Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles.

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

Predictive toxicology of chemical mixtures using proteome-wide thermal profiling and protein target properties.

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 the 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.

Contribution of laboratory medicine and emerging technologies to cardiovascular risk reduction via exposome analysis: an opinion of the IFCC Division on Emerging Technologies.

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.

Micro-nanoplastics and cardiovascular diseases: evidence and perspectives.

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.

Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood.

Chemical exposomes can now be comprehensively measured in human blood, but knowledge of their variability and longitudinal stability is required for robust application in cohort studies. Here, we applied high-resolution chemical exposomics to plasma of 46 adults, each sampled 6 times over 2 years in a multiomic cohort, resulting in 276 individual exposomes. In addition to quantitative analysis of 83 priority target analytes, we discovered and semiquantified substances that have rarely or never been reported in humans, including personal care products, pesticide transformation products, and polymer additives. Hierarchical cluster analysis for 519 confidently annotated substances revealed unique and distinctive coexposures, including clustered pesticides, poly(ethylene glycols), chlorinated phenols, or natural substances from tea and coffee; interactive heatmaps were publicly deposited to support open exploration of the complex (meta)data. Intraclass correlation coefficients (ICC) for all annotated substances demonstrated the relatively low stability of the exposome compared to that of proteome, microbiome, and endogenous small molecules. Implications are that the chemical exposome must be measured more frequently than other omics in longitudinal studies and four longitudinal exposure types are defined that can be considered in study design. In this small cohort, mixed-effect models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, demonstrating great potential for longitudinal exposomics in precision health research.

A review of geospatial exposure models and approaches for health data integration.

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.

Multi-adductomics: Advancing mass spectrometry techniques for comprehensive exposome characterization.

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.

Socioeconomic position during pregnancy and pre-school exposome in children from eight European birth cohort studies.

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.

Socioeconomic Inequalities in the External Exposome in European Cohorts: The EXPANSE Project.

Socioeconomic inequalities in the exposome have been found to be complex and highly context-specific, but studies have not been conducted in large population-wide cohorts from multiple countries. This study aims to examine the external exposome, encompassing individual and environmental factors influencing health over the life course, and to perform dimension reduction to derive interpretable characterization of the external exposome for multicountry epidemiological studies. Analyzing data from over 25 million individuals across seven European countries including 12 administrative and traditional cohorts, we utilized domain-specific principal component analysis (PCA) to define the external exposome, focusing on air pollution, the built environment, and air temperature. We conducted linear regression to estimate the association between individual- and area-level socioeconomic position and each domain of the external exposome. Consistent exposure patterns were observed within countries, indicating the representativeness of traditional cohorts for air pollution and the built environment. However, cohorts with limited geographical coverage and Southern European countries displayed lower temperature variability, especially in the cold season, compared to Northern European countries and cohorts including a wide range of urban and rural areas. The individual- and area-level socioeconomic determinants (i.e., education, income, and unemployment rate) of the urban exposome exhibited significant variability across the European region, with area-level indicators showing stronger associations than individual variables. While the PCA approach facilitated common interpretations of the external exposome for air pollution and the built environment, it was less effective for air temperature. The diverse socioeconomic determinants suggest regional variations in environmental health inequities, emphasizing the need for targeted interventions across European countries.

Neonatal Encephalopathy is a Complex Phenotype Representing Reproductive and Pregnancy Exposome Effects on the Maternal-Placental-Fetal Triad.

Reproductive, pregnancy, and placental exposomes influence the fetal neural exposome through toxic stressor interplay, impairing the maternal-placental-fetal (MPF) triad. Neonatal encephalopathy represents different clinical presentations based on complex time-dependent etiopathogenetic mechanisms including hypoxia-ischemia that challenge diagnosis and prognosis. Reproductive, pregnancy, and placental exposomes impair the fetal neural exposome through toxic stressor interplay within the MPF triad. Long intervals often separate disease onset from phenotype. Interdisciplinary fetal-neonatal neurology training, practice, and research closes this knowledge gap. Maintaining reproductive health preserves MPF triad health with life-course benefits.

