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Background: Endocrine disrupting compounds (EDCs) such as phthalates and phenols can affect placental functioning and fetal health, potentially via epigenetic modifications. We investigated the associations between pregnancy exposure to synthetic phenols and phthalates estimated from repeated urine sampling and genome wide placental DNA methylation. Methods: The study is based on 387 women with placental DNA methylation assessed with Infinium MethylationEPIC arrays and with 7 phenols, 13 phthalates, and two non-phthalate plasticizer metabolites measured in pools of urine samples collected twice during pregnancy. We conducted an exploratory analysis on individual CpGs (EWAS) and differentially methylated regions (DMRs) as well as a candidate analysis focusing on 20 previously identified CpGs. Sex-stratified analyses were also performed. Results: In the exploratory analysis, when both sexes were studied together no association was observed in the EWAS. In the sex-stratified analysis, 114 individual CpGs (68 in males, 46 in females) were differentially methylated, encompassing 74 genes (36 for males and 38 for females). We additionally identified 28 DMRs in the entire cohort, 40 for females and 42 for males. Associations were mostly positive (for DMRs: 93% positive associations in the entire cohort, 60% in the sex-stratified analysis), with the exception of several associations for bisphenols and DINCH metabolites that were negative. Biomarkers associated with most DMRs were parabens, DEHP, and DiNP metabolite concentrations. Some DMRs encompassed imprinted genes including APC (associated with parabens and DiNP metabolites), GNAS (bisphenols), ZIM2;PEG3;MIMT1 (parabens, monoethyl phthalate), and SGCE;PEG10 (parabens, DINCH metabolites). Terms related to adiposity, lipid and glucose metabolism, and cardiovascular function were among the enriched phenotypes associated with differentially methylated CpGs. The candidate analysis identified one CpG mapping to imprinted LGALS8 gene, negatively associated with ethylparaben. Conclusions: By combining improved exposure assessment and extensive placental epigenome coverage, we identified several novel genes associated with the exposure, possibly in a sex-specific manner.

Abstract Background Intra-breath oscillometry has been proposed as a sensitive means of detecting airway obstruction in young children. We aimed to assess the impact of early life wheezing and lower respiratory tract illness on lung function, using both standard and intra-breath oscillometry in 3 year old children. Methods History of doctor-diagnosed asthma, wheezing, bronchiolitis and bronchitis and hospitalisation for respiratory problems were assessed by questionnaires in 384 population-based children. Association of respiratory history with standard and intra-breath oscillometry parameters, including resistance at 7 Hz (R7), frequency-dependence of resistance (R7 − 19), reactance at 7 Hz (X7), area of the reactance curve (AX), end-inspiratory and end-expiratory R (ReI, ReE) and X (XeI, XeE), and volume-dependence of resistance (ΔR = ReE-ReI) was estimated by linear regression adjusted on confounders. Results Among the 320 children who accepted the oscillometry test, 281 (88%) performed 3 technically acceptable and reproducible standard oscillometry measurements and 251 children also performed one intra-breath oscillometry measurement. Asthma was associated with higher ReI, ReE, ΔR and R7 and wheezing was associated with higher ΔR. Bronchiolitis was associated with higher R7 and AX and lower XeI and bronchitis with higher ReI. No statistically significant association was observed for hospitalisation. Conclusions Our findings confirm the good success rate of oscillometry in 3-year-old children and indicate an association between a history of early-life wheezing and lower respiratory tract illness and lower lung function as assessed by both standard and intra-breath oscillometry. Our study supports the relevance of using intra-breath oscillometry parameters as sensitive outcome measures in preschool children in epidemiological cohorts.

Abstract Once an external factor has been deemed likely to influence human health and a dose response function is available, an assessment of its health impact or that of policies aimed at influencing this and possibly other factors in a specific population can be obtained through a quantitative risk assessment, or health impact assessment (HIA) study. The health impact is usually expressed as a number of disease cases or disability-adjusted life-years (DALYs) attributable to or expected from the exposure or policy. We review the methodology of quantitative risk assessment studies based on human data. The main steps of such studies include definition of counterfactual scenarios related to the exposure or policy, exposure(s) assessment, quantification of risks (usually relying on literature-based dose response functions), possibly economic assessment, followed by uncertainty analyses. We discuss issues and make recommendations relative to the accuracy and geographic scale at which factors are assessed, which can strongly influence the study results. If several factors are considered simultaneously, then correlation, mutual influences and possibly synergy between them should be taken into account. Gaps or issues in the methodology of quantitative risk assessment studies include 1) proposing a formal approach to the quantitative handling of the level of evidence regarding each exposure-health pair (essential to consider emerging factors); 2) contrasting risk assessment based on human dose–response functions with that relying on toxicological data; 3) clarification of terminology of health impact assessment and human-based risk assessment studies, which are actually very similar, and 4) other technical issues related to the simultaneous consideration of several factors, in particular when they are causally linked.

Background: Most previous studies investigating the associations between prenatal exposure to phthalates and fetal growth relied on measurements of phthalate metabolites at a single time point. They also focused on weight at birth without assessing growth over pregnancy, preventing the identification of potential periods of fetal vulnerability. We examined the associations between pregnancy urinary phthalate metabolites and fetal growth outcomes measured twice during pregnancy and at birth. Methods: For 484 pregnant women, we assessed 13 phthalate and two 1,2-cyclohexane dicarboxylic acid, diisononyl ester (DINCH) metabolite concentrations from two within-subject weekly pools of up to 21 urine samples (median of 18 and 34 gestational weeks, respectively). Fetal biparietal diameter, femur length, head and abdominal circumferences were measured during two routine pregnancy follow-up ultrasonographies (median 22 and 32 gestational weeks, respectively) and estimated fetal weight (EFW) was calculated. Newborn weight, length, and head circumference were measured at birth. Associations between phthalate/DINCH metabolite and growth parameters were investigated using adjusted linear regression and Bayesian kernel machine regression models. Results: Detection rates were above 99 % for all phthalate/DINCH metabolites. While no association was observed with birth measurements, mono-iso-butyl phthalate (MiBP) and mono-n-butyl phthalate (MnBP) were positively associated with most fetal growth parameters measured at the second trimester. Specifically, MiBP was positively associated with biparietal diameter, head and abdominal circumferences, while MnBP was positively associated with EFW, head and abdominal circumferences, with stronger associations among males. Pregnancy MnBP was positively associated with biparietal diameter and femur length at third trimester. Mixture of phthalate/DINCH metabolites was positively associated with EFW at second trimester. Conclusions: In this pregnancy cohort using repeated urine samples to assess exposure, MiBP and MnBP were associated with increased fetal growth parameters. Further investigation on the effects of phthalates on child health would be relevant for expanding current knowledge on their long-term effects.

