Advancing the application of omics-based biomarkers in environmental epidemiology

Analytical challenges and opportunities in the study of endocrine disrupting chemicals within an exposomics framework

Exposomics aims to measure human exposures throughout the lifespan and the changes they produce in the human body. Exposome-scale studies have significant potential to understand the interplay of environmental factors with complex multifactorial diseases widespread in our society and whose origin remain unclear. In this framework, the study of the chemical exposome aims to cover all chemical exposures and their effects in human health but, today, this goal still seems unfeasible or at least very challenging, which makes the exposome for now only a concept. Furthermore, the study of the chemical exposome faces several methodological challenges such as moving from specific targeted methodologies towards high-throughput multitargeted and non-targeted approaches, guaranteeing the availability and quality of biological samples to obtain quality analytical data, standardization of applied analytical methodologies, as well as the statistical assignment of increasingly complex datasets, or the identification of (un)known analytes. This review discusses the various steps involved in applying the exposome concept from an analytical perspective. It provides an overview of the wide variety of existing analytical methods and instruments, highlighting their complementarity to develop combined analytical strategies to advance towards the chemical exposome characterization. In addition, this review focuses on endocrine disrupting chemicals (EDCs) to show how studying even a minor part of the chemical exposome represents a great challenge. Analytical strategies applied in an exposomics context have shown great potential to elucidate the role of EDCs in health outcomes. However, translating innovative methods into etiological research and chemical risk assessment will require a multidisciplinary effort. Unlike other review articles focused on exposomics, this review offers a holistic view from the perspective of analytical chemistry and discuss the entire analytical workflow to finally obtain valuable results.

Metabolomics Profiles Alterations in Cigarette Smokers and Heated Tobacco Product Users

BACKGROUND

Heated tobacco products (HTPs) have gained global popularity, but their health risks remain unclear. Therefore, the current study aimed to identify plasma metabolites associated with smoking and HTP use in a large Japanese population to improve health risk assessment.

METHODS

Metabolomics data from 9,922 baseline participants of the Tsuruoka Metabolomics Cohort Study (TMCS) were analyzed to determine the association between smoking habits and plasma metabolites. Moreover, alterations in smoking-related metabolites among HTP users were examined based on data obtained from 3,334 participants involved from April 2018 to June 2019 in a follow-up survey.

RESULTS

Our study revealed that cigarette smokers had metabolomics profiles distinct from never smokers, with 22 polar metabolites identified as candidate biomarkers for smoking. These biomarker profiles of HTP users were closer to those of cigarette smokers than those of never smokers. The concentration of glutamate was higher in cigarette smokers, and biomarkers involved in glutamate metabolism were also associated with cigarette smoking and HTP use. Network pathway analysis showed that smoking was associated with the glutamate pathway, which could lead to endothelial dysfunction and atherosclerosis of the vessels.

CONCLUSION

Our study showed that the glutamate pathway is affected by habitual smoking. These changes in the glutamate pathway may partly explain the mechanism by which cigarette smoking causes cardiovascular disease. HTP use was also associated with glutamate metabolism, indicating that HTP use may contribute to the development of cardiovascular disease through mechanisms similar to those in cigarette use.

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.

Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS)

The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study uses an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants, and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability and functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.

Association of serum metal levels with type 2 diabetes: A prospective cohort and mediating effects of metabolites analysis in Chinese population

Several studies have suggested an association between exposure to various metals and the onset of type 2 diabetes (T2D). However, the results vary across different studies. We aimed to investigate the associations between serum metal concentrations and the risk of developing T2D among 8734 participants using a prospective cohort study design. We utilized inductively coupled plasmamass spectrometry (ICP-MS) to assess the serum concentrations of 27 metals. Cox regression was applied to calculate the hazard ratios (HRs) for the associations between serum metal concentrations on the risk of developing T2D. Additionally, 196 incident T2D cases and 208 healthy control participants were randomly selected for serum metabolite measurement using an untargeted metabolomics approach to evaluate the mediating role of serum metabolite in the relationship between serum metal concentrations and the risk of developing T2D with a nested casecontrol study design. In the cohort study, after Bonferroni correction, the serum concentrations of zinc (Zn), mercury (Hg), and thallium (Tl) were positively associated with the risk of developing T2D, whereas the serum concentrations of manganese (Mn), molybdenum (Mo), barium (Ba), lutetium (Lu), and lead (Pb) were negatively associated with the risk of developing T2D. After adding these eight metals, the predictive ability increased significantly compared with that of the traditional clinical model (AUC: 0.791 vs. 0.772, P=8.85×10-5). In the nested casecontrol study, a machine learning analysis revealed that the serum concentrations of 14 out of 1579 detected metabolites were associated with the risk of developing T2D. According to generalized linear regression models, 7 of these metabolites were significantly associated with the serum concentrations of the identified metals. The mediation analysis showed that two metabolites (2-methyl-1,2-dihydrophthalazin-1-one and mestranol) mediated 46.81% and 58.70%, respectively, of the association between the serum Pb concentration and the risk of developing T2D. Our study suggested that serum Mn, Zn, Mo, Ba, Lu, Hg, Tl, and Pb were associated with T2D risk. Two metabolites mediated the associations between the serum Pb concentration and the risk of developing T2D.

Metabolomics perspectives into the co-exposure effect of polycyclic aromatic hydrocarbons and metals on renal function: A meet-in-the-middle approach

Studies on the dose effects of kidney impairment and metabolomes in co-exposure to polycyclic aromatic hydrocarbons (PAHs) and metals are limited. We aimed to identify overall associations and metabolic perturbations in 130 participants (53 petrochemical workers and 77 controls) exposed to a PAHs-metals mixture in Southern China. The urinary 7 hydroxylated PAHs and 15 metal(loid)s were determined, and serum creatinine, beta-2 microglobulin, and estimated glomerular filtration rate were health outcomes. The liquid chromatography-mass spectrometry-based method was applied to serum metabolomics. Generalized weighted quantile sum (gWQS) regressions were used to estimate the overall dose-response relationships, and pathway analysis, "meet-in-the-middle" approach, and mediation effect analyses were conducted to identify potential metabolites and biological mechanisms linking exposure with nephrotoxic effects. Our results indicated that renal function reduction was associated with a PAHs-metals mixture in a dose-dependent manner, and 1-hydroxynaphthalene and copper were the most predominant contributors among the two families of pollutants. Furthermore, the metabolic disruptions associated with the early onset of kidney impairment induced by the combination of PAHs and metals encompassed pathways such as phenylalanine-tyrosine-tryptophan biosynthesis, phenylalanine metabolism, and alpha-linolenic acid metabolism. In addition, the specifically identified metabolites demonstrated excellent potential as bridging biomarkers connecting the reduction in renal function with the mixture of PAHs and metals. These findings shed light on understanding the overall associations and metabolic mechanism of nephrotoxic effects of co-exposure to PAHs and metals.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease

INTRODUCTION

Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association.

METHODS

We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs.

RESULTS

PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation.

DISCUSSION

Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD.

HIGHLIGHTS

First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

A population-based urinary and plasma metabolomics study of environmental exposure to cadmium

BACKGROUND

The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies.

METHOD

We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure.

RESULT

Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle).

