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Abstract Childhood obesity poses a significant public health challenge, yet the molecular intricacies underlying its pathobiology remain elusive. Leveraging extensive multi-omics profiling (methylome, miRNome, transcriptome, proteins and metabolites) and a rich phenotypic characterization across two parts of Europe within the population-based Human Early Life Exposome project, we unravel the molecular landscape of childhood obesity and associated metabolic dysfunction. Our integrative analysis uncovers three clusters of children defined by specific multi-omics profiles, one of which characterized not only by higher adiposity but also by a high degree of metabolic complications. This high-risk cluster exhibits a complex interplay across many biological pathways, predominantly underscored by inflammation-related cascades. Further, by incorporating comprehensive information from the environmental risk-scape of the critical pregnancy period, we identify pre-pregnancy body mass index and environmental pollutants like perfluorooctanoate and mercury as important determinants of the high-risk cluster. Overall, our work helps to identify potential risk factors for prevention and intervention strategies early in the life course aimed at mitigating obesity and its long-term health consequences.

Introduction: Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes. Objective: In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS). Methods: The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value

Background: Bisphenol A (BPA; or 4,4′-isopropylidenediphenol) is an endocrine disrupting chemical. It was widely used in a variety of plastic-based manufactured products for several years. The European Food Safety Authority (EFSA) recently reduced the Tolerable Daily Intake (TDI) for BPA by 20,000 times due to concerns about immune-toxicity. Objective: We used human biomonitoring (HBM) data to investigate the general level of BPA exposure from 2007 to 2014 of European women aged 18–73 years (n = 4,226) and its determinants. Methods: Fifteen studies from 12 countries (Austria, Belgium, Denmark, France, Germany, Greece, Israel, Luxembourg, Slovenia, Spain, Sweden, and the United Kingdom) were included in the BPA Study protocol developed within the European Joint Programme HBM4EU. Seventy variables related to the BPA exposure were collected through a rigorous post-harmonization process. Linear mixed regression models were used to investigate the determinants of total urine BPA in the combined population. Results: Total BPA was quantified in 85–100 % of women in 14 out of 15 contributing studies. Only the Austrian PBAT study (Western Europe), which had a limit of quantification 2.5 to 25-fold higher than the other studies (LOQ=2.5 µg/L), found total BPA in less than 5 % of the urine samples analyzed. The geometric mean (GM) of total urine BPA ranged from 0.77 to 2.47 µg/L among the contributing studies. The lowest GM of total BPA was observed in France (Western Europe) from the ELFE subset (GM=0.77 µg/L (0.98 µg/g creatinine), n = 1741), and the highest levels were found in Belgium (Western Europe) and Greece (Southern Europe), from DEMOCOPHES (GM=2.47 µg/L (2.26 µg/g creatinine), n = 129) and HELIX-RHEA (GM=2.47 µg/L (2.44 µg/g creatinine), n = 194) subsets, respectively. One hundred percent of women in 14 out of 15 data collections in this study exceeded the health-based human biomonitoring guidance value for the general population (HBM-GVGenPop) of 0.0115 µg total BPA/L urine derived from the updated EFSA’s BPA TDI. Variables related to the measurement of total urine BPA and those related to the main socio-demographic characteristics (age, height, weight, education, smoking status) were collected in almost all studies, while several variables related to BPA exposure factors were not gathered in most of the original studies (consumption of beverages contained in plastic bottles, consumption of canned food or beverages, consumption of food in contact with plastic packaging, use of plastic film or plastic containers for food, having a plastic floor covering in the house, use of thermal paper…). No clear determinants of total urine BPA concentrations among European women were found. A broader range of data planned for collection in the original questionnaires of the contributing studies would have resulted in a more thorough investigation of the determinants of BPA exposure in European women. Conclusion: This study highlights the urgent need for action to further reduce exposure to BPA to protect the population, as is already the case in the European Union. The study also underscores the importance of pre-harmonizing HBM design and data for producing comparable data and interpretable results at a European-wide level, and to increase HBM uptake by regulatory agencies.