Abstract Background Early-life environmental exposures are suspected to be involved in the development of chronic diseases later in life. Most studies conducted so far considered single or few exposures and single-health parameter. Our study aimed to identify a childhood general health score and assess its association with a wide range of pre- and post-natal environmental exposures. Methods The analysis is based on 870 children (6–12 years) from six European birth cohorts participating in the Human Early-Life Exposome project. A total of 53 prenatal and 105 childhood environmental factors were considered, including lifestyle, social, urban and chemical exposures. We built a general health score by averaging three sub-scores (cardiometabolic, respiratory/allergy and mental) built from 15 health parameters. By construct, a child with a low score has a low general health status. Penalized multivariable regression through Least Absolute Shrinkage and Selection Operator (LASSO) was fitted in order to identify exposures associated with the general health score. Findings The results of LASSO show that a lower general health score was associated with maternal passive and active smoking during pregnancy and postnatal exposure to methylparaben, copper, indoor air pollutants, high intake of caffeinated drinks and few contacts with friends and family. Higher child’s general health score was associated with prenatal exposure to a bluespace near residency and postnatal exposures to pets, cobalt, high intakes of vegetables and more physical activity. Against our hypotheses, postnatal exposure to organochlorine compounds and perfluorooctanoate were associated with a higher child’s general health score. Conclusion By using a general health score summarizing the child cardiometabolic, respiratory/allergy and mental health, this study reinforced previously suspected environmental factors associated with various child health parameters (e.g. tobacco, air pollutants) and identified new factors (e.g. pets, bluespace) warranting further investigations.

Outcome-wide analysis can offer several benefits, including increased power to detect weak signals and the ability to identify exposures with multiple effects on health, which may be good targets for preventive measures. Recently, advanced statistical multivariate techniques for outcome-wide analysis have been developed, but they have been rarely applied to exposome analysis. In this work, we provide an overview of a selection of methods that are well-suited for outcome-wide exposome analysis and are implemented in the R statistical software. Our work brings together six different methods presenting innovative solutions for typical problems arising from outcome-wide approaches in the context of the exposome, including dependencies among outcomes, high dimensionality, mixed-type outcomes, missing data records, and confounding effects. The identified methods can be grouped into four main categories: regularized multivariate regression techniques, multi-task learning approaches, dimensionality reduction approaches, and bayesian extensions of the multivariate regression framework. Here, we compare each technique presenting its main rationale, strengths, and limitations, and provide codes and guidelines for their application to exposome data. Additionally, we apply all selected methods to a real exposome dataset from the Human Early-Life Exposome (HELIX) project, demonstrating their suitability for exposome research. Although the choice of the best method will always depend on the challenges to be faced in each application, for an exposome-like analysis we find dimensionality reduction and bayesian methods such as reduced rank regression (RRR) or multivariate bayesian shrinkage priors (MBSP) particularly useful, given their ability to deal with critical issues such as collinearity, high-dimensionality, missing data or quantification of uncertainty.

Environmental exposures in early life can have lasting health effects, but the molecular mechanisms are not well understood. Here, the authors discover >1000 associations between exposure factors and child multi-omics profiles, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions.

Abstract Background Maternal blood pressure levels reflect cardiovascular adaptation to pregnancy and proper maternal-fetal exchanges through the placenta and are very sensitive to numerous environmental stressors. Maternal hypertension during pregnancy has been associated with impaired placental functions and with an increased risk for children to suffer from cardiovascular and respiratory diseases later on. Investigating changes in placental DNA methylation levels and cell-type composition in association with maternal blood pressure could help elucidate its relationships with placental and fetal development. Methods Taking advantage of a large cohort of 666 participants, we investigated the association between epigenome-wide DNA methylation patterns in the placenta, measured using the Infinium HumanMethylation450 BeadChip, placental cell-type composition, estimated in silico, and repeated measurements of maternal steady and pulsatile blood pressure indicators during pregnancy. Results At the site-specific level, no significant association was found between maternal blood pressure and DNA methylation levels after correction for multiple testing (false discovery rate < 0.05), but 5 out of 24 previously found CpG associations were replicated (p-value < 0.05). At the regional level, our analyses highlighted 64 differentially methylated regions significantly associated with at least one blood pressure component, including 35 regions associated with mean arterial pressure levels during late pregnancy. These regions were found enriched for genes implicated in lung development and diseases. Further mediation analyses show that a significant part of the association between steady blood pressure—but not pulsatile pressure—and placental methylation can be explained by alterations in placental cell-type composition. In particular, elevated blood pressure levels are associated with a decrease in the ratio between mesenchymal stromal cells and syncytiotrophoblasts, even in the absence of preeclampsia. Conclusions This study provides the first evidence that the association between maternal steady blood pressure during pregnancy and placental DNA methylation is both direct and partly explained by changes in cell-type composition. These results could hint at molecular mechanisms linking maternal hypertension to lung development and early origins of childhood respiratory problems and at the importance of controlling maternal blood pressure during pregnancy.

Abstract Background Frequent car use contributes to health and environmental issues such as air pollution, climate change and obesity. Active and sustainable mobility (bike, walk, public transport, car sharing) may address these issues. Different strategies have been implemented in past research, involving hard levers, aimed at modifying the economical or geographical context (e.g., free public transport), and soft levers, aimed at modifying psychological processes (e.g., personalised transport advice). However, few studies have combined both hard and soft levers. In addition, few have used robust methodologies (e.g., randomised controlled trials), followed behavioural changes in the long-term, and been anchored in behaviour change theories. InterMob aims to address these limits by implementing a 24-month randomised controlled trial including hard and soft levers. The objectives of InterMob are to a) evaluate the effectiveness of an experimental arm versus an active controlled arm, and b) identify the processes of mobility change. Methods Regular car users living in Grenoble (N = 300) will be recruited and randomised to one of the two arms. The experimental arm consists in a six-month intervention combining hard levers (free access to transport/bikes), and soft levers (e.g., personalised transport advice). The control arm consists in a six-month intervention aimed at raising awareness on air pollution and its health effects. Both arms will include eight evaluation weeks (spread out over 24 months) based on a GPS, an accelerometer, and a pollution sensor. Moreover, participants will complete mobility logbooks and surveys measuring psychological constructs, socio-economical, and socio-spatial characteristics. Discussion InterMob will assess the effectiveness of two interventions aimed at reducing car use within regular car users in the short-, mid- and long-term. Moreover, InterMob will allow to better understand the psychological processes of behaviour change, and the socio-economical and geographical conditions under which the intervention is efficient in reducing car use. Finally, the benefits of mobility change in terms of physical activity, quality of life, and exposure to pollution will be quantified. Trial registration ClinicalTrials.gov : NCT05096000 on 27/10/2021 (retrospectively registered).

