High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

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.

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.

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.

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.

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.

Personal air pollutant exposure monitoring in South African children in the VHEMBE birth cohort.

The burden of disease associated with environmental exposures disproportionately impacts residents of low- and middle-income countries. Children living in rural regions of these countries may experience higher exposure to insecticides from indoor residual spraying used for malaria control and household air pollution. This study evaluated environmental exposures of children living in a rural region of South Africa. Quantifying exposure levels and identifying characteristics that are associated with exposure in this geographic region has been challenging due to limitations with available monitoring techniques. Wearable passive samplers have recently been shown to be a convenient and reliable tool for assessing personal exposures. In this study, a passive sampler wristband, known as Fresh Air wristband, was worn by 49 children (five-years of age) residing in the Limpopo province of South Africa. The study leveraged ongoing research within the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE) birth cohort. A wide range of chemicals (35 in total) were detected using the wristbands, including polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides, phthalates, and organophosphate esters (OPEs) flame retardants. Higher concentrations of PAHs were observed among children from households that fell below the food poverty threshold, did not have access to electric cookstoves/burners, or reported longer times of cooking or burning materials during the sampling period. Concentrations of p,p'-DDD and p,p'-DDT were also found to be elevated for children from households falling below the food poverty threshold as well as for children whose households were sprayed for malaria control within the previous 1.5 years. This study demonstrates the feasibility of using passive sampler wristbands as a non-invasive method for personal exposure assessment of children in rural regions of South Africa to complex mixtures environmental contaminants derived from a combination of sources. Future studies are needed to further identify and understand the effects of airborne environmental contaminants on childhood development and strategies to mitigate exposures.

Assessing the External Exposome Using Wearable Passive Samplers and High-Resolution Mass Spectrometry among South African Children Participating in the VHEMBE Study.

Children in low- and middle-income countries are often exposed to higher levels of chemicals and are more vulnerable to the health effects of air pollution. Little is known about the diversity, toxicity, and dynamics of airborne chemical exposures at the molecular level. We developed a workflow employing state-of-the-art wearable passive sampling technology coupled with high-resolution mass spectrometry to comprehensively measure 147 children's personal exposures to airborne chemicals in Limpopo, South Africa, as part of the Venda Health Examination of Mothers, Babies, and Their Environment (VHEMBE). 637 environmental exposures were detected, many of which have never been measured in this population; of these 50 airborne chemical exposures of concern were detected, including pesticides, plasticizers, organophosphates, dyes, combustion products, and perfumes. Biocides detected in wristbands included p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), propoxur, piperonyl butoxide, and triclosan. Exposures differed across the assessment period with 27% of detected chemicals observed to be either higher or lower in the wet or dry seasons.

FluoroMatch 2.0-making automated and comprehensive non-targeted PFAS annotation a reality.

Because of the pervasiveness, persistence, and toxicity of per- and polyfluoroalkyl substances (PFAS), there is growing concern over PFAS contamination, exposures, and health effects. The diversity of potential PFAS is astounding, with nearly 10,000 PFAS catalogued in databases to date (and growing). The ability to detect the thousands of known PFAS, and discover previously uncatalogued PFAS, is necessary to understand the scope of PFAS contamination and to identify appropriate remediation and regulatory solutions. Current non-targeted methods for PFAS analysis require manual curation and are time-consuming, prone to error, and not comprehensive. FluoroMatch Flow 2.0 is the first software to cover all steps of data processing for PFAS discovery in liquid chromatography-high-resolution tandem mass spectrometry samples. These steps include feature detection, feature blank filtering, exact mass matching to catalogued PFAS, mass defect filtering, homologous series detection, retention time pattern analysis, class-based MS/MS screening, fragment screening, and predicted MS/MS from SMILES structures. In addition, a comprehensive confidence level criterion is implemented to help users understand annotation certainty and integrate various layers of evidence to reduce overreporting. Applying the software to aqueous film forming foam analysis, we discovered over one thousand likely PFAS including previously unreported species. Furthermore, we were able to filter out 96% of features which were likely not PFAS. FluoroMatch Flow 2 increased coverage of likely PFAS by over tenfold compared to the previous release. This software will enable researchers to better characterize PFAS in the environment and in biological systems.

Lipidomics and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage.

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

Optimization of a liquid chromatography-ion mobility-high resolution mass spectrometry platform for untargeted lipidomics and application to HepaRG cell extracts.

