A precision environmental health approach to prevention of human disease

The Exposome as a Key to Understanding Pediatric Health Disparities

This viewpoint discusses the benefits of the exposome and the reasons it should be used to understand pediatric health disparities.

An extension of latent unknown clustering integrating multi-omics data (LUCID) incorporating incomplete omics data

Motivation

Latent unknown clustering integrating multi-omics data is a novel statistical model designed for multi-omics data analysis. It integrates omics data with exposures and an outcome through a latent cluster, elucidating how exposures influence processes reflected in multi-omics measurements, ultimately affecting an outcome. A significant challenge in multi-omics analysis is the issue of list-wise missingness. To address this, we extend the model to incorporate list-wise missingness within an integrated imputation framework, which can also handle sporadic missingness when necessary.

Results

Simulation studies demonstrate that our integrated imputation approach produces consistent and less biased estimates, closely reflecting true underlying values. We applied this model to data from the ISGlobal/ATHLETE "Exposome Data Challenge Event" to explore the association between maternal exposure to hexachlorobenzene and childhood body mass index by integrating incomplete proteomics data from 1301 children. The model successfully estimated proteomics profiles for two clusters representing higher and lower body mass index, characterizing the potential profiles linking prenatal hexachlorobenzene levels and childhood body mass index.

Availability and implementation

The proposed methods have been implemented in the R package LUCIDus. The source code is available at https://github.com/USCbiostats/LUCIDus.

Chemical and non-chemical stressors in a postpartum cohort through wristband and self report data: Links between increased chemical burden, economic, and racial stress

Multiple external stressors are known to have adverse impacts on health and development. Certain groups are more vulnerable and/or more likely to be exposed toenvironmental, psychological, and social stressors simultaneously. Yet, few studies have examined combined exposure to environmental toxicants and psychosocial stress. Here, we integrated environmental chemical exposure data collected using silicone wristbands and self-report social stressor data within the Brain and Early Experience (BEE) perinatal cohort to understand co-exposure to environmental chemicals and social stress. Silicone wristbands were worn for one week by mothers throughout central North Carolina who were 6 months postpartum (n = 97). Exposure to 110 environmental chemicals across eight chemical classes was quantified on silicone wristbands using gas chromatography mass spectrometry. Social stress was evaluated using eight established self-report questionnaires (e.g., Brief Symptom Inventory, Perceived Stress Scale), quantifying experiences such as race-related stress, economic strain, and relationship conflict. Hair cortisol levels were measured as an additional metric of stress. The chemical exposure landscape and associations among chemical exposure, demographic characteristics, and social stress were characterized through individual variable analyses, cluster and data reduction, and compiled scoring approaches to comprehensively evaluate chemical and social stress burdens. We found that chemicals contain co-occurring patterns largely based on chemical class, with phthalates representing the chemical class with highest exposure and polychlorinated biphenyls the lowest. Chemicals showed differential exposure across racial groups, with diethyl phthalate, triphenyl phosphate, and tris(3,5-dimethyl phenyl) phosphate at higher levels in Black participants compared with White participants. Integrating social stressor profiling with chemical exposure data identified one particularly vulnerable subset of participants in which high chemical exposure burden coincided with high experiences of racism and economic stress. These findings demonstrate co-occurring chemical and social stress, warranting further investigation to better understand how these combined stressors may contribute to disparities in maternal and child health.

Exposure-associated DNA methylation among people exposed to multiple industrial pollutants

BACKGROUND

Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations.

RESULTS

On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases.

CONCLUSION

Our findings underscore the pivotal role of AHRR methylation in gene-environment interactions and highlight SNPs that could potentially serve as indicators of population susceptibility in regions exposed to multiple heavy metals and PAHs.

Integrating Multi-Omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease

BACKGROUND

Precision Health aims to revolutionize disease prevention by leveraging information across multiple omic datasets (multi-omics). However, existing methods generally do not consider personalized environmental risk factors (e.g., environmental pollutants).

OBJECTIVE

To develop and apply a precision health framework which combines multiomic integration (including early, intermediate, and late integration, representing sequential stages at which omics layers are combined for modeling) with mediation approaches (including high-dimensional mediation to identify biomarkers, mediation with latent factors to identify pathways, and integrated/quasi-mediation to identify high-risk subpopulations) to identify novel biomarkers of prenatal mercury induced metabolic dysfunction-associated fatty liver disease (MAFLD), elucidate molecular pathways linking prenatal mercury with MAFLD in children, and identify high-risk children based on integrated exposure and multiomics data.