IntroductionImmune function in pregnancy is influenced by host-specific and environmental factors. This may impact fetal immune development, but the link between maternal and neonatal immune function is still poorly characterized. Here, we investigate the relationship between maternal and neonatal immune function, and identify factors affecting the association between maternal and child cytokine secretion.MethodsIn the French prospective cohort SEPAGES, blood samples were obtained from pregnant women (n=322) at gestational week 20 ± 4 and from their child at birth (n=156). Maternal and cord blood cytokine and chemokine (CK) levels were measured at baseline in all subjects and after T cell or dendritic cell activation with phytohemagglutinin or R848 (in total 29 and 27 measures in maternal and cord blood samples, respectively). Associations between environmental, individual factors and CK level were estimated by linear regression modeling. The maternal-cord blood CK relations were assessed by Pearson correlation and regression models.ResultsWe observed that pregnant women and neonates displayed specific CK secretion profiles in the innate and adaptive compartments at baseline and upon activation. Activation of T cells in cord blood induced high levels of IL-2, but low levels of IFNγ, IL-13 or IL-10, in comparison to maternal blood samples. Elsewhere, neonatal innate immune responses were characterized by low production of IFNα, while productions of IL-1β, IL-6, IL-8, IL-10 and TNFα were higher than maternal responses. Strong correlations were observed between most CK after activation in maternal and cord blood samples. Strikingly, a statistical association between global mother and child cytokine profiles was evidenced. Correlations were observed between some individual CK of pregnant women and their children, both at baseline (MCP1, RANTES) and after activation with R848 (IL-6, IL-8 and IL-10). We looked for factors which could influence cytokine secretion in maternal or cord blood, and found that leucocyte counts, maternal age, pre-conception BMI, smoking and season were associated with the levels of several CK in mothers or children. DiscussionOur study reveals in utero immune imprinting influencing immune responses in infants, opening the way to investigate the mechanisms responsible for this imprinting. Whether such influences have long lasting effects on children health warrants further investigation.

Background: Individuals are exposed to environmental pollutants with endocrine disrupting activity (endocrine disruptors, EDCs) and the early stages of life are particularly susceptible to these exposures. Previous studies have focused on identifying molecular signatures associated with EDCs, but none have used repeated sampling strategy and integrated multiple omics. We aimed to identify multi-omic signatures associated with childhood exposure to non-persistent EDCs. Methods: We used data from the HELIX Child Panel Study, which included 156 children aged 6 to 11. Children were followed for one week, in two time periods. Twenty-two non-persistent EDCs (10 phthalate, 7 phenol, and 5 organophosphate pesticide metabolites) were measured in two weekly pools of 15 urine samples each. Multi-omic profiles (methylome, serum and urinary metabolome, proteome) were measured in blood and in a pool urine samples. We developed visit-specific Gaussian Graphical Models based on pairwise partial correlations. The visit-specific networks were then merged to identify reproducible associations. Independent biological evidence was systematically sought to confirm some of these associations and assess their potential health implications. Results: 950 reproducible associations were found among which 23 were direct associations between EDCs and omics. For 9 of them, we were able to find corroborating evidence from previous literature: DEP - serotonin, OXBE - cg27466129, OXBE - dimethylamine, triclosan - leptin, triclosan - serotonin, MBzP - Neu5AC, MEHP - cg20080548, oh-MiNP - kynurenine, oxo-MiNP − 5-oxoproline. We used these associations to explore possible mechanisms between EDCs and health outcomes, and found links to health outcomes for 3 analytes: serotonin and kynurenine in relation to neuro-behavioural development, and leptin in relation to obesity and insulin resistance. Conclusions: This multi-omics network analysis at two time points identified biologically relevant molecular signatures related to non-persistent EDC exposure in childhood, suggesting pathways related to neurological and metabolic outcomes.

Background: In vitro and toxicological studies have shown that non-persistent environmental chemicals can perturb thyroid hormone homeostasis. Epidemiological studies with improved exposure assessment (i.e., repeated urine samples) are needed to evaluate effects of these compounds, individually or as a mixture, in humans. We studied the associations between prenatal exposure to non-persistent environmental chemicals and neonatal thyroid hormones. Methods: The study population consisted of 442 mother–child pairs from the French SEPAGES mother–child cohort recruited between July 2014 and July 2017. For each participant, four parabens, five bisphenols, triclosan, triclocarban, benzophenone-3 as well as metabolites of phthalates and of di(isononyl)cyclohexane-1,2-dicarboxylate were assessed in two pools of repeated urine samples (median: 21 spot urines per pool), collected in the 2nd and 3rd trimesters of pregnancy, respectively. Thyroid stimulating hormone (TSH) and total thyroxine (T4) levels were determined in newborns from a heel-prick blood spot. Maternal iodine and selenium were assessed in urine and serum, respectively. Adjusted linear regression (uni-pollutant model) and Bayesian Kernel Machine Regression (BKMR, mixture model) were applied to study overall and sex-stratified associations between chemicals and hormone concentrations. Results: Interaction with child sex was detected for several compounds. Triclosan, three parabens, and one phthalate metabolite (OH-MPHP) were negatively associated with T4 among girls in the uni-pollutant model. BKMR also suggested a negative association between the mixture and T4 in girls, whereas in boys the association was positive. The mixture was not linked to TSH levels, and for this hormone the uni-pollutant model revealed associations with only a few compounds. Conclusion: Our study, based on repeated urine samples to assess exposure, showed that prenatal exposure to some phenols and phthalates disturb thyroid hormone homeostasis at birth. Furthermore, both uni-pollutant and mixture models, suggested effect modification by child sex, while, to date underlying mechanisms for such sex-differences are not well understood.

Abstract Background We aimed to estimate the seroprevalence of SARS-CoV-2 infection in France and to identify the populations most exposed during the first epidemic wave. Methods Random selection of individuals aged 15 years or over, from the national tax register (96% coverage). Socio-economic data, migration history, and living conditions were collected via self-computer-assisted-web or computer-assisted-telephone interviews. Home self-sampling was performed for a random subsample, to detect IgG antibodies against spike protein (Euroimmun), and neutralizing antibodies with in-house assays, in dried blood spots (DBS). Results The questionnaire was completed by 134,391 participants from May 2nd to June 2st, 2020, including 17,441 eligible for DBS 12,114 of whom were tested. ELISA-S seroprevalence was 4.5% [95% CI 3.9–5.0] overall, reaching up to 10% in the two most affected areas. High-density residences, larger household size, having reported a suspected COVID-19 case in the household, working in healthcare, being of intermediate age and non-daily tobacco smoking were independently associated with seropositivity, whereas living with children or adolescents did not remain associated after adjustment for household size. Adjustment for both residential density and household size accounted for much of the higher seroprevalence in immigrants born outside Europe, twice that in French natives in univariate analysis. Conclusion The EPICOV cohort is one of the largest national representative population-based seroprevalence surveys for COVID-19. It shows the major role of contextual living conditions in the initial spread of COVID-19 in France, during which the availability of masks and virological tests was limited.

