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Background: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that persist in the environment and can accumulate in humans, leading to adverse health effects. MicroRNAs (miRNAs) are emerging biomarkers that can advance the understanding of the mechanisms of PFAS effects on human health. However, little is known about the associations between PFAS exposures and miRNA alterations in humans., Objective: To investigate associations between PFAS concentrations and miRNA levels in children., Methods: Data from two distinct cohorts were utilized: 176 participants (average age 17.1 years; 75.6% female) from the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) cohort in the United States, and 64 participants (average age 6.5 years, 39.1% female) from the Rhea study, a mother-child cohort in Greece. PFAS concentrations and miRNA levels were assessed in plasma samples from both studies. Associations between individual PFAS and plasma miRNA levels were examined after adjusting for covariates. Additionally, the cumulative effects of PFAS mixtures were evaluated using an exposure burden score. Ingenuity Pathways Analysis was employed to identify potential disease functions of PFAS-associated miRNAs., Results: Plasma PFAS concentrations were associated with alterations in 475 miRNAs in the Teen-LABs study and 5 miRNAs in the Rhea study (FDR p < 0.1). Specifically, plasma PFAS concentrations were consistently associated with decreased levels of miR-148b-3p and miR-29a-3p in both cohorts. Pathway analysis indicated that PFAS-related miRNAs were linked to numerous chronic disease pathways, including cardiovascular diseases, inflammatory conditions, and carcinogenesis., Conclusion: Through miRNA screenings in two independent cohorts, this study identified both known and novel miRNAs associated with PFAS exposure in children. Pathway analysis revealed the involvement of these miRNAs in several cancer and inflammation-related pathways. Further studies are warranted to enhance our understanding of the relationships between PFAS exposure and disease risks, with miRNA emerging as potential biomarkers and/or mediators in these complex pathways., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Vaia Lida Chatzi reports financial support was provided by The National Institute of Environmental Health Sciences. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Many epidemiological studies use a single blood sample per participant to assess exposure, but it is unclear how well a single sample represents longer term exposure. We performed a simulation study using summary statistics for repeated serum PFOA measurements from several previous studies in men to generate plausible serum concentrations over time, taking within-subject correlations into account. Simulated serum concentrations for controls were categorized into quintiles at each time point, and used to determine the extent of misclassification at each time point compared to the "true" long-term average exposure. We then generated case counts by quintile needed to produce an odds ratio (OR) of 1.5 for the highest vs. lowest quintile categorized based on long term exposure, and used the same misclassification rates observed in the controls to simulate misclassified exposure quintiles for cases. Comparing long term vs. single baseline exposure measures for repeated serum samples collected within about 5-13 years of each other revealed similar effect estimates, although there was a small bias to the null. Trend tests across quintiles were mostly significant using either baseline or long-term exposure. For the general population sample of men in Norway, with 5 repeated measurements over 28 years, serum PFOA was substantially lower prior to 1987, and using either of the two earliest samples as the exposure metric, compared to the long term average, produced larger bias to the null and non-significant trend tests; however using later time points as the exposure metric resulted in only a small bias. Using data based on studies of men, single baseline serum samples represented rather well the mean of repeated samples collectedup to 13 years apart, but were not always reliable surrogates for average exposure over 3 decades, during which time PFOA exposure levels in the general population have changed substantially., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Scott M. Bartell has served as a compensated expert witness for PFOA medical monitoring lawsuits in New Hampshire. The terms of this arrangement were reviewed and approved by the University of California, Irvine in accordance with its conflict-of-interest policies. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