CONCLUSION

These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Mediating role of host metabolites in strontium's effect on osteoporosis among older individuals: Findings from Wuhan, China

Strontium is receiving widespread attention due to its remarkable biological qualities in preventing bone resorption and fostering osteogenesis. However, the chemical processes behind strontium's dual activities on bone cells are not yet fully understood. This study used the metabolomic technique to identify and examine potential biomarkers between strontium exposure and osteoporosis (OP) risk. A total of 806 participants were recruited for the detection of plasma strontium content via inductively coupled plasma-mass spectrometry. Plasma metabolites were profiled in 254 participants through an untargeted metabolomics technique. Generalized linear models were primarily used to analyze associations among plasma strontium, metabolites, and OP. The mediating effects of metabolites on the strontium-OP association were further investigated. A total of 31 differential metabolites were observed, 10 of which were upregulated and 21 were downregulated in the OP group compared with the non-OP group. Five metabolites (3-phenoxybenzoic acid, Cer (t18:0/16:1), HexCer(t16:1/12:1(2OH)), HexCer(t14:2/18:1(2OH)), and TG(16:0-18:1-24:4)) were selected as potential mediators based on their significant association with OP risk and with femoral neck and lumbar spine bone mineral density (BMD). Moreover, all except TG(16:0-18:1-24:4) were involved in the OP discrimination model with excellent power combined with several traditional variables. 3-Phenoxybenzoic acid and Cer(t18:0/16:1) had significant indirect effects on the strontium-OP association. The five candidate metabolites mediated 83.79 % of the strontium-OP association. Plasma strontium level was associated with reduced OP risk in the Han population in Wuhan. Thus, plasma metabolite profiling revealed five BMD/OP-associated metabolites that acted as mediators in the strontium-OP association. Our findings provided evidence of the mediating role of host plasma metabolites in strontium's effect on OP pathology.

Differential DNA Methylation in the Brain as Potential Mediator of the Association between Traffic-related PM2.5 and Neuropathology Markers of Alzheimer's Disease

INTRODUCTION

Growing evidence indicates fine particulate matter (PM2.5) as risk factor for Alzheimer's' disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as potential mediator of this association.

METHODS

We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3 and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs.

RESULTS

PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-six CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation.

DISCUSSION

Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD.

A review of statistical strategies to integrate biomarkers of chemical exposure with biomarkers of effect applied in omic-scale environmental epidemiology

Humans are exposed to a growing list of synthetic chemicals, some of them becoming a major public health concern due to their capacity to impact multiple biological endpoints and contribute to a range of chronic diseases. The integration of endogenous (omic) biomarkers of effect in environmental health studies has been growing during the last decade, aiming to gain insight on the potential mechanisms linking the exposures and the clinical conditions. The emergence of high-throughput omic platforms has raised a list of statistical challenges posed by the large dimension and complexity of data generated. Thus, the aim of the present study was to critically review the current state-of-the-science about statistical approaches used to integrate endogenous biomarkers in environmental-health studies linking chemical exposures with health outcomes. The present review specifically focused on internal exposure to environmental chemical pollutants, involving both persistent organic pollutants (POPs), non-persistent pollutants like phthalates or bisphenols, and metals. We identified 42 eligible articles published since 2016, reporting 48 different statistical workflows, mostly focused on POPs and using metabolomic profiling in the intermediate layer. The outcomes were mainly binary and focused on metabolic disorders. A large diversity of statistical strategies were reported to integrate chemical mixtures and endogenous biomarkers to characterize their associations with health conditions. Multivariate regression models were the most predominant statistical method reported in the published workflows, however some studies applied latent based methods or multipollutant models to overcome the specific constraints of omic or exposure of data. A minority of studies used formal mediation analysis to characterize the indirect effects mediated by the endogenous biomarkers. The principles of each specific statistical method and overall workflow set-up are summarized in the light of highlighting their applicability, strengths and weaknesses or interpretability to gain insight into the causal structures underlying the triad: exposure, effect-biomarker and outcome.

Implementation of effect biomarkers in human biomonitoring studies: A systematic approach synergizing toxicological and epidemiological knowledge

Human biomonitoring (HBM) studies have highlighted widespread daily exposure to environmental chemicals. Some of these are suspected to contribute to adverse health outcomes such as reproductive, neurological, and metabolic disorders, among other developmental and chronic impairments. One of the objectives of the H2020 European Human Biomonitoring Initiative (HBM4EU) was the development of informative effect biomarkers for application in a more systematic and harmonized way in large-scale European HBM studies. The inclusion of effect biomarkers would complement exposure data with mechanistically-based information on early and late adverse effects. For this purpose, a stepwise strategy was developed to identify and implement a panel of validated effect biomarkers in European HBM studies. This work offers an overview of the complete procedure followed, from comprehensive literature search strategies, selection of criteria for effect biomarkers and their classification and prioritization, based on toxicological data and adverse outcomes, to pilot studies for their analytical, physiological, and epidemiological validation. We present the example of one study that demonstrated the mediating role of the effect biomarker status of brain-derived neurotrophic factor BDNF in the longitudinal association between infant bisphenol A (BPA) exposure and behavioral function in adolescence. A panel of effect biomarkers has been implemented in the HBM4EU Aligned Studies as main outcomes, including traditional oxidative stress, reproductive, and thyroid hormone biomarkers. Novel biomarkers of effect, such as DNA methylation status of BDNF and kisspeptin (KISS) genes were also evaluated as molecular markers of neurological and reproductive health, respectively. A panel of effect biomarkers has also been applied in HBM4EU occupational studies, such as micronucleus analysis in lymphocytes and reticulocytes, whole blood comet assay, and malondialdehyde, 8-oxo-2'-deoxyguanosine and untargeted metabolomic profile in urine, to investigate, for example, biological changes in response to hexavalent chromium Cr(VI) exposure. The use of effect biomarkers in HBM4EU has demonstrated their ability to detect early biological effects of chemical exposure and to identify subgroups that are at higher risk. The roadmap developed in HBM4EU confirms the utility of effect biomarkers, and support one of the main objectives of HBM research, which is to link exposure biomarkers to mechanistically validated effect and susceptibility biomarkers in order to better understand the public health implications of human exposure to environmental chemicals.

Heavy metals and inflammatory, oxidative/antioxidant and DNA damage biomarkers among people living with HIV/AIDS (PLWHA) in Niger Delta, Nigeria

This study evaluated the association of heavy metals (HMs) and effect biomarkers (inflammation, oxidative stress/antioxidant capacity and DNA damage) among people living with HIV/AIDS (PHWHA) in Niger Delta area, Nigeria. Blood levels of lead (BPb), cadmium (BCd), copper (BCu), zinc (BZn), iron (BFe), C-reactive protein (CRP), Interleukin-6 (IL-6), Tumor necrosis factor-α (TNF-α), Interferon-γ (IFN-γ), Malondialdehyde (MDA), Glutathione (GSH) and 8-hydroxy-2-deoxyguanosine (8-OHdG) were determined in a total of 185 participants, 104 HIV-positive and 81 HIV-negative sampled in both Niger Delta and non-Niger Delta regions. BCd (p < 0.001) and BPb (p = 0.139) were higher in HIV-positive subjects compared to HIV-negative controls; on the contrary, BCu, BZn and BFe levels were lower (p < 0.001) in HIV-positive subjects compared to HIV-negative controls. The Niger Delta population had higher levels of heavy metals (p < 0.01) compared to non-Niger Delta residents. CRP and 8-OHdG were higher (p < 0.001) in HIV-positive than in HIV-negative subjects and in Niger-Delta than in non-Niger Delta residents. BCu had significant positive dose-response relationship with CRP (61.9%, p = 0.063) and GSH (1.64%, p = 0.035) levels in HIV-positive subjects, and negative response with MDA levels (26.6%, p < 0.001). Periodic assessment of HMs levels among PLWHA is recommended.