ObjectiveTo assess whether lack of trust in the government and scientists reinforces social and racial inequalities in vaccination practices.DesignA follow-up of the EpiCov random population-based cohort survey.SettingIn July 2021, in France.ParticipantsEighty-thousand nine hundred and seventy-one participants aged 18 years and more.Main Outcome MeasuresAdjusted odds ratios of COVID-19 vaccination status (received at least one dose/ intends to get vaccinated/ does not know whether to get vaccinated/refuses vaccination) were assessed using multinomial regressions to test associations with social and trust factors and to study how these two factors interacted with each other.ResultsIn all, 72.2% were vaccinated at the time of the survey. The population of unvaccinated people was younger, less educated, had lower incomes, and more often belonged to racially minoritized groups, as compared to vaccinated people. Lack of trust in the government and scientists to curb the spread of the epidemic were the factors most associated with refusing to be vaccinated: OR = 8.86 (7.13 to 11.00) for the government and OR = 9.07 (7.71 to 10.07) for scientists, compared to vaccinated people. Lack of trust was more prevalent among the poorest which consequently reinforced social inequalities in vaccination. The poorest 10% who did not trust the government reached an OR of 16.2 (11.9 to 22.0) for refusing to be vaccinated compared to the richest 10% who did.ConclusionThere is a need to develop depoliticised outreach programmes targeted at the most socially disadvantaged groups, and to design vaccination strategies conceived with people from different social and racial backgrounds to enable them to make fully informed choices.

We aimed to analyze inequalities in social isolation among older adults in a time of COVID-19 social restrictions, using a gender perspective. A random population-based survey, including 21,543 older adults (65+) was conducted during and post COVID-19 lockdown in France. Our main outcome was a three-dimension indicator of social isolation based on living conditions, i.e., living alone (i) and not having gone out in the past week (ii), completed by an indicator measuring Internet use i.e., never using the Internet (iii). Logistic regressions were used to identify factors associated with isolation for women and men. Women were more likely to live alone (aOR = 2.72 [2.53; 2.92]), not to have gone out in the past week (aOR = 1.53 [1.39; 1.68]), and not to use the Internet (aOR = 1.30 [1.20; 1.44]). In addition to gender effects, being older, at the bottom of the social hierarchy, and from an ethno-racial minority was also associated with social isolation. Preventive policies should take into account these inequalities when addressing the issue of social isolation among older women and men, so as to enable all social groups to maintain social contacts, and access health information.

Abstract Background The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. Methods We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. Results Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. Conclusion In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Background: Exposure to phthalates during pregnancy may alter DNA methylation in the placenta, a crucial organ for the growth and development of the fetus. Objectives: We studied associations between urinary concentrations of phthalate biomarkers during pregnancy and placental DNA methylation. Methods: We measured concentrations of 11 phthalate metabolites in maternal spot urine samples collected between 22 and 29 gestational weeks in 202 pregnant women. We analyzed DNA methylation levels in placental tissue (fetal side) collected at delivery. We first investigated changes in global DNA methylation of repetitive elements Alu and LINE-1. We then performed an adjusted epigenome-wide association study using IlluminaHM450 BeadChips and identified differentially methylated regions (DMRs) associated with phthalate exposure. Results: Monobenzyl phthalate concentration was inversely associated with placental methylation of Alu repeats. Moreover, all phthalate biomarkers except for monocarboxy-iso-octyl phthalate and mono(2-ethyl-5-hydroxyhexyl) phthalate were associated with at least one DMR. All but three DMRs showed increased DNA methylation with increased phthalate exposure. The largest identified DMR (22 CpGs) was positively associated with monocarboxy-iso-nonyl phthalate and encompassed heat shock proteins (HSPA1A, HSPA1L). The remaining DMRs encompassed transcription factors and nucleotide exchange factors, among other genes. Conclusions: This is the first description of genome-wide modifications of placental DNA methylation in association with pregnancy exposure to phthalates. Our results suggest epigenetic mechanisms by which exposure to these compounds could affect fetal development. Of interest, four identified DMRs had been previously associated with maternal smoking, which may suggest particular sensitivity of these genomic regions to the effect of environmental contaminants.

Context: Policies aiming at decreasing air pollutants (e.g., fine particulate matter, PM2.5) are often designed without targeting an explicit health benefit nor carrying out cost-benefit analyses. Methods: We developed a transdisciplinary backward and forward approach at the conurbation level: from health objectives set by local decision-makers, we estimated which reductions in PM2.5 exposures and emissions would allow to reach them, and identified urban policies leading to these reductions (backward approach). We finally conducted health impact and cost-benefit analyses of these policies (forward approach). The policies were related to the most emitting sectors in the considered area (Grenoble, France), wood heating and transport sectors. The forward approach also considered the health impact and co-benefits of these policies related to changes in physical activity and CO2 emissions. Findings: Decision-makers set three health targets, corresponding to decreases by 33% to 67% in PM2.5-attributable mortality in 2030, compared to 2016. A decrease by 42% in PM2.5 exposure (from 13.9 µg/m3) was required to reach the decrease by 67% in PM2.5-attributable mortality. For each Euro invested, the total benefit was about 30€ for policies focusing on wood heating, and 1 to 68€ for traffic policies. Acting on a single sector was not enough to attain a 67% decrease in PM2.5-attributable mortality. This target could be achieved by replacing all inefficient wood heating equipment by low-emission pellet stoves and reducing by 36% the traffic of private motorized vehicles. This would require to increase the share of active modes (walking, biking…), inducing increases in physical activity and additional health benefits beyond the initial target. Annual net benefits were between €484 and €629 per capita for policies with report on active modes, compared to between €162 and €270 without. Conclusions: Urban policies strongly reducing air pollution-attributable mortality can be identified by our approach. Such policies can be cost-efficient.