To address the growing epidemic of liver disease, particularly in pediatric populations, it is crucial to identify modifiable risk factors for the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Per- and polyfluoroalkyl substances (PFAS) are persistent ubiquitous chemicals and have emerged as potential risk factors for liver damage. However, their impact on the etiology and severity of MASLD remains largely unexplored in humans. This study aims to bridge the gap between human and in vitro studies to understand how exposure to perfluoroheptanoic acid (PFHpA), one of the emerging PFAS replacements which accumulates in high concentrations in the liver, contributes to MASLD risk and progression. First, we showed that PFHpA plasma concentrations were significantly associated with increased risk of MASLD in obese adolescents. Further, we examined the impact of PFHpA on hepatic metabolism using 3D human liver spheroids and single-cell transcriptomics to identify major hepatic pathways affected by PFHpA. Next, we integrated the in vivo and in vitro multi-omics datasets with a novel statistical approach which identified signatures of proteins and metabolites associated with MASLD development triggered by PFHpA exposure. In addition to characterizing the contribution of PFHpA to MASLD progression, our study provides a novel strategy to identify individuals at high risk of PFHpA-induced MASLD and develop early intervention strategies. Notably, our analysis revealed that the proteomic signature exhibited a stronger correlation between both PFHpA exposure and MASLD risk compared to the metabolomic signature. While establishing a clear connection between PFHpA exposure and MASLD progression in humans, our study delved into the molecular mechanisms through which PFHpA disrupts liver metabolism. Our in vitro findings revealed that PFHpA primarily impacts lipid metabolism, leading to a notable increase of lipid accumulation in human hepatocytes after PFHpA exposure. Among the pathways involved in lipid metabolism in hepatocytes, regulation of lipid metabolism by PPAR-a showed a remarkable activation. Moreover, the translational research framework we developed by integrating human and in vitro data provided us biomarkers to identify individuals at a high risk of MASLD due to PFHpA exposure. Our framework can inform policies on PFAS-induced liver disease and identify potential targets for prevention and treatment strategies.

The appropriate use of human biomonitoring data to model population chemical exposures is challenging, especially for rapidly metabolized chemicals, such as agricultural chemicals. The objective of this study is to demonstrate a novel approach integrating model predicted dietary exposures and biomonitoring data to potentially inform regulatory risk assessments. We use lambda-cyhalothrin as a case study, and for the same representative U.S. population in the National Health and Nutrition Examination Survey (NHANES), an integrated exposure and pharmacokinetic model predicted exposures are calibrated to measurements of the urinary metabolite 3-phenoxybenzoic acid (3PBA), using an approximate Bayesian computing (ABC) methodology. We demonstrate that the correlation between modeled urinary 3PBA and the NHANES 3PBA measurements more than doubled as ABC thresholding narrowed the acceptable tolerance range for predicted versus observed urinary measurements. The median predicted urinary concentrations were closer to the median measured value using ABC than using current regulatory Monte Carlo methods.

(1) Background: American Indians are disproportionately affected by air pollution, an important risk factor for dementia. However, few studies have investigated the effects of air pollution on the risk of dementia among American Indians. (2) Methods: This retrospective cohort study included a total of 26,871 American Indians who were 55+ years old in 2007, with an average follow-up of 3.67 years. County-level average air pollution data were downloaded from land-use regression models. All-cause dementia was identified using ICD-9 diagnostic codes from the Indian Health Service's (IHS) National Data Warehouse and related administrative databases. Cox models were employed to examine the association of air pollution with dementia incidence, adjusting for co-exposures and potential confounders. (3) Results: The average PM 2.5 levels in the IHS counties were lower than those in all US counties, while the mean O 3 levels in the IHS counties were higher than the US counties. Multivariable Cox regressions revealed a positive association between dementia and county-level O 3 with a hazard ratio of 1.24 (95% CI: 1.02-1.50) per 1 ppb standardized O 3 . PM 2.5 and NO 2 were not associated with dementia risk after adjusting for all covariates. (4) Conclusions: O 3 is associated with a higher risk of dementia among American Indians.

