Cody Z Watling,Jessica L Petrick,Barry I Graubard,Xuehong Zhang,Matthew J Barnett,Julie E Buring,Yu Chen,A Heather Eliassen,Michael Gaziano,Jae H Kang,Jill Koshiol,Wen-Yi Huang,I-Min Lee,Steven C Moore,Lorelei A Mucci,Marian L Neuhouser,Christina C Newton,Julie R Palmer,Lynn Rosenberg,Howard D Sesso,Martha Shrubsole,Lesley Tinker,Matthew Triplette,Caroline Y Um,Kala Visvanathan,Jean Wactawski-Wende,Walter Willett,Fen Wu,Wei Zheng,Jonathan Hofmann,Mark P Purdue,Peter T Campbell,Dinesh Barupal,Katherine A McGlynn
BACKGROUNDPer- and polyfluoroalkyl substances (PFAS) have been associated with numerous deleterious health outcomes including liver damage. However, whether exposure to PFAS is associated with liver cancer risk remains unclear.METHODSWe conducted a matched nested case-control study among 12 prospective cohort studies located in the United States. Pre-diagnostic PFAS, namely perfluorooctanesulfonate (PFOS), perfluorooctanoate (PFOA), and perfluorohexanesulfonate (PFHxS), were measured from blood samples among 853 individuals who developed liver cancer and 853 matched control participants. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable-adjusted conditional logistic regression for liver cancer risk by study-specific quartiles of concentrations and per 90th vs. 10th percentile incremental increase.RESULTSIn the main multivariable-adjusted model, circulating PFOS, PFOA, and PFHxS levels were not associated with liver cancer risk (OR per 90th vs. 10th percentile increase: 1.00, 95% CI: 0.79-1.28; 0.92, 0.73-1.15; and 0.95, 0.75-1.21, respectively). However, when analyses were stratified by sex, PFOA concentrations were positively associated with liver cancer risk in males (OR per 90th vs. 10th percentile increase: 1.62 95% CI:1.07-2.45), whereas an inverse association was observed amongst females (OR per 90th vs. 10th percentile increase:0.68, 0.50-0.92; p-interaction=0.005). Analyses separating liver cancer subtypes, hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma, showed no evidence of heterogeneity, although associations were stronger but not significant for HCC. No evidence of interaction was observed by time to diagnosis, time period of blood draw, body mass index, alcohol intake, ethnicity, or diabetes status.CONCLUSIONSIn the largest study to date, none of the measured circulating PFAS were associated with liver cancer risk; however, PFOA associations appeared to differ by sex and further research is needed to explore these apparent differences by sex. https://doi.org/10.1289/EHP16980.
{"title":"Circulating per- and polyfluoroalkyl substances and liver cancer risk: a nested case-control analysis of individual participant data from 12 prospective cohorts.","authors":"Cody Z Watling,Jessica L Petrick,Barry I Graubard,Xuehong Zhang,Matthew J Barnett,Julie E Buring,Yu Chen,A Heather Eliassen,Michael Gaziano,Jae H Kang,Jill Koshiol,Wen-Yi Huang,I-Min Lee,Steven C Moore,Lorelei A Mucci,Marian L Neuhouser,Christina C Newton,Julie R Palmer,Lynn Rosenberg,Howard D Sesso,Martha Shrubsole,Lesley Tinker,Matthew Triplette,Caroline Y Um,Kala Visvanathan,Jean Wactawski-Wende,Walter Willett,Fen Wu,Wei Zheng,Jonathan Hofmann,Mark P Purdue,Peter T Campbell,Dinesh Barupal,Katherine A McGlynn","doi":"10.1289/ehp16980","DOIUrl":"https://doi.org/10.1289/ehp16980","url":null,"abstract":"BACKGROUNDPer- and polyfluoroalkyl substances (PFAS) have been associated with numerous deleterious health outcomes including liver damage. However, whether exposure to PFAS is associated with liver cancer risk remains unclear.METHODSWe conducted a matched nested case-control study among 12 prospective cohort studies located in the United States. Pre-diagnostic PFAS, namely perfluorooctanesulfonate (PFOS), perfluorooctanoate (PFOA), and perfluorohexanesulfonate (PFHxS), were measured from blood samples among 853 individuals who developed liver cancer and 853 matched control participants. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable-adjusted conditional logistic regression for liver cancer risk by study-specific quartiles of concentrations and per 90th vs. 10th percentile incremental increase.RESULTSIn the main multivariable-adjusted model, circulating PFOS, PFOA, and PFHxS levels were not associated with liver cancer risk (OR per 90th vs. 10th percentile increase: 1.00, 95% CI: 0.79-1.28; 0.92, 0.73-1.15; and 0.95, 0.75-1.21, respectively). However, when analyses were stratified by sex, PFOA concentrations were positively associated with liver cancer risk in males (OR per 90th vs. 10th percentile increase: 1.62 95% CI:1.07-2.45), whereas an inverse association was observed amongst females (OR per 90th vs. 10th percentile increase:0.68, 0.50-0.92; p-interaction=0.005). Analyses separating liver cancer subtypes, hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma, showed no evidence of heterogeneity, although associations were stronger but not significant for HCC. No evidence of interaction was observed by time to diagnosis, time period of blood draw, body mass index, alcohol intake, ethnicity, or diabetes status.CONCLUSIONSIn the largest study to date, none of the measured circulating PFAS were associated with liver cancer risk; however, PFOA associations appeared to differ by sex and further research is needed to explore these apparent differences by sex. https://doi.org/10.1289/EHP16980.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"57 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yazan Alwadi,Barrak Alahmad,Marc G Weisskopf,Petros Koutrakis
BACKGROUNDTraditional temperature-health studies have predominantly relied on temperature measurements from stations or modelled spatial averages from gridded temperature datasets. It has been suggested that population-weighted spatial averages would perform better in remote regions with large temperature and population variability. This would be particularly true in regions other than North America and Europe where outcome data is often only available on a crude spatial scale, but no studies have examined this in such regions, where temperatures can be particularly hot.OBJECTIVEUsing the Middle East as a climate hotspot, our objective was to illustrate the utility of population weighting temperature exposures in understudied regions with large health data aggregation areas.METHODSWe used a daily 1km × 1km temperature dataset for 152 administrative regions in 12 Middle Eastern countries. From 2003 to 2020, for each administrative region, we computed daily minimum and maximum population-weighted and unweighted spatial average temperatures. To illustrate, we examined temperature-mortality associations in two countries: Kuwait