Developing children are particularly vulnerable to the effects of exposure to per- and polyfluoroalkyl substances (PFAS), a group of endocrine disrupting chemicals. We hypothesized that early life exposure to PFASs is associated with poor metabolic health in children.We studied the association between prenatal and postnatal PFASs mixture exposure and cardiometabolic health in children, and the role of inflammatory proteins.In 1,101 mothers-child pairs from the Human Early Life Exposome project, we measured the concentrations of PFAS in blood collected in pregnancy and at 8 years (range = 6–12 years). We applied Bayesian Kernel Machine regression (BKMR) to estimate the associations between exposure to PFAS mixture and the cardiometabolic factors as age and sex- specific z-scores of waist circumference (WC), systolic and diastolic blood pressures (BP), and concentrations of triglycerides (TG), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) cholesterol. We measured thirty six inflammatory biomarkers in child plasma and examined the underlying role of inflammatory status for the exposure-outcome association by integrating the three panels into a network.Exposure to the PFAS mixture was positively associated with HDL-C and systolic BP, and negatively associated with WC, LDL-C and TG. When we examined the independent effects of the individual chemicals in the mixture, prenatal PFHxS was negatively associated with HDL-C and prenatal PFNA was positively associated with WC and these were opposing directions from the overall mixture. Further, the network consisted of five distinct communities connected with positive and negative correlations. The selected inflammatory biomarkers were positively, while the postnatal PFAS were negatively related with the included cardiometabolic factors, and only prenatal PFOA was positively related with the pro-inflammatory cytokine IL-1beta and WC.Our study supports that prenatal, rather than postnatal, PFAS exposure might contribute to an unfavorable lipidemic profile and adiposity in childhood.

Background: Synthetic phenols and phthalates can interfere with biological pathways involved in brain development. Despite the high within-subject temporal variability of urinary concentrations observed for their metabolites, studies investigating effects of phenols and phthalates on child behaviour often relied on a limited number of spot biospecimens to assess exposure. Besides, the majority did not consider mixture effects. Objectives: To study the combined effect of prenatal exposure to synthetic phenols and phthalates on child behaviour using repeated exposure measurements. Methods: We assessed concentrations of 12 phenols, 13 phthalate and 2 non-phthalate plasticizer metabolites in within-subject pools of multiple urine samples (median = 21 samples per individual pool) collected at two distinct time points during pregnancy in 416 mother–child pairs from the French SEPAGES cohort. Child behaviour was evaluated at two years using the Child Behaviour Checklist 1.5–5 (CBCL). Associations between a mixture of biomarkers of exposure and externalizing and internalizing behaviour scores were studied using adjusted Weighted Quantile Sum (WQS) regressions with a repeated holdout validation (100 repetitions). Results: The positive WQS indexes were associated with both the externalizing and internalizing behaviour scores in the whole population, indicating greater risk of behavioural problems. Stratification for child sex suggested stronger associations in girls than boys. On average, girls externalizing and internalizing scores increased by 3.67 points (95% CI: 1.24, 6.10) and 2.47 points (95 %CI: 0.60, 4.33) respectively, for an increase of one tertile in the WQS index, compared with 1.70 points (95 %CI: −0.42, 3.81) and 1.17 points (95 %CI: −0.50, 2.84) in boys. Main contributors for the associations observed in girls were bisphenol A (weight of 18%), triclosan (17%) and monoethyl phthalate (MEP, 15%) for the externalizing score and MEP (19%), mono-benzyl phthalate (MBzP, 19%) and mono-n-butyl phthalate (MnBP, 16%) for the internalizing score. Discussion: Our results suggest adverse associations between in utero exposure to a mixture of phenols and phthalates and child behaviour, mainly in girls. Public health consequences may be substantial due to the widespread exposure of the population to these compounds.

Objective Although social inequalities in COVID-19 mortality by race, gender and socioeconomic status are well documented, less is known about social disparities in infection rates and their shift over time. We aim to study the evolution of social disparities in infection at the early stage of the epidemic in France with regard to the policies implemented.Design Random population-based prospective cohort.Setting From May to June 2020 in France.Participants Adults included in the Epidémiologie et Conditions de Vie cohort (n=77 588).Main outcome measures Self-reported anosmia and/or ageusia in three categories: no symptom, during the first epidemic peak (in March 2020) or thereafter (during lockdown).Results In all, 2052 participants (1.53%) reported anosmia/ageusia. The social distribution of exposure factors (density of place of residence, overcrowded housing and working outside the home) was described. Multinomial regressions were used to identify changes in social variables (gender, class and race) associated with symptoms of anosmia/ageusia. Women were more likely to report symptoms during the peak and after. Racialised minorities accumulated more exposure risk factors than the mainstream population and were at higher risk of anosmia/ageusia during the peak and after. By contrast, senior executive professionals were the least exposed to the virus with the lower rate of working outside the home during lockdown. They were more affected than lower social classes at the peak of the epidemic, but this effect disappeared after the peak.Conclusion The shift in the social profile of the epidemic was related to a shift in exposure factors under the implementation of a stringent stay-at-home order. Our study shows the importance to consider in a dynamic way the gender, socioeconomic and race direct and indirect effects of the COVID-19 pandemic, notably to implement policies that do not widen health inequalities.

Background: There is only scant evidence that air pollution increases the risk of breast cancer. Objectives: We investigated this relationship for three air pollutants: nitrogen dioxide (NO2) and particulate matter with an aerodynamical diameter below 10 µm (PM10) and 2.5 µm (PM2.5). Methods: We conducted a population-based case-control study on breast cancer in two French départements, including 1,229 women diagnosed with breast cancer in 2005–2007 and 1,316 control women frequency-matched on age. Concentrations of NO2, PM10 and PM2.5 at participants’ addresses occupied during the last 10 years were assessed using a chemistry transport model. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using multivariable logistic regression models where each woman was assigned a weight depending on her probability of selection into the study. Results: The OR for breast cancer per 10-µg/m3 increase in NO2 was 1.11 (95% CI, 0.98, 1.26), and 1.41 (95% CI 1.07, 1.86) in the highest exposure quintile (Q5), compared to the first. The ORs per 10-µg/m3 NO2 did not markedly differ between pre- (OR 1.09, 95% CI 0.89, 1.35)) and post-menopausal women (OR 1.14, 95% CI 0.97, 1.33)), but the OR was substantially higher for hormone-receptor positive (ER+/PR+) breast tumor subtypes (OR 1.15, 95% CI 1.00, 1.31) than for ER–/PR– tumors (OR 0.95, 95% CI 0.72, 1.26). Breast cancer risk was not associated with either PM10 (OR per 1 µg/m3 1.01, 95% CI, 0.96, 1.06) or PM2.5 (OR per 1 µg/m3 1.02, 95% CI 0.95, 1.08), regardless of the menopausal status or of the breast tumor subtype. Discussion: Our study provides evidence that NO2 exposure, a marker of traffic-related air pollutants, may be associated with an increased risk of breast cancer, particularly ER+/PR+ tumors.

