BACKGROUND: Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health.
OBJECTIVE: Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications.
METHODS: We conduct a literature review and synthesis.
RESULTS: First, we discuss key concepts and terminology for geospatial exposure data and models. Second, we provide an overview of workflows in geospatial exposure model development and health data integration. Third, we review modeling approaches, including proximity-based, statistical, and mechanistic approaches, across diverse exposure types, such as air quality, water quality, climate, and socioeconomic factors. For each model type, we provide descriptions, general equations, and example applications for environmental exposure assessment. Fourth, we discuss the approaches used to integrate geospatial exposure data and health data, such as methods to link data sources with disparate spatial and temporal scales. Fifth, we describe the landscape of open-source tools supporting these workflows.

Adductomics, an emerging field within the \'omics sciences, focuses on the formation and prevalence of DNA, RNA, and protein adducts induced by endogenous and exogenous agents in biological systems. These modifications often result from exposure to environmental pollutants, dietary components, and xenobiotics, impacting cellular functions and potentially leading to diseases such as cancer. This review highlights advances in mass spectrometry (MS) that enhance the detection of these critical modifications and discusses current and emerging trends in adductomics, including developments in MS instrument use, screening techniques, and the study of various biomolecular modifications from mono-adducts to complex hybrid crosslinks between different types of biomolecules. The review also considers challenges, including the need for specialized MS spectra databases and multi-omics integration, while emphasizing techniques to distinguish between exogenous and endogenous modifications. The future of adductomics possesses significant potential for enhancing our understanding of health in relation to environmental exposures and precision medicine.

UNASSIGNED: Environmental contaminants (ECs) are increasingly recognized as crucial drivers of dyslipidemia and cardiovascular disease (CVD), but the comprehensive impact spectrum and interlinking mechanisms remain uncertain.
UNASSIGNED: We aimed to systematically evaluate the association between exposure to 80 ECs across seven divergent categories and markers of dyslipidemia and investigate their underpinning biomolecular mechanisms via an unbiased integrative approach of internal chemical exposome and multi-omics.
UNASSIGNED: A longitudinal study involving 76 healthy older adults was conducted in Jinan, China, and participants were followed five times from 10 September 2018 to 19 January 2019 in 1-month intervals. A broad spectrum of seven chemical categories covering the prototypes and metabolites of 102 ECs in serum or urine as well as six serum dyslipidemia markers [total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, apolipoprotein (Apo)A1, ApoB, and ApoE4] were measured. Multi-omics, including the blood transcriptome, serum/urine metabolome, and serum lipidome, were profiled concurrently. Exposome-wide association study and the deletion/substitution/addition algorithms were applied to explore the associations between 80 EC exposures detection frequency >50% and dyslipidemia markers. Weighted quantile sum regression was used to assess the mixture effects and relative contributions. Multi-omics profiling, causal inference model, and pathway analysis were conducted to interpret the mediating biomolecules and underlying mechanisms. Examination of cytokines and electrocardiograms was further conducted to validate the observed associations and biomolecular pathways.
UNASSIGNED: Eight main ECs [1-naphthalene, 1-pyrene, 2-fluorene, dibutyl phosphate, tri-phenyl phosphate, mono-(2-ethyl-5-hydroxyhexyl) phthalate, chromium, and vanadium] were significantly associated with most dyslipidemia markers. Multi-omics indicated that the associations were mediated by endogenous biomolecules and pathways, primarily pertinent to CVD, inflammation, and metabolism. Clinical measures of cytokines and electrocardiograms further cross-validated the association of these exogenous ECs with systemic inflammation and cardiac function, demonstrating their potential mechanisms in driving dyslipidemia pathogenesis.
UNASSIGNED: It is imperative to prioritize mitigating exposure to these ECs in the primary prevention and control of the dyslipidemia epidemic. https://doi.org/10.1289/EHP13864.

Emerging evidence indicates that chemical exposures in the environment are overlooked drivers of cardiovascular diseases (CVD). Recent evidence suggests that micro- and nanoplastic (MNP) particles derived largely from the chemical or mechanical degradation of plastics might represent a novel CVD risk factor. Experimental data in preclinical models suggest that MNPs can foster oxidative stress, platelet aggregation, cell senescence, and inflammatory responses in endothelial and immune cells while promoting a range of cardiovascular and metabolic alterations that can lead to disease and premature death. In humans, MNPs derived from various plastics, including polyethylene and polyvinylchloride, have been detected in atherosclerotic plaques and other cardiovascular tissues, including pericardia, epicardial adipose tissues, pericardial adipose tissues, myocardia, and left atrial appendages. MNPs have measurable levels within thrombi and seem to accumulate preferentially within areas of vascular lesions. Their presence within carotid plaques is associated with subsequent increased incidence of cardiovascular events. To further investigate the possible causal role of MNPs in CVD, future studies should focus on large, prospective cohorts assessing the exposure of individuals to plastic-related pollution, the possible routes of absorption, the existence of a putative safety limit, the correspondence between exposure and accumulation in tissues, the timing between accumulation and CVD development, and the pathophysiological mechanisms instigated by pertinent concentrations of MNPs. Data from such studies would allow the design of preventive, or even therapeutic, strategies. Meanwhile, existing evidence suggests that reducing plastic production and use will produce benefits for the environment and for human health. This goal could be achieved through the UN Global Plastics Treaty that is currently in negotiation.

