Environmental Health Perspectives最新文献

{"title":"Wildfire-Season Fine Particulate Matter Exposure and Associations with Influenza and Influenza-like-Illness Risk in the Western USA.","authors":"Ava Orr, Nisha B Alden, Elizabeth Austin, Zeina Jaffar, Jonathon Knudson, Jon Graham, Christopher T Migliaccio, Curtis Noonan, Shawn Urbanski, Maximilian Wegener, Erin L Landguth","doi":"10.1021/EHP.6c00326","DOIUrl":"10.1021/EHP.6c00326","url":null,"abstract":"<p><strong>Background: </strong>Influenza remains a significant public health threat with pandemic potential. Understanding environmental factors influencing virus spread and severity is critical, particularly as wildfires become more frequent and intense. While temperature and humidity's roles in virus seasonality and persistence are well understood, the impacts of air pollution ─ especially wildfire-specific particulate matter (PM_2.5) ─ on respiratory infections are less explored.</p><p><strong>Objectives: </strong>This study aimed to investigate the association between wildfire PM_2.5 exposure and influenza or influenza-like illness (ILI) incidence. Specifically, we assessed (1) the long-term impact of PM_2.5 exposure during the preceding wildfire season on influenza/ILI risk in the following flu season, and (2) the effects of short-term PM_2.5 exposure during the active flu season.</p><p><strong>Methods: </strong>We utilized ILI and influenza data from state health departments in six Western U.S. states (Arizona, Colorado, Montana, Nevada, Oregon, and Washington) from 2010 to 2019. We applied generalized linear distributed lag models to assess the impact of PM_2.5 exposure during the preceding wildfire season on influenza or ILI risk in the subsequent flu season, as well as the effect of short-term PM_2.5 exposure during the current flu season.</p><p><strong>Results: </strong>Long-term exposure to wildfire PM_2.5 was associated with increased influenza risk in states with influenza data: Arizona ([Rate Ratio (RR) = 1.061 (1.026-1.100)]), Colorado [RR = 1.067 (1.056-1.078)], Montana [RR = 1.038 (1.013-1.063)], and Oregon [RR = 1.049 (1.041-1.057)], per 10 μg/m³ PM_2.5 increase. However, the states with only ILI data did not follow this pattern, revealing no observed effect in Nevada [RR = 1.005 (0.920-1.097)] and a negative effect in Washington [RR = 0.884 (0.842-0.919)]. Similarly, but to a lesser degree, short-term PM_2.5 exposure effects were noted in states with only influenza data but not ILI data.</p><p><strong>Discussion: </strong>Our findings underscore a positive association between wildfire-specific PM_2.5 and influenza risk in states with influenza data, suggesting a differential effect of PM_2.5 on respiratory infections. This study supports further investigation into the causative mechanisms behind these correlations, particularly considering the increasing frequency of wildfires and the resulting air quality impacts.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 4","pages":"397-407"},"PeriodicalIF":10.9,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13445268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148683904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expanded Tox21 Biological Assay Panel for the Prediction of Drug-Induced Liver Injury and Cardiotoxicity.","authors":"Tuan Xu, Masato Ooka, Jinghua Zhao, Srilatha Sakamuru, Deborah K Ngan, Li Zhang, Shu Yang, Jameson Travers, Menghang Xia, Tongan Zhao, Carleen Klumpp-Thomas, Hu Zhu, Mathew D Hall, Stephen Ferguson, Natalie D Shaw, David M Reif, Anton Simeonov, Ruili Huang","doi":"10.1021/EHP.6c00052","DOIUrl":"10.1021/EHP.6c00052","url":null,"abstract":"<p><strong>Background: </strong>Toxicology in the 21st Century (Tox21) assay data provide a valuable resource for the prediction of <i>in vivo</i> toxicity using machine learning models. However, the performances of these models previously developed using the pre-existing Tox21 assay data were less than ideal, likely due to insufficient coverage of the biological response space by the assay targets.</p><p><strong>Objectives: </strong>This study aimed to assess whether expanding the Tox21 portfolio with new assays that probe under-represented targets/pathways related to unanticipated adverse drug effects could improve the predictive capacity of <i>in vitro</i> assay data for <i>in vivo</i> toxicity such as drug-induced liver injury (DILI) and cardiotoxicity (DICT).