Bone lead serves as a better, more accessible biomarker to many communities experiencing chronic exposure to lead. A new method using low energy x-ray fluorescence in a handheld device (portable XRF) allows us to measure this chronic biomarker in only a few minutes. However, many unknowns remain about this biomarker measured using a new low energy x-ray technique. The low energy of the new method was theorized to measure a slightly different portion of the bone than previous techniques, which could influence measurements at different bone sites and types. We tested how bone measurements varied across five bone sites: mid-tibial shaft, proximal tibia, distal tibia (ankle), ilium, and cranium. We found bone lead measurements are not significantly different between skeletal elements when measured using a portable XRF. On average, bone lead in the repository samples was measured to be 21.6 ± 21.3 μg/g with an XRF detection limit of 2.1 ± 0.5 μg/g. Cumulative lead exposure can be effectively measured using the portable XRF on a variety of bone types, but the tibia should be preferentially measured to compare between studies and individuals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Unmatched spatially stratified random sampling (SSRS) of non-cases selects geographically balanced controls by dividing the study area into spatial strata and randomly selecting controls from all non-cases within each stratum. The performance of SSRS control selection was evaluated in a case study spatial analysis of preterm birth in Massachusetts. In a simulation study, we fit generalized additive models using controls selected by SSRS or simple random sample (SRS) designs. We compared mean squared error (MSE), bias, relative efficiency (RE), and statistically significant map results to the model results with all non-cases. SSRS designs had lower average MSE (0.0042-0.0044) and higher RE (77-80%) compared to SRS designs (MSE: 0.0072-0.0073; RE across designs: 71%). SSRS map results were more consistent across simulations, reliably identifying statistically significant areas. SSRS designs improved efficiency by selecting controls that are geographically distributed, particularly from low population density areas, and may be more appropriate for spatial analyses., Competing Interests: Declaration of Competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Perfluorooctanoic acid (PFOA) has been associated with kidney cancer in human studies., Methods: We conducted a pooled analysis of two large studies of PFOA and renal cell carcinoma (RCC, the most common type of kidney cancer); one from the National Cancer Institute (NCI) (324 cases and controls), and a second from the C8 Science Panel (103 cases and 511 controls). Serum PFOA levels were estimated a median of 8 years before diagnosis. Analyses were conducted via conditional logistic regression. Lifetime risk of kidney cancer per unit serum PFOA concentration and per unit dose were calculated., Results: The 25th, 50th and 75th percentiles of serum PFOA levels were 4.8, 7.3, and 23.9 ng/ml for the pooled analysis. The preferred model for the pooled datawas a two-piece linear spline model (knot at 12.5 ng/ml serum PFOA); the log odds of RCC increased 0.1349 per 1 ng/ml increase in serum PFOA up to the knot (eg, an OR of 2.02 (1.45-2.80) from the median to the knot), and was flat thereafter. The estimated lifetime excess risk (cancer slope factor) with an exposure of 1 ng/ml was 0.0018, similar to the excess risk of 0.0026 recently reported by CalEPA based on different methods. Assuming a serum half-life of 2.3 years and a distribution volume of 170 ml/kg for PFOA, our results are equivalent to 0.0128 per ng/kg/d of PFOA intake. To limit excess lifetime kidney cancer risk to 1/1,000,000, our data suggest a limit of 0.0015 ng/L (0.0015 ppt) for PFOA in drinking water, similar to CalEPA's proposed Public Health Goal and the new US EPA Drinking Water Health Advisory., Conclusions: Our results correspond reasonably well with cancer slope factors developed by other investigators using published summary data, and suggest drinking water limits similar to new recommendations by the US EPA., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: In environmental epidemiology, measurements of toxicants in biological samples are often used as individual exposure assignments. It is common to obtain only one or a few exposure biomarkers per person and use those measurements to represent each person's relevant toxicant exposure for a given health outcome, even though most exposure biomarkers can fluctuate over time. When the timing of the exposure reflected by the biomarker measurement is misaligned with disease development especially if it occurs after the disease outcome, results could be subject to reverse causality or exposure measurement error., Objective: This study aimed to use an approximate Bayesian computation (ABC) method to improve PFOA exposure estimates and characterize the effects of PFOA on preeclampsia in the C8 Studies., Methods: Serum PFOA concentrations were measured in blood samples collected during 2005-2006 in West Virginia and Ohio (the C8 Studies), and residential and water use histories and pregnancy outcomes were obtained from self-reports. Our previous results may have been influenced by the choice of methods for characterizing PFOA exposures. Here we use an ABC method to combine measured PFOA serum concentrations and environmentally modeled PFOA concentrations to reconstruct historical PFOA exposures. We also expanded our previous work by assuming more realistic lognormal distributions for key input parameters in the exposure and pharmacokinetic models., Results: Compared to using fixed values of model parameters and Monte Carlo simulations, ABC produced similar Spearman correlations