americans with Diabetes or the Metabolic Syndrome. Br. J. Nutr. 2012, 107 (4), 547– 555, DOI: 10.1017/S0007114511003230There is no corresponding record for this reference.
- 54Saadatian-Elahi, M.; Slimani, N.; Chajès, V.; Jenab, M.; Goudable, J.; Biessy, C.; Ferrari, P.; Byrnes, G.; Autier, P.; Peeters, P. H. M.; Ocké, M.; Bueno de Mesquita, B.; Johansson, I.; Hallmans, G.; Manjer, J.; Wirfält, E.; González, C. A.; Navarro, C.; Martinez, C.; Amiano, P.; Suárez, L. R.; Ardanaz, E.; Tjønneland, A.; Halkjaer, J.; Overvad, K.; Jakobsen, M. U.; Berrino, F.; Pala, V.; Palli, D.; Tumino, R.; Vineis, P.; Santucci de Magistris, M.; Spencer, E. A.; Crowe, F. L.; Bingham, S.; Khaw, K.-T.; Linseisen, J.; Rohrmann, S.; Boeing, H.; Noethlings, U.; Olsen, K. S.; Skeie, G.; Lund, E.; Trichopoulou, A.; Oustoglou, E.; Clavel-Chapelon, F.; Riboli, E. Plasma Phospholipid Fatty Acid Profiles and Their Association with Food Intakes: Results from a Cross-Sectional Study within the European Prospective Investigation into Cancer and Nutrition. Am. J. Clin. Nutr. 2009, 89 (1), 331– 346, DOI: 10.3945/ajcn.2008.26834There is no corresponding record for this reference.
- 55Goodrich, J. A.; Walker, D. I.; He, J.; Lin, X.; Baumert, B. O.; Hu, X.; Alderete, T. L.; Chen, Z.; Valvi, D.; Fuentes, Z. C.; Rock, S.; Wang, H.; Berhane, K.; Gilliland, F. D.; Goran, M. I.; Jones, D. P.; Conti, D. V.; Chatzi, L. Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study. Environ. Health Perspect. 2023, 131 (2), 027005 DOI: 10.1289/EHP11372There is no corresponding record for this reference.
- 56Guidance on PFAS Exposure, Testing, and Clinical Follow-Up; National Academies Press: Washington, D.C., 2022 DOI: 10.17226/26156 .There is no corresponding record for this reference.
- 57EFSA Panel on Contaminants in the Food Chain (CONTAM); Knutsen, H. K.; Alexander, J.; Barregård, L.; Bignami, M.; Brüschweiler, B.; Ceccatelli, S.; Cottrill, B.; Dinovi, M.; Edler, L.; Grasl-Kraupp, B.; Hogstrand, C.; Hoogenboom, L. R.; Nebbia, C. S.; Oswald, I. P.; Petersen, A.; Rose, M.; Roudot, A.-C.; Vleminckx, C.; Vollmer, G.; Wallace, H.; Bodin, L.; Cravedi, J.-P.; Halldorsson, T. I.; Haug, L. S.; Johansson, N.; van Loveren, H.; Gergelova, P.; Mackay, K.; Levorato, S.; van Manen, M.; Schwerdtle, T. Risk to Human Health Related to the Presence of Perfluorooctane Sulfonic Acid and Perfluorooctanoic Acid in Food. EFSA J. 2018, 16 (12), e05194 DOI: 10.2903/j.efsa.2018.5194There is no corresponding record for this reference.
