The exposome--exciting opportunities for discoveries in reproductive and perinatal epidemiology

Exploring applications of non-targeted analysis in the characterization of the prenatal exposome

Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n = 592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n = 860,000 chemicals) and Human Metabolome Database (n = 3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72 % of the features (total features = 32,197, levels 1-4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.

Imprinting and Reproductive Health: A Toxicological Perspective

This overview discusses the role of imprinting in the development of an organism, and how exposure to environmental chemicals during fetal development leads to the physiological and biochemical changes that can have adverse lifelong effects on the health of the offspring. There has been a recent upsurge in the use of chemical products in everyday life. These chemicals include industrial byproducts, pesticides, dietary supplements, and pharmaceutical products. They mimic the natural estrogens and bind to estradiol receptors. Consequently, they reduce the number of receptors available for ligand binding. This leads to a faulty signaling in the neuroendocrine system during the critical developmental process of 'imprinting'. Imprinting causes structural and organizational differentiation in male and female reproductive organs, sexual behavior, bone mineral density, and the metabolism of exogenous and endogenous chemical substances. Several studies conducted on animal models and epidemiological studies provide profound evidence that altered imprinting causes various developmental and reproductive abnormalities and other diseases in humans. Altered metabolism can be measured by various endpoints such as the profile of cytochrome P-450 enzymes (CYP450's), xenobiotic metabolite levels, and DNA adducts. The importance of imprinting in the potentiation or attenuation of toxic chemicals is discussed.

earlyMYCO: A Pilot Mother-Child Cohort Study to Assess Early-Life Exposure to Mycotoxins—Challenges and Lessons Learned

Early-life exposure occurs during gestation through transfer to the fetus and later, during lactation. Recent monitoring data revealed that the Portuguese population is exposed to mycotoxins, including young children. This study aimed to develop a pilot study to assess the early-life exposure to mycotoxins through a mother–child cohort, and to identify the associated challenges. Participants were recruited during pregnancy (1st trimester) and followed-up in three moments of observation: 2nd trimester of pregnancy (mother), and 1st and 6th month of the child’s life (mother and child), with the collection of biological samples and sociodemographic and food consumption data. The earlyMYCO pilot study enrolled 19 mother–child pairs. The analysis of biological samples from participants revealed the presence of 4 out of 15 and 5 out of 18 mycotoxins’ biomarkers of exposure in urine and breast milk samples, respectively. The main aspects identified as contributors for the successful development of the cohort were the multidisciplinary and dedicated team members in healthcare units, reduced burden of participation, and the availability of healthcare units for the implementation of the fieldwork. Challenges faced, lessons learned, and suggestions were discussed as a contribution for the development of further studies in this area.

Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, transformation, excretion, and coexistence with other endogenous molecules, however, greatly complicate the interpretation of features detected in nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites from xenobiotics is also often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate a xenobiotic structural annotation workflow using ion mobility spectrometry coupled with MS (IMS-MS), mass defect filtering, and machine learning to uncover potential xenobiotic classes and species in large metabolomic feature lists. Xenobiotic classes examined included those of known high toxicities, including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and pesticides. Specifically, when the workflow was applied to identify PFAS in the NIST SRM 1957 and 909c human serum samples, it greatly reduced the hundreds of detected liquid chromatography (LC)-IMS-MS features by utilizing both mass defect filtering and m/z versus IMS collision cross sections relationships. These potential PFAS features were then compared to the EPA CompTox entries, and while some matched within specific m/z tolerances, there were still many unknowns illustrating the importance of nontargeted studies for detecting new molecules with known chemical characteristics. Additionally, this workflow can also be utilized to evaluate other xenobiotics and enable more confident annotations from nontargeted studies.

Environmental contaminants and child development: Developmentally-informed opportunities and recommendations for integrating and informing child environmental health science

Child environmental health (CEH) science has identified numerous effects of early life exposures to common, ubiquitous environmental toxicants. CEH scientists have documented the costs not only to individual children but also to population-level health effects of such exposures. Importantly, such risks are unequally distributed in the population, with historically marginalized communities and the children living in these communities receiving the most damaging exposures. Developmental science offers a lens and set of methodologies to identify nuanced biological and behavioral processes that drive child development across physical, cognitive, and socioemotional domains. Developmental scientists are also experts in considering the multiple, hierarchically-layered contexts that shape development alongside toxicant exposure. Such contexts and the individuals acting within them make up an overarching "child serving ecosystem" spanning systems and sectors that serve children directly and indirectly. Articulating how biobehavioral mechanisms and social-ecological contexts unfold from a developmental perspective are needed in order to inform CEH translation and intervention efforts across this child-serving ecosystem. Developmentalists can also benefit from integrating CEH science findings in their work by considering the role of the physical environment, and environmental toxicants specifically, on child health and development. Building on themes that were laid out by Trentacosta and Mulligan in 2020, this commentary presents recommendations for connecting developmental and CEH science and for translating such work so that it can be used to promote child development in an equitable manner across this child-serving ecosystem. These opportunities include (1) Using Developmentally-Informed Conceptual Models; (2) Applying Creative, Sophisticated, and Rigorous Methods; (3) Integrating Developmentally-Sensitive Intervention Considerations; and (4) Establishing Interdisciplinary Collaborations and Cross-Sector Partnerships.