between estimated and measured serum PFOA concentrations, yet substantially reduced the mean squared error by over 50%. Based on ABC, compared to previous studies, we found a similar adjusted odds ratio (AOR) for the association between PFOA and preeclampsia., Conclusions: Bayesian combination of modeled exposure and measured biomarker concentrations can reduce exposure measurement error compared to modeled exposure., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Per- and polyfluoroalkyl substances (PFAS) widely exist in the environment and human bodies. Contaminated drinking water is one of the major exposure pathways for humans. Previous studies found weak or moderate associations between PFAS and hypertensive disorders of pregnancy (HDP)., Methods: We obtained the number of births and counts of HDP cases for singleton births multiply stratified by county, maternal age, race, education, smoking status, and parity from CDC WONDER, and PFAS water concentrations from EPA UCMR3 data in the United States during 2013-2015. We used binomial regression on the multiply stratified HDP data to produce equal effect estimates and standard errors to those that would be derived from using individual-level data on binary HDP status and demographic covariates in logistic regression., Results: After adjusting for demographic covariates, we found small but statistically significant positive associations between HDP and population-weighted average water concentrations (ng/L) of all four PFAS: Odds ratio (OR) = 1.009, 95% CI = (1.001, 1.016) per IQR increase in perfluorooctanoic acid (PFOA); 1.030, 95% CI = (1.021, 1.040) per IQR increase in perfluorooctane sulfonate (PFOS); 1.008, 95% CI = (1.005, 1.011) per IQR increase in perfluoroheptanoic acid (PFHpA); 1.007, 95% CI = (1.004, 1.010) per IQR increase in perfluorohexane sulfonic acid (PFHxS), and 1.032, 95% CI = (1.022, 1.042) per IQR increase in the sum of four PFAS. Further adjustment for coexposures reversed the effect of PFOA from positive to inverse, and attenuated the effects of PFOS and PFHxS toward the null. After drinking water to serum concentration conversions, our effect estimates for PFOA, PFOS, and PFHxS are similar to previous studies., Conclusions: We found a weak positive association between the PFAS mixture and HDP, although the generalizability is subject to inherent limitations of the public-available datasets., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Scott M. Bartell serves as a compensated expert witness for PFOA medical monitoring lawsuits in New Hampshire. The terms of this arrangement were reviewed and approved by the University of California, Irvine in accordance with its conflict-of-interest policies. Sponsorships or competing interests that may be relevant to content are disclosed at the end of the article., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.)

Background: Prenatal exposure to drinking water with arsenic concentrations >50 μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50 μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells-federally unregulated for drinking water contaminants-and evaluated associations with birth outcomes throughout the conterminous U.S., Methods: Using several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n = 3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering., Results: We generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5 μg/L was associated with a -1.83 g (95% CI: -3.30, -0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10 μg/L was associated with a -2.79 g (95% CI: -4.99, -0.58) lower term birth weight. Associations with gestational age were null., Conclusion: In this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Water consumption is a necessity for human life, though it also presents an opportunity for exposure to harmful chemicals and toxins. In order to gain a better understanding of the potential levels of chronic exposure, accurate estimates of long-term water consumption are needed., Objective: The objective of this study is to estimate long-term water consumption using a nationally representative sample of the US population., Methods: In this study, we use a random effects model to obtain shrinkage estimates of average daily water consumption for National Health and Nutrition Examination Survey (NHANES) participants from 2005 to 2010, and compare to their empirical 2-day averages., Results: Our results demonstrate that the shrinkage estimates yielded a reduction in estimated mean water consumption. The 95th percentile was reduced from 3292 to 2529 ml/day. In addition, standard deviation of water consumption for this group decreased from 1052 to 688 ml/day. Similar reductions in the mean and variance were observed stratifying by age and race., Significance: Random effects models may provide a more accurate measure of daily water consumption and could be utilized for future exposure and risk assessments., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc. part of Springer Nature.)

We conducted a detailed analysis of coronavirus disease in a large population center in southern California, USA (Orange County, population 3.2 million), to determine heterogeneity in risks for infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the actual burden of disease and testing intensity, test positivity, and mortality. In the first month of the local epidemic (March 2020), case incidence clustered in high-income areas. This pattern quickly shifted, and cases next clustered in much higher rates in the north-central area of the county, which has a lower socioeconomic status. Beginning in April 2020, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race or ethnicity, and ZIP codes with low educational attainment) strongly affected risk for seropositivity and death.