Multi-omics responses in tree swallow (Tachycineta bicolor) nestlings from the Maumee Area of Concern, Maumee River, Ohio

A multi-omics approach was utilized to identify altered biological responses and functions, and to prioritize contaminants to assess the risks of chemical mixtures in the Maumee Area of Concern (AOC), Maumee River, OH, USA. The Maumee AOC is designated by the United States Environmental Protection Agency as having significant beneficial use impairments, including degradation of fish and wildlife populations, bird or animal deformities or reproduction problems, and loss of fish and wildlife habitat. Tree swallow (Tachycineta bicolor) nestlings were collected at five sites along the Maumee River, which included wastewater treatment plants (WWTPs) and industrial land-use sites. Polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), polychlorinated dibenzo p dioxins and furans (PCDD/Fs), and chlorinated pesticide concentrations were elevated in Maumee tree swallows, relative to a remote reference site, Star Lake, WI, USA. Liver tissue was utilized for non-targeted transcriptome and targeted metabolome evaluation. A significantly differentially expressed gene cluster related to a downregulation in cell growth and cell cycle regulation was identified when comparing all Maumee River sites with the reference site. There was an upregulation of lipogenesis genes, such as PPAR signaling (HMGCS2, SLC22A5), biosynthesis of unsaturated fatty acids (FASN, SCD, ELOVL2, and FADS2), and higher lipogenesis related metabolites, such as docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and arachidonic acid (AA) at two industrial land-use sites, Ironhead and Maumee, relative to WWTP sites (Perrysburg and SideCut), and the reference site. Toledo Water, in the vicinity of the other two industrial sites and also adjacent to a WWTP, showed a mix of signals between industrial land-use and WWTP land-use. PAHs, oxychlordane, and PBDEs were determined to be the most likely causes of the differentiation in biological responses, including de novo lipogenesis and biosynthesis of unsaturated fatty acids.

Associations of PFAS-related plasma metabolites with cholesterol and triglyceride concentrations

The wide-spread environmental pollutants per- and polyfluoroalkyl substances (PFAS) have repeatedly been associated with elevated serum cholesterol in humans. However, underlying mechanisms are still unclear. Furthermore, we have previously observed inverse associations with plasma triglycerides. To better understand PFAS-induced effects on lipid pathways we investigated associations of PFAS-related metabolite features with plasma cholesterol and triglyceride concentrations. We used 290 PFAS-related metabolite features that we previously discovered from untargeted liquid chromatography-mass spectometry metabolomics in a case-control study within the Swedish Västerbotten Intervention Programme cohort. Herein, we studied associations of these PFAS-related metabolite features with plasma cholesterol and triglyceride concentrations in plasma samples from 187 healthy control subjects collected on two occasions between 1991 and 2013. The PFAS-related features did not associate with cholesterol, but 50 features were associated with triglycerides. Principal component analysis on these features indicated that one metabolite pattern, dominated by glycerophospholipids, correlated with longer chain PFAS and associated inversely with triglycerides (both cross-sectionally and prospectively), after adjustment for confounders. The observed time-trend of the metabolite pattern resembled that of the longer chain PFAS, with higher levels during the years 2004-2010. Mechanisms linking PFAS exposures to triglycerides may thus occur via longer chain PFAS affecting glycerophospholipid metabolism. If the results reflect a cause-effect association, as implied by the time-trend and prospective analyses, this may affect the general adult population.

Inter-method reliability of silicone exposome wristbands and urinary biomarker assays in a pregnancy cohort

Silicone wristbands act as passive environmental samplers capable of detecting and measuring concentrations of a variety of chemicals. They offer a noninvasive method to collect complex exposure data in large-scale epidemiological studies. We evaluated the inter-method reliability of silicone wristbands and urinary biomarkers in the New Hampshire Birth Cohort Study. A subset of study participants (n = 96) provided a urine sample and wore a silicone wristband for 7 days at approximately 12 gestational weeks. Women were instructed to wear the wristbands during all their normal activities. Concentrations of urinary compounds and metabolites in the urine and parent compounds in wristbands were compared. High detection rates were observed for triphenyl phosphate (76.0%) and benzophenone (78.1%) in wristbands, although the distribution of corresponding urinary concentrations of chemicals did not differ according to whether chemicals were detected or not detected in wristbands. While detected among only 8.3% of wristbands, median urinary triclosan concentrations were higher among those with triclosan detected in wristbands (9.04 ng/mL) than without (0.16 ng/mL). For most chemicals slight to fair agreement was observed across exposure assessment methods, potentially due to low rates of detection in the wristbands for chemicals where observed urinary concentrations were relatively low as compared to background concentrations in the general population. Our findings support the growing body of research in support of deploying silicone wristbands as an important exposure assessment tool.

Metabolic linkages between zinc exposure and lung cancer risk: A nested case-control study

Epidemiologic studies have suggested that elevated concentrations of zinc are associated with a decreased risk of lung cancer, but the underlying mechanisms remain to be investigated. The metabolites are highly sensitive to environmental stress, which will help to reveal the linkages between zinc exposure and lung cancer risk. We designed a nested case-control study including 101 incident lung cancer cases and 1:2 age- and sex-frequency-matched 202 healthy controls from the Dongfeng-Tongji (DFTJ) cohort. Their plasma level of zinc was determined by using inductively coupled plasma-mass spectrometry (ICP-MS) and plasma profiles of metabolites were detected by using an untargeted metabolomics approach. The generalized linear models (GLM) were applied to assess the associations of plasma zinc with metabolites, and the mediation effects of zinc-related metabolites on zinc-lung cancer association were further testified. The concentrations of 55 metabolites had linear dose-response relationships with plasma zinc at a false discovery rate (FDR) < 0.05, among which L-proline, phosphatidylcholine (PC, 34:2), phosphatidylethanolamine (PE, O-36:5), L-altrose, and sphingomyelin (SM, 40:3) showed different levels between lung cancer cases and healthy controls (fold change = 0.92, 0.95, 1.07, 0.90, and 1.08, respectively, and all P < 0.05). The plasma concentration of SM(40:3) was negatively associated with incident risk of lung cancer [OR(95%CI) = 0.71(0.55, 0.91), P = 0.007] and could mediate 41.7% of the association between zinc and lung cancer risk (P = 0.004). Moreover, compared to the traditional factors, addition of SM(40:3) exerted improved prediction performance for incident risk of lung cancer [AUC(95%CIs) = 0.714(0.654, 0.775) vs. 0.663(0.600, 0.727), P = 0.030]. Our findings revealed metabolic profiles with zinc exposure and provide new insight into the alternations of metabolites underpinning the links between zinc exposure and lung cancer development.