Risk Preference, Health Risk Perception, and Environmental Exposure Nexus: Evidence from Rural Women as Pig Breeders, China

Rural women are an integral part of the agricultural economy. Still, their exposure to environmental pollution, especially in the context of risk preference and health risk perception, has not gained much attention in the existing literature. So to explore this notion, a survey and experimental data of 714 rural Chinese women as pig breeders are taken, we innovatively evaluate the degree of environmental exposure from the pre-exposure, in-exposure, post-exposure intervention of women breeders, and two-stage least squares (2SLS) method is employed to address the endogeneity issue between health risk perception and environmental exposure. The results show that rural women breeders suffer from severe environmental exposure, and the degree of environmental exposure is up to 72.102(Min = 0, Max = 100). Risk preference also emerges as a crucial determinant behind their environmental exposure, but health risk perception significantly deters the degree of environmental exposure. The health risk perception can offset risk preference effects on women breeders' environmental exposure by 15.15%. Moreover, considering the heterogeneity of the breeding scale, it is found that the impact of risk preference and health risk perception on women breeders' environmental exposure is an inverted U-shaped relationship, i.e., the results are at the turning stage when the breeding scale is 31-40 heads. Based on the empirical findings, the study offers guidelines for policymakers to enhance awareness amongst women breeders regarding health and pollution and encourage them to opt for environment-friendly breeding. Moreover, this research also has substantial guiding significance for related research on environmental exposure of rural women in other developing countries.

The exposome in practice: an exploratory panel study of biomarkers of air pollutant exposure in Chinese people aged 60-69 years (China BAPE Study)

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60-69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques.

The Impact of Early-Life Exposures on Women's Reproductive Health in Adulthood

Purpose of Review

To review the effects of early-life, preconception, and prior-generation exposures on reproductive health in women.

Recent Findings

Women’s early-life factors can affect reproductive health by contributing to health status or exposure level on entering pregnancy. Alternately, they can have permanent effects, regardless of later-life experience. Nutrition, social class, parental smoking, other adverse childhood experiences, environmental pollutants, infectious agents, and racism and discrimination all affect reproductive health, even if experienced in childhood or in utero. Possible transgenerational effects are now being investigated through three- or more-generation studies. These effects occur with mechanisms that may include direct exposure, behavioral, endocrine, inflammatory, and epigenetic pathways.

Summary

Pregnancy is increasingly understood in a life course perspective, but rigorously testing hypotheses on early-life effects is still difficult. In order to improve the health outcomes of all women, we need to expand our toolkit of methods and theory.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40471-021-00279-0.

Interstitial Lung Diseases and Air Pollution: Narrative Review of Literature

Air pollution has been associated with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and lung malignancies. The aim of this narrative review is to analyze the current data on the possible association between air pollution and interstitial lung disease (ILD). There are multiple studies showing the association of ILD with air pollution but the mechanism remains unclear. Although some of the environmental factors have been associated with idiopathic pulmonary fibrosis (IPF), hypersensitivity pneumonitis (HP), and pneumoconiosis, data about other ILDs are scarce and not well known. Air pollution as an etiology for ILD may act in multiple ways, leading to disease pathogenesis or exacerbation of underlying ILD. Clinical implications of this association are manifold; limiting the exposure to poor-quality air could possibly reduce the fall in lung functions and the risk of acute exacerbations of the underlying ILD.

Air pollution is a major problem worldwide. Pollutants are vented out in the ambient air by sources like vehicular fume exhaust, factory pollution, combustion by burning of biomass fuels, and indoor pollution. The probable constituents responsible for respiratory diseases are particulate matter 2.5 and 10, nitrogen dioxide (NO₂), and ozone present in polluted air. The role of these pollutants in pathogenesis of interstitial lung disease (ILD) is complex. The probable pathways include: oxidative stress, inflammation, and telomere shortening. ILD is a heterogeneous group of diseases, and the effect of pollution on various types is also varied. Air pollution has been associated with poor lung function and exacerbations in idiopathic pulmonary fibrosis (IPF), increased prevalence of hypersensitivity pneumonitis (HP), and presence of pulmonary fibrosis in healthy adults and children. The incidence rate of IPF has also been associated with pollutant levels such as NO₂. Thus, patients with ILD should be cautious during bad-quality air days and they are advised to avoid outdoor activities and use facemasks during this period.

Unravelling the chemical exposome in cohort studies: routes explored and steps to become comprehensive

Environmental factors contribute to the risk for adverse health outcomes against a background of genetic predisposition. Among these factors, chemical exposures may substantially contribute to disease risk and adverse outcomes. In fact, epidemiological cohort studies have established associations between exposure against individual chemicals and adverse health effects. Yet, in daily life individuals are exposed to complex mixtures in varying compositions. To capture the totality of environmental exposures the concept of the exposome has been developed. Here, we undertake an overview of major exposome projects, which pioneered the field of exposomics and explored the links between chemical exposure and health outcomes using cohort studies. We seek to reflect their achievements with regard to (i) capturing a comprehensive picture of the environmental chemical exposome, (ii) aggregating internal exposures using chemical and bioanalytical means of detection, and (iii) identifying associations that provide novel options for risk assessment and intervention. Various complementary approaches can be distinguished in addressing relevant exposure routes and it emerges that individual exposure histories may not easily be grouped. The number of chemicals for which human exposure can be detected is substantial and highlights the reality of mixture exposures. Yet, to a large extent it depends on targeted chemical analysis with the specific challenges to capture all relevant exposure routes and assess the chemical concentrations occurring in humans. The currently used approaches imply prior knowledge or hypotheses about relevant exposures. Typically, the number of chemicals considered in exposome projects is counted in dozens-in contrast to the several thousands of chemicals for which occurrence have been reported in human serum and urine. Furthermore, health outcomes are often still compared to single chemicals only. Moreover, explicit consideration of mixture effects and the interrelations between different outcomes to support causal relationships and identify risk drivers in complex mixtures remain underdeveloped and call for specifically designed exposome-cohort studies.

