PolyMatch: Novel Libraries, Algorithms, and Visualizations for Discovering Polymers and Chemical Series.

Polymers are integral components of everyday products, ranging from plastics and emulsifiers to lubricants and detergents. Characterization of these materials at the molecular level is essential to understanding their physicochemical properties and potential health impacts, considering factors such as the number of repeating units, chemical moieties, functional groups, and degree of unsaturation. This study introduces a free open-source vendor neutral software, PolyMatch, designed to annotate polysorbates, polysorbides, polyethylene glycols (PEGs), fatty acid esterified species, and related chemical species based on mass spectral and chromatographic patterns inherent in the repeating nature of chemical moieties. PolyMatch facilitates the generation of MS/MS libraries for polymeric chemical species characterization (with over 800 000 structures with associated fragment masses already built in) and covers the entire liquid chromatography-high-resolution mass spectrometry (LC-HRMS/MS) data-processing workflow. PolyMatch covers peak picking, blank filtering, annotation, data visualization, and sharing of interactive data sets via an HTML link to the community. The software was applied to a Tween 80 mixture, using LC-HRMS/MS on an Agilent 6546 Q-TOF instrument with iterative exclusion for comprehensive fragmentation coverage. PolyMatch automatically assigned 86 features with high confidence at the species level, 362 based on PEG containing fragments and accurate mass matching to a simulated polymer database, and over 10 000 based on being a member of a homologous series (three or more) with CH2CH2O repeating units. The ease of use of PolyMatch and comprehensive coverage with species level assignment is expected to contribute to the advancement of materials science, health research, and product development.

Household air pollution and risk of pulmonary tuberculosis in HIV-Infected adults.

BACKGROUND: In low- and middle-income countries countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection. METHODS: We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB. RESULTS: We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/week were more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm]. CONCLUSION: Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

Assessment of wood smoke induced pulmonary toxicity in normal- and chronic bronchitis-like bronchial and alveolar lung mucosa models at air-liquid interface.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) has the highest increased risk due to household air pollution arising from biomass fuel burning. However, knowledge on COPD patho-mechanisms is mainly limited to tobacco smoke exposure. In this study, a repeated direct wood smoke (WS) exposure was performed using normal- (bro-ALI) and chronic bronchitis-like bronchial (bro-ALI-CB), and alveolar (alv-ALI) lung mucosa models at air-liquid interface (ALI) to assess broad toxicological end points. METHODS: The bro-ALI and bro-ALI-CB models were developed using human primary bronchial epithelial cells and the alv-ALI model was developed using a representative type-II pneumocyte cell line. The lung models were exposed to WS (10 min/exposure; 5-exposures over 3-days; n = 6-7 independent experiments). Sham exposed samples served as control. WS composition was analyzed following passive sampling. Cytotoxicity, total cellular reactive oxygen species (ROS) and stress responsive NFkB were assessed by flow cytometry. WS exposure induced changes in gene expression were evaluated by RNA-seq (p ≤ 0.01) followed by pathway enrichment analysis. Secreted levels of proinflammatory cytokines were assessed in the basal media. Non-parametric statistical analysis was performed. RESULTS: 147 unique compounds were annotated in WS of which 42 compounds have inhalation toxicity (9 very high). WS exposure resulted in significantly increased ROS in bro-ALI (11.2%) and bro-ALI-CB (25.7%) along with correspondingly increased NFkB levels (bro-ALI: 35.6%; bro-ALI-CB: 18.1%). A total of 1262 (817-up and 445-down), 329 (141-up and 188-down), and 102 (33-up and 69-down) genes were differentially regulated in the WS-exposed bro-ALI, bro-ALI-CB, and alv-ALI models respectively. The enriched pathways included the terms acute phase response, mitochondrial dysfunction, inflammation, oxidative stress, NFkB, ROS, xenobiotic metabolism of AHR, and chronic respiratory disorder. The enrichment of the 'cilium' related genes was predominant in the WS-exposed bro-ALI (180-up and 7-down). The pathways primary ciliary dyskinesia, ciliopathy, and ciliary movement were enriched in both WS-exposed bro-ALI and bro-ALI-CB. Interleukin-6 and tumor necrosis factor-α were reduced (p < 0.05) in WS-exposed bro-ALI and bro-ALI-CB. CONCLUSION: Findings of this study indicate differential response to WS-exposure in different lung regions and in chronic bronchitis, a condition commonly associated with COPD. Further, the data suggests ciliopathy as a candidate pathway in relation to WS-exposure.