</p><p><strong>Methods: </strong>Models were constructed using data from the pre-existing panel of 36 assay targets and the expanded panel of 49 assay targets. A feature selection approach was used to determine the optimal number of assays needed for each model. The models were then applied to predict the potential hepatotoxicity and cardiotoxicity of compounds in the Tox21 10K compound library.</p><p><strong>Results: </strong>For both DILI and DICT prediction, the best-performing models developed using the expanded assay panel required a smaller number of assays to achieve the same level of performance compared to those based on the pre-existing assays. Models constructed by combining both assay data (pre-existing + expanded) and chemical structure consistently outperformed those constructed based on assay data alone but showed similar performance to those constructed based on chemical structure. The compounds predicted to have the highest toxic potential were experimentally verified to demonstrate the effectiveness of our models in identifying new potentially toxic compounds.</p><p><strong>Discussion: </strong>The expansion of the Tox21 assay panel has significantly enhanced the predictive capacity of assay data for predicting the DILI and DICT potential. This improvement underscores the importance of a diverse and comprehensive <i>in vitro</i> assay portfolio in advancing safety assessment.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"361-374"},"PeriodicalIF":10.9,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prenatal Exposure to Ambient Air Pollution and Fetal Growth Trajectories in Wuhan, China.","authors":"Chen Hu, Hongxiu Liu, Yang Peng, Jie Hu, Wei Xia, Shunqing Xu, Yuanyuan Li","doi":"10.1021/EHP.6c00033","DOIUrl":"10.1021/EHP.6c00033","url":null,"abstract":"<p><strong>Background: </strong>While numerous studies have examined associations between prenatal air pollution exposure and fetal growth measures, investigations assessing longitudinal growth trajectories across multiple time points during mid-to-late pregnancy remain limited.</p><p><strong>Objectives: </strong>The aim of this study is to explore the effects of prenatal exposure to air pollution on fetal growth trajectories.</p><p><strong>Methods: </strong>From a prospective birth cohort in Wuhan, China, recruited from 2013 to 2016, we included a total of 4283 eligible pregnant women. At 16, 24, 31, and 38 weeks of gestation, we collected ultrasound measurements, including biparietal diameter (BPD), abdominal circumference (AC), femur length (FL), and estimated fetal weight (EFW). Exposure to air pollution during pregnancy was estimated for the participants' residential addresses using a spatial interpolation method. Associations between air pollutants and fetal growth parameters across four exposure windows were examined by using multiple informant models. Group-based trajectory modeling (GBTM) combined with a multinomial logistic regression model was used to explore the effect of air pollution exposure on fetal growth trajectories.</p><p><strong>Results: </strong>Four trajectory groups for AC, FL, and EFW, and three trajectory groups for BPD were selected based on GBTM. Compared with the reference trajectory group, exposure to higher PM_2.5 during weeks 1-16 was significantly associated with lower odds of being in the \"fast growth group\" for AC (OR = 0.68, 95% CI: 0.55, 0.84) and EFW (OR = 0.71, 95% CI: 0.56, 0.91). Exposures to PM_2.5, PM₁₀, NO₂, SO₂, and CO during 1-16 weeks were negatively associated with AC, FL, and EFW at 16 weeks as well as BPD, FL, and EFW at 24 weeks. Similar negative associations were observed between air pollution exposure during 25-38 weeks and AC and EFW at 38 weeks.</p><p><strong>Discussion: </strong>Our study provided evidence of negative associations between air pollution exposure during 1-16 weeks of gestation and the fast growth trajectory group. In addition, we observed distinct lagged associations between air pollution and fetal growth, with early pregnancy exposure negatively related to early and midgestational growth, and mid-to-late pregnancy exposure negatively related to growth in the late window. These results underscore the importance of identifying critical windows of susceptibility during pregnancy and support early intervention strategies to mitigate adverse fetal developmental outcomes.