Bayesian Profile Regression to Deal With Multiple Highly Correlated Exposures and a Censored Survival Outcome. First Application in Ionizing Radiation Epidemiology

As multifactorial and chronic diseases, cancers are among these pathologies for which the exposome concept is essential to gain more insight into the associated etiology and, ultimately, lead to better primary prevention strategies for public health. Indeed, cancers result from the combined influence of many genetic, environmental and behavioral stressors that may occur simultaneously and interact. It is thus important to properly account for multifactorial exposure patterns when estimating specific cancer risks at individual or population level. Nevertheless, the risk factors, especially environmental, are still too often considered in isolation in epidemiological studies. Moreover, major statistical difficulties occur when exposures to several factors are highly correlated due, for instance, to common sources shared by several pollutants. Suitable statistical methods must then be used to deal with these multicollinearity issues. In this work, we focused on the specific problem of estimating a disease risk from highly correlated environmental exposure covariates and a censored survival outcome. We extended Bayesian profile regression mixture (PRM) models to this context by assuming an instantaneous excess hazard ratio disease sub-model. The proposed hierarchical model incorporates an underlying truncated Dirichlet process mixture as an attribution sub-model. A specific adaptive Metropolis-Within-Gibbs algorithm-including label switching moves-was implemented to infer the model. This allows simultaneously clustering individuals with similar risks and similar exposure characteristics and estimating the associated risk for each group. Our Bayesian PRM model was applied to the estimation of the risk of death by lung cancer in a cohort of French uranium miners who were chronically and occupationally exposed to multiple and correlated sources of ionizing radiation. Several groups of uranium miners with high risk and low risk of death by lung cancer were identified and characterized by specific exposure profiles. Interestingly, our case study illustrates a limit of MCMC algorithms to fit full Bayesian PRM models even if the updating schemes for the cluster labels incorporate label-switching moves. Then, although this paper shows that Bayesian PRM models are promising tools for exposome research, it also opens new avenues for methodological research in this class of probabilistic models.

Father absence, age at menarche, and genetic confounding: A replication and extension using a polygenic score

Father absence has a small but robust association with earlier age at menarche (AAM), likely reflecting both genetic confounding and an environmental influence on life history strategy development. Studies that have attempted to disambiguate genetic versus environmental contributions to this association have shown conflicting findings, though genomic-based studies have begun to establish the role of gene-environment interplay in the father absence/AAM literature. The purpose of this study was to replicate and extend prior genomic work using the Avon Longitudinal Study of Parents and Children (ALSPAC), a prospective longitudinal cohort study (N = 2,685), by (a) testing if an AAM polygenic score (PGS) could account for the father absence/AAM association, (b) replicating G×E research on lin-28 homolog B (LIN28B) variation and father absence, and (c) testing the G×E hypothesis using the PGS. Results showed that the PGS could not explain the father absence/AAM association and there was no interaction between father absence and the PGS. Findings using LIN28B largely replicated prior work that showed LIN28B variants predicted later AAM in father-present girls, but this AAM-delaying effect was absent or reversed in father-absent girls. Findings are discussed in terms genetic confounding, the unique biological role of LIN28B, and using PGSs for G×E tests.

Patterns and Variability of Endocrine-disrupting Chemicals During Pregnancy: Implications for Understanding the Exposome of Normal Pregnancy

BACKGROUND

The exposome is a novel research paradigm offering promise for understanding the complexity of human exposures, including endocrine-disrupting chemicals (EDCs) and pregnancy outcomes. The physiologically active state of pregnancy requires understanding temporal changes in EDCs to better inform the application of the exposome research paradigm and serve as the impetus for study.

METHODS

We randomly selected 50 healthy pregnant women with uncomplicated pregnancies from a pregnancy cohort who had available serum/urine samples in each trimester for measuring 144 persistent and 48 nonpersistent EDCs. We used unsupervised machine-learning techniques capable of handling hierarchical clustering of exposures to identify EDC patterns across pregnancy, and linear mixed-effects modeling with false-discovery rate correction to identify those that change over pregnancy trimesters. We estimated the percent variation in chemical concentrations accounted for by time (pregnancy trimester) using Akaike Information Criterion-based R methods.

RESULTS

Four chemical clusters comprising 80 compounds, of which six consistently increased, 63 consistently decreased, and 11 reflected inconsistent patterns over pregnancy. Overall, concentrations tended to decrease over pregnancy for persistent EDCs; a reverse pattern was seen for many nonpersistent chemicals. Explained variance was highest for five persistent chemicals: polybrominated diphenyl ethers #191 (51%) and #126 (47%), hexachlorobenzene (46%), p,p'-dichloro-diphenyl-dichloroethylene (46%), and o,p'-dichloro-diphenyl-dichloroethane (36%).

CONCLUSIONS

Concentrations of many EDCs are not stable across pregnancy and reflect varying patterns depending on their persistency underscoring the importance of timed biospecimen collection. Analytic techniques are available for assessing temporal patterns of EDCs during pregnancy apart from physiologic changes.

