The exposome concept was defined in 2005 as encompassing all environmental exposures from conception onwards, as a new strategy to evidence environmental disease risk factors. Although very ...appealing, the exposome concept is challenging in many respects. In terms of assessment, several hundreds of time-varying exposures need to be considered, but increasing the number of exposures assessed should not be done at the cost of increased exposure misclassification. Accurately assessing the exposome currently requires numerous measurements, which rely on different technologies; resulting in an expensive set of protocols. In the future, high-throughput 'omics technologies may be a promising technique to integrate a wide range of exposures from a small numbers of biological matrices. Assessing the association between many exposures and health raises statistical challenges. Due to the correlation structure of the exposome, existing statistical methods cannot fully and efficiently untangle the exposures truly affecting the health outcome from correlated exposures. Other statistical challenges relate to accounting for exposure misclassification or identifying synergistic effects between exposures. On-going exposome projects are trying to overcome technical and statistical challenges. From a public health perspective, a better understanding of the environmental risk factors should open the way to improved prevention strategies.
The exposome concept aims to consider all environmental stressors simultaneously. The dimension of the data and the correlation that may exist between exposures lead to various statistical ...challenges. Some methodological studies have provided insight regarding the efficiency of specific modeling approaches in the context of exposome data assessed once for each subject. However, few studies have considered the situation in which environmental exposures are assessed repeatedly. Here, we conduct a simulation study to compare the performance of statistical approaches to assess exposome-health associations in the context of multiple exposure variables. Different scenarios were tested, assuming different types and numbers of exposure-outcome causal relationships. An application study using real data collected within the INMA mother-child cohort (Spain) is also presented. In the simulation experiment, assessed methods showed varying performance across scenarios, making it challenging to recommend a one-size-fits-all strategy. Generally, methods such as sparse partial least-squares and the deletion-substitution-addition algorithm tended to outperform the other tested methods (ExWAS, Elastic-Net, DLNM, or sNPLS). Notably, as the number of true predictors increased, the performance of all methods declined. The absence of a clearly superior approach underscores the additional challenges posed by repeated exposome data, such as the presence of more complex correlation structures and interdependencies between variables, and highlights that careful consideration is essential when selecting the appropriate statistical method. In this regard, we provide recommendations based on the expected scenario. Given the heightened risk of reporting false positive or negative associations when applying these techniques to repeated exposome data, we advise interpreting the results with caution, particularly in compromised contexts such as those with a limited sample size.
Asthma is a widespread respiratory disease caused by complex contribution from genetic, environmental and behavioral factors. For several decades, its sensitivity to environmental factors has been ...investigated in single exposure (or single family of exposures) studies, which might be a narrow approach to tackle the etiology of such a complex multifactorial disease. The emergence of the exposome concept, introduced by C. Wild (2005), offers an alternative to address exposure-health associations. After presenting an overview of the exposome concept, we discuss different statistical approaches used to study the exposome-health associations and review recent studies linking multiple families of exposures to asthma-related outcomes. The few studies published so far on the association between the exposome and asthma-related outcomes showed differences in terms of study design, population, exposome definition and statistical methods used, making their results difficult to compare. Regarding statistical methods, most studies applied successively univariate (Exposome-Wide Association Study (ExWAS)) and multivariate (adjusted for co-exposures) (e.g., Deletion-Substitution-Addition (DSA) algorithm) regression-based models. This latest approach makes it possible to assess associations between a large set of exposures and asthma outcomes. However, it cannot address complex interactions (i.e., of order ≥3) or mixture effects. Other approaches like cluster-based analyses, that lead to the identification of specific profiles of exposure at risk for the studied health-outcome, or mediation analyses, that allow the integration of information from intermediate biological layers, could offer a new avenue in the understanding of the environment-asthma association. European projects focusing on the exposome research have recently been launched and should provide new results to help fill the gap that currently exists in our understanding of the effect of environment on respiratory health.
Within-subject biospecimens pooling can theoretically reduce bias in dose-response functions from biomarker-based studies when exposure assessment suffers from classical-type error. However, ...collecting many urine voids each day is cumbersome. We evaluated the empirical validity of a within-subject pooling approach and compared several options to avoid sampling each void.