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"351-360"},"PeriodicalIF":10.9,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Gut Microbiota in the Association between Air Pollution and Cognitive Function in Older Adults.","authors":"Wenhao Qi, Mengmeng Kong, Xia Meng, Zhonghan Sun, Zhendong Mei, Yanni Pu, Xiaofeng Zhou, Qichu Wang, Jian-Ge Qiu, Bing-Hua Jiang, Jie Shen, Changzheng Yuan, John S Ji, Xiaofeng Wang, Haidong Kan, Yan Zheng","doi":"10.1021/EHP.6c00026","DOIUrl":"10.1021/EHP.6c00026","url":null,"abstract":"<p><strong>Background: </strong>Growing evidence links air pollution to cognitive dysfunction in older adults. The gut microbiome and circulating metabolites present an important yet unexplored pathway given their crucial role in the gut-brain axis.</p><p><strong>Objectives: </strong>We aimed to explore the potential roles of gut bacteria, fungi, microbial functional potentials, and circulating metabolites in the association of residential PM_2.5 and O₃ exposure with cognitive dysfunction.</p><p><strong>Methods: </strong>We analyzed gut microbiome data from 1,027 older adults using metagenome and internal transcribed spacer sequencing to profile bacterial and fungal taxa, functional pathways, and enzyme abundances. Targeted metabolomics quantified 195 circulating metabolites, such as amino acids and organic acids. Annual average ambient PM_2.5 and O₃ exposures were estimated by using satellite-based models. Cognitive outcomes, including mild cognitive impairment and cognitive decline, were assessed using the Mini-Mental State Examination and Hasegawa Dementia Scale. Statistical analyses included Microbiome Multivariable Association with Linear Models (with a false discovery rate threshold of 0.25) for microbial associations and multivariate regression for metabolites and cognitive outcomes.</p><p><strong>Results: </strong>Higher PM_2.5 and O₃ exposures were associated with disturbances in microbial composition, altered taxonomic profiles (e.g., decreased abundances of <i>Blautia obeum</i> and <i>Gordonibacter pamelaeae</i>), and disrupted functional pathways, particularly those regulating 2-oxoglutarate. These findings were partially replicated in an independent population. Higher air pollution levels were associated with increased circulating levels of 2-oxoglutarate and l-glutamine (key metabolites in neurodegenerative progression), which were further linked to higher odds of concurrent mild cognitive impairment (OR: 1.39-1.56) and an increased 2-year risk of cognitive decline (OR: 1.26-1.37). These associations were partially mediated by air pollution-related changes in microbial anaerobic energy metabolism pathways, especially involving 2-oxoglutarate metabolism and the enzyme aspartate transaminase.</p><p><strong>Conclusions: </strong>Our findings highlight the role of the gut microbiome and microbial metabolites in mediating the detrimental impact of air pollution on cognitive health in older adults, providing new insights into the underlying etiology for future hypothesis generation.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"335-350"},"PeriodicalIF":10.9,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Extreme Heat Exposure on Heatstroke and Liver Injury in Mice: The Role of PPARα.","authors":"Guoqing Zhang, Lisha Zhao, Jiahui Wang, Kunyi Wang, Xiuyu Ji, Renjie Hu, Tong Hou, Lu Zhang, Ran Li, Qinghua Sun, Kezhong Zhang, Cuiqing Liu","doi":"10.1021/EHP.6c00267","DOIUrl":"10.1021/EHP.6c00267","url":null,"abstract":"<p><p><b>BACKGROUND:</b> Liver injury is a frequent complication of heatstroke and constitutes a direct cause of death. However, only a few studies examined the mechanism underlying heatstroke-induced liver injury. <b>OBJECTIVE:</b> We aimed to evaluate the role of peroxisome proliferator-activated receptor α (PPARα) in heatstroke-induced liver injury and to explore the potential mechanisms. <b>METHODS:</b> Male C57BL/6N mice were subjected to a control (22 ± 1 °C) or extreme heat temperature (39.5 ± 0.5 °C) to induce a heatstroke-associated liver injury animal model. PPARα agonist, ferroptosis inhibitor, and AAV8-mediated