and Jordan. We used distributed lag non-linear models to estimate the daily timeseries temperature-mortality associations in using three temperature exposure measurement approaches: station temperatures, unweighted spatial averages, and population-weighted temperatures. For each scenario, we fitted country-specific optimized parameters and compared them using three metrics: 1) exposure-response relationships, 2) minimum mortality temperatures and 3) attributable mortality estimates.RESULTSThe study region had geographically sporadic yet densely populated areas within each country. In both Kuwait and Jordan, population-weighted and unweighted spatial average temperatures resulted in fairly similar exposure-response curves, whereas both were notably different from station temperatures. Minimum mortality temperatures were 30.2, 28.6, and 28.3°C in Kuwait for station, unweighted spatial average, and population-weighted temperatures, respectively. In Jordan, the corresponding temperatures were 20.6, 20.9, and 20°C. Heat attributable mortality calculated using population-weighted temperatures increased by 15% compared to the traditionally used station temperatures in Kuwait and Jordan, respectively, and -0.4% and 5% compared to unweighted spatial average temperatures.DISCUSSIONSpatial averaging, whether weighted or unweighted, is a valuable tool for estimating heat-attributable mortality. This is especially true in regions like the Middle East, where granular temperature data are often unavailable and health studies are urgently needed. Population-weighted temperatures may better capture localized exposures in areas with significant population clustering, though their exact added effect on top of unweighted spatial averages remains a tentative conclusion.. https://doi.org/10.1289/EHP16010.
{"title":"Comparison of Temperature-Mortality Associations Across the Middle East Using Different Exposure Estimation Approaches.","authors":"Yazan Alwadi,Barrak Alahmad,Marc G Weisskopf,Petros Koutrakis","doi":"10.1289/ehp16010","DOIUrl":"https://doi.org/10.1289/ehp16010","url":null,"abstract":"BACKGROUNDTraditional temperature-health studies have predominantly relied on temperature measurements from stations or modelled spatial averages from gridded temperature datasets. It has been suggested that population-weighted spatial averages would perform better in remote regions with large temperature and population variability. This would be particularly true in regions other than North America and Europe where outcome data is often only available on a crude spatial scale, but no studies have examined this in such regions, where temperatures can be particularly hot.OBJECTIVEUsing the Middle East as a climate hotspot, our objective was to illustrate the utility of population weighting temperature exposures in understudied regions with large health data aggregation areas.METHODSWe used a daily 1km × 1km temperature dataset for 152 administrative regions in 12 Middle Eastern countries. From 2003 to 2020, for each administrative region, we computed daily minimum and maximum population-weighted and unweighted spatial average temperatures. To illustrate, we examined temperature-mortality associations in two countries: Kuwait and Jordan. We used distributed lag non-linear models to estimate the daily timeseries temperature-mortality associations in using three temperature exposure measurement approaches: station temperatures, unweighted spatial averages, and population-weighted temperatures. For each scenario, we fitted country-specific optimized parameters and compared them using three metrics: 1) exposure-response relationships, 2) minimum mortality temperatures and 3) attributable mortality estimates.RESULTSThe study region had geographically sporadic yet densely populated areas within each country. In both Kuwait and Jordan, population-weighted and unweighted spatial average temperatures resulted in fairly similar exposure-response curves, whereas both were notably different from station temperatures. Minimum mortality temperatures were 30.2, 28.6, and 28.3°C in Kuwait for station, unweighted spatial average, and population-weighted temperatures, respectively. In Jordan, the corresponding temperatures were 20.6, 20.9, and 20°C. Heat attributable mortality calculated using population-weighted temperatures increased by 15% compared to the traditionally used station temperatures in Kuwait and Jordan, respectively, and -0.4% and 5% compared to unweighted spatial average temperatures.DISCUSSIONSpatial averaging, whether weighted or unweighted, is a valuable tool for estimating heat-attributable mortality. This is especially true in regions like the Middle East, where granular temperature data are often unavailable and health studies are urgently needed. Population-weighted temperatures may better capture localized exposures in areas with significant population clustering, though their exact added effect on top of unweighted spatial averages remains a tentative conclusion.. https://doi.org/10.1289/EHP16010.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"88 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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
BACKGROUNDEmerging observational studies suggest 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 personal exposure to air pollution among adult women in rural Uganda.OBJECTIVESTo determine the effect of a solar lighting intervention on changes to the gut microbiome and virome and secondarily to determine association between these changes on lung health.METHODSBetween 2018 and 2019, we collected stool samples and assessed respiratory symptoms and spirometry from 80 adult women living in rural Uganda at baseline, 12 and 18 months post-randomization. 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 non-viral and viral taxonomic composition. The primary analysis focused on pre- vs. post-intervention changes due 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. post-intervention periods, we used sparse partial least squares models to identify non-viral 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.RESULTSThe average age was 39.2 years. The solar lighting intervention led to larger changes in viral compared to non-viral 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% (p = 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. post-intervention stool samples. Microbiome signatures were associated with a lower risk of respiratory symptoms (OR 0.68 (0.49-0.94), p = 0.020).CONCLUSIONAmong adult women living in rural Uganda, both non-viral 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. https://doi.org/10.1289/EHP16002.