In 16 pregnant women who collected a spot of each urine void over several nonconsecutive weeks, we compared concentrations of 10 phenols in daily, weekly, and pregnancy within-subject pools. We pooled either three or all daily samples. In a simulation study using these data, we quantified bias in dose-response functions when using one to 20 urine samples per subject to assess methylparaben (a compound with moderate within-subject variability) and bisphenol A (high variability) exposures.
Correlations between exposure estimates from pools of all and of only three voids per day were above 0.80 for all time windows and compounds, except for benzophenone-3 and triclosan in the daily time window (correlations, 0.57-0.68). With one spot sample to assess pregnancy exposure, correlations were all below 0.74. Using only one biospecimen led to attenuation bias in the dose-response functions of 29% (methylparaben) and 69% (bisphenol A); four samples for methylparaben and 18 for bisphenol A decreased bias to 10%.
For nonpersistent chemicals, collecting and pooling three samples per day instead of all daily samples efficiently estimates exposures over a week or more. Collecting around 20 biospecimens can strongly limit attenuation bias for nonpersistent chemicals such as bisphenol A.
Toxicology studies have shown adverse effects of developmental exposure to industrial phenols. Evaluation in humans is challenged by potentially marked within-subject variability of phenol biomarkers ...in pregnant women, which is poorly characterized.
We aimed to characterize within-day, between-day, and between-week variability of phenol urinary biomarker concentrations during pregnancy.
In eight French pregnant women, we collected all urine voids over a 1-wk period (average, 60 samples per week per woman) at three occasions (15±2, 24±2, and 32±1 gestational weeks) in 2012-2013. Aliquots of each day and of the whole week were pooled within-subject. We assayed concentrations of 10 phenols in these pools, and, for two women, in all spot (unpooled) samples collected during a 1-wk period. We characterized variability using intraclass correlation coefficients (ICCs) with spot samples (within-day variability), daily pools (between-day variability), and weekly pools (between-week variability).
For most biomarkers, the within-day variability was high (ICCs between 0.03 and 0.50). The between-day variability, based on samples pooled within each day, was much lower, with ICCs >0.60 except for bisphenol S (0.14, 95% confidence interval CI: 0.00, 0.39). The between-week variability differed between compounds, with triclosan and bisphenol S having the lowest ICCs (<0.3) and 2,5-dichlorophenol the highest (ICC >0.9).
During pregnancy, phenol biomarkers showed a strong within-day variability, while the variability between days of a given week was more limited. One biospecimen is not enough to efficiently characterize exposure; collecting biospecimens during a single week may be enough to represent well the whole pregnancy exposure for some but not all phenols. https://doi.org/10.1289/EHP1994.
Air pollution exposure represents a major health threat to the developing foetus. DNA methylation is one of the most well-known molecular determinants of the epigenetic status of cells. Blood DNA ...methylation has been proven sensitive to air pollutants, but the molecular impact of air pollution on new-borns has so far received little attention.
We investigated whether nitrogen dioxide (NO2), particulate matter (PM10), temperature and humidity during pregnancy are associated with differences in placental DNA methylation levels.
Whole-genome DNA-methylation was measured using the Illumina's Infinium HumanMethylation450 BeadChip in the placenta of 668 newborns from the EDEN cohort. We designed an original strategy using a priori biological information to focus on candidate genes with a specific expression pattern in placenta (active or silent) combined with an agnostic epigenome-wide association study (EWAS). We used robust linear regression to identify CpGs and differentially methylated regions (DMR) associated with each exposure during short- and long-term time-windows.
The candidate genes approach identified nine CpGs mapping to 9 genes associated with prenatal NO2 and PM10 exposure false discovery rate (FDR) p < 0.05. Among these, the methylation level of 2 CpGs located in ADORA2B remained significantly associated with NO2 exposure during the 2nd trimester and whole pregnancy in the EWAS (FDR p < 0.05). EWAS further revealed associations between the environmental exposures under study and variations of DNA methylation of 4 other CpGs. We further identified 27 DMRs significantly (FDR p < 0.05) associated with air pollutants exposure and 13 DMRs with meteorological conditions.