Perfluorooctanesulfonic Acid and Perfluorooctanoic Acid Promote Migration of Three-Dimensional Colorectal Cancer Spheroids.

Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) are persistent environmental contaminants that are of increasing public concern worldwide. However, their relationship with colorectal cancer (CRC) is poorly understood. This study aims to comprehensively investigate the effect of PFOS and PFOA on the development and progression of CRC in vitro using a series of biological techniques and metabolic profiling. Herein, the migration of three-dimensional (3D) spheroids of two CRC cell lines, SW48 KRAS wide-type (WT) and SW48 KRAS G12A, were observed after exposure to PFOS and PFOA at 2 µM and 10 µM for 7 days. The time and dose-dependent migration phenotype induced by 10 µM PFOS and PFOA was further confirmed by wound healing and trans-well migration assays. To investigate the mechanism of action, derivatization-mass spectrometry-based metabolic profiles were examined from 3D spheroids of SW48 cell lines exposed to PFOS and PFOA (2 µM and 10 µM). Our findings revealed this exposure altered epithelial-mesenchymal transition related metabolic pathways, including fatty acid ß-oxidation and synthesis of proteins, nucleotides, and lipids. Furthermore, this phenotype was confirmed by the downregulation of E-cadherin and upregulation of N-cadherin and vimentin. These findings show novel insight into the relationship between PFOS, PFOA, and CRC.

Household Air Pollution and Risk of Pulmonary Tuberculosis in HIV-Infected Adults.

Background: In developing countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection. Methods: We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB. Results: We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/weekwere more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm]. Conclusion: Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon.

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor-fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS.

Per- and polyfluoroalkyl substances (PFAS) and thyroid hormone measurements in dried blood spots and neonatal characteristics: a pilot study.

BACKGROUND: Pediatric thyroid diseases have been increasing in recent years. Environmental risk factors such as exposures to chemical contaminants may play a role but are largely unexplored. Archived neonatal dried blood spots (DBS) offer an innovative approach to investigate environmental exposures and effects. OBJECTIVE: In this pilot study, we applied a new method for quantifying per- and polyfluoroalkyl substances (PFAS) to 18 archived DBS from babies born in California from 1985-2018 and acquired thyroid hormone measurements from newborn screening tests. Leveraging these novel data, we evaluated (1) changes in the concentrations of eight PFAS over time and (2) the relationship between PFAS concentrations, thyroid hormone concentrations, and neonatal characteristics to inform future research. METHODS: PFAS concentrations in DBS were measured using ultra-high-performance liquid chromatography-mass spectrometry. Summary statistics and non-parametric Wilcoxon rank-sum and Kruskal-Wallis tests were used to evaluate temporal changes in PFAS concentrations and relationships between PFAS concentrations, thyroid hormone concentrations, and neonatal characteristics. RESULTS: The concentration and detection frequencies of several PFAS (PFOA, PFOS, and PFOSA) declined over the assessment period. We observed that the timing of specimen collection in hours after birth was related to thyroid hormone but not PFAS concentrations, and that thyroid hormones were related to some PFAS concentrations (PFOA and PFOS). IMPACT STATEMENT: This pilot study examines the relationship between concentrations of eight per- and polyfluoroalkyl substances (PFAS), thyroid hormone levels, and neonatal characteristics in newborn dried blood spots (DBS) collected over a period of 33 years. To our knowledge, 6 of the 22 PFAS we attempted to measure have not been quantified previously in neonatal DBS, and this is the first study to examine both PFAS and thyroid hormone concentrations using DBS. This research demonstrates the feasibility of using newborn DBS for quantifying PFAS exposures in population-based studies, highlights methodological considerations in the use of thyroid hormone data for future studies using newborn DBS, and indicates potential relationships between PFAS concentrations and thyroid hormones for follow-up in future research.