Integrating Exposure Knowledge and Serum Suspect Screening as a New Approach to Biomonitoring: An Application in Firefighters and Office Workers

Firefighters (FF) are exposed to recognized and probable carcinogens, yet there are few studies of chemical exposures and associated health concerns in women FFs, such as breast cancer. Biomonitoring often requires a priori selection of compounds to be measured, and so, it may not detect relevant, lesser known, exposures. The Women FFs Biomonitoring Collaborative (WFBC) created a biological sample archive and conducted a general suspect screen (GSS) to address this data gap. Using liquid chromatography-quadrupole time-of-flight tandem mass spectrometry, we sought to identify candidate chemicals of interest in serum samples from 83 women FFs and 79 women office workers (OW) in San Francisco. We identified chemical peaks by matching accurate mass from serum samples against a custom chemical database of 722 slightly polar phenolic and acidic compounds, including many of relevance to firefighting or breast cancer etiology. We then selected tentatively identified chemicals for confirmation based on the following criteria: (1) detection frequency or peak area differences between OW and FF; (2) evidence of mammary carcinogenicity, estrogenicity, or genotoxicity; and (3) not currently measured in large biomonitoring studies. We detected 620 chemicals that matched 300 molecular formulas in the WFBC database, including phthalate metabolites, phosphate flame-retardant metabolites, phenols, pesticides, nitro and nitroso compounds, and per- and polyfluoroalkyl substances. Of the 20 suspect chemicals selected for validation, 8 were confirmed-including two alkylphenols, ethyl paraben, BPF, PFOSAA, benzophenone-3, benzyl p-hydroxybenzoate, and triphenyl phosphate-by running a matrix spike of the reference standards and using m/z, retention time, and the confirmation of at least two fragment ions as criteria for matching. GSS provides a powerful high-throughput approach to identify and prioritize novel chemicals for biomonitoring and health studies.

Characterizing the Neurodevelopmental Pesticide Exposome in a Children's Agricultural Cohort

The exposome provides a conceptual model for identifying and characterizing lifetime environmental exposures and resultant health effects. In this study, we applied key exposome concepts to look specifically at the neurodevelopmental pesticide exposome, which focuses on exposures to pesticides that have the potential to cause an adverse neurodevelopmental impact. Using household dust samples from a children's agricultural cohort located in the Yakima Valley of Washington state, we identified 87 individual pesticides using liquid chromatography-tandem mass spectrometry. A total of 47 of these have evidence of neurotoxicity included in the Environmental Protection Agency (EPA) (re)registration materials. We used a mixed effects model to model trends in pesticide exposure. Over the two study years (2005 and 2011), we demonstrate a significant decrease in the neurodevelopmental pesticide exposome across the cohort, but particularly among farmworker households. Additional analysis with a non-parametric binomial analysis that weighted the levels of potentially neurotoxic pesticides detected in household dust by their reference doses revealed that the decrease in potentially neurotoxic pesticides was largely a result of decreases in some of the most potent neurotoxicants. Overall, this study provides evidence that the neurodevelopmental pesticide exposome framework is a useful tool in assessing the effectiveness of specific interventions in reducing exposure as well as setting priorities for future targeted actions.

Pregnancy vulnerability in urban areas: a pragmatic approach combining behavioral, medico-obstetrical, socio-economic and environmental factors

Multiple risk factors are associated with adverse pregnancy outcomes (APO), but how all these different factors combine and accumulate remains unknown. The objective of this observational retrospective study was to describe the accumulation of multiple vulnerability markers in pregnant women living in an urban area. Women living in Besançon (France) who delivered between 2005 and 2009 were included. Individual data were collected from the obstetrical records while environmental exposures were collected using environmental prediction models. The accumulation of 15 vulnerability markers, grouped into six dimensions (maternal age, smoking, body mass index (BMI), socio-economic, medico-obstetrical and environmental vulnerabilities) was described and analyzed in comparison with four APO. Among the 3686 included women, 20.8% were aged under 20 or over 34 and 21.9% had an extreme pre-pregnancy BMI. 18.8% declared smoking during pregnancy. Women exposed to socio-economic, medico-obstetrical or environmental vulnerability were 14.2%, 31.6% and 42.4% respectively. While 20.6% were not exposed to any marker, 18.8% accumulated three or more dimensions. The risk of APO increased significantly with the cumulative number of vulnerabilities. Define and validate a vulnerability score could be useful to identify vulnerable women, adapt their pregnancy monitoring and help policy makers to implement appropriate education or health promotion programs.

An overview of the current progress, challenges, and prospects of human biomonitoring and exposome studies

Human Biomonitoring (HB), the process for determining whether and to what extent chemical substances penetrated our bodies, serves as a useful tool to quantify human exposure to pollutants. In cases of nutrition and physiologic status, HB plays a critical role in the identification of excess or deficiency of essential nutrients. In pollutant HB studies, levels of substances measured in body fluids (blood, urine, and breast milk) or tissues (hair, nails or teeth) aid in the identification of potential health risks or associated adverse effects. However, even as a widespread practice in several countries, most HB studies reflect exposure to a single compound or mixtures which are measured at a single time point in lifecycle. On the other hand, throughout an individual's lifespan, the contact with different physical, chemical, and social stressors occurs at varying intensities, differing times and durations. Further, the interaction between stressors and body receptors leads to dynamic responses of the entire biological system including proteome, metabolome, transcriptome, and adductome. Bearing this in mind, a relatively new vision in exposure science, defined as the exposome, is postulated to expand the traditional practice of measuring a single exposure to one or few chemicals at one-time point to an approach that addresses measures of exposure to multiple stressors throughout the lifespan. With the exposome concept, the science of exposure advances to an Environment-Wide Association Perspective, which might exhibit a stronger relationship with good health or disease conditions for an individual (phenotype). Thus, this critical review focused on the current progress of HB and exposome investigations, anticipating some challenges, strategies, and future needs to be taken into account for designing future surveys.

