Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections

Potential Effects of Low-Level Toluene Exposure on the Nervous System of Mothers and Infants

In day-to-day living, individuals are exposed to various environmentally hazardous substances that have been associated with diverse diseases. Exposure to air pollutants can occur during breathing, posing a considerable risk to those with environmental health vulnerabilities. Among vulnerable individuals, maternal exposure can negatively impact the mother and child in utero. The developing fetus is particularly vulnerable to environmentally hazardous substances, with potentially greater implications. Among air pollutants, toluene is neurotoxic, and its effects have been widely explored. However, the impact of low-level toluene exposure in daily life remains unclear. Herein, we evaluated 194 mothers and infants from the Growing children's health and Evaluation of Environment (GREEN) cohort to determine the possible effects of early-life toluene exposure on the nervous system. Using Omics experiments, the effects of toluene were confirmed based on epigenetic changes and altered mRNA expression. Various epigenetic changes were identified, with upregulated expression potentially contributing to diseases such as glioblastoma and Alzheimer's, and downregulated expression being associated with structural neuronal abnormalities. These findings were detected in both maternal and infant groups, suggesting that maternal exposure to environmental hazardous substances can negatively impact the fetus. Our findings will facilitate the establishment of environmental health policies, including the management of environmentally hazardous substances for vulnerable groups.

Exposome epidemiology for suspect environmental chemical exposures during pregnancy linked to subsequent breast cancer diagnosis

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry of pregnancy cohort biospecimens in the Child Health and Development Studies to test for associations with breast cancer identified via the California Cancer Registry. Second and third trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both second and third trimesters to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol, linked to variations in amino acid and nucleotide pathways in second trimester and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in third trimester. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

Exposome Epidemiology for Suspect Environmental Chemical Exposures during Pregnancy Linked to Subsequent Breast Cancer Diagnosis

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry (HRMS) of pregnancy cohort biospecimens in the Child Health and Development Studies (CHDS) to test for associations with breast cancer identified via the California Cancer Registry. Second (T2) and third (T3) trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database (T3DB) for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both T2 and T3 to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol (DNP), linked to variations in amino acid and nucleotide pathways in T2 and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in T3. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

Creating personas for exposome research: the experience from the HEAP project

The exposome is a complex scientific field that has enjoyed consistent growth over the last two decades, defined as the composite of every exposure to which an individual is subjected from conception to death. The study of the exposome requires consideration of both the nature of those exposures and their changes over time, and as such necessitates high quality data and software solutions. As the exposome is both a broad and a recent concept, it is challenging to define or to introduce in a structured way. Thus, an approach to assist with clear definitions and a structured framework is needed for the wider scientific and public communication. Results: A set of 14 personas were developed through three focus groups and a series of 14 semi-structured interviews. The focus groups defined the broad themes specific to exposome research, while the sub-themes emerged to saturation via the interviews process. Personas are imaginary individuals that represent segments/groups of real people within a population. Within the context of the HEAP project, the created personas represented both exposome data generators and users. Conclusion: Personas have been implemented successfully in computer science, improving the understanding of human-computer interaction. The creation of personas specific to exposome research adds a useful tool supporting education and outreach activities for a complex scientific field.

High-Throughput Non-targeted Chemical Structure Identification Using Gas-Phase Infrared Spectra

The high-throughput identification of unknown metabolites in biological samples remains challenging. Most current non-targeted metabolomics studies rely on mass spectrometry, followed by computational methods that rank thousands of candidate structures based on how closely their predicted mass spectra match the experimental mass spectrum of an unknown. We reasoned that the infrared (IR) spectra could be used in an analogous manner and could add orthologous structure discrimination; however, this has never been evaluated on large data sets. Here, we present results of a high-throughput computational method for predicting IR spectra of candidate compounds obtained from the PubChem database. Predicted spectra were ranked based on their similarity to gas-phase experimental IR spectra of test compounds obtained from the NIST. Our computational workflow (IRdentify) consists of a fast semiempirical quantum mechanical method for initial IR spectra prediction, ranking, and triaging, followed by a final IR spectra prediction and ranking using density functional theory. This approach resulted in the correct identification of 47% of 258 test compounds. On average, there were 2152 candidate structures evaluated for each test compound, giving a total of approximately 555,200 candidate structures evaluated. We discuss several variables that influenced the identification accuracy and then demonstrate the potential application of this approach in three areas: (1) combining IR and mass spectra rankings into a single composite rank score, (2) identifying the precursor and fragment ions using cryogenic ion vibrational spectroscopy, and (3) the incorporation of a trimethylsilyl derivatization step to extend the method compatibility to less-volatile compounds. Overall, our results suggest that matching computational with experimental IR spectra is a potentially powerful orthogonal option for adding significant high-throughput chemical structure discrimination when used with other non-targeted chemical structure identification methods.

Exposomal research in the context of birth cohorts: What have they taught us?