Per- and polyfluoroalkyl substances and sleep health in U.S. adults, NHANES 2005-2014.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that induce oxidative inflammatory responses and disrupt the endocrine and central nervous systems, all of which can influence sleep. OBJECTIVE: To investigate the association between PFAS exposure and sleep health measures in U.S. adults. METHODS: We analyzed serum concentration data of four PFAS [perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)] reported for 8913 adults in NHANES 2005-2014. Sleep outcomes, including trouble sleeping, having a diagnosis of sleep disorder, and recent daily sleep duration classified as insufficient or excessive sleep (<6 or >9 h/day) were examined. Weighted logistic regression was used to estimate the association between the sleep outcomes and each PFAS modeled continuously (log2) or in exposure tertiles. We applied quantile g-computation to estimate the effect of the four PFAS as a mixture on the sleep outcomes. We conducted a quantitative bias analysis to assess the potential influence of self-selection and uncontrolled confounding. RESULTS: We observed some inverse associations between serum PFAS and trouble sleeping or sleep disorder, which were more consistent for PFOS (e.g., per log2-PFOS (ng/ml) and trouble sleeping OR = 0.93, 95%CI: 0.89, 0.98; sleep disorder OR = 0.89, 95%CI: 0.83, 0.95). Per quartile increase of the PFAS mixture was inversely associated with trouble sleeping and sleep disorder. No consistent associations were found for sleep duration across analyses. Our bias analysis suggests that the finding on sleep disorder could be explained by a moderate level of self-selection and negative confounding effects. CONCLUSIONS: We found no evidence to suggest exposure to four legacy PFAS worsened self-reported sleep health among U.S. adults. While some inverse associations between specific PFAS and sleep disorder were observed, self-selection and uncontrolled confounding biases may play a role in these findings.

Within-city spatial variations in long-term average outdoor oxidant gas concentrations and cardiovascular mortality: Effect modification by oxidative potential in the Canadian Census Health and Environment Cohort.

Health effects of oxidant gases may be enhanced by components of particulate air pollution that contribute to oxidative stress. Our aim was to examine if within-city spatial variations in the oxidative potential of outdoor fine particulate air pollution (PM2.5) modify relationships between oxidant gases and cardiovascular mortality. Methods: We conducted a retrospective cohort study of participants in the Canadian Census Health and Environment Cohort who lived in Toronto or Montreal, Canada, from 2002 to 2015. Cox proportional hazards models were used to estimate associations between outdoor concentrations of oxidant gases (Ox, a redox-weighted average of nitrogen dioxide and ozone) and cardiovascular deaths. Analyses were performed across strata of two measures of PM2.5 oxidative potential and reactive oxygen species concentrations (ROS) adjusting for relevant confounding factors. Results: PM2.5 mass concentration showed little within-city variability, but PM2.5 oxidative potential and ROS were more variable. Spatial variations in outdoor Ox were associated with an increased risk of cardiovascular mortality [HR per 5 ppb = 1.028, 95% confidence interval (CI): 1.001, 1.055]. The effect of Ox on cardiovascular mortality was stronger above the median of each measure of PM2.5 oxidative potential and ROS (e.g., above the median of glutathione-based oxidative potential: HR = 1.045, 95% CI: 1.009, 1.081; below median: HR = 1.000, 95% CI: 0.960, 1.043). Conclusion: Within-city spatial variations in PM2.5 oxidative potential may modify long-term cardiovascular health impacts of Ox. Regions with elevated Ox and PM2.5 oxidative potential may be priority areas for interventions to decrease the population health impacts of outdoor air pollution.

Assessment of children's personal and land use regression model-estimated exposure to NO2 in Springfield, Massachusetts.

Ambient nitrogen dioxide (NO2) is derived from tailpipe vehicle emission and is linked with various of health outcomes. Personal exposure monitoring is crucial for accurate assessment of the associated disease risks. This study aimed to evaluate the utility of a wearable air pollutant sampler in determining the personal NO2 exposure of school children for comparison with a model-based personal exposure assessment. We employed cost-effective, wearable passive samplers to directly measure personal exposure of 25 children (aged 12-13 years) in Springfield, MA to NO2 over a five-day period in winter 2018. NO2 levels were additionally measured at 40 outdoor sites in the same region using stationary passive samplers. A land use regression (LUR) model was developed based on the ambient NO2 measures, with a good prediction performance (R2 = 0.72) using road lengths, distance to highway, and institutional land area as predictor variables. Time-weighted averages (TWA), which incorporated the time-activity patterns of participants and LUR-derived estimates in children's primary microenvironments (homes, the school and commute paths), were calculated as an indirect measure of personal NO2 exposure. Results indicated that the conventional residence-based exposure estimate approach, often used in epidemiological studies, differed from the direct personal exposure and could overestimate the personal exposure by up to 109 %. TWA improved personal NO2 exposure estimates by accounting for the time activity patterns of individuals, a difference of 5.4 % ± 34.2 % was found for exposures compared to wristband measurements. Nevertheless, the personal wristband measurements exhibited a large variability due to the potential contributions from indoor and in-vehicle NO2 sources. The findings suggest that exposure to NO2 can be highly personalized based on individual activities and contact with pollutants in specific microenvironments, reaffirming the importance of measuring personal exposure.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome.