This opinion article highlights the critical role of laboratory medicine and emerging technologies in cardiovascular risk reduction through exposome analysis. The exposome encompasses all external and internal exposures an individual faces throughout their life, influencing the onset and progression of cardiovascular diseases (CVD). Integrating exposome data with genetic information allows for a comprehensive understanding of the multifactorial causes of CVD, facilitating targeted preventive interventions. Laboratory medicine, enhanced by advanced technologies such as metabolomics and artificial intelligence (AI), plays a pivotal role in identifying and mitigating these exposures. Metabolomics provides detailed insights into metabolic changes triggered by environmental factors, while AI efficiently processes complex datasets to uncover patterns and associations. This integration fosters a proactive approach in public health and personalized medicine, enabling earlier detection and intervention. The article calls for global implementation of exposome technologies to improve population health, emphasizing the need for robust technological platforms and policy-driven initiatives to seamlessly integrate environmental data with clinical diagnostics. By harnessing these innovative technologies, laboratory medicine can significantly contribute to reducing the global burden of cardiovascular diseases through precise and personalized risk mitigation strategies.

Distribution of environmental hazards and vulnerability to their effects vary across socioeconomic groups. Our objective was to analyse the relationship between child socioeconomic position (SEP) at birth and the external exposome at pre-school age (0-4 years). This study included more than 60,000 children from eight cohorts in eleven European cities (Oslo, Copenhagen, Bristol, Bradford, Rotterdam, Nancy, Poitiers, Gipuzkoa, Sabadell, Valencia and Turin). SEP was measured through maternal education and a standardised indicator of household income. Three child exposome domains were investigated: behavioral, diet and urban environment. We fitted separate logistic regression model for each exposome variable - dichotomised using the city-specific median - on SEP (medium/low vs high) adjusting for maternal age, country of birth and parity. Analyses were carried out separately in each study-area. Low-SEP children had, consistently across study-areas, lower Odds Ratios (ORs) of breastfeeding, consumption of eggs, fish, fruit, vegetables and higher ORs of TV screen time, pet ownership, exposure to second-hand smoke, consumption of dairy, potatoes, sweet beverages, savory biscuits and crisps, fats and carbohydrates. For example, maternal education-breastfeeding OR (95% Confidence Interval (CI)) ranged from 0.18 (0.14-0.24) in Bristol to 0.73 (0.58-0.90) in Oslo. SEP was also strongly associated with the urban environment with marked between-city heterogeneity. For example, income-PM2.5 OR (95%CI) ranged from 0.69 (0.47-1.02) in Sabadell to 2.44 (2.16-2.72) in Oslo. Already at pre-school age, children with lower SEP have consistently poorer diets and behaviours, which might influence their future health and wellbeing. SEP-urban environment relationships are strongly context-dependent.

Our capability to predict the impact of exposure to chemical mixtures on environmental and human health is limited in comparison to the advances on the chemical characterization of the exposome. Current approaches, such as new approach methodologies, rely on the characterization of the chemicals and the available toxicological knowledge of individual compounds. In this study, we show a new methodological approach for assessment of chemical mixtures based on a proteome-wide identification of the protein targets and revealing the relevance of new targets based on their role in the cellular function. We applied a proteome integral solubility alteration assay to identify 24 protein targets from a chemical mixture of 2,3,7,8-tetrachlorodibenzo-p-dioxin, alpha-endosulfan, and bisphenol A among the HepG2 soluble proteome, and validated the chemical mixture-target interaction orthogonally. To define the range of interactive capability of the new targets, the data from intrinsic properties of the targets were retrieved. Introducing the target properties as criteria for a multi-criteria decision-making analysis called the analytical hierarchy process, the prioritization of targets was based on their involvement in multiple pathways. This methodological approach that we present here opens a more realistic and achievable scenario to address the impact of complex and uncharacterized chemical mixtures in biological systems.

UNASSIGNED: Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels.
UNASSIGNED: Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs).
UNASSIGNED: We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the \"three Rs\" principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure-disease links. https://doi.org/10.1289/EHP13120.

The exposome approach, emphasizing lifelong environmental exposures, is a holistic framework exploring the intricate interplay between genetics and the environment in shaping health outcomes. Complementing this, the one health approach recognizes the interconnectedness of human and ecological health within a shared ecosystem, extending to planetary health, which encompasses the entire planet. Integrating Disease Surveillance Systems with exposome, one health, and planetary health signifies a paradigm shift in health management, fostering a comprehensive public health framework. This publication advocates for combining traditional health surveillance with exposome and one health/planetary health approach, proposing a three-step approach: ecological analysis, territorial intervention in identified issues, and an analytical phase for assessing interventions. Particularly relevant for Latin American countries facing a double burden of diseases, integrating the exposome into traditional health surveillance proves cost-effective by leveraging existing data and environmental measurements. In conclusion, the integration of exposome and one health approaches into traditional health surveillance presents a robust framework for monitoring population health, especially in regions like Latin America with complex health challenges. This innovative approach enables tailored interventions, disease outbreak predictions, and a holistic understanding of the intricate links between human health and the environment, offering substantial benefits for public health and disease prevention despite existing challenges.

Increasing evidence suggests an association between atopic dermatitis, the most chronic inflammatory disease of the skin, and autism spectrum disorders, which are a group of neurodevelopmental diseases. Inflammation and immune dysregulation associated with genetic and environmental factors seem to characterize the pathophysiological mechanisms of both conditions. We conducted a literature review of the PubMed database aimed at identifying the clinical features and alleged risk factors that could be used in clinical practice to predict the onset of ASD and/or AD or worsen their prognosis in the context of comorbidities.