Background: Precision Health aims to revolutionize disease prevention by leveraging information across multiple omic datasets (multi-omics). However, existing methods generally do not consider personalized environmental risk factors (e.g., environmental pollutants). Objective: To develop and apply a precision health framework which combines multiomic integration (including early, intermediate, and late integration, representing sequential stages at which omics layers are combined for modeling) with mediation approaches (including high-dimensional mediation to identify biomarkers, mediation with latent factors to identify pathways, and integrated/quasi-mediation to identify high-risk subpopulations) to identify novel biomarkers of prenatal mercury induced metabolic dysfunction-associated fatty liver disease (MAFLD), elucidate molecular pathways linking prenatal mercury with MAFLD in children, and identify high-risk children based on integrated exposure and multiomics data. Methods: This prospective cohort study used data from 420 mother–child pairs from the Human Early Life Exposome (HELIX) project. Mercury concentrations were determined in maternal or cord blood from pregnancy. Cytokeratin 18 (CK-18; a MAFLD biomarker) and five omics layers (DNA Methylation, gene transcription, microRNA, proteins, and metabolites) were measured in blood in childhood (age 6–10 years). Results: Each standard deviation increase in prenatal mercury was associated with a 0.11 [95% confidence interval: 0.02–0.21] standard deviation increase in CK-18. High dimensional mediation analysis identified 10 biomarkers linking prenatal mercury and CK-18, including six CpG sites and four transcripts. Mediation with latent factors identified molecular pathways linking mercury and MAFLD, including altered cytokine signaling and hepatic stellate cell activation. Integrated/quasi-mediation identified high risk subgroups of children based on unique combinations of exposure levels, omics profiles (driven by epigenetic markers), and MAFLD. Conclusions: Prenatal mercury exposure is associated with elevated liver enzymes in childhood, likely through alterations in DNA methylation and gene expression. Our analytic framework can be applied across many different fields and serve as a resource to help guide future precision health investigations.

Abstract Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P

Abstract Background Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. Methods We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1–11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. Results We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values

Abstract Background Attention-deficit/hyperactivity disorder (ADHD) is a prevalent and highly heritable neurodevelopmental disorder of major societal concern. Diagnosis can be challenging and there are large knowledge gaps regarding its etiology, though studies suggest an interplay of genetic and environmental factors involving epigenetic mechanisms. MicroRNAs (miRNAs) show promise as biomarkers of human pathology and novel therapies, and here we aimed to identify blood miRNAs associated with traits of ADHD as possible biomarker candidates and further explore their biological relevance. Methods Our study population consisted of 1126 children (aged 5–12 years, 46% female) from the Human Early Life Exposome study, a study spanning six ongoing population-based European birth cohorts. Expression profiles of miRNAs in whole blood samples were quantified by microarray and tested for association with ADHD-related measures of behavior and neuropsychological functions from questionnaires (Conner’s Rating Scale and Child Behavior Checklist) and computer-based tests (the N-back task and Attention Network Test). Results We identified 29 miRNAs significantly associated (false discovery rate

The blood levels of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) have been thoroughly investigated in Greek children from the Rhea birth cohort study. This investigation aimed to assess exposure levels, explore their possible relationship with children's age and sex, and indicate potential sources of exposure. Exposure patterns and common sources of PCBs and OCPs were analyzed using bivariate and multivariate statistics.A total of 947 blood samples from study participants were analyzed for OCP and PCB exposure, with 375 samples collected at 4 years old, 239 at 6.5 years old, and 333 at 11 years old. Elevated levels of DDE were observed in 6.5-year-old children compared to corresponding levels in other European countries. Higher levels of DDE were found in 4-year-old children, with the lowest concentrations in the 11-year-old group. The DDT/DDE ratio was consistently less than 1 among all the examined subjects. These results indicate exposure to DDT and DDE both in utero and through breastfeeding and dietary intake. For the entire cohort population, the highest concentration was determined for PCB 28, followed by PCBs 138, 153, and 180. The sum of the six indicator PCBs implied low exposure levels for the majority of the cohort population. Spearman correlations revealed strong associations between PCBs and OCPs, while principal component analysis identified two different groupings of exposure. DDE exhibited a correlation with a series of PCBs (153, 156, 163, 180), indicating a combined OCP-PCB source, and an anticorrelation with others (52, 28, 101), implying a separate and competing source.