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Paired Indoor and Outdoor Nitrogen Dioxide Associated With Childhood Asthma Outcomes in a Mixed Rural-Urban Setting: A Feasibility Study.

INTRODUCTION: Nitrogen dioxide (NO2) is known to be a trigger for asthma exacerbation. However, little is known about the role of seasonal variation in indoor and outdoor NO2 levels in childhood asthma in a mixed rural-urban setting of North America. METHODS: This prospective cohort study, as a feasibility study, included 62 families with children (5-17 years) that had diagnosed persistent asthma residing in Olmsted County, Minnesota. Indoor and outdoor NO2 concentrations were measured using passive air samples over 2 weeks in winter and 2 weeks in summer. We assessed seasonal variation in NO2 levels in urban and rural residential areas and the association with asthma control status collected from participants' asthma diaries during the study period. RESULTS: Outdoor NO2 levels were lower (median: 2.4 parts per billion (ppb) in summer, 3.9 ppb in winter) than the Environmental Protection Agency (EPA) annual standard (53 ppb). In winter, a higher level of outdoor NO2 was significantly associated with urban residential living area (P = .014) and lower socioeconomic status (SES) (P = .027). For both seasons, indoor NO2 was significantly higher (P < .05) in rural versus urban areas and in homes with gas versus electric stoves (P < .05). Asthma control status was not associated with level of indoor or outdoor NO2 in this cohort. CONCLUSIONS: NO2 levels were low in this mixed rural-urban community and not associated with asthma control status in this small feasibility study. Further research with a larger sample size is warranted for defining a lower threshold of NO2 concentration with health effect on asthma in mixed rural-urban settings.

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants.

People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship between personal and stationary air pollutant measurements in residences of 37 participants working from home during the heating season. Stationary environmental monitors (SEMs) were located in the bedroom, living room or home office and personal exposure monitors (PEMs) were worn by the participants. SEMs and PEMs included both real-time sensors and passive samplers. During three consecutive weekdays, continuous data were obtained for particle number concentration (size range 0.3-10 µm), carbon dioxide (CO2), and total volatile organic compounds (TVOC), while passive samplers collected integrated measures of 36 volatile organic compounds (VOCs) and semi volatile organic compounds (SVOCs). The personal cloud effect was detected in >80% of the participants for CO2 and >50% participants for PM10. Multiple linear regression analysis showed that a single CO2 monitor placed in the bedroom efficiently represented personal exposure to CO2 (R2 = 0.90) and moderately so for PM10 (R2 = 0.55). Adding a second or third sensor in a residence did not lead to improved exposure estimates for CO2, with only 6-9% improvement for particles. Selecting data from SEMs when participants were in the same room improved personal exposure estimates by 33% for CO2 and 5% for particles. Out of 36 detected VOCs and SVOCs, 13 had at least 50% higher concentrations in personal versus stationary samples. Findings from this study aid improved understanding of the complex dynamics of gaseous and particle pollutants and their sources in residences, and could support the development of refined procedures for residential air quality monitoring and inhalation exposure assessment.

Novel perfluoroalkyl substances (PFAS) discovered in whole blood using automated non-targeted analysis of dried blood spots.