- 58Christensen, K. Y.; Raymond, M.; Blackowicz, M.; Liu, Y.; Thompson, B. A.; Anderson, H. A.; Turyk, M. Perfluoroalkyl Substances and Fish Consumption. Environ. Res. 2017, 154, 145– 151, DOI: 10.1016/j.envres.2016.12.03258https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXmsV2ktA%253D%253D&md5=a3e61934bdd38e79583b9deda2165f32Perfluoroalkyl substances and fish consumptionChristensen, Krista Y.; Raymond, Michelle; Blackowicz, Michael; Liu, Yangyang; Thompson, Brooke A.; Anderson, Henry A.; Turyk, MaryEnvironmental Research (2017), 154 (), 145-151CODEN: ENVRAL; ISSN:0013-9351. (Elsevier)Perfluoroalkyl substances (PFAS) are an emerging class of contaminants. Certain PFAS are regulated or voluntarily limited due to concern about environmental persistence and adverse health effects, including thyroid disease and dyslipidemia. The major source of PFAS exposure in the general population is thought to be consumption of seafood. In this anal. we examine PFAS levels and their determinants, as well as assocns. between PFAS levels and self-reported fish and shellfish consumption, using a representative sample of the U.S. population. Data on PFAS levels and self-reported fish consumption over the past 30 days were collected from the 2007-2008, 2009-2010, 2011-2012, and 2013-2014 cycles of the National Health and Nutrition Examn. Survey. Twelve different PFAS were measured in serum samples from participants. Ordinary least squares regression models were used to identify factors (demog. characteristics and fish consumption habits) assocd. with serum PFAS concns. Addnl. models were further adjusted for other potential exposures including military service and consumption of ready-to-eat and fast foods. Seven PFAS were detected in at least 30% of participants and were examd. in subsequent analyses (PFDA, PFOA, PFOS, PFHxS, MPAH, PFNA, PFUA). The PFAS with the highest concns. were PFOS, followed by PFOA, PFHxS and PFNA (medians of 8.3, 2.7, 1.5 and 1.0 ng/mL). Fish consumption was generally low, with a median of 1.2 fish meals and 0.14 shellfish meals, reported over the past 30 days. After adjusting for demog. characteristics, total fish consumption was assocd. with reduced MPAH, and with elevated PFDE, PFNA and PFuDA. Shellfish consumption was assocd. with elevations of all PFAS examd. except MPAH. Certain specific fish and shellfish types were also assocd. with specific PFAS. Adjustment for addnl. exposure variables resulted in little to no change in effect ests. for seafood variables. PFAS are emerging contaminants with widespread exposure, persistence, and potential for adverse health effects. In the general population, fish and shellfish consumption are assocd. with PFAS levels, which may indicate an avenue for education and outreach.
- 59Chen, B.; McClements, D. J.; Decker, E. A. Design of Foods with Bioactive Lipids for Improved Health. Annu. Rev. Food Sci. Technol. 2013, 4, 35– 56, DOI: 10.1146/annurev-food-032112-135808There is no corresponding record for this reference.
- 60Zhang, X.; Zhao, L.; Ducatman, A.; Deng, C.; von Stackelberg, K. E.; Danford, C. J.; Zhang, X. Association of Per- and Polyfluoroalkyl Substance Exposure with Fatty Liver Disease Risk in US Adults. JHEP Rep. 2023, 5 (5), 100694 DOI: 10.1016/j.jhepr.2023.100694There is no corresponding record for this reference.
- 61Roth, K.; Petriello, M. C. Exposure to Per- and Polyfluoroalkyl Substances (PFAS) and Type 2 Diabetes Risk. Front. Endocrinol. 2022, 13, 965384 DOI: 10.3389/fendo.2022.965384There is no corresponding record for this reference.
- 62Athyros, V. G.; Doumas, M.; Imprialos, K. P.; Stavropoulos, K.; Georgianou, E.; Katsimardou, A.; Karagiannis, A. Diabetes and Lipid Metabolism. Hormones 2018, 17 (1), 61– 67, DOI: 10.1007/s42000-018-0014-8There is no corresponding record for this reference.
- 63Paul, B.; Lewinska, M.; Andersen, J. B. Lipid Alterations in Chronic Liver Disease and Liver Cancer. JHEP Rep. 2022, 4 (6), 100479 DOI: 10.1016/j.jhepr.2022.100479There is no corresponding record for this reference.
- 64Zheng, G.; Eick, S. M.; Salamova, A. Elevated Levels of Ultrashort- and Short-Chain Perfluoroalkyl Acids in US Homes and People. Environ. Sci. Technol. 2023, 57 (42), 15782– 15793, DOI: 10.1021/acs.est.2c0671564https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3sXitVynur3E&md5=026693b740aa19df2ee504d87deaceb7Elevated Levels of Ultrashort- and Short-Chain Perfluoroalkyl Acids in US Homes and PeopleZheng, Guomao; Eick, Stephanie M.; Salamova, AminaEnvironmental Science & Technology (2023), 57 (42), 15782-15793CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)Per- and polyfluoroalkyl substances (PFAS) make up a large group of fluorinated org. compds. extensively used in consumer products and industrial applications. Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), the two perfluoroalkyl acids (PFAAs) with 8 carbons in their structure, were phased out on a global scale because of their high environmental persistence and toxicity. As a result, shorter-chain PFAAs with \<8 carbons in their structure are being used as their replacements and are now widely detected in the environment, raising concerns about their effects on the environment and human health. In this study, 47 PFAAs and their precursors were measured in paired samples of dust and drinking water collected from residential homes in Indiana, United States, and in blood and urine samples collected from the residents of these homes. Ultrashort- (with 2 or 3 carbons [C2-C3]) and short-chain (with 4-7 carbons [C4-C7]) PFAAs were the most abundant in all four matrixes and constituted on av. 69-100% of the total PFAA concns. Specifically, trifluoroacetic acid (TFA, C2) and perfluoropropanoic acid (PFPrA, C3) were the predominant PFAA congeners in most of the samples. Significant pos. correlations (n = 81; r = 0.23-0.42; p < 0.05) were found between TFA, perfluorobutanoic acid (PFBA, C4) and perfluoroheptanoic acid (PFHpA, C7) concns. in dust or water and those in serum, suggesting dust ingestion and/or drinking water consumption as important exposure pathways for these compds. This study demonstrates that ultrashort- and short-chain PFAAs are now abundant in the indoor environment and in people and warrants further research on potential adverse health effects of these exposures.