PPARα overexpression were administered to the mice to investigate the role of PPARα and ferroptosis in the heatstroke-induced liver injury. Serum was collected for liver function evaluation. Liver tissues were applied for morphological observation, staining detection, ferroptosis examination, and mechanistic exploration. <b>RESULTS:</b> Compared with the control group, extreme heat exposure-induced temperature dysregulation, impaired liver function, and morphological damage in mice. Proteomics screened PPARα as a protein of interest, with its level being significantly decreased in response to extreme heat exposure. Both PPARα activation and overexpression attenuated extreme heat-induced heatstroke and liver injury. Hmox1 was next screened and higher Hmox1 expression was identified, accompanied by elevated markers of ferroptosis including prostaglandin-endoperoxide synthase 2 (Ptgs2), malondialdehyde (MDA), lipid peroxidation (LPO) and Fe²⁺ levels. Ferroptosis inhibition mitigated heatstroke and liver injury induced by heat exposure. In the setting of extreme heat exposure, PPARα activation suppressed Hmox1 expression and the levels of ferroptosis markers. It not only induced differences in the expression of members of iron generation, efflux and uptake process and reduced hepatic intracellular Fe²⁺ accumulation, but also stimulated expression of molecules for countering lipid peroxidation including Nrf2-SLC7A11-GPX4 axis and FSP1 signaling. <b>DISCUSSION:</b> PPARα played an essential role in extreme heat exposure-induced heatstroke and liver injury, and PPARα intervention conferred protection against it via inhibition of ferroptosis.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 1","pages":"110-123"},"PeriodicalIF":10.9,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13151047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prenatal Air Pollution Exposure and Autism Spectrum Disorder in the ECHO Consortium.","authors":"Akhgar Ghassabian, Aisha S Dickerson, Yuyan Wang, Joseph M Braun, Deborah H Bennett, Lisa A Croen, Kaja Z LeWinn, Heather H Burris, Rima Habre, Kristen Lyall, Jean A Frazier, Hannah C Glass, Stephen R Hooper, Robert M Joseph, Catherine J Karr, Rebecca J Schmidt, Chloe Friedman, Margaret R Karagas, Annemarie Stroustrup, Jennifer K Straughen, Anne L Dunlop, Jody M Ganiban, Leslie D Leve, Rosalind J Wright, Cindy T McEvoy, Alison E Hipwell, Angelo P Giardino, Hudson P Santos, Hannah Krause, Emily Oken, Carlos A Camargo, Jiwon Oh, Christine Loftus, T Michael O'Shea, Thomas G O'Connor, Adam Szpiro, Heather E Volk","doi":"10.1021/EHP.6c00106","DOIUrl":"10.1021/EHP.6c00106","url":null,"abstract":"<p><strong>Background: </strong>The relationship between prenatal exposure to low-level air pollution and child autism spectrum disorder (ASD) is unclear.</p><p><strong>Objective: </strong>To examine associations of prenatal air pollution exposure with autism.</p><p><strong>Methods: </strong>We analyzed data from 8,035 mother-child pairs from 44 United States cohorts in the Environmental influences on Child Health Outcomes (ECHO) Cohort. Fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and 8-h-max ozone (O₃) levels were estimated at residential addresses during pregnancy. Parents rated children's autism-related traits using the Social Responsiveness Scale (SRS) (mean age 9.4 years, SD = 3.6) and reported physician-diagnosed ASD. We examined associations of the three air pollutants with SRS scores (10th, 50th, and 90th quantiles) using quantile regression and with ASD diagnosis using logistic regression. Models were run within census divisions, and coefficients were pooled in a meta-analysis.</p><p><strong>Results: </strong>Average (SD) pregnancy exposures were 9.3 μg/m³ (2.7) for PM_2.5, 21.8 ppb (8.8) for NO₂, and 40.3 ppb (5.5) for O₃, with variations across census divisions. The median SRS T-score was 46 (IQR = 41 to 52), and 444 children (5.5%) had an ASD diagnosis. Higher PM_2.5 was associated with higher SRS scores at the 10th quantile (β = 0.74, 95% CI: 0.09, 1.40) but not at the median or highest quantile. The association between PM_2.5 and ASD diagnosis was highly heterogeneous, with associations present in the South Central, Mountain, and Pacific census divisions. Heterogeneity was also high in the association between NO₂ and SRS at the median and only in the mid-Atlantic, West North Central, and South Atlantic census divisions. Higher O₃ was associated with higher SRS scores at the median (β per IQR increment = 0.83, 95% CI: 0.05, 1.61) and highest quantile (β = 2.19, 95% CI: 0.06, 4.32) in the meta-analysis. Higher O₃ also was associated with ASD.