A small subset of per- and polyfluoroalkyl substances (PFAS) are routinely screened in human blood. These compounds generally explain <50 % of the total PFAS in human blood. The percentage of known PFAS in human blood has been decreasing as replacement PFAS and more complex PFAS chemistries are introduced to the market. Most of these novel PFAS have not been previously identified. Non-targeted methods are required to characterize this "dark matter" PFAS. Our objective was to apply non-targeted PFAS analysis to human blood to gain an understanding about the sources, concentrations, and toxicity of these compounds. A high-resolution tandem mass spectrometry (HRMS) and software workflow for PFAS characterization in dried blood spots is reported. Dried blood spots are a less invasive collection technique compared to venous blood draws, allowing collection from vulnerable populations. Biorepositories of archived dried blood spots are available internationally from newborns and present opportunities to study prenatal exposure to PFAS. In this study, dried blood spot cards were analyzed using iterative MS/MS by liquid chromatography HRMS. Data processing was conducted using FluoroMatch Suite including a visualizer tool that presents homologous series, retention time vs m/z plots, MS/MS spectra, feature tables, annotations, and fragments for fragment screening. The researcher performing data-processing and annotation was blinded to the fact that standards were spiked in, and was able to annotate 95 % of standards spiked on dried blood spot samples, signifying a low false negative rate using FluoroMatch Suite. A total of 28 PFAS (20 standards and 4 exogenous compounds) were detected across five homologous series with Schymanski Level 2 confidence. Of these 4, 3 were perfluoroalkyl ether carboxylic acids (PFECA), a chemical class of PFAS which is increasingly being detected in environmental and biological matrices but is not currently screened in most targeted analysese. A further 86 potential PFAS were detected using fragment screening. PFAS are extremely persistent and widespread yet remain largely unregulated. Our findings will contribute to an improved an understanding of exposures. Application of these methods in environmental epidemiology studies have the potential to inform policy with regards to PFAS monitoring, regulation, and individual-level mitigation strategies.

Trace analysis of per- and polyfluorinated alkyl substances (PFAS) in dried blood spots - Demonstration of reproducibility and comparability to venous blood samples.

Per- and polyfluoroalkyl substances (PFAS) are a group of man-made chemicals that have been widely used in consumer, personal care, and household products for their stain- and water-repellent properties. PFAS exposure has been linked to various adverse health outcomes. Such exposure has commonly been evaluated in venous blood samples. While this sample type can be obtained from healthy adults, a less invasive method of blood collection is required when evaluating vulnerable populations. Dried blood spots (DBS) have gained attention as a biomatrix for exposure assessment given the relative ease of collection, transport, and storage. The objective of this study was to develop and validate an analytical method to measure PFAS in DBS. A workflow is presented for extracting PFAS from DBS, chemical analysis by liquid chromatography-high resolution mass spectrometry, normalization for blood mass, and blank correction to account for potential contamination. Over 80 % recovery was achieved for the 22 PFAS measured with an average coefficient of variation of 14 %. Comparison of PFAS concentrations detected in DBS and paired whole blood samples from six healthy adults was correlated (R2 > 0.9). Findings demonstrate trace levels of a broad range of PFAS in DBS can be reproducibly measured and are comparable to liquid whole blood samples. DBS can offer novel insights to environmental exposures, including during critical windows of susceptibility (i.e., in utero, early life), which have been largely uncharacterized.

Association between Organophosphate Ester Exposure and Insulin Resistance with Glycometabolic Disorders among Older Chinese Adults 60-69 Years of Age: Evidence from the China BAPE Study.

BACKGROUND: Organophosphate esters (OPEs) are common endocrine-disrupting chemicals, and OPE exposure may be associated with type 2 diabetes (T2D). However, greater knowledge regarding the biomolecular intermediators underlying the impact of OPEs on T2D in humans are needed to understand biological etiology. OBJECTIVES: We explored the associations between OPE exposure and glycometabolic markers among older Chinese adults 60-69 years of age to elucidate the underlying mechanisms using a multi-omics approach. METHODS: This was a longitudinal panel study comprising 76 healthy participants 60-69 years of age who lived in Jinan city of northern China. The study was conducted once every month for 5 months, from September 2018 to January 2019. We measured a total of 17 OPEs in the blood, 11 OPE metabolites in urine, and 4 glycometabolic markers (fasting plasma glucose, glycated serum protein, fasting insulin, and homeostatic model assessment for insulin resistance). The blood transcriptome and serum/urine metabolome were also evaluated. The associations between individual OPEs and glycometabolic markers were explored. An adverse outcome pathway (AOP) was established to determine the biomolecules mediating the associations. RESULTS: Exposure to five OPEs and OPE metabolites (trimethylolpropane phosphate, triphenyl phosphate, tri-iso-butyl phosphate, dibutyl phosphate, and diphenyl phosphate) was associated with increased levels of glycometabolic markers. The mixture effect analysis further indicated the adverse effect of OPE mixtures. Multi-omics analyses revealed that the endogenous changes in the transcriptional and metabolic levels were associated with OPE exposure. The putative AOPs model suggested that triggers of molecular initiation events (e.g., insulin receptor and glucose transporter type 4) with subsequent key events, including disruptions in signal transduction pathways (e.g., phosphatidylinositol 3-kinase/protein kinase B and insulin secretion signaling) and biological functions (glucose uptake and insulin secretion), may constitute the diabetogenic effects of OPEs. DISCUSSION: OPEs are associated with the elevated risk of T2D among older Chinese adults 60-69 years of age. Implementing OPE exposure reduction strategies may help reduce the T2D burden among these individuals, if the relationship is causal. https://doi.org/10.1289/EHP11896.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions.