Towards Mass Spectrometry-Based Chemical Exposome: Current Approaches, Challenges, and Future Directions

The proposal of the “exposome” concept represents a shift of the research paradigm in studying exposure-disease relationships from an isolated and partial way to a systematic and agnostic approach. Nevertheless, exposome implementation is facing a variety of challenges including measurement techniques and data analysis. Here we focus on the chemical exposome, which refers to the mixtures of chemical pollutants people are exposed to from embryo onwards. We review the current chemical exposome measurement approaches with a focus on those based on the mass spectrometry. We further explore the strategies in implementing the concept of chemical exposome and discuss the available chemical exposome studies. Early progresses in the chemical exposome research are outlined, and major challenges are highlighted. In conclusion, efforts towards chemical exposome have only uncovered the tip of the iceberg, and further advancement in measurement techniques, computational tools, high-throughput data analysis, and standardization may allow more exciting discoveries concerning the role of exposome in human health and disease.

Welding Fume Exposure and Epigenetic Alterations: A Systematic Review

Epigenetics are heritable changes in gene expression not coded in the DNA sequence, which stand at the interface between the genome, environmental exposure and development. From an occupational health perspective, epigenetic variants may link workplace exposures and health effects. Therefore, this review aimed to overview possible epigenetic effects induced by welding fumes on exposed workers and health implications. A systematic search was performed on Pubmed, Scopus, and ISI Web of Knowledge databases. DNA methylation changes have been reported in genes responsible for the cardiac autonomic function and coagulation, i.e., LINE-1, GPR133 and F2RL3, in mitochondrial-DNA-sequences involved in the regulation of energy-generation/redox-signaling, as well as in inflammatory activated genes, i.e., iNOS. However, the limited number of retrieved articles, their cross-sectional nature, the lack of a suitable qualitative-quantitative exposure assessment, and the heterogeneity of biological-outcomes investigated, prevent the extrapolation of a definite causal relationship between welding fumes and epigenetic phenomena. Future studies should clarify the function of such epigenetic alterations as possible markers of occupational exposure and early effect, dose-response relationships, and underlying molecular mechanisms. Overall, this may be helpful to guide suitable risk assessment and management strategies to protect the health of workers exposed to welding fumes.

Investigating Possible Trans/Intergenerational Associations With Obesity in Young Adults Using an Exposome Approach

Animal experiments demonstrate ways in which an exposure in one generation can be reflected in a variety of outcomes in later generations. In parallel human observational studies have shown associations between grandparental and parental exposures to cigarette smoking and/or nutrition and growth and survival of the grandchild. These studies have controlled for just a few confounders selected ad hoc. Here we use an exposome approach (using all available measures of exposure) to determine trans/inter-generational factors that may be important in studying environmental factors associated with fat mass in young human adults. The study takes advantage of the rich data available in the Avon Longitudinal Study of Parents and Children (ALSPAC). We test associations with features of grandparents (G0) and the childhood of the parents (G1) of 24-year olds (G2). We hypothesized that intergenerational associations would be revealed, particularly with exposure to cigarette smoke, and that these would vary with the sexes of all three generations. The study exposome analyzed 172 exposures to the maternal line and 182 to the paternal line. A series of stepwise regression analyses reduced the initial 40 unadjusted factors (P < 0.05) to eight independent features on the maternal line, and of 26 on the paternal line to five. We found strong associations between the father starting to smoke cigarettes regularly before age 11 and increased fat mass in his adult children (unadjusted = +7.82 [95% CI +2.75, +12.90] Kg; adjusted = +11.22 [+5.23, +17.22] Kg); this association was stronger in male offspring. In addition, when the paternal grandmother had smoked in pregnancy her adult granddaughters, but not grandsons had elevated mean fat mass (interaction with sex after adjustment, P = 0.001). The exposome technique identified other factors that were independently associated with fat mass in young adults. These may be useful in identifying appropriate confounders in other more proximal analyses, but also may identify features that may be on epigenetic pathways leading to increased fat mass in subsequent generations. We acknowledge that the results need to be replicated in other cohorts and encourage further linkage of outcomes with previous generational exposures, particularly along the paternal line.

Exposome-wide association study of semen quality: Systematic discovery of endocrine disrupting chemical biomarkers in fertility require large sample sizes

OBJECTIVES

Exposome-wide association studies (EWAS) are a systematic and unbiased way to investigate multiple environmental factors associated with phenotype. We applied EWAS to study semen quality and queried the sample size requirements to detect modest associations in a reproductive cohort.

STUDY DESIGN AND SETTING

We conducted 1) a multivariate EWAS of 128 endocrine disrupting chemicals (EDCs) from 15 chemical classes measured in urine/serum relative to 7 semen quality endpoints in a prospective cohort study comprising 473 men and 2) estimated the sample size requirements for EWAS etiologic investigations.

RESULTS

None of the EDCs were associated with semen quality endpoints after adjusting for multiple tests. However, several EDCs (e.g., polychlorinated biphenyl congeners 99, 105, 114, and 167) were associated with raw p < 0.05. In a post hoc statistical power analysis with the observed effect sizes, we determined that EWAS research in male fertility will require a mean sample size of 2696 men (1795-3625) to attain a power of 0.8. The average size of four published studies is 201 men.

CONCLUSION

Existing cohort studies with hundreds of participants are underpowered (<0.8) for EWAS-related investigations. Merging cohorts to ensure a sufficient sample size can facilitate the use of EWAS methods for assessing EDC mixtures that impact semen quality.