越来越多的观察性研究表明，空气污染会影响肠道微生物群。然而，这种联系往往被饮食和贫困等因素严重混淆。肠道病毒组可能独立于肠道微生物组影响呼吸系统健康。我们最近在一项随机候补对照试验（ClinicalTrials.gov NCT03351504）中证明，清洁照明干预减少了乌干达农村成年妇女对空气污染的个人暴露。目的：确定太阳光照干预对肠道微生物组和病毒组变化的影响，并确定这些变化与肺部健康之间的关系。方法在2018年至2019年期间，我们收集了生活在乌干达农村的80名成年女性的粪便样本，并在随机分组后的基线、12个月和18个月评估了呼吸道症状和肺活量测定法。干预组在随机分配后接受太阳能照明系统，而等候名单对照组在12个月后接受太阳能照明系统。对粪便进行了深度宏基因组测序，并对非病毒和病毒分类组成进行了分析。主要分析集中在干预前和干预后由于功率考虑的变化，调整了年龄、饮食、抗生素使用和季节的潜在混淆。采用意向-治疗原则进行敏感性分析。在比较干预前后时期时，我们使用稀疏偏最小二乘模型来识别减少空气污染暴露的非病毒和病毒特征。使用混合效应模型来评估健康结果的变化以及减少空气污染暴露的微生物特征与健康之间的关系。结果患者平均年龄39.2岁。与非病毒微生物群落结构和细菌、真核生物和病毒丰度的差异相比，太阳光照干预导致病毒微生物群落结构发生了更大的变化。提供太阳能照明系统与呼吸道症状的出现从57.1%减少到36.1% （p = 0.002）相关，而对肺功能没有影响。在预测干预前和干预后粪便样本时，微生物组和病毒组特征的auc分别为0.74和0.76。微生物组特征与较低的呼吸道症状风险相关（OR 0.68 (0.49-0.94), p = 0.020）。结论生活在乌干达农村的成年妇女，在清洁照明干预后，肠道微生物群落的非病毒和病毒成分都发生了变化。反映较低空气污染暴露的微生物组特征与呼吸道症状的改善有关。这些观察结果表明，空气污染可能通过肠-肺轴影响肺部健康，值得在未来的干预研究中进一步探索。https://doi.org/10.1289/EHP16002。
{"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":"10.1289/ehp16002","DOIUrl":"https://doi.org/10.1289/ehp16002","url":null,"abstract":"BACKGROUNDEmerging observational studies suggest 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 personal exposure to air pollution among adult women in rural Uganda.OBJECTIVESTo determine the effect of a solar lighting intervention on changes to the gut microbiome and virome and secondarily to determine association between these changes on lung health.METHODSBetween 2018 and 2019, we collected stool samples and assessed respiratory symptoms and spirometry from 80 adult women living in rural Uganda at baseline, 12 and 18 months post-randomization. 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 non-viral and viral taxonomic composition. The primary analysis focused on pre- vs. post-intervention changes due 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. post-intervention periods, we used sparse partial least squares models to identify non-viral 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.RESULTSThe average age was 39.2 years. The solar lighting intervention led to larger changes in viral compared to non-viral 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% (p = 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. post-intervention stool samples. Microbiome signatures were associated with a lower risk of respiratory symptoms (OR 0.68 (0.49-0.94), p = 0.020).CONCLUSIONAmong adult women living in rural Uganda, both non-viral 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. https://doi.org/10.1289/EHP16002.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"4 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDAnthropogenic land modification influences human-livestock-wildlife interactions and zoonotic spillover emergence. However, the extent of this impact remains unclear and could be better understood through the collaborative use of advanced predictive and explanatory analytical tools, alongside, an up-to-date dataset on zoonotic spillover events.OBJECTIVEThe main objective is to develop and evaluate an integrated modeling framework to predict and explain spatial patterns and nonlinear relationships of zoonotic spillover events, using updated datasets and the human modification index to differentiate anthropogenic pressures.METHODSOur study expanded the historical datasets to include recent spillover events and a comprehensive set of predictors. By combining robustness of finely-tuned stacking algorithms with structural equation modeling, we considered global heterogeneity in relative reporting adequacy and mapped spillover patterns at different scales. Using the human modification index, we disentangled anthropogenic processes modifying natural ecosystem across land modification gradients, and described their linkages to spillover occurrence over the past three decades.RESULTSThis integrated approach effectively improved the model's predictive and explanatory power. Our analysis reveals that the intermediate levels of human pressure facilitated the zoonotic spillover. The indirect effects of anthropogenic pressure, mediated by specific cropping intensity, are strongly associated with zoonoses emergence. Livestock distribution serves as an indicator of spillover hotspots, acting as effective proxies for distinctive landscapes.DISCUSSIONOur findings identify high zoonotic spillover risks present across geographically and socioeconomically diverse regions worldwide, extending beyond tropical areas, including extensive regions experiencing high-intensity human modification. These insights support targeted surveillance in areas with potentially high relative risk or uncertainty, and demonstrate how zoonotic spillover responds to complex human-environment interactions. https://doi.org/10.1289/EHP15937.