Identifying the most critical behavioral lifestyles associated with MAFLD: evidence from the NHANES 2017-2020.

Background & aims: Accumulating studies have demonstrated associations between single lifestyle exposures and metabolic dysfunction-associated fatty liver disease (MAFLD). However, the joint effects of lifestyle exposures remain unclear, hindering the development of targeted prevention and control strategies. We aimed to investigate the joint associations between lifestyle exposomes and MAFLD. Methods: This study included 5,002 participants from NHANES 2017-2020. Lifestyle exposomes, including sleep duration, metabolic equivalent of task (MET), Healthy Eating Index (HEI)-2015 score, alcohol consumption, and smoke exposure, were identified from questionnaire data. MAFLD was diagnosed by vibration-controlled transient elastography measurements and laboratory data. A logistic regression model and the weighted quantile sum method were used to evaluate the associations of single and joint lifestyle exposomes, respectively, with MAFLD. The population attributable fractions (PAFs) were calculated to assess the population benefits of different intervention strategies. Results: Per-quartile range increases in sleep duration (OR=0.883, 95% CI: 0.826-0.944), MET (0.916, 0.871-0.963), and HEI-2015 score (0.827, 0.756-0.904) were significantly associated with MAFLD. The joint exposure of sleep duration, MET, and HEI-2015 score was associated with MAFLD (0.772, 0.688-0.865), with the highest weight (importance) for MET (0.526). PAFs revealed greater intervention benefits for sleep and the HEI-2015 when the majority of the population (>5%) had a low MAFLD risk (weak intervention targets), whereas MET was the most efficient intervention strategy when minority populations (≤5%) had a low MAFLD risk (strong intervention targets). Conclusion: This study demonstrated significant associations between MAFLD and single and joint exposures to sleep duration, MET, and HEI-2015 and identified physical activity as the most important lifestyle factor. Further population benefit analyses may provide evidence and suggestions for population-level interventions.

ExpoNano: A Strategy Based on Hyper-Cross-Linked Polymers Achieves Urinary Exposome Assessment for Biomonitoring.

Urinary analysis of exogenous and endogenous molecules constitutes an efficient, noninvasive approach to evaluate human health status. However, the exposome characterization of urinary molecules remains extremely challenging with current techniques. Herein, we develop an ExpoNano strategy based on hyper-cross-linked polymers (HCPs) to achieve ultrahigh-throughput measurement of exo/endogenous molecules in urine. The strategy includes a simple trapping-detrapping procedure (15 min) with HCPs in enzymatically treated urine, followed by mass spectrometer determination. Molecules that can be determined by ExpoNano have a wide range of molecular weight (75-837 Da) and Log Kow (octanol-water partition coefficient; -9.86 to 10.56). The HCPs can be repeatedly used five times without decreasing the trapping efficiency. Application of ExpoNano in a biomonitoring study revealed a total of 63 environmental chemicals detected in >50% of the urine pools collected from Chinese adults living in 13 cities, with a median concentration of 0.026-47 ng/mL, while nontargeted analysis detected an additional 243 exogenous molecules. Targeted and nontargeted analysis also detected 926 endogenous molecules in pooled urine. Collectively, the ExpoNano strategy demonstrates unique advantages over traditional urine analysis approaches, including a wide range of analytes, satisfactory trapping efficiency, high simplicity and reusability, and extremely reduced time demand and financial cost.

Screening persistent organic pollutants for effects on testosterone and estrogen synthesis at human-relevant concentrations using H295R cells in 96-well plates.