In utero and children’s exposure to per- and polyfluoroalkyl substances (PFAS) is a major concern in health risk assessment as early life exposures are suspected to induce adverse health effects. Our work aims to estimate children’s exposure (from birth to 12 years old) to PFOA and PFOS, using a Physiologically-Based Pharmacokinetic (PBPK) modelling approach.A model for PFAS was updated to simulate the internal PFAS exposures during the in utero life and childhood, and including individual characteristics and exposure scenarios (e.g., duration of breastfeeding, weight at birth, etc.). Our approach was applied to the HELIX cohort, involving 1,239 mother–child pairs with measured PFOA and PFOS plasma concentrations at two sampling times: maternal and child plasma concentrations (6 to 12 y.o).Our model predicted an increase in plasma concentrations during fetal development and childhood until 2 y.o when the maximum concentrations were reached. Higher plasma concentrations of PFOA than PFOS were predicted until 2 y.o, and then PFOS concentrations gradually became higher than PFOA concentrations. From 2 to 8 y.o, mean concentrations decreased from 3.1 to 1.88 µg/L or ng/mL (PFOA) and from 4.77 to 3.56 µg/L (PFOS). The concentration–time profiles vary with the age and were mostly influenced by in utero exposure (on the first 4 months after birth), breastfeeding (from 5 months to 2 (PFOA) or 5 (PFOS) y.o of the children), and food intake (after 3 (PFOA) or 6 (PFOS) y.o of the children). Similar measured biomarker levels can correspond to large differences in the simulated internal exposures, highlighting the importance to investigate the children’s exposure over the early life to improve exposure classification.Our approach demonstrates the possibility to simulate individual internal exposures using PBPK models when measured biomarkers are scarce, helping risk assessors in gaining insight into internal exposure during critical windows, such as early life.

Background: Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD). Objectives: We investigated associations between urban environment exposures during pregnancy and PPD. Methods: We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686–30,716 depending on exposure; representing 26–46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3–18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD. Results: Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs.

Chemical exposures often occur in mixtures and exposures during pregnancy may lead to adverse effects on the fetal brain, potentially reducing lower cognitive abilities and fine motor function of the child. We investigated the association of motheŕs exposure to a mixture of chemicals during pregnancy (i.e., organochlorine compounds, per- and polyfluoroalkyl substances, phenols, phthalates, organophosphate pesticides) with cognitive abilties and fine motor function in their children. We studied 1097 mother–child pairs from five European cohorts participating in the Human Early Life Exposome study (HELIX). Measurement of 26 biomarkers of exposure to chemicals was performed on urine or blood samples of pregnant women (mean age 31 years). Cognitive abilities and fine motor function were assessed in their children (mean age 8 years) with a battery of computerized tests administered in person (Raveńs Coloured Progressive Matrices, Attention Network Test, N-back Test, Trail Making Test, Finger Tapping Test). We estimated the joint effect of prenatal exposure to chemicals on cognitive abilities and fine motor function using the quantile-based g-computation method, adjusting for sociodemographic characteristics. A quartile increase in all the chemicals in the overall mixture was associated with worse fine motor function, specifically lower scores in the Finger Tapping Test [-8.5 points, 95 % confidence interval (CI) −13.6 to −3.4; −14.5 points, 95 % CI –22.4 to −6.6, and −18.0 points, 95 % CI −28.6 to −7.4) for the second, third and fourth quartile of the overal mixture, respectively, when compared to the first quartile]. Organochlorine compounds, phthalates, and per- and polyfluoroalkyl substances contributed most to this association. We did not find a relationship with cognitive abilities. We conclude that exposure to chemical mixtures during pregnancy may influence neurodevelopment, impacting fine motor function of the offspring.