Harmonization of transcriptomic and methylomic analysis in environmental epidemiology studies for potential application in chemical risk assessment

Recent efforts have posited the utility of transcriptomic-based approaches to understand chemical-related perturbations in the context of human health risk assessment. Epigenetic modification (e.g., DNA methylation) can influence gene expression changes and is known to occur as a molecular response to some chemical exposures. Characterization of these methylation events is critical to understand the molecular consequences of chemical exposures. In this context, a novel workflow was developed to interrogate publicly available epidemiological transcriptomic and methylomic data to identify relevant pathway level changes in response to chemical exposure, using inorganic arsenic as a case study. Gene Set Enrichment Analysis (GSEA) was used to identify causal methylation events that result in concomitant downstream transcriptional deregulation. This analysis demonstrated an unequal distribution of differentially methylated regions across the human genome. After mapping these events to known genes, significant enrichment of a subset of these pathways suggested that arsenic-mediated methylation may be both specific and non-specific. Parallel GSEA performed on matched transcriptomic samples determined that a substantially reduced subset of these pathways are enriched and that not all chemically-induced methylation results in a downstream alteration in gene expression. The resulting pathways were found to be representative of well-established molecular events known to occur in response to arsenic exposure. The harmonization of enriched transcriptional patterns with those identified from the methylomic platform promoted the characterization of plausibly causal molecular signaling events. The workflow described here enables significant gene and methylation-specific pathways to be identified from whole blood samples of individuals exposed to environmentally relevant chemical levels. As future efforts solidify specific causal relationships between these molecular events and relevant apical endpoints, this novel workflow could aid risk assessments by identifying molecular targets serving as biomarkers of hazard, informing mechanistic understanding, and characterizing dose ranges that promote relevant molecular/epigenetic signaling events occuring in response to chemical exposures.

Biomarkers for the adverse effects on respiratory system health associated with atmospheric particulate matter exposure

Large amounts of epidemiological evidence have confirmed the atmospheric particulate matter (PM_2.5) exposure was positively correlated with the morbidity and mortality of respiratory diseases. Nevertheless, its pathogenesis remains incompletely understood, probably resulting from the activation of oxidative stress, inflammation, altered genetic and epigenetic modifications in the lung upon PM_2.5 exposure. Currently, biomarker investigations have been widely used in epidemiological and toxicological studies, which may help in understanding the biologic mechanisms underlying PM_2.5-elicited adverse health outcomes. Here, the emerging biomarkers to indicate PM_2.5-respiratory system interactions were summarized, primarily related to oxidative stress (ROS, MDA, GSH, etc.), inflammation (Interleukins, FE_NO, CC16, etc.), DNA damage (8-OHdG, γH2AX, OGG1) and also epigenetic modulation (DNA methylation, histone modification, microRNAs). The identified biomarkers shed light on PM_2.5-elicited inflammation, fibrogenesis and carcinogenesis, thus may favor more precise interventions in public health. It is worth noting that some inconsistent findings may possibly relate to the inter-study differentials in the airborne PM_2.5 sample, exposure mode and targeted subjects, as well as methodological issues. Further research, particularly by -omics technique to identify novel, specific biomarkers, is warranted to illuminate the causal relationship between PM_2.5 pollution and deleterious lung outcomes.

The preliminary investigation of potential response biomarkers to PAHs exposure on childhood asthma

BACKGROUND

Exposure to polycyclic aromatic hydrocarbons (PAHs) is a potential risk factor for asthma prevalence. This study aims to explore whether PAHs exposure is associated with childhood asthma by altering microbial diversity and metabolic profiles.

METHODS

Thirty children with asthma and 30 children as control in Nanjing, China were recruited. Urinary 1-hydroxypyrene (1-OHPyr) level was determined by UPLC-Orbitrap-MS as a PAHs exposure biomarker. Logistic regression was conducted to investigate the association between 1-OHPyr and childhood asthma. Microbial diversity was analyzed by 16S rRNA gene sequencing. Metabolic profiles were obtained by UPLC-Orbitrap-MS methods. Differential microbiota and metabolites were screened and selected as response biomarkers or intermediates. Mediation analysis was conducted to assess the association between PAHs and asthma mediated by intermediates.

RESULTS

Participating children with and without asthma aged 6.43 ± 2.23 years. The urinary 1-OHPyr level ranged from 0.10 to 1.51 μmol/mol (creatinine corrected) in the participants. The urinary 1-OHPyr level was associated with childhood asthma (OR = 7.21, 95% CI: 1.03-50.42 per 1 μmol/mol unit). Microbial diversity was decreased in the group with asthma and there was a significant shift in the abundance of Proteobacteria (at the phylum level), Veillonella and Prevotella (at the genus level). The enrichment pathway analysis showed that differentially expressed metabolites were involved in purine metabolism, amino acid metabolism, and lipid and fatty acid metabolism. The urinary 1-OHPyr level was associated with the abundance of Actinomyces sp. oral clone IO076 and 7-methylguanine that showed a mediation effect on the association between urinary 1-OHPyr levels and childhood asthma by mediation analysis.

CONCLUSIONS

Urinary 1-OHPyr exposure was associated with childhood asthma, microbial diversity, and metabolic profiles. Microbial diversity and metabolic profiles may be intermediates as response biomarkers to PAHs exposure in childhood asthma. Further research is needed to confirm these study results and determine the underlying mechanism.

Exposure study on susceptible people - SPES: An integrative biomonitoring approach

BACKGROUND

The evaluation of environmental exposure risk requires a global analysis of pollution phenomena, including biological effects and potentially correlated clinical outcomes in susceptible populations. Although human biomonitoring plays a fundamental role in assessing the degree of contamination, it is not effective alone in identifying a direct link between exposure, biomolecular effects and outcomes on target organisms. While toxicogenomics and epidemiology are mainly focused on the investigation of molecular reactions and clinical outcomes, the monitoring of environmental matrices works independently to characterize the territorial distribution of toxic compounds, without proving any correlated health risk for residents.

OBJECTIVES

We propose a new biomonitoring model based on a whole systemic analytical evaluation of environmental context. The paradigm of the method consists of identifying the sources of pollution, the migration pathways of those pollutants and their effects on target organisms. By means of this innovative, holistic epidemiological approach, we included healthy human subjects in a cohort to identify potential risks of exposure and predict possible correlated clinical outcomes. 4205 residents of the Campania region were enrolled in the "SPES" biomonitoring study, which especially focused on the areas dubbed "Land of Fires" in the recent decades.

DISCUSSION

The analysis of environmental exposure risk suffers the lack of data integration from various science fields, and this comes down to a limited point of view and a limited knowledge of phenomena. In implementing our model, we first constructed an analytical picture of the Real-world situation. We next conducted a comparative risk assessment, in order to identify possible correlations between pollution and health within a holistic view.

CONCLUSION

This type of research activities aims to support the implementation of public health interventions and to become a reference model in the evaluation of the risk of exposure to environmental pollutants.

Evaluating carbon content in airway macrophages as a biomarker of personal exposure to fine particulate matter and its acute respiratory effects

It remains unclear whether carbon content in airway macrophages (AM) can predict personal short-term exposure to fine particulate matter (PM_2.5) air pollution and its respiratory health effects. We aimed to evaluate the pathway from personal PM_2.5 exposure to adverse respiratory outcomes through AM carbon content. We designed a longitudinal panel study with 3 scheduled follow-ups among 113 non-smoking patients of chronic obstructive pulmonary disease in Shanghai, China, from April 2017 to January 2019. We quantified AM carbon content from induced sputum by image analysis, tested lung function and measured sputum levels of 4 pro-inflammatory cytokines and 2 anti-inflammatory cytokines. We applied the "meet in the middle" approach incorporating linear mixed-effect models to evaluate the associations from external PM_2.5 exposure to respiratory outcomes through AM carbon content. Our results indicated that personal exposure to PM_2.5 within 24 h was significantly associated with decreased forced expiratory volume in 1s and anti-inflammatory cytokines, as well as increased macrophages and pro-inflammatory cytokines. These changes were accompanied by increased areas of AM carbon and higher percentage of AM area occupied by carbon, both of which were associated with increased levels of pro-inflammatory cytokines and decreased levels of anti-inflammatory cytokines. Exposure to ambient black carbon and organic carbon in PM_2.5 within 2 days was significantly associated with increased AM carbon area and percentage of AM area occupied by carbon. Our findings reinforced the causality in respiratory health effects of PM_2.5 in which increased AM carbon content might serve as a valid exposure biomarker.