</p><p><strong>Discussion: </strong>Associations with ASD outcomes were present even at low levels of air pollutants.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"324-334"},"PeriodicalIF":10.9,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Tubewell Use and Child Diarrhea in Rural Bangladesh: Results from a Prospective Community Surveillance Study.","authors":"Varun Goel, Mia Ziade, Brianna Chan, Md Yunus, Md Taslim Ali, Md Al Fazal Khan, Md Nurul Alam, Asg Faruque, Shahabuddin Babu, Md Masnoon Kabir, Paul L Delamater, Marc L Serre, Mark D Sobsey, Md Sirajul Islam, Michael Emch","doi":"10.1021/EHP.6c00045","DOIUrl":"10.1021/EHP.6c00045","url":null,"abstract":"<p><strong>Background: </strong>Diarrheal diseases remain a leading cause of mortality and morbidity among under-five children in South Asia. In rural Bangladesh, deep tubewells that tap into low-arsenic deep aquifers have been installed to provide microbially safe and arsenic-free drinking water at the source. However, unlike more widely used shallow tubewells, deep tubewells are sparsely distributed, and households often travel farther for drinking-water consumption from such wells. Hence, benefits from deep tubewells may be abated by higher levels of microbial contamination during water handling and storage that could increase the risk of diarrheal diseases.</p><p><strong>Objectives: </strong>We examined the association between deep tubewell use and diarrheal disease risk in under-five children and investigated the role of social and environmental factors on modifying the association.</p><p><strong>Methods: </strong>We implemented community diarrheal disease surveillance across households with under-five children using deep and shallow tubewells in Matlab, Bangladesh from March 2018 to October 2019. We used Generalized Estimating Equations (GEE) to estimate the association between deep tubewell versus shallow tubewell use and diarrheal disease prevalence.</p><p><strong>Results: </strong>Children in households using deep tubewells had diarrheal disease prevalence 0.83 times that of children in households using shallow tubewells (95% confidence interval (CI): 0.71-0.96). Protective effects of deep tubewell use on diarrhea risk were observed among children in households that drank from wells within their household compound (risk ratio (RR) = 0.70, 95% CI: 0.54 - 0.91), were in flood-prone areas (RR = 0.83, 95% CI: 0.75 - 0.92), and used unimproved latrines (RR = 0.62, 95% CI: 0.43-0.89). Deep tubewell use was more protective against diarrhea than shallow tubewell use during the dry season (RR = 0.71, 95% CI: 0.52-0.97).</p><p><strong>Conclusions: </strong>Despite concerns, using deep tubewells may not translate to higher diarrhea risk among under-five children and may reduce diarrhea further, especially in social and environmental contexts associated with higher groundwater microbial contamination.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"312-323"},"PeriodicalIF":10.9,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic Evidence Map for the Per- and Polyfluoroalkyl Substances (PFAS) Universe.","authors":"Avanti V Shirke, Elizabeth G Radke, Ryan Jones, Barrett D Allen, Cynthia J Lin, Amanda Ross, Nicole Vetter, Courtney Lemeris, Pamela Hartman, Sorina Eftim, Arun Varghese, Robyn Blain, Heidi Hubbard, Antony J Williams, Kristina A Thayer, Laura M Carlson","doi":"10.1021/EHP.6c00127","DOIUrl":"10.1021/EHP.6c00127","url":null,"abstract":"<p><p><b>BACKGROUND:</b> Per- and polyfluoroalkyl substances (PFAS) are a research priority for the U.S. Environmental Protection Agency (EPA). Because PFAS include thousands of structurally diverse chemicals, there is a pressing need for identifying what data are available to assess the human health hazard of these compounds. <b>OBJECTIVES:</b> We used systematic evidence map (SEM) methods to summarize the available epidemiological and mammalian bioassay evidence for ∼14,735 chemicals identified as PFAS