The early-life exposome influences future health and accelerated biological aging has been proposed as one of the underlying biological mechanisms. We investigated the association between more than 100 exposures assessed during pregnancy and in childhood (including indoor and outdoor air pollutants, built environment, green environments, tobacco smoking, lifestyle exposures, and biomarkers of chemical pollutants), and epigenetic age acceleration in 1,173 children aged 7 years old from the Human Early-Life Exposome project. Age acceleration was calculated based on Horvath’s Skin and Blood clock using child blood DNA methylation measured by Infinium HumanMethylation450 BeadChips. We performed an exposure-wide association study between prenatal and childhood exposome and age acceleration. Maternal tobacco smoking during pregnancy was nominally associated with increased age acceleration. For childhood exposures, indoor particulate matter absorbance (PMabs) and parental smoking were nominally associated with an increase in age acceleration. Exposure to the organic pesticide dimethyl dithiophosphate and the persistent pollutant polychlorinated biphenyl-138 (inversely associated with child body mass index) were protective for age acceleration. None of the associations remained significant after multiple-testing correction. Pregnancy and childhood exposure to tobacco smoke and childhood exposure to indoor PMabs may accelerate epigenetic aging from an early age.

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.

Background: Fine particulate matter (PM2.5) exposure entails large health effects in many urban areas. Public measures aiming at decreasing air pollution are often designed without targeting an explicit health benefit. Our objective was to investigate the health and economic benefits and the social inequalities in exposure resulting from several scenarios of reduction of PM2.5 exposure, in order to support decisions about urban policies. Material and methods: In the French conurbations of Grenoble and Lyon (0.4 and 1.4 million inhabitants, respectively), PM2.5 yearly average exposure was estimated on a 10-m grid by coupling a PM2.5 dispersion model to population density. Changes in death cases, life expectancy, lung cancer and term low birth weight incident cases as well as associated health economic costs were estimated for ten PM2.5 reduction scenarios differing in terms of amplitude of reduction and spatial extent. Changes in social differences in PM2.5 exposure were also assessed. Results: During the 2015–2017 period, PM2.5 average exposure was 13.9 μg/m3 in Grenoble and 15.3 μg/m3 in Lyon conurbations. Exposure to PM2.5 led to an estimated 145 (95% Confidence Interval, CI, 90–199) and 531 (95% CI, 330–729) premature deaths, 16 (95% CI, 8–24) and 65 (95% CI, 30–96) incident lung cancers, and 49 (95% CI, 19–76) and 193 (95% CI, 76–295) term low birth weight cases each year in Grenoble and Lyon conurbations, respectively, compared to a situation without PM2.5 anthropogenic sources, i.e. a PM2.5 concentration of 4.9 μg/m3. The associated costs amounted to 495 (Grenoble) and 1767 (Lyon) M€/year for the intangible costs related to all-cause non-accidental mortality and 27 and 105 M€ for the tangible and intangible costs induced by lung cancer. A PM2.5 exposure reduction down to the WHO air quality guideline (10 μg/m3) would reduce anthropogenic PM2.5-attributable mortality by half while decreases by 2.9 μg/m3 (Grenoble) and 3.3 μg/m3 (Lyon) were required to reduce it by a third. Scenarios focusing only on the most exposed areas had little overall impact. Scenarios seeking to reach a homogeneous exposure in the whole study area were the most efficient in alleviating social inequalities in exposure. Conclusions: Reduction scenarios targeting only air pollution hotspots had little expected impact on population health. We provided estimates of the PM2.5 change required to reduce PM2.5-attributable mortality by one third or more. Our approach can help targeting air pollution reduction scenarios expected to entail significant benefits, and it could easily be transposed to other urban areas. Keywords: Dispersion model, Economic costs, Health impact assessment, Lung cancer, Fine particulate matter (PM2.5), Social deprivation

Characterization of the “exposome”, the set of all environmental factors that one is exposed to from conception onwards, has been advocated to better understand the role of environmental factors on chronic diseases.Here, we aimed to describe the early-life exposome. Specifically, we focused on the correlations between multiple environmental exposures, their patterns and their variability across European regions and across time (pregnancy and childhood periods). We relied on the Human Early-Life Exposome (HELIX) project, in which 87 environmental exposures during pregnancy and 122 during the childhood period (grouped in 19 exposure groups) were assessed in 1301 pregnant mothers and their children at 6–11 years in 6 European birth cohorts.Some correlations between exposures in the same exposure group reached high values above 0.8. The median correlation within exposure groups was >0.3 for many exposure groups, reaching 0.69 for water disinfection by products in pregnancy and 0.67 for the meteorological group in childhood. Median correlations between different exposure groups rarely reached 0.3. Some correlations were driven by cohort-level associations (e.g. air pollution and chemicals). Ten principal components explained 45% and 39% of the total variance in the pregnancy and childhood exposome, respectively, while 65 and 90 components were required to explain 95% of the exposome variability. Correlations between maternal (pregnancy) and childhood exposures were high (>0.6) for most exposures modeled at the residential address (e.g. air pollution), but were much lower and even close to zero for some chemical exposures.In conclusion, the early life exposome was high dimensional, meaning that it cannot easily be measured by or reduced to fewer components. Correlations between exposures from different exposure groups were much lower than within exposure groups, which have important implications for co-exposure confounding in multiple exposure studies. Also, we observed the early life exposome to be variable over time and to vary by cohort, so measurements at one time point or one place will not capture its complexities. Keywords: Exposome, Environmental exposures, Early life, Pregnancy, Children

Background: Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. Objectives: We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. Methods: 154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. Results: All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in

Background: Harmonized data describing simultaneous exposure to a large number of environmental contaminants in-utero and during childhood is currently very limited. Objectives: To characterize concentrations of a large number of environmental contaminants in pregnant women from Europe and their children, based on chemical analysis of biological samples from mother-child pairs. Methods: We relied on the Early-Life Exposome project, HELIX, a collaborative project across six established population-based birth cohort studies in Europe. In 1301 subjects, biomarkers of exposure to 45 contaminants (i.e. organochlorine compounds, polybrominated diphenyl ethers, per- and polyfluoroalkyl substances, toxic and essential elements, phthalate metabolites, environmental phenols, organophosphate pesticide metabolites and cotinine) were measured in biological samples from children (6–12 years) and their mothers during pregnancy, using highly sensitive biomonitoring methods. Results: Most of the exposure biomarkers had high detection frequencies in mothers (35 out of 45 biomarkers with >90% detected) and children (33 out of 45 biomarkers with >90% detected). Concentrations were significantly different between cohorts for all compounds, and were generally higher in maternal compared to children samples. For most of the persistent compounds the correlations between maternal and child concentrations were moderate to high (Spearman Rho > 0.35), while for most non-persistent compounds correlations were considerably lower (Spearman Rho 100,000 concentrations of environmental contaminants in mother-child pairs forms a unique possibility for conducting epidemiological studies using an exposome approach. Keywords: Exposome, Children, Pregnant women, Mother-child pairs, Exposure