METHODS

This prospective cohort study used data from 420 mother-child pairs from the Human Early Life Exposome (HELIX) project. Mercury concentrations were determined in maternal or cord blood from pregnancy. Cytokeratin 18 (CK-18; a MAFLD biomarker) and five omics layers (DNA Methylation, gene transcription, microRNA, proteins, and metabolites) were measured in blood in childhood (age 6-10 years).

RESULTS

Each standard deviation increase in prenatal mercury was associated with a 0.11 [95% confidence interval: 0.02-0.21] standard deviation increase in CK-18. High dimensional mediation analysis identified 10 biomarkers linking prenatal mercury and CK-18, including six CpG sites and four transcripts. Mediation with latent factors identified molecular pathways linking mercury and MAFLD, including altered cytokine signaling and hepatic stellate cell activation. Integrated/quasi-mediation identified high risk subgroups of children based on unique combinations of exposure levels, omics profiles (driven by epigenetic markers), and MAFLD.

CONCLUSIONS

Prenatal mercury exposure is associated with elevated liver enzymes in childhood, likely through alterations in DNA methylation and gene expression. Our analytic framework can be applied across many different fields and serve as a resource to help guide future precision health investigations.

Effect of environmental education program implemented with university student participation on secondary school students' environmental attitude

Study aimed to increase university students' sensitivity and the environmental attitudes of secondary school students through environmental education program. It was planned as quasi-experimental research. The first phase was completed with five fourth-year students who took Social Awareness Course at a university's nursing department in Turkey. In second phase, sample consisted of 264 5th-grade students studying at Secondary School in Black Sea Region. University students implemented Environmental Education Program for secondary school students for four weeks. Mean environmental attitude scale score of 5th-grade students before education was 2.79 ± 0.32, and after education was 3.51 ± 0.41. A statistically significant difference was determined between mean total scale scores of university and 5th-grade students before and after education (p ˂ 0.05). It was determined that environmental sensitivity of university students and environmental attitudes of secondary school students were at medium level before Environmental Education Program and high level after education.

A review of disrupted biological response associated with volatile organic compound exposure: Insight into identification of biomarkers

Volatile organic compounds (VOCs) are widespread harmful atmospheric pollutants, which have long been concerned and elucidated to be one of the risks of acute and chronic diseases for human, such as leukemia and cancer. Although numerous scientific studies have documented the potential adverse outcomes caused by VOC exposure, the mechanisms which biological response pathways of these VOC disruption remain poorly understood. Therefore, the identification of biochemical markers associated with metabolism, health effects and diseases orientation can be an effective means of screening biological targets for VOC exposure, which provide evidences to the toxicity assessment of compounds. The current review aims to understand the mechanisms underlying VOCs-elicited adverse outcomes by charactering various types of biomarkers. VOCs-related biomarkers from three aspects were summarized through in vitro, animal and epidemiological studies. i) Unmetabolized and metabolized VOC biomarkers in human samples for assessing exposure characteristics in different communities; ii) Adverse endpoint effects related biomarkers, mainly including (anti)oxidative stress, inflammation response and DNA damage; iii) Omics-based molecular biomarkers alteration in gene, protein, lipid and metabolite aspects associated with biological signaling pathway disorders response to VOC exposure. Further research, advanced machine learning and bioinformation approaches combined with experimental results are urgently needed to ascertain the selection of biomarkers and further illuminate toxic mechanisms of VOC exposure. Finally, VOCs-induced disease causes can be predicted with proven results.

Gene-environment interactions within a precision environmental health framework

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

Precision public health in the era of genomics and big data

Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

Longitudinal Mapping of Personal Biotic and Abiotic Exposomes and Transcriptome in Underwater Confined Space Using Wearable Passive Samplers

Silicone-based passive samplers, commonly paired with gas chromatography-mass spectrometry (GC-MS) analysis, are increasingly utilized for personal exposure assessments. However, its compatibility with the biotic exposome remains underexplored. In this study, we introduce the wearable silicone-based AirPie passive sampler, coupled with nontargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS), GC-HRMS, and metagenomic shotgun sequencing methods, offering a comprehensive view of personalized airborne biotic and abiotic exposomes. We applied the AirPie samplers to 19 participants in a unique deep underwater confined environment, annotating 4,390 chemical and 2,955 microbial exposures, integrated with corresponding transcriptomic data. We observed significant shifts in environmental exposure and gene expression upon entering this unique environment. We noted increased exposure to pollutants, such as benzenoids, polycyclic aromatic hydrocarbons (PAHs), opportunistic pathogens, and associated antibiotic-resistance genes (ARGs). Transcriptomic analyses revealed the activation of neurodegenerative disease-related pathways, mostly related to chemical exposure, and the repression of immune-related pathways, linked to both biological and chemical exposures. In summary, we provided a comprehensive, longitudinal exposome map of the unique environment and underscored the intricate linkages between external exposures and human health. We believe that the AirPie sampler and associated analytical methods will have broad applications in exposome and precision medicine.

