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Environmental factors, here taken to include pollutants, lifestyle factors and behaviours, can play an important role in serious, chronic pathologies with large societal and economic costs, including respiratory disease. However, measurement of the environmental component in epidemiological studies has traditionally relied on much more uncertain and incomplete assessments than measurement of the genome. The ‘exposome’ has therefore been proposed as a new paradigm to encompass the totality of human environmental (meaning all non-genetic) exposures from conception onwards, complementing the genome. Evidently, there are large challenges in developing the exposome concept into a workable approach for epidemiological research. These include: (1) the accurate and reliable measurement of many exposures in the external environment, (2) the measurement of a wide range of biological responses in the internal environment, and (3) addressing the dynamic, life course nature of the exposome. New tools and technologies that can be applied to address these challenges include exposure biomarker technologies, geographical mapping and remote sensing technologies, smartphone applications and personal exposure sensors, and high-throughput molecular ‘omics’ techniques. Prospective, population-based cohort studies have recently started to implement these methods using the exposome framework. The exposome thus offers a new and exciting paradigm for improvement and integration of currently scattered and uncertain data on the environmental component in disease aetiology. This should lead to a better understanding of the role of environmental risk factors in respiratory disease and other chronic pathologies, and ultimately to better primary prevention strategies.

The exposome represents the totality of life course environmental exposures (including lifestyle and other non-genetic factors), from the prenatal period onwards. This holistic concept of exposure provides a new framework to advance the understanding of complex and multifactorial diseases. Prospective pregnancy and birth cohort studies provide a unique opportunity for exposome research as they are able to capture, from prenatal life onwards, both the external (including lifestyle, chemical, social and wider community-level exposures) and the internal (including inflammation, metabolism, epigenetics, and gut microbiota) domains of the exposome. In this paper, we describe the steps required for applying an exposome approach, describe the main strengths and limitations of different statistical approaches and discuss their challenges, with the aim to provide guidance for methodological choices in the analysis of exposome data in birth cohort studies. An exposome approach implies selecting, pre-processing, describing and analyzing a large set of exposures. Several statistical methods are currently available to assess exposome-health associations, which differ in terms of research question that can be answered, of balance between sensitivity and false discovery proportion, and between computational complexity and simplicity (parsimony). Assessing the association between many exposures and health still raises many exposure assessment issues and statistical challenges. The exposome favors a holistic approach of environmental influences on health, which is likely to allow a more complete understanding of disease etiology.

Environmental exposures during early life play a critical role in life-course health, yet the molecular phenotypes underlying environmental effects on health are poorly understood. In the Human Early Life Exposome (HELIX) project, a multi-centre cohort of 1301 mother-child pairs, we associate individual exposomes consisting of >100 chemical, outdoor, social and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, proteins and metabolites) in childhood. We identify 1170 associations, 249 in pregnancy and 921 in childhood, which reveal potential biological responses and sources of exposure. Pregnancy exposures, including maternal smoking, cadmium and molybdenum, are predominantly associated with child DNA methylation changes. In contrast, childhood exposures are associated with features across all omics layers, most frequently the serum metabolome, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions, among others. Our comprehensive and unique resource of all associations ( https://helixomics.isglobal.org/ ) will serve to guide future investigation into the biological imprints of the early life exposome. 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.

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

Pregnant women and children are especially vulnerable to exposures to food contaminants, and a balanced diet during these periods is critical for optimal nutritional status. Our objective was to study the association between diet and measured blood and urinary levels of environmental contaminants in mother-child pairs from six European birth cohorts ( mothers and 1,288 children). We assessed the consumption of seven food groups and the blood levels of organochlorine pesticides, polybrominated diphenyl ethers, polychlorinated biphenyls (PCBs), per- and polyfluoroalkyl substances (PFAS), and heavy metals and urinary levels of phthalate metabolites, phenolic compounds, and organophosphate pesticide (OP) metabolites. Organic food consumption during childhood was also studied. We applied multivariable linear regressions and targeted maximum likelihood based estimation (TMLE). Maternal high ( ) versus low ( ) fish consumption was associated with 15% higher PCBs [geometric mean (GM) ; 95% confidence interval (CI): 1.02, 1.29], 42% higher perfluoroundecanoate (PFUnDA) ( ; 95% CI: 1.20, 1.68), 89% higher mercury (Hg) ( ; 95% CI: 1.47, 2.41) and a 487% increase in arsenic (As) ( ; 95% CI: 2.57, 9.23) levels. In children, high ( ) versus low ( ) fish consumption was associated with 23% higher perfluorononanoate (PFNA) ( ; 95% CI: 1.08, 1.40), 36% higher PFUnDA ( ; 95% CI: 1.12, 1.64), 37% higher perfluorooctane sulfonate (PFOS) ( ; 95% CI: 1.22, 1.54), and higher Hg and As [ (95% CI: 1.91, 4.31) and (95% CI: 2.23, 3.21)] concentrations. Using TMLE analysis, we estimated that fish consumption within the recommended 2-3 times/week resulted in lower PFAS, Hg, and As compared with higher consumption. Fruit consumption was positively associated with OP metabolites. Organic food consumption was negatively associated with OP metabolites. Fish consumption is related to higher PFAS, Hg, and As exposures. In addition, fruit consumption is a source of exposure to OPs. https://doi.org/10.1289/EHP5324.