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.

Background: The EU LifeCycle Project was launched in 2017 to combine, harmonize, and analyze data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview of the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project. Methods: Data on cognitive, behavioral, and psychological development has been collected on participants from birth until adulthood through questionnaire and medical data. We developed an inventory of the available data by mapping individual instruments, domain types, and age groups, providing the basis for statistical harmonization across mental health measures. Results: The mental health data in LifeCycle contain longitudinal and cross-sectional data from birth throughout the life course, covering domains across a wide range of behavioral and psychopathology indicators and outcomes, including executive function, depression, ADHD, and cognition. These data span a unique combination of qualitative data collected through behavioral/cognitive/mental health questionnaires and examination, as well as data from biological samples and indices in the form of imaging (MRI, fetal ultrasound) and DNA methylation data. Harmonized variables on a subset of mental health domains have been developed, providing statistical equivalence of measures required for longitudinal meta-analyses across instruments and cohorts. Conclusion: Mental health data harmonized through the LifeCycle project can be used to study life-course trajectories and exposure-outcome models that examine early life risk factors for mental illness and develop predictive markers for later-life disease.

Epimutations are rare alterations of the normal DNA methylation pattern at specific loci, which can lead to rare diseases. Methylation microarrays enable genome-wide epimutation detection, but technical limitations prevent their use in clinical settings: methods applied to rare diseases’ data cannot be easily incorporated to standard analyses pipelines, while epimutation methods implemented in R packages (ramr) have not been validated for rare diseases. We have developed epimutacions, a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/epimutacions.html). epimutacions implements two previously reported methods and four new statistical approaches to detect epimutations, along with functions to annotate and visualize epimutations. Additionally, we have developed an user-friendly Shiny app to facilitate epimutations detection (https://github.com/isglobal-brge/epimutacionsShiny) to non-bioinformatician users. We first compared the performance of epimutacions and ramr packages using three public datasets with experimentally validated epimutations. Methods in epimutacions had a high performance at low sample sizes and outperformed methods in ramr. Second, we used two general population children cohorts (INMA and HELIX) to determine the technical and biological factors that affect epimutations detection, providing guidelines on how designing the experiments or preprocessing the data. In these cohorts, most epimutations did not correlate with detectable regional gene expression changes. Finally, we exemplified how epimutacions can be used in a clinical context. We run epimutacions in a cohort of children with autism disorder and identified novel recurrent epimutations in candidate genes for autism. Overall, we present epimutacions a new Bioconductor package for incorporating epimutations detection to rare disease diagnosis and provide guidelines for the design and data analyses.

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.

Background: While biological age in adults is often understood as representing general health and resilience, the conceptual interpretation of accelerated biological age in children and its relationship to development remains unclear. We aimed to clarify the relationship of accelerated biological age, assessed through two established biological age indicators, telomere length and DNA methylation age, and two novel candidate biological age indicators, to child developmental outcomes, including growth and adiposity, cognition, behavior, lung function and the onset of puberty, among European school-age children participating in the HELIX exposome cohort. Methods: The study population included up to 1173 children, aged between 5 and 12 years, from study centres in the UK, France, Spain, Norway, Lithuania, and Greece. Telomere length was measured through qPCR, blood DNA methylation, and gene expression was measured using microarray, and proteins and metabolites were measured by a range of targeted assays. DNA methylation age was assessed using Horvath’s skin and blood clock, while novel blood transcriptome and ‘immunometabolic’ (based on plasma proteins and urinary and serum metabolites) clocks were derived and tested in a subset of children assessed six months after the main follow-up visit. Associations between biological age indicators with child developmental measures as well as health risk factors were estimated using linear regression, adjusted for chronological age, sex, ethnicity, and study centre. The clock derived markers were expressed as Δ age (i.e. predicted minus chronological age). Results: Transcriptome and immunometabolic clocks predicted chronological age well in the test set (r=0.93 and r=0.84 respectively). Generally, weak correlations were observed, after adjustment for chronological age, between the biological age indicators. Conclusions: In children, as in adults, biological aging appears to be a multi-faceted process and adiposity is an important correlate of accelerated biological aging. Patterns of associations suggested that accelerated immunometabolic age may be beneficial for some aspects of child development while accelerated DNA methylation age and telomere attrition may reflect early detrimental aspects of biological aging, apparent even in children. Funding: UK Research and Innovation (MR/S03532X/1); European Commission (grant agreement numbers: 308333; 874583).