Outdoor air pollution is a leading environmental cause of death and cancer incidence in humans. We aimed to estimate the fraction of lung cancer incidence attributable to fine particulate matter (PM2.5) exposure in France, and secondarily to illustrate the influence of the input data and the spatial resolution of information on air pollution levels on this estimate. The population attributable fraction (PAF) was estimated using a nationwide spatially refined chemistry-transport model with a 2-km spatial resolution, neighbourhood-scale population density data, and a relative risk from a published meta-analysis. We used the WHO guideline value for PM2.5 exposure (10 μg/m3) as reference. Sensitivity analyses consisted in attributing the nation-wide median exposure to all areas and using alternative input data such as reference of PM2.5 exposure level and relative risk. Population-weighted median PM2.5 level in 2005 was 13.8 μg/m3; 87% of the population was exposed above the guideline value. The burden of lung cancer attributable to PM2.5 exposure corresponded to 1466 cases, or 3.6% of all cases diagnosed in 2015. Sensitivity analyses showed that the use of a national median of PM2.5 exposure would have led to an underestimation of the PAF by 11% (population-weighted median) and by 72% (median of raw concentration), suggesting that our estimates would have been higher with even more finely spatially-resolved models. When the PM2.5 reference level was replaced by the 5th percentile of country-scale exposure (4.9 μg/m3), PAF increased to 7.6%. Other sensitivity analyses resulted in even higher PAFs. Improvements in air pollution are crucial for quantitative health impacts assessment studies. Actions to reduce PM2.5 levels could substantially reduce the burden of lung cancer in France. Keywords: Air pollution, Lung cancer, Population attributable fraction, France

Background: The urban environment is characterised by many exposures that may influence hypertension development from early life onwards, but there is no systematic evaluation of their impact on child blood pressure (BP). Methods: Systolic and diastolic blood pressure were measured in 4,279 children aged 4–5 years from a multi-centre European cohort (France, Greece, Spain, and UK). Urban environment exposures were estimated during pregnancy and childhood, including air pollution, built environment, natural spaces, traffic, noise, meteorology, and socioeconomic deprivation index. Single- and multiple-exposure linear regression models and a cluster analysis were carried out. Results: In multiple exposure models, higher child BP, in particular diastolic BP, was observed in association with higher exposure to air pollution, noise and ambient temperature during pregnancy, and with higher exposure to air pollution and higher building density during childhood (e.g., mean change [95% confidence interval] for an interquartile range increase in prenatal NO2 = 0.7 mmHg[0.3;1.2]). Lower BP was observed in association with higher temperature and better street connectivity during childhood (e.g., temperature = -1.1[-1.6;-0.6]). Some of these associations were not robust in the sensitivity analyses. Mother-child pairs were grouped into six urban environment exposure clusters. Compared to the cluster representing the least harmful urban environment, the two clusters representing the most harmful environment (high in air pollution, traffic, noise, and low in green space) were both associated with higher diastolic BP (1.3[0.1;2.6] and 1.5[0.5;2.5]). Conclusion: This first large systematic study suggests that living in a harmful urban environment may impact BP regulation in children. These findings reinforce the importance of designing cities that promote healthy environments to reduce long-term risk of hypertension and other cardiovascular diseases.

Background: Heat stress during pregnancy may limit fetal growth, with ramifications throughout the life course. However, critical exposure windows are unknown, and effects of meteorological variability have not been investigated. Objectives: We aimed to identify sensitive windows for the associations of mean and variability of temperature and humidity with term birthweight. Methods: We analyzed data from two French mother–child cohorts, EDEN and PELAGIE (n = 4771), recruited in 2002–2006. Temperature exposure was assessed using a satellite-based model with daily 1-km2 resolution, and relative humidity exposure data were obtained from Météo France monitors. Distributed lag models were constructed using weekly means and standard deviation (SD, to quantify variability) from the first 37 gestational weeks. Analyses were then stratified by sex. Results for each exposure were adjusted for the other exposures, gestational age at birth, season and year of conception, cohort and recruitment center, and individual confounders. Results: There was no evidence of association between term birthweight and mean temperature. We identified a critical window in weeks 6–20 for temperature variability (cumulative change in term birthweight of −54.2 g [95% CI: −102, −6] for a 1 °C increase in SD of temperature for each week in that window). Upon stratification by sex of the infant, the relationship remained for boys (weeks 1–21, cumulative change: −125 g [95% CI: −228, −21]). For mean humidity, there was a critical window in weeks 26–37, with a cumulative change of −28 g (95% CI: −49, −7) associated with a 5% increase in humidity for each week. The critical window was longer and had a stronger association in boys (weeks 29–37; −37 g, 95% CI: −63, −11) than girls (week 14; −1.8 g, 95% CI: −3.6, −0.1). Discussion: Weekly temperature variability and mean humidity during critical exposure windows were associated with decreased term birthweight, especially in boys.

Background: Parabens, bisphenol A and triclosan have been forbidden or restricted in specific types of consumer goods in Europe and France. Limited biomonitoring data are available in France since the implementation of these regulations, and exposure data on infants is scarce worldwide. Understanding the predictors of phenol urinary concentrations will help identify potential targets for prevention. Aim: We described levels, variability and predictors of exposure to 12 phenols in pregnant women and infants recruited between 2014 and 2017 in a French couple-child cohort. Methods: Among 479 pregnant women and 150 of their infants, we studied phenol urinary concentrations in within-subject, within-period pools of repeated urine samples collected during the second and third trimesters of pregnancy (up to 42 samples per woman), at 2 months and 12 months (up to 14 samples per infant). Time trends and associations with demographic, protocol, occupational and behavioral factors were studied using interval censored models to accommodate for undetected and unquantified urine concentrations. Results: Detection rates were above 90% for bisphenol A, ethylparaben, methylparaben, benzophenone-3 and triclosan and below 5% for bisphenol AF, B, F and triclocarban. Median levels of bisphenol A, bisphenol S, methylparaben, ethylparaben and propylparaben at 12 months were similar or higher than during pregnancy. For pregnant women all phenols but benzophenone-3 and bisphenol S showed a linear decrease between 2014 and 2017 (p-values

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. Keywords: Biological a priori, Child body mass index – exposome, dimension reduction – DNA methylation, Reverse causality

Background: Uncertainly continues to exist regarding the role of air pollution on pediatric asthma and allergic conditions, especially as air pollution levels have started to decrease in recent decades. Objective: We examined associations of long-term air pollution levels at the home address with pediatric eczema, rhinoconjunctivitis and asthma prevalences in five birth cohorts (BIB, EDEN, GASPII, RHEA and INMA) from seven areas in five European countries. Methods: Current eczema, rhinoconjunctivitis and asthma were assessed in children aged four (N = 6527) and eight years (N = 2489). A multi-morbidity outcome (≥2 conditions versus none) was also defined. Individual outdoor levels of nitrogen dioxide (NO2), nitrogen oxides, mass of particulate matter with an aerodynamic diameter