The Exposome Research Paradigm: an Opportunity to Understand the Environmental Basis for Human Health and Disease

PURPOSE OF REVIEW

This paper presents an overview of the exposome research paradigm with particular application to understanding human reproduction and development and its implications for health across a lifespan.

RECENT FINDINGS

The exposome research paradigm has generated considerable discussion about its feasibility and utility for delineating the impact of environmental exposures on human health. Early initiatives are underway, including smaller proof-of-principle studies and larger concerted efforts. Despite the notable challenges underlying the exposome paradigm, analytic techniques are being developed to handle its untargeted approach and correlated and multi-level or hierarchical data structures such initiatives generate, while considering multiple comparisons. The relatively short intervals for critical and sensitive windows of human reproduction and development seem well suited for exposome research and may revolutionize our understanding of later onset diseases. Early initiatives suggest that the exposome paradigm is feasible, but its utility remains to be established with applications to population human health research.

Developing the Regulatory Utility of the Exposome: Mapping Exposures for Risk Assessment through Lifestage Exposome Snapshots (LEnS)

BACKGROUND

Exposome-related efforts aim to document the totality of human exposures across the lifecourse. This field has advanced rapidly in recent years but lacks practical application to risk assessment, particularly for children's health.

OBJECTIVES

Our objective was to apply the exposome to children's health risk assessment by introducing the concept of Lifestage Exposome Snapshots (LEnS). Case studies are presented to illustrate the value of the framework.

DISCUSSION

The LEnS framework encourages organization of exposome studies based on windows of susceptibility for particular target organ systems. Such analyses will provide information regarding cumulative impacts during specific critical periods of the life course. A logical extension of this framework is that regulatory standards should analyze exposure information by target organ, rather than for a single chemical only or multiple chemicals grouped solely by mechanism of action.

CONCLUSIONS

The LEnS concept is a practical refinement to the exposome that accounts for total exposures during particular windows of susceptibility in target organ systems. Application of the LEnS framework in risk assessment and regulation will improve protection of children's health by enhancing protection of sensitive developing organ systems that are critical for lifelong health and well-being. https://doi.org/10.1289/EHP1250.

Low-level environmental metals and metalloids and incident pregnancy loss

Environmental exposure to metals and metalloids is associated with pregnancy loss in some but not all studies. We assessed arsenic, cadmium, mercury, and lead concentrations in 501 couples upon trying for pregnancy and followed them throughout pregnancy to estimate the risk of incident pregnancy loss. Using Cox proportional hazard models, we estimated hazard ratios (HR) and 95% confidence intervals (CIs) for pregnancy loss after covariate adjustment for each partner modeled individually then we jointly modeled both partners' concentrations. Incidence of pregnancy loss was 28%. In individual partner models, the highest adjusted HRs were observed for female and male blood cadmium (HR=1.08; CI 0.81, 1.44; HR=1.09; 95% CI 0.84, 1.41, respectively). In couple based models, neither partner's blood cadmium concentrations were associated with loss (HR=1.01; 95% CI 0.75, 1.37; HR=0.92; CI 0.68, 1.25, respectively). We observed no evidence of a significant relation between metal(loids) at these environmentally relevant concentrations and pregnancy loss.

Toward Greater Implementation of the Exposome Research Paradigm within Environmental Epidemiology

Investigating a single environmental exposure in isolation does not reflect the actual human exposure circumstance nor does it capture the multifactorial etiology of health and disease. The exposome, defined as the totality of environmental exposures from conception onward, may advance our understanding of environmental contributors to disease by more fully assessing the multitude of human exposures across the life course. Implementation into studies of human health has been limited, in part owing to theoretical and practical challenges including a lack of infrastructure to support comprehensive exposure assessment, difficulty in differentiating physiologic variation from environmentally induced changes, and the need for study designs and analytic methods that accommodate specific aspects of the exposome, such as high-dimensional exposure data and multiple windows of susceptibility. Recommendations for greater data sharing and coordination, methods development, and acknowledgment and minimization of multiple types of measurement error are offered to encourage researchers to embark on exposome research to promote the environmental health and well-being of all populations.

A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations

BACKGROUND

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures.

OBJECTIVES

We compared the performances of linear regression-based statistical methods in assessing exposome-health associations.

METHODS

In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity.

RESULTS

On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates.

CONCLUSIONS

Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

A data-driven search for semen-related phenotypes in conception delay

Sperm count, morphology, and motility have been reported to be predictive of pregnancy, although with equivocal basis prompting some authors to question the prognostic value of semen analysis. To assess the utility of including semen quality data in predicting conception delay or requiring >6 cycles to become pregnant (referred to as conception delay), we utilized novel data-driven analytic techniques in a pre-conception cohort of couples prospectively followed up for time-to-pregnancy. The study cohort comprised 402 (80%) male partners who provided semen samples and had time-to-pregnancy information. Female partners used home pregnancy tests and recorded results in daily journals. Odds ratios (OR), false discovery rates, and 95% confidence intervals (CIs) for conception delay (time-to-pregnancy > 6 cycles) were estimated for 40 semen quality phenotypes comprising 35 semen quality endpoints and 5 closely related fecundity determinants (body mass index, time of contraception, lipids, cotinine and seminal white blood cells). Both traditional and strict sperm phenotype measures were associated with lower odds of conception delay. Specifically, for an increase in percent morphologically normal spermatozoa using traditional methods, we observed a 40% decrease in conception delay (OR = 0.6, 95% CI = 0.50, 0.81; p = 0.0003). Similarly, for an increase in strict criteria, we observed a 30% decrease in odds for conception delay (OR = 0.7, 95% CI = 0.52, 0.83; p = 0.001). On the other hand, an increase in percent coiled tail spermatozoa was associated with a 40% increase in the odds for conception delay (OR = 1.4, 95% CI = 1.12, 1.75; p = 0.003). However, our findings suggest that semen phenotypes have little predictive value of conception delay (area under the curve of 73%). In a multivariate model containing significant semen factors and traditional risk factors (i.e. age, body mass index, cotinine and ever having fathered a pregnancy), there was a modest improvement in prediction of conception delay (16% increase in area under the curve, p < 0.0002).