PURPOSE OF REVIEW: We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale. RECENT FINDINGS: Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Characterizing the external exposome using passive samplers-comparative assessment of chemical exposures using different wearable form factors.

BACKGROUND: Organic contaminants are released into the air from building materials/furnishings, personal care, and household products. Wearable passive samplers have emerged as tools to characterize personal chemical exposures. The optimal placement of these samplers on an individual to best capture airborne exposures has yet to be evaluated. OBJECTIVE: To compare personal exposure to airborne contaminants detected using wearable passive air samplers placed at different positions on the body. METHODS: Participants (n = 32) simultaneously wore four passive Fresh Air samplers, on their head, chest, wrist, and foot for 24 hours. Exposure to 56 airborne organic contaminants was evaluated using thermal desorption gas chromatography high resolution mass spectrometry with a targeted data analysis approach. RESULTS: Distinct exposure patterns were detected by samplers positioned on different parts of the body. Chest and wrist samplers were the most similar with correlations identified for 20% of chemical exposures (Spearman's Rho > 0.8, p < 0.05). In contrast, the greatest differences were found for head and foot samplers with the weakest correlations across evaluated exposures (8% compounds, Spearman's Rho > 0.8, p < 0.05). SIGNIFICANCE: The placement of wearable passive air samplers influences the exposures captured and should be considered in future exposure and epidemiological studies. IMPACT STATEMENT: Traditional approaches for assessing personal exposure to airborne contaminants with active samplers presents challenges due to their cost, size, and weight. Wearable passive samplers have recently emerged as a non-invasive, lower cost tool for measuring environmental exposures. While these samplers can be worn on different parts of the body, their position can influence the type of exposure that is captured. This study comprehensively evaluates the exposure to airborne chemical contaminants measured at different passive sampler positions worn on the head, chest, wrist, and foot. Findings provide guidance on sampler placement based on chemicals and emission sources of interest.

Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study.

Dried blood spot (DBS) metabolomics has numerous applications in newborn health screening, exposomics, and biomonitoring of environmental chemicals in pregnant women and the elderly. However, accurate metabolite quantification is hindered by several challenges: notably the "hematocrit effect" and unknown blood-spotting volumes. Different techniques have been employed to overcome these issues but there is no consensus on the optimal normalization method for DBS metabolomics, and in some cases no normalization is used. We compared five normalization methods (hemoglobin (Hb), specific gravity (SG), protein, spot weight, potassium (K+)) to unnormalized data, and assessed sex-related differences in the DBS metabolome in 21 adults (group 1, n = 10 males, n = 11 females). The performance of each normalization method was evaluated using multiple criteria: (a) reduction of intragroup variation (pooled median absolute deviation, pooled estimate of variance, pooled coefficient of variation, NMDS and principal component analysis), (b) effect on differential metabolic analysis (dendrogram, heatmap, p-value distribution), and (c) influence on classification accuracy (partial least squares discriminant analysis, sparse partial least squares discriminant analysis error rates, receiver operating curve, random forest out of bag error rate). Our results revealed that Hb normalization outperformed all the other methods based on the three criteria and 13 different parameters; the performance of Hb was further demonstrated in an independent group of DBS from 18 neonates (group 2, n = 9 males, n = 9 females). Furthermore, we showed that SG and Hb are correlated in adults (rs = 0.86, p < 0.001), and validated this relationship in an independent group of 18 neonates and infants (group 3) (rs = 0.84, p < 0.001). Using the equation, SG = -0.4814Hb2 + 2.44Hb + 0.005, SG can be used as a surrogate for normalization by Hb. This is the first comparative study to concurrently evaluate multiple normalization methods for DBS metabolomics which will serve as a robust methodological platform for future environmental epidemiological studies.

An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry.

Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.