{"title":"An integrated machine learning framework to understand zoonotic spillover emergence across anthropogenically modified landscapes.","authors":"Yinsheng Zhang,Jinchen Wang,Luqi Wang,Linxuan Miao,Yifan Sun,Xin Yang,Ruying Fang,Yiyang Guo,Sophie Vanwambeke,Sen Li","doi":"10.1289/ehp15937","DOIUrl":"https://doi.org/10.1289/ehp15937","url":null,"abstract":"BACKGROUNDAnthropogenic land modification influences human-livestock-wildlife interactions and zoonotic spillover emergence. However, the extent of this impact remains unclear and could be better understood through the collaborative use of advanced predictive and explanatory analytical tools, alongside, an up-to-date dataset on zoonotic spillover events.OBJECTIVEThe main objective is to develop and evaluate an integrated modeling framework to predict and explain spatial patterns and nonlinear relationships of zoonotic spillover events, using updated datasets and the human modification index to differentiate anthropogenic pressures.METHODSOur study expanded the historical datasets to include recent spillover events and a comprehensive set of predictors. By combining robustness of finely-tuned stacking algorithms with structural equation modeling, we considered global heterogeneity in relative reporting adequacy and mapped spillover patterns at different scales. Using the human modification index, we disentangled anthropogenic processes modifying natural ecosystem across land modification gradients, and described their linkages to spillover occurrence over the past three decades.RESULTSThis integrated approach effectively improved the model's predictive and explanatory power. Our analysis reveals that the intermediate levels of human pressure facilitated the zoonotic spillover. The indirect effects of anthropogenic pressure, mediated by specific cropping intensity, are strongly associated with zoonoses emergence. Livestock distribution serves as an indicator of spillover hotspots, acting as effective proxies for distinctive landscapes.DISCUSSIONOur findings identify high zoonotic spillover risks present across geographically and socioeconomically diverse regions worldwide, extending beyond tropical areas, including extensive regions experiencing high-intensity human modification. These insights support targeted surveillance in areas with potentially high relative risk or uncertainty, and demonstrate how zoonotic spillover responds to complex human-environment interactions. https://doi.org/10.1289/EHP15937.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"59 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Hao,Amber L Cathey,Max M Aung,Jonathan Boss,John D Meeker,Bhramar Mukherjee
BACKGROUNDQuantitative characterization of the health impacts associated with exposure to chemical mixtures has received considerable attention in current environmental and epidemiological studies. With many existing statistical methods and emerging approaches, it is important for practitioners to understand which method is best suited for their inferential goals.OBJECTIVEThe goal of this paper is to provide empirical simulation-based evidence regarding performance of mixture methods to help guide researchers on selecting the best available methods to address three scientific questions in mixtures analysis: identifying important components of a mixture, identifying interactions among mixture components and creating a summary score for risk stratification and prediction.METHODSWe conduct a review and comparison of 11 analytical methods available for use in mixtures research, through extensive simulation studies for continuous and binary outcomes. In addition, we carry out an illustrative data analysis using the PROTECT birth cohort from Puerto Rico, to examine the associations between exposure to chemical mixtures-metals, polycyclic aromatic hydrocarbons (PAHs), phthalates and phenols-and birth outcomes.RESULTSOur simulation results suggest that the choice of methods depends on the goal of analysis and there is no clear winner across the board. For selection of important toxicants in the mixtures and for identifying interactions, Elastic net by Zou et al. (Enet), Lasso for Hierarchical Interactions by Bien et al.(HierNet), Selection of nonlinear interactions by a forward stepwise algorithm by Narisetty et al. (SNIF) have the most stable performance across simulation settings. For overall summary or a cumulative measure, we find that using the Super Learner to combine multiple Environmental Risk Scores can lead to improved risk stratification and prediction properties.CONCLUSIONSWe develop an integrated R package "CompMix" that provides a platform for mixtures analysis where the practitioners can implement a pipeline that includes several approaches for mixtures analysis. Our study offers guidelines for selecting appropriate statistical methods for addressing specific scientific questions related to mixtures research. We identify critical gaps where new and better methods are needed. https://doi.org/10.1289/EHP15305.