Lipidomics of children and adolescents exposed to multiple industrial pollutants

BACKGROUND

There are limited studies on the lipidomics of children and adolescents exposed to multiple industrial pollutants.

OBJECTIVES

In this study, we aimed to investigate lipid profile perturbations in 99 children and adolescents (aged 9-15) who lived in a polluted area surrounding the largest petrochemical complex in Taiwan. Previous studies have reported increased risks of acute and chronic diseases including liver dysfunctions and chronic kidney disease (CKD) in residents living in this area.

METHODS

We measured urinary concentrations of 11 metals and metalloids and polycyclic aromatic hydrocarbons (PAHs) metabolite 1-hydroxypyrene (1-OHP) as exposure biomarkers, and urinary oxidative stress biomarkers and serum acylcarnitines as early health effect biomarkers. The association between individual exposure biomarkers and early health effect biomarkers were analyzed using linear regression, while association of combined exposure biomarkers with four oxidative stress biomarkers and acylcarnitines were analyzed using weighted quantile sum (WQS) regression. Lipid profiles were analyzed using an untargeted liquid chromatography mass spectrometry-based technique. "Meet-in-the-middle" approach was applied to identify potential lipid features that linked multiple industrial pollutants exposure with early health effects.

RESULTS

We identified 15 potential lipid features that linked elevated multiple industrial pollutants exposure with three increased oxidative stress biomarkers and eight deregulated serum acylcarnitines, including one lysophosphatidylcholines (LPCs), four phosphatidylcholines (PCs), and two sphingomyelins (SMs) that were up-regulated in high exposure group compared to low exposure group, and two LPCs, four PCs, and two phosphatidylinositols (PIs) down-regulated in high exposure group compared to low exposure group.

CONCLUSION

Our findings could provide information for understanding the health effects, including early indicators and biological mechanism identification, of children and adolescents exposed to multiple industrial pollutants during critical stages of development.

Performance of approaches relying on multidimensional intermediary data to decipher causal relationships between the exposome and health: A simulation study under various causal structures

Challenges in the assessment of the health effects of the exposome, defined as encompassing all environmental exposures from the prenatal period onwards, include a possibly high rate of false positive signals. It might be overcome using data dimension reduction techniques. Data from the biological layers lying between the exposome and its possible health consequences, such as the methylome, may help reducing exposome dimension. We aimed to quantify the performances of approaches relying on the incorporation of an intermediary biological layer to relate the exposome and health, and compare them with agnostic approaches ignoring the intermediary layer. We performed a Monte-Carlo simulation, in which we generated realistic exposome and intermediary layer data by sampling with replacement real data from the Helix exposome project. We generated a Gaussian outcome assuming linear relationships between the three data layers, in 2381 scenarios under five different causal structures, including mediation and reverse causality. We tested 3 agnostic methods considering only the exposome and the health outcome: ExWAS (for Exposome-Wide Association study), DSA, LASSO; and 3 methods relying on an intermediary layer: two implementations of our new oriented Meet-in-the-Middle (oMITM) design, using ExWAS and DSA, and a mediation analysis using ExWAS. Methods' performances were assessed through their sensitivity and FDP (False-Discovery Proportion). The oMITM-based methods generally had lower FDP than the other approaches, possibly at a cost in terms of sensitivity; FDP was in particular lower under a structure of reverse causality and in some mediation scenarios. The oMITM-DSA implementation showed better performances than oMITM-ExWAS, especially in terms of FDP. Among the agnostic approaches, DSA showed the highest performance. Integrating information from intermediary biological layers can help lowering FDP in studies of the exposome health effects; in particular, oMITM seems less sensitive to reverse causality than agnostic exposome-health association studies.

Analytical aspects of meet-in-metabolite analysis for molecular pathway reconstitution from exposure to adverse outcome

To explore the etiology of diseases is one of the major goals in epidemiological study. Meet-in-metabolite analysis reconstitutes biomonitoring-based adverse outcome (AO) pathways from environmental exposure to a disease, in which the chemical exposome-related metabolism responses are transmitted to incur the AO-related metabolism phenotypes. However, the ongoing data-dependent acquisition of non-targeted biomonitoring by high-resolution mass spectrometry (HRMS) is biased against the low abundance molecules, which forms the major of molecular internal exposome, i.e., the totality of trace levels of environmental pollutants and/or their metabolites in human samples. The recent development of data-independent acquisition protocols for HRMS screening has opened new opportunities to enhance unbiased measurement of the extremely low abundance molecules, which can encompass a wide range of analytes and has been applied in metabolomics, DNA, and protein adductomics. In addition, computational MS for small molecules is urgently required for the top-down exposome databases. Although a holistic analysis of the exposome and endogenous metabolites is plausible, multiple and flexible strategies, instead of "putting one thing above all" are proposed.

A Systematic Framework for Collecting Site-Specific Sampling and Survey Data to Support Analyses of Health Impacts from Land-Based Pollution in Low- and Middle-Income Countries

The rise of small-scale and localized economic activities in low- and middle-income countries (LMICs) has led to increased exposures to contaminants associated with these processes and the potential for resulting adverse health effects in exposed communities. Risk assessment is the process of building models to predict the probability of adverse outcomes based on concentration-response functions and exposure scenarios for individual contaminants, while epidemiology uses statistical methods to explore associations between potential exposures and observed health outcomes. Neither approach by itself is practical or sufficient for evaluating the magnitude of exposures and health impacts associated with land-based pollution in LMICs. Here we propose a more pragmatic framework for designing representative studies, including uniform sampling guidelines and household surveys, that draws from both methodologies to better support community health impact analyses associated with land-based pollution sources in LMICs. Our primary goal is to explicitly link environmental contamination from land-based pollution associated with specific localized economic activities to community exposures and health outcomes at the household level. The proposed framework was applied to the following three types of industries that are now widespread in many LMICs: artisanal scale gold mining (ASGM), used lead-acid battery recycling (ULAB), and small tanning facilities. For each activity, we develop a generalized conceptual site model (CSM) that describes qualitative linkages from chemical releases or discharges, environmental fate and transport mechanisms, exposure pathways and routes, populations at risk, and health outcomes. This upfront information, which is often overlooked, is essential for delineating the contaminant zone of influence in a community and identifying relevant households for study. We also recommend cost-effective methods for use in LMICs related to environmental sampling, biological monitoring, survey questionnaires, and health outcome measurements at contaminated and unexposed reference sites. Future study designs based on this framework will facilitate consistent, comparable, and standardized community exposure, risk, and health impact assessments for land-based pollution in LMICs. The results of these studies can also support economic burden analyses and risk management decision-making around site cleanup, risk mitigation, and public health education.

Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer

Metabolomics deals with multiple and complex chemical reactions within living organisms and how these are influenced by external or internal perturbations. It lies at the heart of omics profiling technologies not only as the underlying biochemical layer that reflects information expressed by the genome, the transcriptome and the proteome, but also as the closest layer to the phenome. The combination of metabolomics data with the information available from genomics, transcriptomics, and proteomics offers unprecedented possibilities to enhance current understanding of biological functions, elucidate their underlying mechanisms and uncover hidden associations between omics variables. As a result, a vast array of computational tools have been developed to assist with integrative analysis of metabolomics data with different omics. Here, we review and propose five criteria-hypothesis, data types, strategies, study design and study focus- to classify statistical multi-omics data integration approaches into state-of-the-art classes under which all existing statistical methods fall. The purpose of this review is to look at various aspects that lead the choice of the statistical integrative analysis pipeline in terms of the different classes. We will draw particular attention to metabolomics and genomics data to assist those new to this field in the choice of the integrative analysis pipeline.