Analytical methods to evaluate the lipidome of biological samples need to provide high data quality to ensure comprehensive profiling and reliable structural elucidation. In this perspective, liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art technique for lipidomic analysis of biological samples. There are thousands of lipids in most biological samples, and therefore separation methods before introduction to the mass spectrometer is key for relative quantitation and identification. Chromatographic methods differ across laboratories, without any consensus on the best methodologies. Therefore, we designed an experiment to determine the optimal LC methodology, and assessed the value of ion mobility for an additional dimension of separation. To apply an untargeted method for hypothesis generation focused on lipidomics, LC-HRMS parameters were optimized based on the measurement of 50 panel lipids covering key human metabolic pathways. Reversed-phase liquid chromatography columns were compared based on a quality scoring system considering the signal-to-noise ratio, peak shape, and retention factor. Furthermore, drift tube ion mobility spectrometry (DTIMS) was implemented to increase peak capacity and confidence during annotation by providing collision cross section (CCS) values for the analytes under investigation. However, hyphenating DTIMS to LC-HRMS may result in a reduced sensitivity due to impaired duty cycles. To increase the signal intensity, a Box-Behnken design (BBD) was used to optimize four key factors, i.e. drift entrance voltage, drift exit voltage, rear funnel entrance, and rear funnel exit voltages. Application of a maximized desirability function provided voltages for the above-mentioned parameters resulting in higher signal intensity compared to each combination of parameters used during the BBD. In addition, the influence of single pulse and Hadamard 4-bit multiplexed modes on signal intensity was explored and different trap filling and release times of ions were evaluated. The optimized LC-DTIM-HRMS platform was applied to extracts from HepaRG cells and resulted in 3912 high-quality features (<30% median relative standard deviation; n = 6, t = 24 h). From these features, 436 lipid species could be annotated (i.e., matching based on accurate mass <5 ppm, isotopic pattern, in-silico MS/MS fragmentation, and in-silico CCS database matching <3%). The application of LC-DTIM-HRMS for untargeted analysis workflows is growing and the platform optimization, as described here, can be used to guide the method development and CCS database comparison for high confidence lipid annotation.

A Novel Technique for Redox Lipidomics Using Mass Spectrometry: Application on Vegetable Oils Used to Fry Potatoes.

Vegetables oils, rich in polyunsaturated fatty acids, are vulnerable to oxidation during manufacturing, processing, and food preparation. Currently, individual oxidation products are not well characterized, and hence, the health impacts of these unique lipid species remain unknown. Here, we introduce an extensive oxidized lipidomics in silico tandem mass spectrometry library and integrate these libraries within a user-friendly software covering a comprehensive redox lipidomics workflow. We apply this workflow to olive, soy, and walnut cooking oil; comparing unheated oil, oil after deep frying potatoes, and oil after oven frying potatoes. We annotated over a thousand oxidized triglycerides across 273 features (many coeluted). This software was validated against traditional chemical assays of oxidation, known oxidized lipids in castor oil, synthesized standards, and an alternate software LPPtiger. Development of these new software programs for redox lipidomics opens the door to characterize health implications of individual oxidation products.

Exploring personal chemical exposures in China with wearable air pollutant monitors: A repeated-measure study in healthy older adults in Jinan, China.

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p < 0.05). Specifically, dimethyl phthalate (rs = 0.31) decreased as temperatures declined, while nitrobenzene (rs = -0.35) and naphthalene (rs = -0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p < 0.05) and hexachlorobutadiene was lower across participants (p < 0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements.

Head, Shoulders, Knees, and Toes: Placement of Wearable Passive Samplers Alters Exposure Profiles Observed.

Chemical exposures are a major risk factor for many diseases. Comprehensive characterization of personal exposures is necessary to highlight chemicals of concern and factors that influence these chemical exposure dynamics. For this purpose, wearable passive samplers can be applied to assess longitudinal personal exposures to airborne contaminants. Questions remain regarding the impact of sampler placement at different locations of the body on the exposure profiles observed and how these placements affect the monitoring of seasonal dynamics in exposures. This study assessed personal air contaminant exposure using passive samplers worn in parallel across 32 participant's wrists, chest, and shoes over 24 h. Samplers were analyzed by thermal desorption gas chromatography high-resolution mass spectrometry. Personal exposure profiles were similar for about one-third of the 275 identified chemicals, irrespective of sampler placement. Signals of certain semivolatile organic compounds (SVOCs) were enhanced in shoes and, to a lesser extent, wrist samplers, as compared to those in chest samplers. Signals of volatile organic compounds were less impacted by sampler placement. Results showed that chest samplers predominantly captured more volatile exposures, as compared to those of particle-bound exposures, which may indicate predominant monitoring of chemicals via the inhalation route of exposure for chest samplers. In contrast, shoe samplers were more sensitive to particle-bound SVOCs. Seventy-one chemicals changed across participants between winter and summer in the same manner for two or more different sampler placements on the body, whereas 122 chemicals were observed to have seasonal differences in only one placement. Hence, the placement in certain cases significantly impacts exposure dynamics observed. This work shows that it is essential in epidemiological studies undertaking exposure assessment to consider the consequence of the placement of exposure monitors.