背景：在当前的环境和流行病学研究中，与接触化学混合物有关的健康影响的定量表征受到了相当大的关注。对于许多现有的统计方法和新兴的方法，从业者了解哪种方法最适合他们的推理目标是很重要的。本文的目的是提供关于混合方法性能的基于经验模拟的证据，以帮助指导研究人员选择最佳可用方法来解决混合物分析中的三个科学问题：确定混合物的重要成分，确定混合物成分之间的相互作用以及为风险分层和预测创建汇总评分。方法我们通过对连续和二元结果的广泛模拟研究，对11种可用于混合物研究的分析方法进行了回顾和比较。此外，我们使用波多黎各的PROTECT出生队列进行了说明性数据分析，以检查暴露于化学混合物-金属，多环芳烃（PAHs），邻苯二甲酸盐和苯酚-与出生结果之间的关系。结果我们的模拟结果表明，方法的选择取决于分析的目标，并且没有明确的赢家。对于混合物中重要毒物的选择和相互作用的识别，Zou等人的Elastic net (Enet)， Bien等人的Lasso分层相互作用（HierNet）， Narisetty等人（SNIF）通过前向逐步算法选择非线性相互作用在模拟设置中具有最稳定的性能。对于总体总结或累积测量，我们发现使用超级学习者组合多个环境风险评分可以提高风险分层和预测性能。我们开发了一个集成的R软件包“CompMix”，它提供了一个混合物分析平台，从业者可以在其中实现包括几种混合物分析方法的管道。我们的研究为选择适当的统计方法提供了指导方针，以解决与混合物研究相关的具体科学问题。我们确定需要新的和更好的方法的关键差距。https://doi.org/10.1289/EHP15305。
{"title":"Statistical methods for chemical mixtures: a roadmap for practitioners using simulation studies and a sample data analysis in the PROTECT cohort.","authors":"Wei Hao,Amber L Cathey,Max M Aung,Jonathan Boss,John D Meeker,Bhramar Mukherjee","doi":"10.1289/ehp15305","DOIUrl":"https://doi.org/10.1289/ehp15305","url":null,"abstract":"BACKGROUNDQuantitative characterization of the health impacts associated with exposure to chemical mixtures has received considerable attention in current environmental and epidemiological studies. With many existing statistical methods and emerging approaches, it is important for practitioners to understand which method is best suited for their inferential goals.OBJECTIVEThe goal of this paper is to provide empirical simulation-based evidence regarding performance of mixture methods to help guide researchers on selecting the best available methods to address three scientific questions in mixtures analysis: identifying important components of a mixture, identifying interactions among mixture components and creating a summary score for risk stratification and prediction.METHODSWe conduct a review and comparison of 11 analytical methods available for use in mixtures research, through extensive simulation studies for continuous and binary outcomes. In addition, we carry out an illustrative data analysis using the PROTECT birth cohort from Puerto Rico, to examine the associations between exposure to chemical mixtures-metals, polycyclic aromatic hydrocarbons (PAHs), phthalates and phenols-and birth outcomes.RESULTSOur simulation results suggest that the choice of methods depends on the goal of analysis and there is no clear winner across the board. For selection of important toxicants in the mixtures and for identifying interactions, Elastic net by Zou et al. (Enet), Lasso for Hierarchical Interactions by Bien et al.(HierNet), Selection of nonlinear interactions by a forward stepwise algorithm by Narisetty et al. (SNIF) have the most stable performance across simulation settings. For overall summary or a cumulative measure, we find that using the Super Learner to combine multiple Environmental Risk Scores can lead to improved risk stratification and prediction properties.CONCLUSIONSWe develop an integrated R package \"CompMix\" that provides a platform for mixtures analysis where the practitioners can implement a pipeline that includes several approaches for mixtures analysis. Our study offers guidelines for selecting appropriate statistical methods for addressing specific scientific questions related to mixtures research. We identify critical gaps where new and better methods are needed. https://doi.org/10.1289/EHP15305.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"32 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDBoth environmental exposure and type 2 diabetes (T2D) genetic susceptibility affect fetal growth. However, most previous studies used single exposure rather than an exposome strategy to explore the association between environmental factors and fetal growth, and the interactions of environmental exposures with maternal and fetal genes were often overlooked.OBJECTIVESTo explore the associations between a broad range of prenatal environmental factors and fetal growth and further evaluate the effect modification of maternal and fetal T2D genetic susceptibility on the identified exposures.METHODSFrom 1,933 mother-neonate pairs from the Shanghai Birth Cohort, we estimated the associations between 70 prenatal exposure measures (including outdoor environment, residential environment, chemical exposures, lifestyle factors, and psychosocial status) and fetal growth, measured by birth-weight-for-gestational-age z-score (WAZ). Single-exposure analysis, elastic net regression, sparse partial least squares regression, extreme gradient boosting, and random forest were applied jointly to screen for WAZ-associated exposures. Multivariable linear regression models were used to assess the interactions of WAZ-associated exposures with maternal and fetal T2D polygenetic risk score (PRS).RESULTSSixteen prenatal exposures were associated with fetal growth, of which manganese, strontium, and residential greenspace showed a positive association while bisphenol A (BPA), 2,4-dihydroxy benzophenone (BP-1), ethyl 4-hydroxybenzoate (EtP), 4-hydroxybenzophenone (4-HBP), artificial light at night, noise, nitrogen dioxide, rubidium, thallium, silver, and humidity had a negative association. Temperature had an inverse U-shaped association with WAZ. The interactions of BPA and silver with maternal and fetal T2D PRS and rubidium with fetal T2D PRS were statistically significant, with more pronounced exposure effects in individuals with high T2D genetic risks.DISCUSSIONOur study identified several prenatal environmental exposures within the outdoor environment, phenols, and metal(loid)s that were associated with fetal growth. Mother-neonate pairs with high T2D genetic susceptibility were particularly vulnerable to the environmental insults. https://doi.org/10.1289/EHP15902.