by EPA's Center for Computational Toxicology and Exposure (CCTE). This work is a continuation of our previous 2022 and 2024 SEMs that inventoried evidence on a separate set of ∼500 PFAS. The Comprehensive PFAS Dashboard includes evidence identified from our past SEMs and completed EPA assessments. <b>METHODS:</b> We conducted literature searches from peer-reviewed and gray literature sources to identify, screen, and inventory mammalian bioassay and epidemiological literature. A combination of manual review and machine learning software were utilized. A diverse array of potentially relevant supplemental content was also tracked, including mechanistic data, exposure-only studies, and studies informing chemical toxicokinetics and clearance. For each study meeting predefined population, exposure, comparator, and outcome (PECO) criteria, experimental design details and health end points evaluated were summarized in interactive web-based literature inventory visuals. Epidemiology studies and animal bioassay studies with ≥21-day exposure duration or reproductive/developmental study design proceeded to undergo a study evaluation for risk of bias and sensitivity, as well as detailed extraction of health end point data. Underlying data are publicly available and can be downloaded. <b>RESULTS:</b> Scientific database searches retrieved 152,205 references. After full-text screening, there were 347 mammalian bioassay and 44 epidemiological studies that met PECO criteria. The mammalian bioassay and epidemiological evidence assessed 99 and 30 individual PFAS, respectively (<i>n</i> = 18 PFAS with both). The epidemiological evidence assessed 15 health systems and the mammalian bioassay evidence assessed 16 health systems. <b>DISCUSSION:</b> Results from our 2022 and 2024 SEMs and completed EPA assessments are compiled into Comprehensive PFAS Dashboard. This dashboard is a resource for better understanding the currently available PFAS human health hazard data. It can be used as a tool for researchers and regulators interested in PFAS data gaps and research needs. Across all the data sources compiled into the Comprehensive PFAS Dashboard, only 1.4% (214/14,735) of PFAS had any mammalian bioassay or epidemiological data available. The vast majority of PFAS lack publicly available information about the potential human health effects of exposure to these chemicals.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 3","pages":"252-273"},"PeriodicalIF":10.9,"publicationDate":"2026-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347649/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148419786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Workflow for Statistical Analysis of Environmental Mixtures.","authors":"Bonnie R Joubert, Glenn Palmer, David Dunson, Marianthi-Anna Kioumourtzoglou, Brent A Coull","doi":"10.1021/EHP.6c00155","DOIUrl":"10.1021/EHP.6c00155","url":null,"abstract":"<p><p><b>BACKGROUND</b>: Human exposure to complex, changing, and variably correlated mixtures of environmental chemicals has presented analytical challenges to epidemiologists and human health researchers. There has been a wide variety of recent advances in statistical methods for analyzing mixtures data, with most methods having open-source software for implementation. However, there is no one-size-fits-all method for analyzing mixture data given the considerable heterogeneity in scientific focus and study design. For example, some methods focus on predicting the overall health effect of a mixture and others seek to disentangle main effects and pairwise interactions. Some methods are only appropriate for cross-sectional designs, while other methods can accommodate longitudinally measured exposures or outcomes. <b>OBJECTIVES</b>: This article focuses on simplifying the task of identifying which methods are most appropriate to a particular study design, data type, and scientific focus. <b>METHODS</b>: We present an organized workflow for statistical analysis considerations in environmental mixtures data and two example applications implementing the workflow. This systematic strategy builds on epidemiological and statistical principles, considering specific nuances for the mixtures' context. We also present an accompanying methods repository to increase awareness of and inform application of existing methods and new methods as they are developed. <b>DISCUSSION</b>: We note several methods may be equally appropriate for a specific context. This article does not present a comparison or contrast of methods or recommend one method over another. Rather, the presented workflow can be used to identify a set of methods that are appropriate for a given application. Accordingly, this effort will inform application, educate researchers (e.g., new researchers or trainees), and identify research gaps in statistical methods for environmental mixtures that warrant further development.