Research suggests that maternal exposure to natural environments (i.e., green and blue spaces) promotes healthy fetal growth. However, the available evidence is heterogeneous across regions, with very few studies on the effects of blue spaces. This study evaluated associations between maternal exposure to natural environments and birth outcomes in 11 birth cohorts across nine European countries. This study, part of the LifeCycle project, was based on a total sample size of 69,683 newborns with harmonised data. For each participant, we calculated seven indicators of residential exposure to natural environments: surrounding greenspace in 100m, 300m, and 500m using Normalised Difference Vegetation Index (NDVI) buffers, distance to the nearest green space, accessibility to green space, distance to the nearest blue space, and accessibility to blue space. Measures of birth weight and small for gestational age (SGA) were extracted from hospital records. We used pooled linear and logistic regression models to estimate associations between exposure to the natural environment and birth outcomes, controlling for the relevant covariates. We evaluated the potential effect modification by socioeconomic status (SES) and region of Europe and the influence of ambient air pollution on the associations. In the pooled analyses, residential surrounding greenspace in 100m, 300m, and 500m buffer was associated with increased birth weight and lower odds for SGA. Higher residential distance to green space was associated with lower birth weight and higher odds for SGA. We observed close to null associations for accessibility to green space and exposure to blue space. We found stronger estimated magnitudes for those participants with lower educational levels, from more deprived areas, and living in the northern European region. Our associations did not change notably after adjustment for air pollution. These findings may support implementing policies to promote natural environments in our cities, starting in more deprived areas.

Background: In Greece, influenza vaccination is currently recommended for children with high-risk conditions. There are limited data on influenza vaccination uptake among Greek children with and without high-risk conditions. We aim to describe the annual influenza vaccination uptake until the age of ten in a population-based mother–child cohort and identify the factors influencing vaccination rates. Methods: Immunization data from the child’s health cards at 4 and 10 years were available for 830 and 298 children participating in the Rhea cohort (2008–2019). We calculated vaccination coverage by age, winter season and among children with asthma and obesity for whom the vaccine is indicated. Univariable and multivariable stepwise logistic regression models were utilized to identify the association between several sociodemographic, lifestyle and health-related variables and vaccine uptake by age four. Results: By the ages of four and ten, 37% and 40% of the children, respectively, had received at least one influenza vaccination. Only 2% of the children were vaccinated for all winter seasons during their first four years of life. The vaccination rate was highest at the age of two and during the 2009–2010 season. Vaccination rates for children with asthma and obesity were 18.2% and 13.3% at age four and 8.3% and 2.9% at age ten. About 10% of all vaccines were administered after December and 24% of the children received only one dose upon initial vaccination. Children with younger siblings and those who had experienced more respiratory infections were more likely to be vaccinated by the age of four, while children exposed to smoking were less likely to be vaccinated. Conclusions: Children in our study were more likely to be vaccinated against influenza at an early age with the peak occurring at the age of two. Nonetheless, annual vaccination uptake was uncommon. Vaccination rates of children with asthma and obesity were well below the national target of 75% for individuals with chronic conditions. Certain groups may merit increased attention in future vaccination campaigns such as children raised in families with unfavourable health behaviours.