Epidemiological Research on Occupational and Environmental Carcinogens

The cancer risk associated with exposure to environmental and occupational carcinogens such as asbestos, benzene, radiation, or lifestyle carcinogens such as cigarette smoking depends on the entire history of exposure to the carcinogen, including the age of exposure and the time-varying intensity of exposure [...].

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

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

Biomarkers of metabolic disorders and neurobehavioral diseases in a PCB- exposed population: What we learned and the implications for future research

Polychlorinated biphenyls (PCBs) are one of the original twelve classes of toxic chemicals covered by the Stockholm Convention on Persistent Organic Pollutants (POP), an international environmental treaty signed in 2001. PCBs are present in the environment as mixtures of multiple isomers at different degree of chlorination. These compounds are manmade and possess useful industrial properties including extreme longevity under harsh conditions, heat absorbance, and the ability to form an oily liquid at room temperature that is useful for electrical utilities and in other industrial applications. They have been widely used for a wide range of industrial purposes over the decades. Despite a ban in production in 1979 in the US and many other countries, they remain persistent and ubiquitous in environment as contaminants due to their improper disposal. Humans, independent of where they live, are therefore exposed to PCBs, which are routinely found in random surveys of human and animal tissues. The prolonged exposures to PCBs have been associated with the development of different diseases and disorders, and they are classified as endocrine disruptors. Due to its ability to interact with thyroid hormone, metabolism and function, they are thought to be implicated in the global rise of obesity diabetes, and their potential toxicity for neurodevelopment and disorders, an example of gene by environmental interaction (GxE). The current review is primarily intended to summarize the evidence for the association of PCB exposures with increased risks for metabolic dysfunctions and neurobehavioral disorders. In particular, we present evidence of gene expression alterations in PCB-exposed populations to construct the underlying pathways that may lead to those diseases and disorders in course of life. We conclude the review with future perspectives on biomarker-based research to identify susceptible individuals and populations.

Using methylome data to inform exposome-health association studies: An application to the identification of environmental drivers of child body mass index

BACKGROUND

The exposome is defined as encompassing all environmental exposures one undergoes from conception onwards. Challenges of the application of this concept to environmental-health association studies include a possibly high false-positive rate.

OBJECTIVES

We aimed to reduce the dimension of the exposome using information from DNA methylation as a way to more efficiently characterize the relation between exposome and child body mass index (BMI).

METHODS

Among 1,173 mother-child pairs from HELIX cohort, 216 exposures ("whole exposome") were characterized. BMI and DNA methylation from immune cells of peripheral blood were assessed in children at age 6-10 years. A priori reduction of the methylome to preselect BMI-relevant CpGs was performed using biological pathways. We then implemented a tailored Meet-in-the-Middle approach to identify from these CpGs candidate mediators in the exposome-BMI association, using univariate linear regression models corrected for multiple testing: this allowed to point out exposures most likely to be associated with BMI ("reduced exposome"). Associations of this reduced exposome with BMI were finally tested. The approach was compared to an agnostic exposome-wide association study (ExWAS) ignoring the methylome.

RESULTS

Among the 2284 preselected CpGs (0.6% of the assessed CpGs), 62 were associated with BMI. Four factors (3 postnatal and 1 prenatal) of the exposome were associated with at least one of these CpGs, among which postnatal blood level of copper and PFOS were directly associated with BMI, with respectively positive and negative estimated effects. The agnostic ExWAS identified 18 additional postnatal exposures, including many persistent pollutants, generally unexpectedly associated with decreased BMI.

DISCUSSION

Our approach incorporating a priori information identified fewer significant associations than an agnostic approach. We hypothesize that this smaller number corresponds to a higher specificity (and possibly lower sensitivity), compared to the agnostic approach. Indeed, the latter cannot distinguish causal relations from reverse causation, e.g. for persistent compounds stored in fat, whose circulating level is influenced by BMI.

Application of metabolomics to characterize environmental pollutant toxicity and disease risks

The increased incidence of non-communicable human diseases may be attributed, at least partially, to exposures to toxic chemicals such as persistent organic pollutants (POPs), air pollutants and heavy metals. Given the high mortality and morbidity of pollutant exposure associated diseases, a better understanding of the related mechanisms of toxicity and impacts on the endogenous host metabolism are needed. The metabolome represents the collection of the intermediates and end products of cellular processes, and is the most proximal reporter of the body's response to environmental exposures and pathological processes. Metabolomics is a powerful tool for studying how organisms interact with their environment and how these interactions shape diseases related to pollutant exposure. This mini review discusses potential biological mechanisms that link pollutant exposure to metabolic disturbances and chronic human diseases, with a focus on recent studies that demonstrate the application of metabolomics as a tool to elucidate biochemical modes of actions of various environmental pollutants. In addition, classes of metabolites that have been shown to be modulated by multiple environmental pollutants will be discussed with an emphasis on their use as potential early biomarkers of disease risks. Taken together, metabolomics is a useful and versatile tool for characterizing the disease risks and mechanisms associated with various environmental pollutants.

A strategy to validate a selection of human effect biomarkers using adverse outcome pathways: Proof of concept for phthalates and reproductive effects

Human biomonitoring measures the concentrations of environmental chemicals or their metabolites in body fluids or tissues. Complementing exposure biomarkers with mechanistically based effect biomarkers may further elucidate causal pathways between chemical exposure and adverse health outcomes. We combined information on effect biomarkers previously implemented in human observational studies with mechanisms of action reported in experimental studies and with information from published Adverse Outcome Pathways (AOPs), focusing on adverse reproductive effects of phthalate exposure. Phthalates constitute a group of chemicals that are ubiquitous in consumer products and have been related to a wide range of adverse health effects. As a result of a comprehensive literature search, we present an overview of effect biomarkers for reproductive toxicity that are substantiated by mechanistic information. The activation of several receptors, such as PPARα, PPARγ, and GR, may initiate events leading to impaired male and female fertility as well as other adverse effects of phthalate exposure. Therefore, these receptors appear as promising targets for the development of novel effect biomarkers. The proposed strategy connects the fields of epidemiology and toxicology and may strengthen the weight of evidence in observational studies that link chemical exposures to health outcomes.

Metabolomics of Children and Adolescents Exposed to Industrial Carcinogenic Pollutants

Studies on metabolomes of carcinogenic pollutants among children and adolescents are limited. We aim to identify metabolic perturbations in 107 children and adolescents (aged 9-15) exposed to multiple carcinogens in a polluted area surrounding the largest petrochemical complex in Taiwan. We measured urinary concentrations of eight carcinogen exposure biomarkers (heavy metals and polycyclic aromatic hydrocarbons (PAHs) represented by 1-hydroxypyrene), and urinary oxidative stress biomarkers and serum acylcarnitines as biomarkers of early health effects. Serum metabolomics was analyzed using a liquid chromatography mass spectrometry-based method. Pathway analysis and "meet-in-the-middle" approach were applied to identify potential metabolites and biological mechanisms linking carcinogens exposure with early health effects. We found 10 potential metabolites possibly linking increased exposure to IARC group 1 carcinogens (As, Cd, Cr, Ni) and group 2 carcinogens (V, Hg, PAHs) with elevated oxidative stress and deregulated serum acylcarnitines, including inosine monophosphate and adenosine monophosphate (purine metabolism), malic acid and oxoglutaric acid (citrate cycle), carnitine (fatty acid metabolism), and pyroglutamic acid (glutathione metabolism). Purine metabolism was identified as the possible mechanism affected by children and adolescents' exposure to carcinogens. These findings contribute to understanding the health effects of childhood and adolescence exposure to multiple industrial carcinogens during critical periods of development.