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 1","pages":"8-22"},"PeriodicalIF":10.9,"publicationDate":"2026-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13151037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Household Air Pollution on the Gut Microbiome and Virome of Adult Women Living in Uganda.","authors":"Ching-Ying Huang, Edwin Nuwagira, Michael Tisza, Minsik Kim, Mellon Tayebwa, Jacob Vieira, Nicholas Lam, Eli Wallach, Matthew Wiens, Alexander C Tsai, Linda Valeri, Jose Vallarino, Joseph G Allen, Peggy S Lai","doi":"10.1021/EHP.6c00064","DOIUrl":"10.1021/EHP.6c00064","url":null,"abstract":"<p><p><b>BACKGROUND:</b> Emerging observational studies suggest that air pollution can influence the gut microbiome. However, this association is often highly confounded by factors, such as diet and poverty. The gut virome may influence respiratory health independent of the gut microbiome. We recently demonstrated in a randomized waitlist-controlled trial (ClinicalTrials.gov NCT03351504) that a clean lighting intervention reduced the level of personal exposure to air pollution among adult women in rural Uganda. <b>OBJECTIVES:</b> To determine the effect of a solar lighting intervention on changes to the gut microbiome and virome and secondarily to determine the association between these changes on lung health. <b>METHODS:</b> Between 2018 and 2019, we collected stool samples and assessed respiratory symptoms and spirometry from 80 adult women living in rural Uganda at baseline and 12 and 18 months postrandomization. The intervention group received a solar lighting system after randomization, while the waitlist-controlled group received one at 12 months. Deep metagenomics sequencing of stool was performed and profiled for nonviral and viral taxonomic composition. The primary analysis focused on pre- vs postintervention changes due to power considerations, adjusting for potential confounding by age, diet, antibiotic use, and season. A sensitivity analysis was conducted using intention-to-treat principles. When comparing pre- vs postintervention periods, we used sparse partial least-squares models to identify nonviral and viral signatures of reduced air pollution exposure. Mixed effects models were used to evaluate changes in health outcomes as well as associations between microbial signatures of reduced air pollution exposure and health. <b>RESULTS:</b> The average age was 39.2 years. The solar lighting intervention led to larger changes in viral compared to nonviral microbial community structure and differential abundance of bacteria, eukaryotes, and viruses. Provision of solar lighting systems was associated with a reduction in the presence of respiratory symptoms from 57.1% to 36.1% (<i>p</i> = 0.002), while there was no impact on lung function. Microbiome and virome signatures had AUCs of 0.74 and 0.76, respectively, in predicting pre- vs postintervention stool samples. Microbiome signatures were associated with a lower risk of respiratory symptoms (OR = 0.68 (0.49 - 0.94), <i>p</i> = 0.020). <b>CONCLUSION:</b> Among adult women living in rural Uganda, both nonviral and viral components of the gut microbial community changed after a clean lighting intervention. Microbiome signatures reflective of lower air pollution exposures were associated with improved respiratory symptoms. These observations suggest that air pollution may influence lung health through the gut-lung axis, warranting further exploration in future intervention studies.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"134 1","pages":"75-90"},"PeriodicalIF":10.9,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13151042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}