Influence of environmental exposure on human epigenetic regulation

Environmental toxicants can alter epigenetic regulatory features such as DNA methylation and microRNA expression. As the sensitivity of epigenomic regulatory features may be greatest during the in utero period, when critical windows are narrow, and when epigenomic profiles are being set, this review will highlight research focused on that period. I will focus on work in human populations, where the impact of environmental toxicants in utero, including cigarette smoke and toxic trace metals such as arsenic, mercury and manganese, on genome-wide, gene-specific DNA methylation has been assessed. In particular, arsenic is highlighted, as this metalloid has been the focus of a number of studies and its detoxification mechanisms are well understood. Importantly, the tissues and cells being examined must be considered in context in order to interpret the findings of these studies. For example, by studying the placenta, it is possible to identify potential epigenetic adaptations of key genes and pathways that may alter the developmental course in line with the developmental origins of health and disease paradigm. Alternatively, studies of newborn cord blood can be used to examine how environmental exposure in utero can impact the composition of cells within the peripheral blood, leading to immunological effects of exposure. The results suggest that in humans, like other vertebrates, there is a susceptibility for epigenomic alteration by the environment during intrauterine development, and this may represent a mechanism of plasticity of the organism in response to its environment as well as a mechanism through which long-term health consequences can be shaped.

Air pollution exposure: a novel environmental risk factor for interstitial lung disease?

Air pollution exposure is a well-established risk factor for several adverse respiratory outcomes, including airways diseases and lung cancer. Few studies have investigated the relationship between air pollution and interstitial lung disease (ILD) despite many forms of ILD arising from environmental exposures. There are potential mechanisms by which air pollution could cause, exacerbate, or accelerate the progression of certain forms of ILD via pulmonary and systemic inflammation as well as oxidative stress. This article will review the current epidemiologic and translational data supporting the plausibility of this relationship and propose a new conceptual framework for characterizing novel environmental risk factors for these forms of lung disease.

Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting

In risk evaluation, the effect of mixtures of environmental chemicals on a common adverse outcome is of interest. However, due to the high dimensionality and inherent correlations among chemicals that occur together, the traditional methods (e.g. ordinary or logistic regression) suffer from collinearity and variance inflation, and shrinkage methods have limitations in selecting among correlated components. We propose a weighted quantile sum (WQS) approach to estimating a body burden index, which identifies "bad actors" in a set of highly correlated environmental chemicals. We evaluate and characterize the accuracy of WQS regression in variable selection through extensive simulation studies through sensitivity and specificity (i.e., ability of the WQS method to select the bad actors correctly and not incorrect ones). We demonstrate the improvement in accuracy this method provides over traditional ordinary regression and shrinkage methods (lasso, adaptive lasso, and elastic net). Results from simulations demonstrate that WQS regression is accurate under some environmentally relevant conditions, but its accuracy decreases for a fixed correlation pattern as the association with a response variable diminishes. Nonzero weights (i.e., weights exceeding a selection threshold parameter) may be used to identify bad actors; however, components within a cluster of highly correlated active components tend to have lower weights, with the sum of their weights representative of the set.

Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting

In risk evaluation, the effect of mixtures of environmental chemicals on a common adverse outcome is of interest. However, due to the high dimensionality and inherent correlations among chemicals that occur together, the traditional methods (e.g. ordinary or logistic regression) suffer from collinearity and variance inflation, and shrinkage methods have limitations in selecting among correlated components. We propose a weighted quantile sum (WQS) approach to estimating a body burden index, which identifies "bad actors" in a set of highly correlated environmental chemicals. We evaluate and characterize the accuracy of WQS regression in variable selection through extensive simulation studies through sensitivity and specificity (i.e., ability of the WQS method to select the bad actors correctly and not incorrect ones). We demonstrate the improvement in accuracy this method provides over traditional ordinary regression and shrinkage methods (lasso, adaptive lasso, and elastic net). Results from simulations demonstrate that WQS regression is accurate under some environmentally relevant conditions, but its accuracy decreases for a fixed correlation pattern as the association with a response variable diminishes. Nonzero weights (i.e., weights exceeding a selection threshold parameter) may be used to identify bad actors; however, components within a cluster of highly correlated active components tend to have lower weights, with the sum of their weights representative of the set.

Using personal sensors to assess the exposome and acute health effects

Introduction: The exposome encompasses the totality of human environmental exposures. Recent developments in sensor technology have made it possible to better measure personal exposure to environmental pollutants and other factors. We aimed to discuss and demonstrate the recent developments in personal sensors to measure multiple exposures and possible acute health responses, and discuss the main challenges ahead. Methods: We searched for a range of sensors to measure air pollution, noise, temperature, UV, physical activity, location, blood pressure, heart rate and lung function and to obtain information on green space and emotional status/mood and put it on a person. Results and Conclusions: We discussed the recent developments and main challenges for personal sensors to measure multiple exposures. We found and put together a personal sensor set that measures a comprehensive set of personal exposures continuously over 24 h to assess part of the current exposome and acute health responses. We obtained data for a whole range of exposures and some acute health responses, but many challenges remain to apply the methodology for extended time periods and larger populations including improving the ease of wear, e.g., through miniaturization and extending battery life, and the reduction of costs. However, the technology is moving fast and opportunities will come closer for further wide spread use to assess, at least part of the exposome.