Background: Urban environmental design is increasingly considered influential for health and wellbeing, but evidence is mostly based on adults and single exposure studies. We evaluated the association between a wide range of urban environment characteristics and health behaviours in childhood. Methods: We estimated exposure to 32 urban environment characteristics (related to the built environment, traffic, and natural spaces) for home and school addresses of 1,581 children aged 6–11 years from six European cohorts. We collected information on health behaviours including total amount of overall moderate-to-vigorous physical activity, physical activity outside school hours, active transport, sedentary behaviours and sleep duration, and developed patterns of behaviours with principal component analysis. We used an exposure-wide association study to screen all exposure-outcome associations, and the deletion-substitution-addition algorithm to build a final multi-exposure model. Results: In multi-exposure models, green spaces (Normalized Difference Vegetation Index, NDVI) were positively associated with active transport, and inversely associated with sedentary time (22.71 min/day less (95 %CI −39.90, −5.51) per interquartile range increase in NDVI). Residence in densely built areas was associated with more physical activity and less sedentary time, and densely populated areas with less physical activity outside school hours and more sedentary time. Presence of a major road was associated with lower sleep duration (-4.80 min/day (95 %CI −9.11, −0.48); compared with no major road). Results for the behavioural patterns were similar. Conclusions: This multicohort study suggests that areas with more vegetation, more building density, less population density and without major roads are associated with improved health behaviours in childhood.

Abstract Background Child blood pressure (BP) is predictive of future cardiovascular risk. Prenatal exposure to metals has been associated with higher BP in childhood, but most studies have evaluated elements individually and measured BP at a single time point. We investigated impacts of prenatal metal mixture exposures on longitudinal changes in BP during childhood and elevated BP at 11 years of age. Methods The current study included 176 mother-child pairs from the Rhea Study in Heraklion, Greece and focused on eight elements (antimony, arsenic, cadmium, cobalt, lead, magnesium, molybdenum, selenium) measured in maternal urine samples collected during pregnancy (median gestational age at collection: 12 weeks). BP was measured at approximately 4, 6, and 11 years of age. Covariate-adjusted Bayesian Varying Coefficient Kernel Machine Regression and Bayesian Kernel Machine Regression (BKMR) were used to evaluate metal mixture impacts on baseline and longitudinal changes in BP (from ages 4 to 11) and the development of elevated BP at age 11, respectively. BKMR results were compared using static versus percentile-based cutoffs to define elevated BP. Results Molybdenum and lead were the mixture components most consistently associated with BP. J-shaped relationships were observed between molybdenum and both systolic and diastolic BP at age 4. Similar associations were identified for both molybdenum and lead in relation to elevated BP at age 11. For molybdenum concentrations above the inflection points (~ 40–80 μg/L), positive associations with BP at age 4 were stronger at high levels of lead. Lead was positively associated with BP measures at age 4, but only at high levels of molybdenum. Potential interactions between molybdenum and lead were also identified for BP at age 11, but were sensitive to the cutoffs used to define elevated BP. Conclusions Prenatal exposure to high levels of molybdenum and lead, particularly in combination, may contribute to higher BP at age 4. These early effects appear to persist throughout childhood, contributing to elevated BP in adolescence. Future studies are needed to identify the major sources of molybdenum and lead in this population.

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: In utero exposure to bisphenols, widely used in consumer products, may alter lung development and increase the risk of respiratory morbidity in the offspring. However, evidence is scarce and mostly focused on bisphenol A (BPA) only. Objective: To examine the associations of in utero exposure to BPA, bisphenol F (BPF), and bisphenol S (BPS) with asthma, wheeze, and lung function in school-age children, and whether these associations differ by sex. Methods: We included 3,007 mother–child pairs from eight European birth cohorts. Bisphenol concentrations were determined in maternal urine samples collected during pregnancy (1999–2010). Between 7 and 11 years of age, current asthma and wheeze were assessed from questionnaires and lung function by spirometry. Wheezing patterns were constructed from questionnaires from early to mid-childhood. We performed adjusted random-effects meta-analysis on individual participant data. Results: Exposure to BPA was prevalent with 90% of maternal samples containing concentrations above detection limits. BPF and BPS were found in 27% and 49% of samples. In utero exposure to BPA was associated with higher odds of current asthma (OR = 1.13, 95% CI = 1.01, 1.27) and wheeze (OR = 1.14, 95% CI = 1.01, 1.30) (p-interaction sex = 0.01) among girls, but not with wheezing patterns nor lung function neither in overall nor among boys. We observed inconsistent associations of BPF and BPS with the respiratory outcomes assessed in overall and sex-stratified analyses. Conclusion: This study suggests that in utero BPA exposure may be associated with higher odds of asthma and wheeze among school-age girls.