Costs of molecular adaptation to the chemical exposome: a focus on xenobiotic metabolism pathways

Organisms adapt to their environment through different pathways. In vertebrates, xenobiotics are detected, metabolized and eliminated through the inducible xenobiotic-metabolizing pathways (XMP) which can also generate reactive toxic intermediates. In this review, we will discuss the impacts of the chemical exposome complexity on the balance between detoxication and side effects. There is a large discrepancy between the limited number of proteins involved in these pathways (few dozens) and the diversity and complexity of the chemical exposome (tens of thousands of chemicals). Several XMP proteins have a low specificity which allows them to bind and/or metabolize a large number of chemicals. This leads to undesired consequences, such as cross-inhibition, inefficient metabolism, release of toxic intermediates, etc. Furthermore, several XMP proteins have endogenous functions that may be disrupted upon exposure to exogenous chemicals. The gut microbiome produces a very large number of metabolites that enter the body and are part of the chemical exposome. It can metabolize xenobiotics and either eliminate them or lead to toxic derivatives. The complex interactions between chemicals of different origins will be illustrated by the diverse roles of the aryl hydrocarbon receptor which binds and transduces the signals of a large number of xenobiotics, microbiome metabolites, dietary chemicals and endogenous compounds. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

Per- and polyfluoroalkyl substances, polychlorinated biphenyls, organochlorine pesticides, and polybrominated diphenyl ethers and dysregulation of MicroRNA expression in humans and animals-A systematic review

BACKGROUND

Persistent organic pollutants (POPs) are chemicals characterized by their environmental persistence. Evidence suggests that exposure to POPs, which is ubiquitous, is associated with microRNA (miRNA) dysregulation. miRNA are key regulators in many physiological processes. It is thus of public health concern to understand the relationships between POPs and miRNA as related to health outcomes.

OBJECTIVES

This systematic review evaluated the relationship between widely recognized, intentionally manufactured, POPs, including per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides (dichlorodiphenyltrichloroethane [DDT], dichlorodiphenyldichloroethylene [DDE], hexachlorobenzene [HCB]), with miRNA expression in both human and animal studies.

METHODS

We used PubMed and Embase to systematically search the literature up to September 29th, 2023. Search results for human and animal studies were included if they incorporated at least one POP of interest in relation to at least one miRNA. Data were synthesized to determine the direction and significance of associations between POPs and miRNA. We utilized ingenuity pathway analysis to review disease pathways for miRNA that were associated with POPs.

RESULTS

Our search identified 38 eligible studies: 9 in humans and 29 in model organisms. PFAS were associated with decreased expression of miR-19, miR-193b, and miR-92b, as well as increased expression of miR-128, miR-199a-3p, and miR-26b across species. PCBs were associated with increased expression of miR-15a, miR-1537, miR-21, miR-22-3p, miR-223, miR-30b, and miR-34a, as well as decreased expression of miR-130a and let-7b in both humans and animals. Pathway analysis for POP-associated miRNA identified pathways related to carcinogenesis.

DISCUSSION

This is the first systematic review of the association of POPs with miRNA in humans and model organisms. Large-scale prospective human studies are warranted to examine the role of miRNA as mediators between POPs and health outcomes.

Autoinducer-2 promotes the colonization of Lactobacillus rhamnosus GG to improve the intestinal barrier function in a neonatal mouse model of antibiotic-induced intestinal dysbiosis

BACKGROUND

Human health is seriously threatened by antibiotic-induced intestinal disorders. Herein, we aimed to determine the effects of Autoinducer-2 (AI-2) combined with Lactobacillus rhamnosus GG (LGG) on the intestinal barrier function of antibiotic-induced intestinal dysbiosis neonatal mice.

METHODS

An antibiotic-induced intestinal dysbiosis neonatal mouse model was created using antibiotic cocktails, and the model mice were randomized into the control, AI-2, LGG, and LGG + AI-2 groups. Intestinal short-chain fatty acids and AI-2 concentrations were detected by mass spectrometry and chemiluminescence, respectively. The community composition of the gut microbiota was analyzed using 16S rDNA sequencing, and biofilm thickness and bacterial adhesion in the colon were assessed using scanning electron microscopy. Transcriptome RNA sequencing of intestinal tissues was performed, and the mRNA and protein levels of HCAR2 (hydroxycarboxylic acid receptor 2), claudin3, and claudin4 in intestinal tissues were determined using quantitative real-time reverse transcription PCR and western blotting. The levels of inflammatory factors in intestinal tissues were evaluated using enzyme-linked immunosorbent assays (ELISAs). D-ribose, an inhibitor of AI-2, was used to treat Caco-2 cells in vitro.