Prenatal exposure to endocrine-disrupting chemicals (EDCs) may induce weight gain and obesity in children, but the obesogenic effects of mixtures have not been studied. We evaluated the associations between pre- and perinatal biomarker concentrations of 27 EDCs and child weight status at 7 years of age. In pregnant women enrolled in a Spanish birth cohort study between 2004 and 2006, we measured the concentrations of 10 phthalate metabolites, bisphenol A, cadmium, arsenic, and lead in two maternal pregnancy urine samples; 6 organochlorine compounds in maternal pregnancy serum; mercury in cord blood; and 6 polybrominated diphenyl ether congeners in colostrum. Among 470 children at 7 years, body mass index (BMI) z-scores were calculated, and overweight was defined as BMI > 85th percentile. We estimated associations with EDCs in single-pollutant models and applied principal-component analysis (PCA) on the 27 pollutant concentrations. In single-pollutant models, HCB (hexachlorobenzene), βHCH (β-hexachlorocyclohexane), and polychlorinated biphenyl (PCB) congeners 138 and 180 were associated with increased child BMI z-scores; and HCB, βHCH, PCB-138, and DDE (dichlorodiphenyldichloroethylene) with overweight risk. PCA generated four factors that accounted for 43.4% of the total variance. The organochlorine factor was positively associated with BMI z-scores and with overweight (adjusted RR, tertile 3 vs. 1: 2.59; 95% CI: 1.19, 5.63), and these associations were robust to adjustment for other EDCs. Exposure in the second tertile of the phthalate factor was inversely associated with overweight. Prenatal exposure to organochlorines was positively associated with overweight at age 7 years in our study population. Other EDCs exposures did not confound this association.

Exposure to perfluoroalkyl substances (PFASs) may increase risk for metabolic diseases; however, epidemiologic evidence is lacking at the present time. Pregnancy is a period of enhanced tissue plasticity for the fetus and the mother and may be a critical window of PFAS exposure susceptibility. We evaluated the associations between PFAS exposures and metabolic outcomes in pregnant women. We analyzed 1,240 pregnant women from the Spanish INMA [Environment and Childhood Project (INfancia y Medio Ambiente)] birth cohort study (recruitment period: 2003-2008) with measured first pregnancy trimester plasma concentrations of four PFASs (in nanograms/milliliter). We used logistic regression models to estimate associations of PFASs (log -transformed and categorized into quartiles) with impaired glucose tolerance (IGT) and gestational diabetes mellitus (GDM), and we used linear regression models to estimate associations with first-trimester serum levels of triglycerides, total cholesterol, and C-reactive protein (CRP). Perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS) were positively associated with IGT (137 cases) [OR per log -unit increase=1.99 (95% CI: 1.06, 3.78) and OR=1.65 ( 95% CI: 0.99, 2.76), respectively]. PFOS and PFHxS associations with GDM (53 cases) were in a similar direction, but less precise. PFOS and perfluorononanoate (PFNA) were negatively associated with triglyceride levels [percent median change per log -unit increase=-5.86% (95% CI: -9.91%, -1.63%) and percent median change per log -unit increase=-4.75% (95% CI: -8.16%, -0.61%, respectively], whereas perfluorooctanoate (PFOA) was positively associated with total cholesterol [percent median change per log -unit increase=1.26% (95% CI: 0.01%, 2.54%)]. PFASs were not associated with CRP in the subset of the population with available data ( =640). Although further confirmation is required, the findings from this study suggest that PFAS exposures during pregnancy may influence lipid metabolism and glucose tolerance and thus may impact the health of the mother and her child. https://doi.org/10.1289/EHP1062.