Transplacental exposure to carcinogens and risks to children: evidence from biomarker studies and the utility of omic profiling

The factors underlying the increasing rates and the geographic variation of childhood cancers are largely unknown. Epidemiological studies provide limited evidence for a possible role in the etiology of certain types of childhood cancer of the exposure of pregnant women to environmental carcinogens (e.g., tobacco smoke and pesticides); however, such evidence is inadequate to allow definitive conclusions. Complementary evidence can be obtained from biomarker-based population studies. Such studies have demonstrated that, following exposure of pregnant mothers, most environmental carcinogens reach the fetus and, in many cases, induce therein genotoxic damage which in adults is known to be associated with increased cancer risk, implying that environmental carcinogens may contribute to the etiology of childhood cancer. During recent years, intermediate disease biomarkers, obtained via omic profiling, have provided additional insights into the impact of transplacental exposures on fetal tissues which, in some cases, are also compatible with a precarcinogenic role of certain in utero exposures. Here we review the epidemiological and biomarker evidence and discuss how further research, especially utilizing high-density profiling, may allow a better evaluation of the links between in utero environmental exposures and cancer in children.

Determinants of the urinary and serum metabolome in children from six European populations

BACKGROUND

Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment-health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project ( http://www.projecthelix.eu ).

METHODS

Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6-11) recruited from birth cohorts in six European countries were measured using high-throughput ¹H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit).

RESULTS

We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythreonic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum.

CONCLUSIONS

We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children.

Perturbation of metabolic pathways mediates the association of air pollutants with asthma and cardiovascular diseases

BACKGROUND

Epidemiologic evidence indicates common risk factors, including air pollution exposure, for respiratory and cardiovascular diseases, suggesting the involvement of common altered molecular pathways.

OBJECTIVES

The goal was to find intermediate metabolites or metabolic pathways that could be associated with both air pollutants and health outcomes ("meeting-in-the-middle"), thus shedding light on mechanisms and reinforcing causality.

METHODS

We applied a statistical approach named 'meet-in-the-middle' to untargeted metabolomics in two independent case-control studies nested in cohorts on adult-onset asthma (AOA) and cardio-cerebrovascular diseases (CCVD). We compared the results to identify both common and disease-specific altered metabolic pathways.

RESULTS

A novel finding was a strong association of AOA with ultrafine particles (UFP; odds ratio 1.80 [1.26, 2.55] per increase by 5000 particles/cm3). Further, we have identified several metabolic pathways that potentially mediate the effect of air pollution on health outcomes. Among those, perturbation of Linoleate metabolism pathway was associated with air pollution exposure, AOA and CCVD.

CONCLUSIONS

Our results suggest common pathway perturbations may occur as a consequence of chronic exposure to air pollution leading to increased risk for both AOA and CCVD.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Applying an Exposome-Wide (ExWAS) Approach to Cancer Research

Traditional research approaches, including genome-wide association studies (GWAS), epigenome-wide association studies (EWAS) and Gene × Environment (G × E) studies are limited in their ability to handle the multiplicity of chemical and non-chemical toxicants to which people are exposed in the real world, over their life course, their impact on epigenomics and other biological systems, and their relationship to cancer onset, progression, and outcomes. Exposome-wide association study (ExWAS) provides a new approach for conceptualizing the roles and relationships of multiple chemical and non-chemical exposures in the etiology and progression of cancer at key developmental periods, over the life course, and across generations. ExWAS challenges us to consider the influence of both internal and external environment, chemical and non-chemical stressors, risk and protective factors, and spatial and temporal dimensions of exposures in our models of cancer incidence, outcomes, and disparities. Applying an ExWAS approach to cancer and cancer disparities research supports robust computational models and methods that will allow for analysis of the dynamic and complex interactions between genetics, epigenetics, and exposomics factors. In the coming months, we will spatially and temporally align environmental exposures with SCCS participant data from time of enrollment forward to move us closer to identifying complete exposure pathways that lead to cancer. In the future, we hope to link external sources of exposure to biomarkers of exposure, biomarkers of disease, disease phenotypes, and population level disparities.

Filling the gap between chemical carcinogenesis and the hallmarks of cancer: A temporal perspective

BACKGROUND

Cancer is believed to arise through the perturbation of pathways and the order of pathway perturbation events can enhance understanding and evaluation of carcinogenicity. This order has not been examined so far, and this study aimed to fill this gap by attempting to gather evidence on the potential temporal sequence of events in carcinogenesis.

DESIGN

The methodology followed was to discuss first the temporal sequence of hallmarks of cancer from the point of view of pathological specimens of cancer (essentially branched mutations) and then to consider the hallmarks of cancer that one well-known carcinogen, benzo(a)pyrene, can modify.

RESULTS

Even though the sequential order of driving genetic alterations can vary between and within tumours, the main cancer pathways affected are almost ubiquitous and follow a generally common sequence: resisting cell death, insensitivity to antigrowth signals, sustained proliferation, deregulated energetics, replicative immortality and activation of invasion and metastasis. The first 3 hallmarks can be regarded as almost simultaneous while angiogenesis and avoiding immune destruction are perhaps the only hallmarks with a varying position in the above sequence.

CONCLUSIONS

Our review of hallmarks of cancer and their temporal sequence, based on mutational spectra in biopsies from different cancer sites, allowed us to propose a hypothetical temporal sequence of the hallmarks. This sequence can add molecular support to the evaluation of an agent as a carcinogen as it can be used as a conceptual framework for organising and evaluating the strength of existing evidence.

Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC

Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites.Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk.Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%.Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk.Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators. Cancer Epidemiol Biomarkers Prev; 27(5); 531-40. ©2018 AACR.

Oxidative stress and inflammation mediate the effect of air pollution on cardio- and cerebrovascular disease: A prospective study in nonsmokers

Air pollution is associated with a broad range of adverse health effects, including mortality and morbidity due to cardio- and cerebrovascular diseases (CCVD), but the molecular mechanisms involved are not entirely understood. This study aims to investigate the involvement of oxidative stress and inflammation in the causal chain, and to identify intermediate biomarkers that are associated retrospectively with the exposure and prospectively with the disease. We designed a case-control study on CCVD nested in a cohort of 18,982 individuals from the EPIC-Italy study. We measured air pollution, inflammatory biomarkers, and whole-genome DNA methylation in blood collected up to 17 years before the diagnosis. The study sample includes all the incident CCVD cases among former- and never-smokers, with available stored blood sample, that arose in the cohort during the follow-up. We identified enrichment of altered DNA methylation in "ROS/Glutathione/Cytotoxic granules" and "Cytokine signaling" pathways related genes, associated with both air pollution (multiple comparisons adjusted p for enrichment ranging from 0.01 to 0.03 depending on pollutant) and with CCVD risk (P = 0.04 and P = 0.03, respectively). Also, Interleukin-17 was associated with higher exposure to NO2 (P = 0.0004), NOx (P = 0.0005), and CCVD risk (OR = 1.79; CI 1.04-3.11; P = 0.04 comparing extreme tertiles). Our findings indicate that chronic exposure to air pollution can lead to oxidative stress, which in turn activates a cascade of inflammatory responses mainly involving the "Cytokine signaling" pathway, leading to increased risk of CCVD. Inflammatory proteins and DNA methylation alterations can be detected several years before CCVD diagnosis in blood samples, being promising preclinical biomarkers. Environ. Mol. Mutagen. 59:234-246, 2018. © 2017 Wiley Periodicals, Inc.