RESULTS

Compared with the control, AI-2, and LGG groups, the LGG + AI-2 group showed increased levels of intestinal AI-2 and proportions of Firmicutes and Lacticaseibacillus, but a reduced fraction of Proteobacteria. Specifically, the LGG + AI-2 group had considerably more biofilms and LGG on the colon surface than those of other three groups. Meanwhile, the combination of AI-2 and LGG markedly increased the concentration of butyric acid and promoted Hcar2, claudin3 and claudin4 expression levels compared with supplementation with LGG or AI-2 alone. The ELISAs revealed a significantly higher tumor necrosis factor alpha (TNF-α) level in the control group than in the LGG and LGG + AI-2 groups, whereas the interleukin 10 (IL-10) level was significantly higher in the LGG + AI-2 group than in the other three groups. In vitro, D-ribose treatment dramatically suppressed the increased levels of Hcar2, claudin3, and claudin4 in Caco-2 cells induced by AI-2 + LGG.

CONCLUSIONS

AI-2 promotes the colonization of LGG and biofilm formation to improve intestinal barrier function in an antibiotic-induced intestinal dysbiosis neonatal mouse model.

Role of intrinsic apoptosis in environmental exposure health outcomes

Environmental exposures are linked to diseases of high public health concern, including cancer, neurodegenerative disorders, and autoimmunity. These diseases are caused by excessive or insufficient cell death, prompting investigation of mechanistic links between environmental toxicants and dysregulation of cell death pathways, including apoptosis. This review describes how legacy and emerging environmental exposures target the intrinsic apoptosis pathway to potentially drive pathogenesis. Recent discoveries reveal that dynamic regulation of apoptosis may heighten the vulnerability of healthy tissues to exposures in children, and that apoptotic signaling can guide immune responses, tissue repair, and tumorigenesis. Understanding how environmental toxicants dysregulate apoptosis will uncover opportunities to deploy apoptosis-modulating agents for the treatment or prevention of exposure-linked diseases.

Enabling translational geroscience by broadening the scope of geriatric care

Geroscience poses that core biological mechanisms of aging contribute to chronic diseases and disabilities in late life and that health span and longevity can be modulated by pharmacological and behavioral interventions. Despite strong evidence from studies in model organisms and great potentials for translation, most geriatricians remain skeptical that geroscience will help them in the day-by-day battle with the consequences of aging in their patients. We believe that a closer collaboration between gerontologists and geriatricians is the key to overcome this impasse. There is evidence that trajectories of health with aging are rooted in intrinsic and extrinsic exposures that occur early in life and affect the pace of molecular and cellular damage accumulation with aging, also referred to as the "pace" of biological aging. Tools that measure the pace of aging currently allow for the identification of individuals experiencing accelerated aging and at higher risk of multimorbidity and disability. What we term "Translational Geroscience", i.e., the merger of fundamental and translational science with clinical practice, is thus poised to extend the action of geriatric care to a life course perspective. By targeting core mechanisms of aging, gerotherapeutics should be effective in treating patients with multimorbidity and disability, phenotypes that are all too common among geriatric patients nowadays. We call for initiatives that enhance the flow of ideas between gerontologists and geriatricians to facilitate the growth of translational geroscience. This approach can widen the scope of geriatric care, including a new role for geroscience in the promotion and operationalization of healthy longevity.

Direct Impact of the Air on Mutant Cells for Mutagenicity Assessments in Urban Environments

BACKGROUND

Urban air pollution is recognized as a critical problem for public health and is classified as a carcinogen for humans. A great number of studies have focused on the monitoring of urban air mutagenicity. One of the best-known and applied methods for assessing mutagenicity is the Ames test, a bacterial reverse mutation test. The classic protocol for assessing air mutagenicity involves the concentration of particulate matter (PM) on filters and subsequent extraction using organic solvents. This work aimed to develop a method for the evaluation of air mutagenicity directly impacted by air on microbial plates already containing an Ames' microbial sensor.

METHODS

A specific six-month sampling campaign was carried out in Turin in a period with high air pollution. Samples were tested for mutagenicity on Salmonella typhimurium strains TA98, TA100, and YG1024 with the traditional method and with the new direct method.

RESULTS

The new protocol is able to evaluate the mutagenicity of the sampled air and obtain repeatable results. The final sensitivity is similar to the traditional method (≈10 net revertants/m3); however, the mutagenic response is due to the complete air pollution mixture, including volatile and semivolatile pollutants avoiding the concentration of filters and the following laborious extraction procedures.

CONCLUSIONS

Despite some critical issues in contamination control, the method is easier, faster, and less expensive than traditional methods.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.