OBJECTIVE

To review birth cohorts with an exposomal approach and their key outcomes and challenges. Exposome encompasses all human environmental exposures from conception onward. The impact of environmental exposures is greatest in critical stages of life, including fetal and early childhood. Birth cohorts provide a good study setting to assess exposome in the sensitive periods of life. Here, we review birth cohorts with an exposomal approach and their key outcomes and challenges.

DATA SOURCES

MEDLINE was searched for birth cohorts that have used an exposomal approach.

STUDY SELECTIONS

Relevant studies in English language were selected and reviewed.

RESULTS

The outcomes of birth cohorts with an exposomal approach improve our understanding of the association between environmental exposures and childhood diseases. For example, results from The Canadian Healthy Infant Longitudinal Development Study suggest an association between first trimester exposure to traffic-related air pollution and increased risk of allergic sensitization at 12 months of age (P = .6). In a smaller Canadian birth cohort study, it was found that regular use of air fresheners (adjusted P = .04) and presence of mold in the residence (adjusted P < .001) were associated with early childhood wheezing and cough. The application of emerging molecular omics technologies and new analytical tools has facilitated the comprehensive assessment of exposome in birth cohorts.

CONCLUSION

Birth cohort studies with an exposomal approach improve our understanding of the origin of childhood diseases by examining a complex network of environmental exposures during pregnancy and years beyond birth. International collaboration is required to develop large birth cohorts for better and more extensive assessment of exposome with standardized protocols and new statistical frameworks.

Analyzing Metabolomics Data for Environmental Health and Exposome Research

The exposome is the cumulative measure of environmental influences and associated biological responses across the life span, with critical relevance for understanding how exposures can impact human health. Metabolomics analysis of biological samples offers unique advantages for examining the exposome. Simultaneous analysis of external exposures, biological responses, and host susceptibility at a systems level can help establish links between external exposures and health outcomes. As metabolomics technologies continue to evolve for the study of the exposome, metabolomics ultimately will help provide valuable insights for exposure risk assessment, and disease prevention and management. Here, we discuss recent advances in metabolomics, and describe data processing protocols that can enable analysis of the exposome. This chapter focuses on using liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics for analysis of the exposome, including (1) preprocessing of untargeted metabolomics data, (2) identification of exposure chemicals and their metabolites, and (3) methods to establish associations between exposures and diseases.

Role of Damage-Associated Molecular Patterns in Light of Modern Environmental Research: A Tautological Approach

Two prominent models emerged as a result of intense interdisciplinary discussions on the environmental health paradigm, called the "exposome" concept and the "adverse outcome pathway" (AOP) concept that links a molecular initiating event to the adverse outcome via key events. Here, evidence is discussed, suggesting that environmental stress/injury-induced damage-associated molecular patterns (DAMPs) may operate as an essential integrating element of both environmental health research paradigms. DAMP-promoted controlled/uncontrolled innate/adaptive immune responses reflect the key events of the AOP concept. The whole process starting from exposure to a distinct environmental stress/injury-associated with the presence/emission of DAMPs-up to the manifestation of a disease may be regarded as an exposome. Clinical examples of such a scenario are briefly sketched, in particular, a model in relation to the emerging COVID-19 pandemic, where the interaction of noninfectious environmental factors (e.g., particulate matter) and infectious factors (SARS CoV-2) may promote SARS case fatality via superimposition of both exogenous and endogenous DAMPs.

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.

The reference values in the interpretation of toxicological data

The worldwide gradual expansion of industrialization has led to a dramatic increase in the production and use of chemical substances. This has resulted in a greater dispersion of these elements in the environment and in an increased exposure of the general population and workers. In this scenario, a thorough knowledge of exposure levels is needed in order to assess chemical risks in environmental and occupational settings. Biological monitoring is among the most useful tools for assessing exposure. However, in order to provide really effective guidance in the application/implementation of risk management measures, biomonitoring results need to be compared with appropriate references. Reference values (RVs) are an excellent resource since useful information for a correct interpretation of toxicological data can be obtained by comparing them with biomonitoring results. In the field of public health, this may enable us to identify potential sources of exposure, define the principal and most frequently exploited routes of exposure, and outline chemical absorption. Similarly, in occupational medicine, RVs can be used to give meaning to biomonitoring findings, especially when a biological limit value is not available for the chemical in question. Furthermore, these values are a valid tool for assessing exposure to chemical carcinogens. Therefore, by integrating reference values in an appropriate and complete system of guide values that also includes action levels and biological limit values, we could obtain both an adequate assessment of exposure and a better understanding of toxicological data.

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.

Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health

Background:

New occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called “work 4.0”, and of the workplace.

Objectives:

To explore the roles and implications of Big Data in the new occupational medicine settings.

Methods:

Comprehensive literature search.

Results:

Big Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques (“molecular Big Data”) and computational infrastructures, including databases, sensors and smart devices (“computational Big Data” and “digital Big Data”).

Conclusions:

In the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.

Beyond genomics: understanding exposotypes through metabolomics

BACKGROUND

Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact.

MAIN TEXT

Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics.

CONCLUSIONS

Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.