Human evidence on the effects of early life phthalate exposure on obesity and cardiovascular disease risks, reported by experimental studies, is limited to a few cross-sectional studies. We evaluated the associations between prenatal phthalate exposure and childhood growth and blood pressure in a Spanish birth cohort study. We assessed exposure using the average of two phthalate metabolite spot-urine concentrations collected from the mothers in the first and third pregnancy trimesters (creatinine-adjusted, n = 391). Study outcomes were the difference in age- and sex-specific z-scores for weight between birth and 6 months of age; and repeated age- and sex-specific z-scores for body mass index (BMI) at 1, 4, and 7 years; waist-to-height ratio at 4 and 7 years; and age- and height-specific z-scores for systolic and diastolic blood pressure at 4 and 7 years. The sum of five high-molecular-weight phthalate metabolites (ΣHMWPm) was associated with lower weight z-score difference between birth and 6 months (β per doubling of exposure = -0.41; 95% CI: -0.75, -0.06) and BMI z-scores at later ages in boys (β = -0.28; 95% CI: -0.60, 0.03) and with higher weight z-score difference (β = 0.24; 95% CI: -0.16, 0.65) and BMI z-scores in girls (β = 0.30; 95% CI: -0.04, 0.64) (p for sex interaction = 0.01 and 0.05, respectively). The sum of three low-molecular-weight phthalates (ΣLMWPm) was not significantly associated with any of the growth outcomes. ΣHMWPm and ΣLMWPm were associated with lower systolic blood pressure z-scores in girls but not in boys. This study suggests that prenatal phthalate exposure may be associated with postnatal growth and blood pressure in a sex-specific manner. Inconsistencies with previous cross-sectional findings highlight the necessity for evaluating phthalate health effects in prospective studies.

Objective: We systematically reviewed epidemiologic studies on ambient air pollution and congenital anomalies and conducted meta-analyses for a number of air pollutant—anomaly combinations. Data sources and extraction: From bibliographic searches we extracted 10 original epidemiologic studies that examined the association between congenital anomaly risk and concentrations of air pollutants. Meta-analyses were conducted if at least four studies published risk estimates for the same pollutant and anomaly group. Summary risk estimates were calculated for a) risk at high versus low exposure level in each study and b) risk per unit increase in continuous pollutant concentration. Data synthesis: Each individual study reported statistically significantly increased risks for some combinations of air pollutants and congenital anomalies, among many combinations tested. In meta-analyses, nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) exposures were related to increases in risk of coarctation of the aorta [odds ratio (OR) per 10 ppb NO₂= 1.17; 95% confidence interval (CI), 1.00-1.36; OR per 1 ppb SO, = 1.07; 95% CI, 1.01-1.13] and tetralogy of Fallot (OR per 10 ppb NO₂ = 1.20; 95% CI, 1.02-1.42; OR per 1 ppb SO?₂ = 1.03; 95% CI, 1.01-1.05), and PM₁₀ (paniculate matter ≤ 10 μrn) exposure was related to an increased risk of atrial septal defects (OR per 10 μg/m³ = 1.14; 95% CI, 1.01-1.28). Meta-analyses found no statistically significant increase in risk of other cardiac anomalies and oral clefts. Conclusions: We found some evidence for an effect of ambient air pollutants on congenital cardiac anomaly risk. Improvements in the areas of exposure assessment, outcome harmonization, assessment of other congenital anomalies, and mechanistic knowledge are needed to advance this field.

BackgroundAmbient air pollution may play a role in childhood obesity development, but evidence is scarce, and the modifying role of socioeconomic status (SES) is unclear. We aimed to examine the association between exposure to air pollution during early childhood and subsequent risk of developing overweight and obesity, and to evaluate whether SES is a modifier of this association.MethodsThis longitudinal study included 416,955 children identified as normal weight between 2–5 years old and registered in an electronic primary healthcare record between 2006 and 2016 in Catalonia (Spain). Children were followed-up until they developed overweight or obesity, reached 15 years of age, died, transferred out, or end of study period (31/12/2018). Overweight and obesity were defined following the WHO reference obtained from height and weight measures. We estimated annual residential census levels of nitrogen dioxide (NO2) and particulate matter <10 μm (PM10), <2.5 μm (PM2.5), and 2.5–10 μm (PMcoarse) at study entry. We estimated the risk of developing overweight and obesity per interquartile range increase in air pollution exposure with Cox proportional hazard models.ResultsA total of 142,590 (34.2%) children developed overweight or obesity. Increased exposure to NO2, PM10, and PMcoarse was associated with a 2–3% increased risk of developing overweight and obesity (hazard ratio [HR] per 21.8 μg/m3 NO2 = 1.03 [95% CI: 1.02–1.04]; HR per 6.4 μg/m3 PM10 = 1.02 [95% CI: 1.02–1.03]; HR per 4.6 µg/m3 PMcoarse = 1.02, [95% CI: 1.01–1.02]). For all air pollutants, associations were stronger among children living in most compared to least deprived areas.ConclusionsThis study suggests that early life exposure to air pollution may be associated with a small increase in the risk of developing overweight and obesity in childhood, and that this association may be exacerbated in the most deprived areas. Even these small associations are of potential global health importance because air pollution exposure is widespread and the long-term health consequences of childhood obesity are clear.