Many persistent organic pollutants (POPs) are suspected endocrine disruptors and it is important to investigate their effects at low concentrations relevant to human exposure. Here, the OECD test guideline #456 steroidogenesis assay was downscaled to a 96-well microplate format to screen 24 POPs for their effects on viability, and testosterone and estradiol synthesis using the human adrenocortical cell line H295R. The compounds (six polyfluoroalkyl substances, five organochlorine pesticides, ten polychlorinated biphenyls and three polybrominated diphenyl ethers) were tested at human-relevant levels (1 nM to 10 µM). Increased estradiol synthesis, above the OECD guideline threshold of 1.5-fold solvent control, was shown after exposure to 10 µM PCB-156 (153%) and PCB-180 (196%). Interestingly, the base hormone synthesis varied depending on the cell batch. An alternative data analysis using a linear mixed-effects model that include multiple independent experiments and considers batch-dependent variation was therefore applied. This approach revealed small but statistically significant effects on estradiol or testosterone synthesis for 17 compounds. Increased testosterone levels were demonstrated even at 1 nM for PCB-74 (18%), PCB-99 (29%), PCB-118 (16%), PCB-138 (19%), PCB-180 (22%), and PBDE-153 (21%). The MTT assay revealed significant effects on cell viability after exposure to 1 nM of perfluoroundecanoic acid (12%), 3 nM PBDE-153 (9%), and 10 µM of PCB-156 (6%). This shows that some POPs can interfere with endocrine signaling at concentrations found in human blood, highlighting the need for further investigation into the toxicological mechanisms of POPs and their mixtures at low concentrations relevant to human exposure.

Optimized analytical strategy based on high-resolution mass spectrometry for unveiling associations between long-term chemical exposome in hair and Alzheimer's disease.

Exposure to environmental pollutants or contaminants is correlated with detrimental effects on human health, such as neurodegenerative diseases. Adopting hair as a biological matrix for biomonitoring is a significant innovation, since it can reflect the long-term chemical exposome, spanning months to years. However, only a limited number of studies have developed analytical strategies for profiling the chemical exposome in this heterogeneous biological matrix. In this study, a systematic investigation of the chemical extraction procedure from human hair was conducted, using a design of experiments and a high-resolution mass spectrometry (HRMS)-based suspect screening approach. The PlackettBurman (PB) design was applied to identify the significant variables influencing the number of detected features. Then, a central composite design was implemented to optimize the levels of each identified significant variable. Under the optimal conditions-15-minute pulverization, 25 mg of hair weight, 40 min of sonication, and a sonication temperature of 35 °C-approximately 32,000 and 15,000 aligned features were detected in positive and negative ion modes, respectively. This optimized analytical procedure was applied to hair samples from patients with Alzheimer's disease (AD) and individuals with normal cognitive function. Overall, 307 chemicals were identified using the suspect screening approach, with 37 chemicals differentiating patients with AD from controls. This study not only optimized an analytical procedure for characterizing the long-term chemical exposome in human hair but also explored the associations between AD and environmental factors.

Wristband Personal Passive Samplers and Suspect Screening Methods Highlight Gender Disparities in Chemical Exposures.

Wristband personal samplers enable human exposure assessments for a diverse range of chemical contaminants and exposure settings with a previously unattainable scale and cost-effectiveness. Paired with nontargeted analyses, wristbands can provide important exposure monitoring data to expand our understanding of the environmental exposome. Here, a custom scripted suspect screening workflow was developed in the R programming language for feature selection and chemical annotations using gas chromatography-high-resolution mass spectrometry data acquired from the analysis of wristband samples collected from five different cohorts. The workflow includes blank subtraction, internal standard normalization, prediction of chemical uses in products, and feature annotation using multiple library search metrics and metadata from PubChem, among other functionalities. The workflow was developed and validated against 104 analytes identified by targeted analytical results in previously published reports of wristbands. A true positive rate of 62 and 48% in a quality control matrix and wristband samples, respectively, was observed for our optimum set of parameters. Feature analysis identified 458 features that were significantly higher on female-worn wristbands and only 21 features that were significantly higher on male-worn wristbands across all cohorts. Tentative identifications suggest that personal care products are a primary driver of the differences observed.