{"title":"A prospective exposome-based gene-environment interaction study on the effects of prenatal environmental exposure on fetal growth in the Shanghai Birth Cohort.","authors":"Wen Jiang,Yun Huang,Hong Jin,Yuexin Gan,Qingli Zhang,Xiaoqing He,Ying Tian,Jun Zhang,The Shanghai Birth Cohort","doi":"10.1289/ehp15902","DOIUrl":"https://doi.org/10.1289/ehp15902","url":null,"abstract":"BACKGROUNDBoth environmental exposure and type 2 diabetes (T2D) genetic susceptibility affect fetal growth. However, most previous studies used single exposure rather than an exposome strategy to explore the association between environmental factors and fetal growth, and the interactions of environmental exposures with maternal and fetal genes were often overlooked.OBJECTIVESTo explore the associations between a broad range of prenatal environmental factors and fetal growth and further evaluate the effect modification of maternal and fetal T2D genetic susceptibility on the identified exposures.METHODSFrom 1,933 mother-neonate pairs from the Shanghai Birth Cohort, we estimated the associations between 70 prenatal exposure measures (including outdoor environment, residential environment, chemical exposures, lifestyle factors, and psychosocial status) and fetal growth, measured by birth-weight-for-gestational-age z-score (WAZ). Single-exposure analysis, elastic net regression, sparse partial least squares regression, extreme gradient boosting, and random forest were applied jointly to screen for WAZ-associated exposures. Multivariable linear regression models were used to assess the interactions of WAZ-associated exposures with maternal and fetal T2D polygenetic risk score (PRS).RESULTSSixteen prenatal exposures were associated with fetal growth, of which manganese, strontium, and residential greenspace showed a positive association while bisphenol A (BPA), 2,4-dihydroxy benzophenone (BP-1), ethyl 4-hydroxybenzoate (EtP), 4-hydroxybenzophenone (4-HBP), artificial light at night, noise, nitrogen dioxide, rubidium, thallium, silver, and humidity had a negative association. Temperature had an inverse U-shaped association with WAZ. The interactions of BPA and silver with maternal and fetal T2D PRS and rubidium with fetal T2D PRS were statistically significant, with more pronounced exposure effects in individuals with high T2D genetic risks.DISCUSSIONOur study identified several prenatal environmental exposures within the outdoor environment, phenols, and metal(loid)s that were associated with fetal growth. Mother-neonate pairs with high T2D genetic susceptibility were particularly vulnerable to the environmental insults. https://doi.org/10.1289/EHP15902.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"131 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDHeat wave frequency and intensity is increasing and this trend is more pronounced in urban areas. Heat waves may be acutely associated with early birth.OBJECTIVESTo examine the acute relationship between heat waves and preterm (<37 weeks) and early-term (37-38 weeks) birth in eight states: California, Florida, Georgia, Kansas, Nevada, New Jersey, North Carolina, and Oregon.METHODSDaily mean temperatures from the novel High-resolution Urban Meteorology for Impacts Dataset (HUMID) were averaged by zip code tabulation area (ZCTA) and linked to singleton preterm and early-term births identified statewide from vital records. Heat waves were defined based on days exceeding the local 97.5%ile temperature threshold during the 4-day exposure window preceding birth. We conducted case-crossover (conditional logistic regression) state-specific analyses and pooled results using inverse-variance weighting to obtain summary effect estimates. We also calculated ORs adjusting for temporal changes in the pregnancy risk set, conducted an analysis excluding medically-induced early-term births, and modeled effects stratified by 97.5th mean temperature threshold categories.RESULTSThe analysis included 2,966,661 early-term and 945,869 preterm births occurring from May - September across the eight states from as early as 1990 to 2017. Results showed modestly elevated odds of early-term birth for heat waves occurring in the 4 days preceding birth. Pooled ORs (95%CIs) for 3- and 4-consecutive days above the 97.5th percentile mean temperature were 1.018 (1.011, 1.026) and 1.017 (1.005, 1.028), respectively. Preterm birth ORs were similar, but less precise; OR=1.015 (1.001, 1.029) and 1.019 (0.999, 1.041) for 3- and 4-consecutive days respectively. Estimated odds ratios tended to be stronger for ZCTAs in thesecond-lowest category of temperature threshold.DISCUSSIONUsing fine-scale surface temperature data capturing urban-heat islands, we observed a modest acute overall effect of heat waves on preterm and early-term birth. https://doi.org/10.1289/EHP15953.