Use of Exposomic Methods Incorporating Sensors in Environmental Epidemiology.

PURPOSE OF REVIEW: The exposome is a recently coined concept that comprises the totality of nongenetic factors that affect human health. It is recognized as a major conceptual advancement in environmental epidemiology, and there is increased demand for technologies that capture the spatial, temporal, and chemical variability of exposures across individuals (i.e., "exposomic sensors"). We review a selection of these tools, highlighting their strengths and limitations with regard to epidemiological research. RECENT FINDINGS: Wearable passive samplers are emerging as promising exposomic sensors for individuals. In conjunction with targeted and untargeted assays, these sensors enable the measurement of complex multipollutant mixtures, which can include both known and previously unknown environmental contaminants. Because of their minimally burdensome and noninvasive nature, they are deployable among sensitive populations, such as seniors, pregnant women, and children. The integration of exposomic data captured by these sensors with other omic data (e.g., transcriptomic and metabolomic) presents exciting opportunities for investigating disease risk factors. For example, the linkage of exposomic sensor data with other omic data may indicate perturbation by multipollutant mixtures at multiple physiological levels, which would strengthen evidence of their effects and potentially indicate targets for interventions. However, there remain considerable theoretical and methodological challenges that must be overcome to realize the potential promise of omic integration. Through continued investment and improvement in exposomic sensor technologies, it may be possible to refine their application and reduce their outstanding limitations to advance the fields of exposure science and epidemiology.

Exploring the external exposome using wearable passive samplers - The China BAPE study.

Environmental exposures are one of the greatest threats to human health, yet we lack tools to answer simple questions about our exposures: what are our personal exposure profiles and how do they change overtime (external exposome), how toxic are these chemicals, and what are the sources of these exposures? To capture variation in personal exposures to airborne chemicals in the gas and particulate phases and identify exposures which pose the greatest health risk, wearable exposure monitors can be deployed. In this study, we deployed passive air sampler wristbands with 84 healthy participants (aged 60-69 years) as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Participants wore the wristband samplers for 3 days each month for five consecutive months. Passive samplers were analyzed using a novel gas chromatography high resolution mass spectrometry data-processing workflow to overcome the bottleneck of processing large datasets and improve confidence in the resulting identified features. The toxicity of chemicals observed frequently in personal exposures were predicted to identify exposures of potential concern via inhalation route or other routes of airborne contaminant exposure. Three exposures were highlighted based on elevated toxicity: dichlorvos from insecticides (mosquito/malaria control), naphthalene partly from mothballs, and 183 polyaromatic hydrocarbons from multiple sources. Other exposures explored in this study are linked to diet and personal care products, cigarette smoke, sunscreen, and antimicrobial soaps. We highlight the potential for this workflow employing wearable passive samplers for prioritizing chemicals of concern at both the community and individual level, and characterizing sources of exposures for follow up interventions.

A Review of Efforts to Improve Lipid Stability during Sample Preparation and Standardization Efforts to Ensure Accuracy in the Reporting of Lipid Measurements.

Lipidomics is a rapidly growing field, fueled by developments in analytical instrumentation and bioinformatics. To date, most researchers and industries have employed their own lipidomics workflows without a consensus on best practices. Without a community-wide consensus on best practices for the prevention of lipid degradation and transformations through sample collection and analysis, it is difficult to assess the quality of lipidomics data and hence trust results. Clinical studies often rely on samples being stored for weeks or months until they are analyzed, but inappropriate sampling techniques, storage temperatures, and analytical protocols can result in the degradation of complex lipids and the generation of oxidized or hydrolyzed metabolite artifacts. While best practices for lipid stability are sample dependent, it is generally recommended that strategies during sample preparation capable of quenching enzymatic activity and preventing oxidation should be considered. In addition, after sample preparation, lipid extracts should be stored in organic solvents with antioxidants at -20 °C or lower in an airtight container without exposure to light or oxygen. This will reduce or eliminate sublimation, and chemically and physically induced molecular transformations such as oxidation, enzymatic transformation, and photon/heat-induced degradation. This review explores the available literature on lipid stability, with a particular focus on human health and/or clinical lipidomic applications. Specifically, this includes a description of known mechanisms of lipid degradation, strategies, and considerations for lipid storage, as well as current efforts for standardization and quality insurance of protocols.