Background: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children’s blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods: Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results: We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at

Background: The urban environment may influence neurodevelopment from conception onwards, but there is no evaluation of the impact of multiple groups of exposures simultaneously. We investigated the association between early-life urban environment and cognitive and motor function in children. Methods: We used data from 5403 mother–child pairs from four population-based birth-cohorts (UK, France, Spain, and Greece). We estimated thirteen urban home exposures during pregnancy and childhood, including: built environment, natural spaces, and air pollution. Verbal, non-verbal, gross motor, and fine motor functions were assessed using validated tests at five years old. We ran adjusted multi-exposure models using the Deletion-Substitution-Addition algorithm. Results: Higher greenness exposure within 300 m during pregnancy was associated with higher verbal abilities (1.5 points (95% confidence interval 0.4, 2.7) per 0.20 unit increase in greenness). Higher connectivity density within 100 m and land use diversity during pregnancy were related to lower verbal abilities. Childhood exposure to PM2.5 mediated 74% of the association between greenness during childhood and verbal abilities. Higher exposure to PM2.5 during pregnancy was related to lower fine motor function (-1.2 points (-2.1, -0.4) per 3.2 μg/m3 increase in PM2.5). No associations were found with non-verbal abilities and gross motor function. Discussion: This study suggests that built environment, greenness, and air pollution may impact child cognitive and motor function at five years old. This study adds evidence that well-designed urban planning may benefit children’s cognitive and motor development.

Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1H NMR spectroscopy in a multicountry study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N-methylnicotinic acid, urea, and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food consumption and also had higher capacity in discriminating children’s diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.

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.

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.

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

Abstract 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-deoxyerythronic 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.

Post-partum depression (PPD) is a severe psychiatric disorder affecting ∼15% of young mothers. Early life stressful conditions in periconceptual, fetal and early infant periods or exposure to maternal psychiatric disorders, have been linked to adverse childhood outcomes interfering with physiological, cognitive and emotional development. The molecular mechanisms of PPD are not yet fully understood. Unraveling the molecular underpinnings of PPD will allow timely detection and establishment of effective therapeutic approaches. To investigate the underlying molecular correlates of PPD in peripheral material, we compared the serum metabolomes of an in detail characterized group of mothers suffering from PPD and a control group of mothers, all from Heraklion, Crete in Greece. Serum samples were analyzed by a mass spectrometry platform for targeted metabolomics, based on selected reaction monitoring (SRM), which measures the levels of up to 300 metabolites. In the PPD group, we observed increased levels of glutathione-disulfide, adenylosuccinate, and ATP, which associate with oxidative stress, nucleotide biosynthesis and energy production pathways. We also followed up the metabolomic findings in a validation cohort of PPD mothers and controls. To the very best of our knowledge, this is the first metabolomic serum analysis in PPD. Our data show that molecular changes related to PPD are detectable in peripheral material, thus paving the way for additional studies in order to shed light on the molecular correlates of PPD.