{"title":"Preterm and early-term delivery after heat waves in eight US states: A case-crossover study using the High-resolution Urban Meteorology for Impacts Dataset (HUMID).","authors":"Amy Fitch,Mengjiao Huang,Matthew Strickland,Andrew Newman,Christina Kalb,Joshua L Warren,Xiaping Zheng,Howard Chang,Lyndsey Darrow","doi":"10.1289/ehp15953","DOIUrl":"https://doi.org/10.1289/ehp15953","url":null,"abstract":"BACKGROUNDHeat wave frequency and intensity is increasing and this trend is more pronounced in urban areas. Heat waves may be acutely associated with early birth.OBJECTIVESTo examine the acute relationship between heat waves and preterm (<37 weeks) and early-term (37-38 weeks) birth in eight states: California, Florida, Georgia, Kansas, Nevada, New Jersey, North Carolina, and Oregon.METHODSDaily mean temperatures from the novel High-resolution Urban Meteorology for Impacts Dataset (HUMID) were averaged by zip code tabulation area (ZCTA) and linked to singleton preterm and early-term births identified statewide from vital records. Heat waves were defined based on days exceeding the local 97.5%ile temperature threshold during the 4-day exposure window preceding birth. We conducted case-crossover (conditional logistic regression) state-specific analyses and pooled results using inverse-variance weighting to obtain summary effect estimates. We also calculated ORs adjusting for temporal changes in the pregnancy risk set, conducted an analysis excluding medically-induced early-term births, and modeled effects stratified by 97.5th mean temperature threshold categories.RESULTSThe analysis included 2,966,661 early-term and 945,869 preterm births occurring from May - September across the eight states from as early as 1990 to 2017. Results showed modestly elevated odds of early-term birth for heat waves occurring in the 4 days preceding birth. Pooled ORs (95%CIs) for 3- and 4-consecutive days above the 97.5th percentile mean temperature were 1.018 (1.011, 1.026) and 1.017 (1.005, 1.028), respectively. Preterm birth ORs were similar, but less precise; OR=1.015 (1.001, 1.029) and 1.019 (0.999, 1.041) for 3- and 4-consecutive days respectively. Estimated odds ratios tended to be stronger for ZCTAs in thesecond-lowest category of temperature threshold.DISCUSSIONUsing fine-scale surface temperature data capturing urban-heat islands, we observed a modest acute overall effect of heat waves on preterm and early-term birth. https://doi.org/10.1289/EHP15953.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"18 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ricardo Scheufen Tieghi,Cleber C Melo-Filho,Holli-Joi Martin,José Teófilo Moreira-Filho,Tripp LaPratt,Dave Allen,Judy Strickland,Alexander Tropsha,Nicole Kleinstreuer,Eugene N Muratov
{"title":"External Validation of STopTox - Novel Alternative Method (NAM) for Acute Systemic and Topical Toxicity.","authors":"Ricardo Scheufen Tieghi,Cleber C Melo-Filho,Holli-Joi Martin,José Teófilo Moreira-Filho,Tripp LaPratt,Dave Allen,Judy Strickland,Alexander Tropsha,Nicole Kleinstreuer,Eugene N Muratov","doi":"10.1289/ehp16647","DOIUrl":"https://doi.org/10.1289/ehp16647","url":null,"abstract":"","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"138 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ricardo Scheufen Tieghi, Marielle Rath, José Teófilo Moreira-Filho, James Wellnitz, Holli-Joi Martin, Kathleen Gates, Helena T Hogberg, Nicole Kleinstreuer, Alexander Tropsha, Eugene N Muratov
Background: Medication use among pregnant women is common, yet the safety of these medications for the developing fetus/baby is widely understudied. Quantitative Structure-Activity Relationship (QSAR) models can be used to predict the overall and trimester-specific developmental toxicity potential of chemicals, supporting the development of safer medications for pregnant women and regulatory assessment aligned with the 3Rs (refining, reducing, and replacing) of animal testing.
Objectives: This study aimed to collect and curate a database of compounds classified according to their developmental toxicity potential, use this database to develop and validate QSAR models for predicting prenatal developmental toxicity, and implement models via a user-friendly online platform to support regulatory assessments of drug candidates.
Methods: We compiled and curated data from the FDA and Teratogen Information System (TERIS) databases and validated annotations with rigorous literature searches. The database was leveraged to create QSAR models using machine learning algorithms (RF, SVM, LightGBM) with Bayesian hyperparameter optimization. These models were implemented into a web tool.
Results: We built a binary classification QSAR model for overall pregnancy risk, and separate QSAR models for trimester-specific risk, exhibiting correct classification rates of and 76% (overall), 80% (1st trimester), 95% (2nd trimester), and 95% (3rd trimester). Models showed a sensitivity between 53% and 90%, specificity between 46% and 100%, and coverage of 76% assessed using a five-fold external validation protocol. We established a publicly accessible web portal (https://detox.mml.unc.edu/) for developmental toxicity prediction of both overall and trimester-specific toxicity predictions.
Conclusions: DeTox can be employed to support regulatory assessment of pharmaceutical and cosmetic products aligned with the 3Rs of animal testing and to guide the development of safer drugs for pregnant populations. The curated dataset of developmental toxicants is publicly available, and all models are implemented in a public, user-friendly web tool, DeTox (Developmental Toxicity), at https://detox.mml.unc.edu/. https://doi.org/10.1289/EHP15307.