- 65Gao, P. The Exposome in the Era of One Health. Environ. Sci. Technol. 2021, 55 (5), 2790– 2799, DOI: 10.1021/acs.est.0c0703365https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXmsFCgug%253D%253D&md5=45813c73d5ec6a42624653c25b42ca21The exposome in the era of One HealthGao, PengEnvironmental Science & Technology (2021), 55 (5), 2790-2799CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)A review. Current studies on environmental chem. mainly focus on a single stressor or single group of stressors, which does not reflect the multiple stressors in the dynamic exposome the authors are facing. Similarly, current studies on environmental toxicol. mostly target humans, animals, or the environment sep., which are inadequate to solve the grand challenge of multiple receptors in One Health. Though chem., biol., and phys. stressors all pose health threats, the susceptibilities of different organisms are different. As such, significant relationships and interactions of the chem., biol., and phys. stressors in the environment and their holistic environmental and biol. consequences remain unclear. Fortunately, the rapid developments in various techniques, as well as the concepts of multistressors in the exposome and multireceptor in One Health provide the possibilities to understand the authors' environment better. Since the combined stressor is location-specific and mixt. toxicity is species-specific, more comprehensive frameworks to guide risk assessment and environmental treatment are urgently needed. Here, three conceptual frameworks to categorize unknown stressors, spatially visualize the riskiest stressors, and investigate the combined effects of multiple stressors across multiple species within the concepts of the exposome and One Health are proposed for the first time.
- 66Aung, M. T.; Yu, Y.; Ferguson, K. K.; Cantonwine, D. E.; Zeng, L.; McElrath, T. F.; Pennathur, S.; Mukherjee, B.; Meeker, J. D. Cross-Sectional Estimation of Endogenous Biomarker Associations with Prenatal Phenols, Phthalates, Metals, and Polycyclic Aromatic Hydrocarbons in Single-Pollutant and Mixtures Analysis Approaches. Environ. Health Perspect. 2021, 129 (3), 037007 DOI: 10.1289/EHP7396There is no corresponding record for this reference.
Supporting Information
Supporting Information
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c00094.
Flow diagram of final sample selection across CiOB, IKIDS, and PROTECT cohorts; directed acyclic graph of the relationships between maternal per- and poly-fluoroalkyl substances and bioactive lipids; correlation matrices of bioactive lipids and high-detect PFAS in the study cohorts (Appendix A. Supplementary Figures S1–S3) (PDF)
PFAS Detection Rates and Distributions Across Cohorts; Bioactive lipids sampled from maternal plasma; Bioactive Lipid Distribution Across Cohorts; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the CiOB Cohort; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the IKIDS Cohort; β Estimates and 95% Confidence Intervals for Associations Between Confounders and Bioactive Lipids/PFAS within the ECHO-PROTECT Cohort; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for random intercept model across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for random intercept model across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for meta-analysis across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated (p ≤ 0.05) with a Doubling in PFAS for meta-analysis across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for CiOB within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for CiOB within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for IKIDS within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for IKIDS within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for PROTECT within-cohort models, unadjusted; β Estimates and 95% Confidence Intervals Corresponding to Percentage Change in Bioactive Lipids associated with a Doubling in PFAS for PROTECT within-cohort models, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates Corresponding to Percentage Change in Bioactive Lipids associated with a 1-Quartile increase in log-transformed PFAS relative to first quartile for random intercept model across all 3 cohorts, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; β Estimates Corresponding to Percentage Change in Bioactive Lipids associated with a 1-Quartile increase in log-transformed PFAS relative to first quartile for random intercept model across CiOB & IKIDS, adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit; Quantile g-computation β Estimates Corresponding to Percentage Change in Bioactive Lipids as a Result of Simultaneous 1-Quartile Increase in All Log-Transformed PFAS, Model adjusted for Maternal Age, Maternal Education, Pre-Pregnancy BMI, Parity, Gestational Age at Visit, and Cohort; Comparison of Mixture Effects between Main Quantile G-Computation Results and Sensitivity Analysis Performing Stepwise Inclusion of Covariates; Comparison of Mixture Effects between Main Quantile G-Computation Results and Sensitivity Analysis Performing Multiple Imputation Supplementary data to this article can be found online (Appendix B. Supplementary Tables S1–S22) (XLSX)
ECHO OIF PFAS Lipids R Script (TXT)
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