Abstract Background There are concerns that developmental exposure to endocrine disrupting chemicals such as phenolic compounds and phthalates could affect child cognitive function. Epidemiological studies tackling this question have mainly focused on phthalate metabolites and bisphenol A, but not on the other phenolic compounds. Our study aimed to assess the relationship between in-utero exposure to phthalates, bisphenol A and other phenolic compounds (parabens, triclosan, dichlorophenols and benzophenone-3) and the Intelligence Quotient (IQ) of boys at 5–6 years. Methods In 452 mother-son dyads from the French EDEN cohort, we measured 11 phthalate metabolites and 9 phenolic compounds (4 parabens, benzophenone-3, bisphenol A, 2 dichlorophenols and triclosan) in spot urine samples collected between 22 and 29 gestational weeks. Verbal and performance IQ of children were assessed at 5–6 years by a psychologist using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI). We used adjusted Structural Equation Models (SEM) combined with Benjamini and Hochberg false discovery rate correction to assess the associations between maternal urine phenol and phthalate metabolite concentrations considered simultaneously and the boys’ IQ. Results No phenol or phthalate metabolite concentration was negatively associated with the boys’ verbal or performance IQ (uncorrected p-values ≥0.09). Mono(3-carboxypropyl) phthalate tended to be associated with increased verbal IQ (β = 0.136, 95% confidence interval, 0.01; 0.27). This association disappeared after correction for multiple comparison (corrected p-value, 0.71). Conclusion Our results did not provide evidence of an inverse association between in-utero exposure to phenols or phthalates and verbal and performance IQ among boys. Since phenols and phthalates may have sex-specific effects, these null findings cannot be generalized to girls. Limitations included use of a single spot urine sample to assess exposures and lack of consideration of postnatal exposures.

Abstract Background There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures from conception onwards). Uncovering such combined effects is challenging owing to the large number of exposures, several of them being highly correlated. We performed a simulation study in an exposome context to compare the performance of several statistical methods that have been proposed to detect statistical interactions. Methods Simulations were based on an exposome including 237 exposures with a realistic correlation structure. We considered several statistical regression-based methods, including two-step Environment-Wide Association Study (EWAS2), the Deletion/Substitution/Addition (DSA) algorithm, the Least Absolute Shrinkage and Selection Operator (LASSO), Group-Lasso INTERaction-NET (GLINTERNET), a three-step method based on regression trees and finally Boosted Regression Trees (BRT). We assessed the performance of each method in terms of model size, predictive ability, sensitivity and false discovery rate. Results GLINTERNET and DSA had better overall performance than the other methods, with GLINTERNET having better properties in terms of selecting the true predictors (sensitivity) and of predictive ability, while DSA had a lower number of false positives. In terms of ability to capture interaction terms, GLINTERNET and DSA had again the best performances, with the same trade-off between sensitivity and false discovery proportion. When GLINTERNET and DSA failed to select an exposure truly associated with the outcome, they tended to select a highly correlated one. When interactions were not present in the data, using variable selection methods that allowed for interactions had only slight costs in performance compared to methods that only searched for main effects. Conclusions GLINTERNET and DSA provided better performance in detecting two-way interactions, compared to other existing methods.

Summary: Background: Several single-exposure studies have documented possible effects of environmental factors on lung function, but none has relied on an exposome approach. We aimed to evaluate the association between a broad range of prenatal and postnatal lifestyle and environmental exposures and lung function in children. Methods: In this analysis, we used data from 1033 mother–child pairs from the European Human Early-Life Exposome (HELIX) cohort (consisting of six existing longitudinal birth cohorts in France, Greece, Lithuania, Norway, Spain, and the UK of children born between 2003 and 2009) for whom a valid spirometry test was recorded for the child. 85 prenatal and 125 postnatal exposures relating to outdoor, indoor, chemical, and lifestyle factors were assessed, and lung function was measured by spirometry in children at age 6–12 years. Two agnostic linear regression methods, a deletion-substitution-addition (DSA) algorithm considering all exposures simultaneously, and an exposome-wide association study (ExWAS) considering exposures independently, were applied to test the association with forced expiratory volume in 1 s percent predicted values (FEV1%). We tested for two-way interaction between exposures and corrected for confounding by co-exposures. Findings: In the 1033 children (median age 8·1 years, IQR 6·5–9·0), mean FEV1% was 98·8% (SD 13·2). In the ExWAS, prenatal perfluorononanoate (p=0·034) and perfluorooctanoate (p=0·030) exposures were associated with lower FEV1%, and inverse distance to nearest road during pregnancy (p=0·030) was associated with higher FEV1%. Nine postnatal exposures were associated with lower FEV1%: copper (p=0·041), ethyl-paraben (p=0·029), five phthalate metabolites (mono-2-ethyl 5-carboxypentyl phthalate [p=0·016], mono-2-ethyl-5-hydroxyhexyl phthalate [p=0·023], mono-2-ethyl-5-oxohexyl phthalate [p=0·0085], mono-4-methyl-7-oxooctyl phthalate [p=0·040], and the sum of di-ethylhexyl phthalate metabolites [p=0·014]), house crowding (p=0·015), and facility density around schools (p=0·027). However, no exposure passed the significance threshold when corrected for multiple testing in ExWAS, and none was selected with the DSA algorithm, including when testing for exposure interactions. Interpretation: Our systematic exposome approach identified several environmental exposures, mainly chemicals, that might be associated with lung function. Reducing exposure to these ubiquitous chemicals could help to prevent the development of chronic respiratory disease. Funding: European Community's Seventh Framework Programme (HELIX project).

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.

BACKGROUND:Accurately characterizing children's body mass index (BMI) trajectories and studying their determinants is a statistical challenge. There is a need to identify early public health measures for obesity prevention. We describe a method that allows studies of the determinants of height, weight and BMI growth up to five years of age. We illustrated this method using maternal smoking during pregnancy as one of the early-life factors that is potentially involved in prenatal programming of obesity. METHODS:Individual height and weight trajectories were fitted using the Jenss-Bayley model on 28,381 and 30,515 measurements, respectively, from 1,666 children to deduce BMI trajectories. We assessed global associations between smoking and growth trajectories and cross-sectional associations at specific ages. RESULTS:Children exposed in late pregnancy had a 0.24 kg/m2 (95% confidence interval: 0.07, 0.41) higher BMI at 5 years of age compared with non-exposed children. Although the BMIs of children exposed during late pregnancy became significantly higher compared with those of non-exposed children from 2 years onwards, the trajectories began to diverge during the first weeks of life. CONCLUSION:Our method is relevant for studies on the relationships between individual-level exposures and the dynamics and shapes of BMI growth during childhood, including key features such as instantaneous growth velocities and the age or BMI value at the BMI infancy peak that benefit from the monotonic pattern of height and weight growth.