{"title":"DeTox: an <i>In-Silico</i> Alternative to Animal Testing for Predicting Developmental Toxicity Potential.","authors":"Ricardo Scheufen Tieghi, Marielle Rath, José Teófilo Moreira-Filho, James Wellnitz, Holli-Joi Martin, Kathleen Gates, Helena T Hogberg, Nicole Kleinstreuer, Alexander Tropsha, Eugene N Muratov","doi":"10.1289/EHP15307","DOIUrl":"https://doi.org/10.1289/EHP15307","url":null,"abstract":"<p><strong>Background: </strong>Medication use among pregnant women is common, yet the safety of these medications for the developing fetus/baby is widely understudied. Quantitative Structure-Activity Relationship (QSAR) models can be used to predict the overall and trimester-specific developmental toxicity potential of chemicals, supporting the development of safer medications for pregnant women and regulatory assessment aligned with the 3Rs (<u>r</u>efining, <u>r</u>educing, and <u>r</u>eplacing) of animal testing.</p><p><strong>Objectives: </strong>This study aimed to collect and curate a database of compounds classified according to their developmental toxicity potential, use this database to develop and validate QSAR models for predicting prenatal developmental toxicity, and implement models via a user-friendly online platform to support regulatory assessments of drug candidates.</p><p><strong>Methods: </strong>We compiled and curated data from the FDA and Teratogen Information System (TERIS) databases and validated annotations with rigorous literature searches. The database was leveraged to create QSAR models using machine learning algorithms (RF, SVM, LightGBM) with Bayesian hyperparameter optimization. These models were implemented into a web tool.</p><p><strong>Results: </strong>We built a binary classification QSAR model for overall pregnancy risk, and separate QSAR models for trimester-specific risk, exhibiting correct classification rates of and 76% (overall), 80% (1<sup>st</sup> trimester), 95% (2<sup>nd</sup> trimester), and 95% (3<sup>rd</sup> trimester). Models showed a sensitivity between 53% and 90%, specificity between 46% and 100%, and coverage of 76% assessed using a five-fold external validation protocol. We established a publicly accessible web portal (https://detox.mml.unc.edu/) for developmental toxicity prediction of both overall and trimester-specific toxicity predictions.</p><p><strong>Conclusions: </strong>DeTox can be employed to support regulatory assessment of pharmaceutical and cosmetic products aligned with the 3Rs of animal testing and to guide the development of safer drugs for pregnant populations. The curated dataset of developmental toxicants is publicly available, and all models are implemented in a public, user-friendly web tool, DeTox (<u>De</u>velopmental <u>Tox</u>icity), at https://detox.mml.unc.edu/. https://doi.org/10.1289/EHP15307.</p>","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":" ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144093205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDThe impact of non-nutritive sweeteners on male reproductive health, particularly at the cellular level, remains insufficiently explored. Sucralose's high stability and resistance to degradation during wastewater treatment raises concerns about its long-term environmental and health impacts. Whether sucralose consumption correlates with reduced reproductive hormone levels and testicular damage remains unclear, and the underlying mechanisms require further investigation.OBJECTIVESThis study aims to investigate the influence of sucralose on cell damage and reproductive health in male.METHODSThe male mouse Leydig cell line TM3 and Sertoli cell line TM4 were used to evaluate sucralose-associated cellular damage. In vitro experiments assessed cell survival rates and the potential disruption of autophagy. Additionally, male SD rats were exposed to sucralose via oral gavage for two months at doses reflecting the acceptable daily intake (ADI) to evaluate sperm viability and reproductive health.RESULTSIn vitro experiments demonstrated cells exposed to sucralose had significantly lower cell survival rates. Sucralose exposure significantly reduced cell viability in TM3 and TM4 cells, induced oxidative stress, and disrupted autophagic flux by impairing autophagosome-lysosome fusion. Additionally, sucralose downregulated T1R3 protein expression, suggesting a role for sweet taste receptor signaling in testicular cell regulation. In vivo, chronic oral exposure to sucralose led to decreased sperm viability and dysregulated reproductive function, including altered testicular morphology and suppressed steroidogenesis.DISCUSSIONThese findings provide new insights into the adverse effects of sucralose on male reproductive physiology, highlighting its role in disrupting autophagy, inducing oxidative stress, and impairing reproductive function. The environmental persistence of sucralose and its potential leakage into wastewater systems present broader implications for public health and ecological stability. This study underscores the importance of carefully evaluating non-nutritive sweeteners in the diet and calls for stricter food safety regulations and wastewater management practices to mitigate potential risks.. https://doi.org/10.1289/EHP15919.
{"title":"Exposure to Sucralose and Its Effects on Testicular Damage and Male Infertility: Insights into Oxidative Stress and Autophagy.","authors":"Yi-Fen Chiang,Yang-Ching Chen,Ko-Chieh Huang,Mohamed Ali,Shih-Min Hsia","doi":"10.1289/ehp15919","DOIUrl":"https://doi.org/10.1289/ehp15919","url":null,"abstract":"BACKGROUNDThe impact of non-nutritive sweeteners on male reproductive health, particularly at the cellular level, remains insufficiently explored. Sucralose's high stability and resistance to degradation during wastewater treatment raises concerns about its long-term environmental and health impacts. Whether sucralose consumption correlates with reduced reproductive hormone levels and testicular damage remains unclear, and the underlying mechanisms require further investigation.OBJECTIVESThis study aims to investigate the influence of sucralose on cell damage and reproductive health in male.METHODSThe male mouse Leydig cell line TM3 and Sertoli cell line TM4 were used to evaluate sucralose-associated cellular damage. In vitro experiments assessed cell survival rates and the potential disruption of autophagy. Additionally, male SD rats were exposed to sucralose via oral gavage for two months at doses reflecting the acceptable daily intake (ADI) to evaluate sperm viability and reproductive health.RESULTSIn vitro experiments demonstrated cells exposed to sucralose had significantly lower cell survival rates. Sucralose exposure significantly reduced cell viability in TM3 and TM4 cells, induced oxidative stress, and disrupted autophagic flux by impairing autophagosome-lysosome fusion. Additionally, sucralose downregulated T1R3 protein expression, suggesting a role for sweet taste receptor signaling in testicular cell regulation. In vivo, chronic oral exposure to sucralose led to decreased sperm viability and dysregulated reproductive function, including altered testicular morphology and suppressed steroidogenesis.DISCUSSIONThese findings provide new insights into the adverse effects of sucralose on male reproductive physiology, highlighting its role in disrupting autophagy, inducing oxidative stress, and impairing reproductive function. The environmental persistence of sucralose and its potential leakage into wastewater systems present broader implications for public health and ecological stability. This study underscores the importance of carefully evaluating non-nutritive sweeteners in the diet and calls for stricter food safety regulations and wastewater management practices to mitigate potential risks.. https://doi.org/10.1289/EHP15919.","PeriodicalId":11862,"journal":{"name":"Environmental Health Perspectives","volume":"96 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：