The methylation of ADORA2B, a gene whose expression was previously associated with hypoxia and pre-eclampsia, was consistently found here sensitive to atmospheric pollutants. In addition, air pollutants were associated to DMRs pointing towards genes previously implicated in preeclampsia, hypertensive and metabolic disorders. These findings demonstrate that air pollutants exposure at levels commonly experienced in the European population are associated with placental gene methylation and provide some mechanistic insight into some of the reported effects of air pollutants on preeclampsia.
•DNA methylation was measured in 668 placentas using the HumanMethylation450 BeadChip.•We used an original strategy combining a concept-driven and agnostic approaches.•Methylation of Alu or LINE-1 sequences was mainly not associated with air pollutants.•Pregnancy NO2 exposure was associated with lower ADORA2B methylation in multiple CpGs.•Highlighted genes were related to preeclampsia, hypertensive and metabolic disorders.
Scarce epidemiological studies have characterised allergic rhinitis (AR) and non-allergic rhinitis (NAR) in adults. In a population-based cohort, our aims were to 1) describe rhinitis, AR and NAR, ...and 2) explore how asthma and conjunctivitis may lead to the identification of novel rhinitis phenotypes.
In this cross-sectional analysis, current rhinitis was defined as present in the last 12 months using a questionnaire from the French CONSTANCES cohort. Participants with current rhinitis reporting nasal allergies were considered as AR, otherwise as NAR. We described AR and NAR phenotypes, and their phenotypes including co-occurrence with ever-asthma and ever-conjunctivitis.
Among the 20 772 participants included in this analysis (mean±sd age 52.6±12.6 years; 55.2% female), crude prevalences of AR and NAR were 28.0% and 10.9%. AR participants more frequently reported persistent rhinitis (31.6%
25.1%) and moderate-to-severe rhinitis (40.1%
24.2%) than NAR participants. Among AR or NAR participants, those with ever-asthma reported more moderate-to-severe rhinitis. Participants with AR, ever-asthma and ever-conjunctivitis had an earlier age of rhinitis onset, more severe rhinitis and higher eosinophil counts than participants in other groups. Results were replicated in another cohort.
In this large population-based cohort, 40% reported current rhinitis, with a lower prevalence of moderate-to-severe rhinitis than in clinical practice. For the first time in a general adult population, we showed that AR and NAR alone or in combination with asthma or in combination with asthma and conjunctivitis are different phenotypes. These results provide new insights on how best to manage rhinitis and its multimorbidities.
Asthma is an oxidative stress related disease, but associations with asthma outcomes are poorly studied in adults. We aimed to study the associations between several biomarkers related to oxidative ...stress and various asthma outcomes.Cross-sectional analyses were conducted in 1388 adults (mean age 43 years, 44% with asthma) from the Epidemiological Study of the Genetics and Environment of Asthma (EGEA2). Three blood antioxidant enzyme activities (biomarkers of response to oxidative stress) and exhaled breath condensate 8-isoprostanes and plasma fluorescent oxidation products (FlOPs) levels (two biomarkers of damage) were measured. Associations between biomarkers and 1) ever asthma and 2) asthma attacks, asthma control and lung function in participants with asthma were evaluated using regression models adjusted for age, sex and smoking.Biomarkers of response were unrelated to asthma outcomes. Higher 8-isoprostane levels were significantly associated with ever asthma (odds ratio for one interquartile range increase 1.28 (95% CI 1.06-1.67). Among participants with asthma, 8-isoprostane levels were negatively associated with adult-onset asthma (0.63, 0.41-0.97) and FlOPs levels were positively associated with asthma attacks (1.33, 1.07-1.65), poor asthma control (1.30, 1.02-1.66) and poor lung function (1.34, 1.04-1.74).Our results suggest that 8-isoprostanes are involved in childhood-onset asthma and FlOPs are linked to asthma expression.
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