Few studies have investigated longitudinal associations between early life phthalate exposure and subsequent obesity and cardiovascular risks in children with inconsistent results. We aimed to evaluate the associations between phthalate exposure during gestation and childhood with offspring obesity and cardiometabolic risk factors in 500 mother-child pairs from the Rhea pregnancy cohort in Crete, Greece. Seven phthalate metabolites [monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), monobenzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP)] were quantified in spot urine samples collected from mothers (1st trimester) and their children at 4 years of age. We calculated the molar sum of DEHP metabolites (MEHP, MEHHP, MEOHP). We measured child weight, height, waist circumference, skinfold thicknesses, blood pressure (BP), and lipids at 4 and 6 years and leptin, adiponectin, and C-reactive protein at 4 years. We used generalized estimating equations to examine associations at each age and tested for interaction by sex. Child exposure to phthalate metabolites was associated with lower BMI z-scores in boys and higher BMI z-scores in girls. Each 10-fold increase in ΣDEHP was associated with a change in waist circumference of −2.6 cm (95% CI: −4.72, −0.48) in boys vs. 2.14 cm (95% CI: −0.14, 4.43) in girls (p-sex interaction = 0.003) and a change in waist-to-height ratio of −0.01 (95% CI: −0.03, 0.01) in boys vs. 0.02 (95% CI: 0.01, 0.04) in girls (p-sex interaction = 0.006). Phthalate metabolite concentrations at age 4 were negatively associated with systolic and diastolic blood pressure. MEP was associated with lower systolic BP z-scores (adj. β = −0.22; 95% CI: −0.36, −0.08) at 4 years. MnBP and MBzP were associated with lower diastolic BP z-scores (adj. β = −0.13; 95%CI: −0.23, −0.04, and adj. β = −0.11; 95% CI: −0.21, −0.01, respectively). A 10-fold increase in MiBP was associated with 4.4% higher total cholesterol levels (95% CI: 0.2, 8.7). Prenatal phthalate exposure was not consistently associated with child adiposity and cardiometabolic measures. Our findings suggest that early life phthalate exposure may affect child growth and adiposity in a sex-specific manner and depends on the timing of exposure.

Background: Persistent organic pollutants (POPs), including polychlorinated biphenyls (PCBs) and pesticides bioaccumulate through the food chain and cross the placenta. POPs are developmental toxicants in animals but the epidemiological evidence on pregnancy outcomes is inconsistent. Maternal gestational weight gain has been recently suggested as a key factor explaining the association between PCBs with lower birth weight. Aims: We examined whether in utero exposure to current low levels of different POPs is associated with fetal growth and gestational age in a mother–child cohort in Crete, Greece (Rhea study), and evaluated specifically whether maternal gestational weight gain may affect this association. Methods: We included 1117 mothers and their newborns from the Rhea study. Mothers were interviewed and blood samples collected during the first trimester of pregnancy. Information on birth outcomes was retrieved from medical records. Concentrations of several PCBs, other organochlorine compounds (dichlorodiphenyl dichloroethene [DDE], dichlorodiphenyl trichloroethane [DDT] and hexachlorobenzene [HCB]) and one polybrominated diphenyl ether congener (tetra-bromodiphenyl ether [BDE-47]), were determined in maternal serum by triple quadrupole mass spectrometry. Multiple linear regression models were used to investigate the associations of birth weight, gestational age, and head circumference with each compound individually on the log10 scale, and with combined exposures through the development of an exposure score. Results: In multivariate models, birth weight was negatively associated with increasing levels of HCB (β = −161.1 g; 95% CI: −296.6, −25.7) and PCBs (β = −174.1 g; 95% CI: −332.4, −15.9); after further adjustment for gestational weight gain these estimates were slightly reduced (β = −154.3 g; 95% CI: −300.8, −7.9 for HCB and β = −135.7 g; 95% CI: −315.4, 43.9 for PCBs). Furthermore, in stratified analysis, the association between POPs and birth weight was only observed in women with inadequate or excessive gestational weight gain. Small, negative associations were observed with head circumference while no association was observed with gestational age. Conclusions: The findings suggest that prenatal exposure to PCBs and HCB impairs fetal growth and adds to the growing literature that demonstrates an association between low-level environmental pollutant exposure and fetal growth. Furthermore our results suggest that the association of POPs, maternal gestational weight gain and birth weight is probably more complex than that previously hypothesized. Keywords: Persistent organic pollutants, PCBs, HCB, Birth outcomes, Gestational weight gain, Cohort studies