Lipid concentrations and semen quality: the LIFE study

The decline in sperm count rates over the last 50 years appears to parallel the rising prevalence of obesity. As lipid levels are strongly associated with obesity, high lipids levels or hyperlipidaemia may thus play an important role in the decline in fertility in addition to other environmental or lifestyle factors. The objective of this population based cohort study was to evaluate the association between men's serum lipid concentrations and semen quality parameters among 501 male partners of couples desiring pregnancy and discontinuing contraception. Each participant provided prospectively up to two semen samples (94% of men provided one or more semen samples, and 77% of men provided a second sample approximately 1 month later). Linear mixed effects models were used to estimate the associations between baseline lipid concentrations and semen quality parameters, adjusted for age, body mass index and race. We found that higher levels of serum total cholesterol, free cholesterol and phospholipids were associated with a significantly lower percentage of spermatozoa with intact acrosome and smaller sperm head area and perimeter. Our results suggest that lipid concentrations may affect semen parameters, specifically sperm head morphology, highlighting the importance of cholesterol and lipid homeostasis for male fecundity.

Assessing the reproductive health of men with occupational exposures

The earliest report linking environmental (occupational) exposure to adverse human male reproductive effects dates back to1775 when an English physician, Percival Pott, reported a high incidence of scrotal cancer in chimney sweeps. This observation led to safety regulations in the form of bathing requirements for these workers. The fact that male-mediated reproductive harm in humans may be a result of toxicant exposures did not become firmly established until relatively recently, when Lancranjan studied lead-exposed workers in Romania in 1975, and later in 1977, when Whorton examined the effects of dibromochloropropane (DBCP) on male workers in California. Since these discoveries, several additional human reproductive toxicants have been identified through the convergence of laboratory and observational findings. Many research gaps remain, as the pool of potential human exposures with undetermined effects on male reproduction is vast. This review provides an overview of methods used to study the effects of exposures on male reproduction and their reproductive health, with a primary emphasis on the implementation and interpretation of human studies. Emphasis will be on occupational exposures, although much of the information is also useful in assessing environmental studies, occupational exposures are usually much higher and better defined.

Semen quality and time to pregnancy: the Longitudinal Investigation of Fertility and the Environment Study

OBJECTIVE

To assess semen parameters and couple fecundity as measured by time to pregnancy (TTP).

DESIGN

Observational prospective cohort with longitudinal measurement of TTP.

SETTING

Sixteen Michigan/Texas counties.

PATIENT(S)

A total of 501 couples discontinuing contraception were followed for 1 year while trying to conceive; 473 men (94%) provided one semen sample, and 80% provided two samples.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Using prospectively measured TTP, fecundability odds ratios (FORs) and 95% confidence intervals (CIs) were estimated for 36 individual semen quality parameters accounting for repeated semen samples, time off contraception, abstinence, enrollment site, and couples' ages, body mass indices, and serum cotinine concentrations.

RESULT(S)

In adjusted models, semen quality parameters were associated with significantly shorter TTP as measured by FORs >1: percent motility, strict and traditional morphology, sperm head width, elongation factor, and acrosome area. Significantly longer TTPs or FORs <1 were observed for morphologic categories amorphous and round sperm heads and neck/midpiece abnormalities. No semen quality parameters achieved significance when simultaneously modeling all other significant semen parameters and covariates, except for percent coiled tail when adjusting for sperm concentration (FOR 0.99; 95% CI 0.99-1.00). Male age was consistently associated with reduced couple fecundity (FOR 0.96; 95% CI 0.93-0.99), reflecting a longer TTP across all combined models. Female but not male body mass index also conferred a longer TTP (FOR 0.98; 95% CI 0.96-0.99).

CONCLUSION(S)

Several semen measures were significantly associated with TTP when modeled individually but not jointly and in the context of relevant couple-based covariates.

Cohort profile: the maternal-infant research on environmental chemicals research platform

BACKGROUND

The Maternal-Infant Research on Environmental Chemicals (MIREC) Study was established to obtain Canadian biomonitoring data for pregnant women and their infants, and to examine potential adverse health effects of prenatal exposure to priority environmental chemicals on pregnancy and infant health.

METHODS

Women were recruited during the first trimester from 10 sites across Canada and were followed through delivery. Questionnaires were administered during pregnancy and post-delivery to collect information on demographics, occupation, life style, medical history, environmental exposures and diet. Information on the pregnancy and the infant was abstracted from medical charts. Maternal blood, urine, hair and breast milk, as well as cord blood and infant meconium, were collected and analysed for an extensive list of environmental biomarkers and nutrients. Additional biospecimens were stored in the study's Biobank. The MIREC Research Platform encompasses the main cohort study, the Biobank and follow-up studies.

RESULTS

Of the 8716 women approached at early prenatal clinics, 5108 were eligible and 2001 agreed to participate (39%). MIREC participants tended to smoke less (5.9% vs. 10.5%), be older (mean 32.2 vs. 29.4 years) and have a higher education (62.3% vs. 35.1% with a university degree) than women giving birth in Canada.

CONCLUSIONS

The MIREC Study, while smaller in number of participants than several of the international cohort studies, has one of the most comprehensive datasets on prenatal exposure to multiple environmental chemicals. The biomonitoring data and biological specimen bank will make this research platform a significant resource for examining potential adverse health effects of prenatal exposure to environmental chemicals.