The child health exposure analysis resource as a vehicle to measure environment in the environmental influences on child health outcomes program

PURPOSE OF REVIEW

Demonstrate the role of environment as a predictor of child health.

RECENT FINDINGS

The children's health exposure analysis resource (CHEAR) assists the Environmental influences on child health outcomes (ECHO) program in understanding the time sensitive and dynamic nature of perinatal and childhood environment on developmental trajectories by providing a central infrastructure for the analysis of biological samples from the ECHO cohort awards. CHEAR will assist ECHO cohorts in defining the critical or sensitive period for effects associated with environmental exposures. Effective incorporation of these principles into multiple existing cohorts requires extensive multidisciplinary expertise, creativity, and flexibility. The pursuit of life course - informed research within the CHEAR/ECHO structure represents a shift in focus from single exposure inquiries to one that addresses multiple environmental risk factors linked through shared vulnerabilities. CHEAR provides ECHO both targeted analyses of inorganic and organic toxicants, nutrients, and social-stress markers and untargeted analyses to assess the exposome and discovery of exposure-outcome relationships.

SUMMARY

Utilization of CHEAR as a single site for characterization of environmental exposures within the ECHO cohorts will not only support the investigation of the influence of environment on children's health but also support the harmonization of data across the disparate cohorts that comprise ECHO.

The Search for Environmental Causes of Parkinson's Disease: Moving Forward

It is widely believed that environmental exposures contribute to the vast majority of late-onset sporadic Parkinson's disease (PD), alone or via interactions with genetic factors. The search for environmental causes of PD has however been hampered by lack of understanding the prodromal phase of PD development and the difficulties in exposure assessment during this prolonged period. On the other hand, the existence of this prodromal period, along with an increasingly better understanding of PD prodromal symptoms, provides an exciting opportunity to identify environmental factors that initiate PD pathogenesis and/or modify its progression. For prevention efforts, this prodromal stage is of a major interest. Targeting factors that enter the body via the nose or gut has become even more important since the discovery of α-synuclein aggregates in the enteric and olfactory nervous systems. In this paper, we speculate about novel research hypotheses and approaches that may help us better define the role of environment in PD etiology, especially during its extended and complex prodromal phase.

Linking sources to early effects by profiling urine metabolome of residents living near oil refineries and coal-fired power plants

BACKGROUND

This study aims at identifying metabolic changes linking external exposure to industrial air toxics with oxidative stress biomarkers.

METHODS

We classified 252 study subjects as 111 high vs. 141 low exposure subjects by the distance from their homes to the two main emission sources, oil refineries and coal-fired power plants. We estimated individual's external exposure to heavy metals and polycyclic aromatic hydrocarbons (PAHs) by dispersion and kriging models, respectively. We measured urinary levels of heavy metals and 1-hydroxypyrene (1-OHP) as biomarkers of internal exposure, and 8-OHdG, HNE-MA, 8-isoPGF_2α, and 8-NO₂Gua as biomarkers of early health effects. We used two-dimensional gas chromatography time-of-flight mass spectrometry to identify urine metabolomics. We applied "meet-in-the-middle" approach to identify potential metabolites as putative intermediate biomarkers linking multiple air toxics exposures to oxidative stress with plausible exposures-related pathways.

RESULTS

High exposure subjects showed elevated ambient concentrations of vanadium and PAHs, increased urine concentrations of 1-OHP, vanadium, nickel, copper, arsenic, strontium, cadmium, mercury, and thallium, and higher urine concentrations of all four urine oxidative stress biomarkers compared to low exposure subjects. We identified a profile of putative intermediate biomarkers that were associated with both exposures and oxidative stress biomarkers in participants. Urine metabolomics identified age-dependent biological pathways, including tryptophan metabolism and phenylalanine metabolism in children subjects (aged 9-11), and glycine, serine, and threonine metabolism in elderly subjects (aged>55), that could associate multiple exposures with oxidative stress.

CONCLUSION

By profiling urine biomarkers and metabolomics in children and elderly residents living near a petrochemical complex, we can link their internal exposure to oxidative stress biomarkers through biological pathways associated with common complex chronic diseases and allergic respiratory diseases. The internal exposure may possibly be traced to multiple air toxics emitted from specific sources of oil refineries and coal-fired power plants.

Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women

BACKGROUND

Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases.

OBJECTIVES

Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population.

METHODS

Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM₁₀ in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM_2.5 and PM₁₀ exposures over 2-years were estimated for each participant's residential address using spatiotemporal interpolation in combination with a dispersion model.

RESULTS

Average long-term PM₁₀ was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m³ in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM₁₀ and the expression of individual genes differed by sex. In the validation cohort, long-term PM₁₀ was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM₁₀ in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM₁₀ exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women).

CONCLUSIONS

Expression of the sex-specific candidate genes identified in the discovery population predicted PM₁₀ exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects.

Biomarkers of the health outcomes associated with ambient particulate matter exposure

Epidemiologic evidence supports the positive association of cardiopulmonary morbidity and mortality, and lung cancer risk with exposure to airborne particulate matter (PM). Oxidative stress and inflammation have been proposed to be the major causal factors involved in mediating PM effects on both cardiovascular and pulmonary health outcomes. However, the mechanism whereby PM causes the health effects is not fully elucidated. To evaluate and investigate human exposure to PM, it is essential to have a specific, sensitive and robust characterization of individual exposure to PM. Biomarkers may mark important intermediate steps leading to overt health effects after PM exposure. Thus biomarkers are promising indicators, which could serve as representative measures of the exposure to PM for assessing the health impacts and understanding the mechanism. Indeed, a number of biomarkers are already in use in the field of epidemiological studies and toxicological research. However, we are facing now the challenges to select robust, specific and sensitive biomarkers, which can be employed in large-scale of population to assess the health risk and to monitor the effectiveness of interventions. In this review, we describe a range of biomarkers that are associated with air pollution exposure, particularly markers of oxidative stress, inflammatory factors, and microRNAs, as well as markers of pollutants metabolites. Understanding the nature of the association of these biomarkers with PM exposure may shed some light on the process of selecting biomarkers for large-scale population studies, developing novel preventative and therapeutic strategies.

From the exposome to mechanistic understanding of chemical-induced adverse effects

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.

Challenges and novel approaches for investigating molecular mediation

Understanding mediation is useful for identifying intermediates lying between an exposure and an outcome which, when intervened upon, will block (some or all of) the causal pathway between the exposure and outcome. Mediation approaches used in conventional epidemiology have been adapted to understanding the role of molecular intermediates in situations of high-dimensional omics data with varying degrees of success. In particular, the limitations of observational epidemiological study including confounding, reverse causation and measurement error can afflict conventional mediation approaches and may lead to incorrect conclusions regarding causal effects. Solutions to analysing mediation which overcome these problems include the use of instrumental variable methods such as Mendelian randomization, which may be applied to evaluate causality in increasingly complex networks of omics data.