Innovative Approach for Human Semen Quality Assessment Based on Volatilomics.

The volatilome profile of some biofluids (blood, urine, and human semen) identified by Solid-Phase Microextraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and collected from young men living in two high-pollution areas in Italy, i.e., Land of Fires and Valley of Sacco River, have been coupled to sperm parameters obtained by spermiogram analysis to build general multiple regression models. Panels of volatile organic compounds (VOCs) have been selected to optimize the models and used as predictive variables to estimate the different sperm quality parameters (sperm cell concentration, total and progressive motility/immotile cells, total/head/neck/tail morphology anomalies, semen round cell concentration). The results of the multiple linear regression models based on the different subgroups of data joining VOCs from one/two or three biofluids have been compared. Surprisingly, the models based on blood and urine VOCs have allowed an excellent estimate of spermiogram values, paving the way towards a new method of indirect evaluation of semen quality and preventive screening. The significance of VOCs in terms of toxicity and dangerousness was discussed with the support of chemical databases available online.

Multiomics Screening Identified CpG Sites and Genes That Mediate the Impact of Exposure to Environmental Chemicals on Cardiometabolic Traits.

An understanding of the molecular mechanism whereby an environmental chemical causes a disease is important for the purposes of future applications. In this study, a multiomics workflow was designed to combine several publicly available datasets in order to identify CpG sites and genes that mediate the impact of exposure to environmental chemicals on cardiometabolic traits. Organophosphate and prenatal lead exposure were previously reported to change methylation level at the cg23627948 site. The outcome of the analyses conducted in this study revealed that, as the cg23627948 site becomes methylated, the expression of the GNA12 gene decreases, which leads to a higher body fat percentage. Prenatal perfluorooctane sulfonate exposure was reported to increase the methylation level at the cg21153102 site. Findings of this study revealed that higher methylation at this site contributes to higher diastolic blood pressure by changing the expression of CHP1 and GCHFR genes. Moreover, HKR1 mediates the impact of B12 supplementation → cg05280698 hypermethylation on higher kidney function, while CTDNEP1 mediates the impact of air pollution → cg03186999 hypomethylation on higher systolic blood pressure. This study investigates CpG sites and genes that mediate the impact of environmental chemicals on cardiometabolic traits. Furthermore, the multiomics approach described in this study provides a convenient workflow with which to investigate the impact of an environmental factor on the body's biomarkers, and, consequently, on health conditions, using publicly available data.

Exploring the Exposome Spectrum: Unveiling Endogenous and Exogenous Factors in Non-Communicable Chronic Diseases.

The exposome encompasses all endogenous and exogenous exposure individuals encounter throughout their lives, including biological, chemical, physical, psychological, relational, and socioeconomic factors. It examines the duration and intensity of these types of exposure and their complex interactions over time. This interdisciplinary approach involves various scientific disciplines, particularly toxicology, to understand the long-term effects of toxic exposure on health. Factors like air pollution, racial background, and socioeconomic status significantly contribute to diseases such as metabolic, cardiovascular, neurodegenerative diseases, infertility, and cancer. Advanced analytical methods measure contaminants in biofluids, food, air, water, and soil, but often overlook the cumulative risk of multiple chemicals. An exposome analysis necessitates sophisticated tools and methodologies to understand health interactions and integrate findings into precision medicine for better disease diagnosis and treatment. Chronic exposure to environmental and biological stimuli can lead to persistent low-grade inflammation, which is a key factor in chronic non-communicable diseases (NCDs), such as obesity, cardiometabolic disorders, cancer, respiratory diseases, autoimmune conditions, and depression. These NCDs are influenced by smoking, unhealthy diets, physical inactivity, and alcohol abuse, all shaped by genetic, environmental, and social factors. Dietary patterns, especially ultra-processed foods, can exacerbate inflammation and alter gut microbiota. This study investigates the exposome's role in the prevention, development, and progression of NCDs, focusing on endogenous and exogenous factors.