Environmental pollutant risk factors for worse COVID-19 related clinical outcomes in predominately hispanic and latino populations.

BACKGROUND: Per- and poly-fluorinated compounds (PFAS) and heavy metals constitute two classes of environmental exposures with known immunotoxicant effects. In this pilot study, we aimed to evaluate the impact of exposure to heavy metals and PFAS on COVID-19 severity. We hypothesized that elevated plasma-PFAS concentrations and urinary heavy metal concentrations would be associated with increased odds of ICU admission in COVID-19 hospitalized individuals. METHODS: Using the University of Southern California Clinical Translational Sciences Institute (SC-CTSI) biorepository of hospitalized COVID-19 patients, urinary concentrations of 15 heavy metals and urinary creatinine were measured in n = 101 patients and plasma concentrations of 13 PFAS were measured in n = 126 patients. COVID-19 severity was determined based on whether a patient was admitted to the ICU during hospitalization. Associations of metals and PFAS with ICU admission were assessed using logistic regression models, controlling for age, sex, ethnicity, smoking status, and for metals, urinary dilution. RESULTS: The average age of patients was 55 ± 14.2 years. Among SC-CTSI participants with urinary measurement of heavy metals and blood measures of PFAS, 54.5% (n = 61) and 54.8% (n = 80) were admitted to the ICU, respectively. For heavy metals, we observed higher levels of Cd, Cr, and Cu in ICU patients. The strongest associations were with Cadmium (Cd). After accounting for covariates, each 1 SD increase in Cd resulted in a 2.00 (95% CI: 1.10-3.60; p = 0.03) times higher odds of admission to the ICU. When including only Hispanic or Latino participants, the effect estimates between cadmium and ICU admission remained similar. Results for PFAS were less consistent, with perfluorodecanesulfonic acid (PFDS) exhibiting a positive but non-significant association with ICU admission (Odds ratio, 95% CI: 1.50, 0.97-2.20) and perfluorodecanoic acid (PFDA) exhibiting a negative association with ICU admission (0.53, 0.31-0.88). CONCLUSIONS: This study supports the hypothesis that environmental exposures may impact COVID-19 severity.

Metal mixture exposures and serum lipid levels in childhood: the Rhea mother-child cohort in Greece.

BACKGROUND: Growing evidence suggests that cardiovascular disease develops over the lifetime, often beginning in childhood. Metal exposures have been associated with cardiovascular disease and important risk factors, including dyslipidemia, but prior studies have largely focused on adult populations and single metal exposures. OBJECTIVE: To investigate the individual and joint impacts of multiple metal exposures on lipid levels during childhood. METHODS: This cross-sectional study included 291 4-year-old children from the Rhea Cohort Study in Heraklion, Greece. Seven metals (manganese, cobalt, selenium, molybdenum, cadmium, mercury, and lead) were measured in whole blood using inductively coupled plasma mass spectrometry. Serum lipid levels included total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol. To determine the joint and individual impacts of child metal exposures (log2-transformed) on lipid levels, Bayesian kernel machine regression (BKMR) was employed as the primary multi-pollutant approach. Potential effect modification by child sex and childhood environmental tobacco smoke exposure was also evaluated. RESULTS: BKMR identified a positive association between the metal mixture and both total and LDL cholesterol. Of the seven metals examined, selenium (median 90.6 [IQR = 83.6, 96.5] µg/L) was assigned the highest posterior inclusion probability for both total and LDL cholesterol. A difference in LDL cholesterol of 8.22 mg/dL (95% CI = 1.85, 14.59) was observed when blood selenium was set to its 75th versus 25th percentile, holding all other metals at their median values. In stratified analyses, the positive association between selenium and LDL cholesterol was only observed among boys or among children exposed to environmental tobacco smoke during childhood. IMPACT STATEMENT: Growing evidence indicates that cardiovascular events in adulthood are the consequence of the lifelong atherosclerotic process that begins in childhood. Therefore, public health interventions targeting childhood cardiovascular risk factors may have a particularly profound impact on reducing the burden of cardiovascular disease. Although growing evidence supports that both essential and nonessential metals contribute to cardiovascular disease and risk factors, such as dyslipidemia, prior studies have mainly focused on single metal exposures in adult populations. To address this research gap, the current study investigated the joint impacts of multiple metal exposures on lipid concentrations in early childhood.

Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children.

Importance: Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. Objective: To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. Design, Setting, and Participants: This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Exposures: Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. Main Outcomes and Measures: At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. Results: The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (ß = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (ß = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (ß = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (ß = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (ß = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (ß = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. Conclusions and Relevance: This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.

Machine learning-based health environmental-clinical risk scores in European children.

BACKGROUND: Early life environmental stressors play an important role in the development of multiple chronic disorders. Previous studies that used environmental risk scores (ERS) to assess the cumulative impact of environmental exposures on health are limited by the diversity of exposures included, especially for early life determinants. We used machine learning methods to build early life exposome risk scores for three health outcomes using environmental, molecular, and clinical data. METHODS: In this study, we analyzed data from 1622 mother-child pairs from the HELIX European birth cohorts, using over 300 environmental, 100 child peripheral, and 18 mother-child clinical markers to compute environmental-clinical risk scores (ECRS) for child behavioral difficulties, metabolic syndrome, and lung function. ECRS were computed using LASSO, Random Forest and XGBoost. XGBoost ECRS were selected to extract local feature contributions using Shapley values and derive feature importance and interactions. RESULTS: ECRS captured 13%, 50% and 4% of the variance in mental, cardiometabolic, and respiratory health, respectively. We observed no significant differences in predictive performances between the above-mentioned methods.The most important predictive features were maternal stress, noise, and lifestyle exposures for mental health; proteome (mainly IL1B) and metabolome features for cardiometabolic health; child BMI and urine metabolites for respiratory health. CONCLUSIONS: Besides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.

Growing up in different environments can greatly affect children's health later in life. This research looked at how living in cities, being exposed to chemicals, and other experiences before birth and during childhood, work together to influence children's mental, cardiovascular and respiratory health. We used advanced computer programs to help us understand these effects and estimate health risk scores. These scores are simple numerical measures that help us quantify the likelihood of children developing health issues based on their environmental exposures. Using those scores, the study identified key factors impacting children's health, in particular psycho-social, perceived environmental and prenatal pollutant exposures for mental health. It also revealed complex patterns and interactions between environmental factors. The results highlighted the potential of such risk scores to support the identification of actionable factors in high-risk children, informing tailored prevention measures in healthcare.

Risk Factors for Thyroid Dysfunction in Pregnancy: An Individual Participant Data Meta-Analysis.

Background: International guidelines recommend targeted screening to identify gestational thyroid dysfunction. However, currently used risk factors have questionable discriminative ability. We quantified the risk for thyroid function test abnormalities for a subset of risk factors currently used in international guidelines. Methods: We included prospective cohort studies with data on gestational maternal thyroid function and potential risk factors (maternal age, body mass index [BMI], parity, smoking status, pregnancy through in vitro fertilization, twin pregnancy, gestational age, maternal education, and thyroid peroxidase antibody [TPOAb] or thyroglobulin antibody [TgAb] positivity). Exclusion criteria were pre-existing thyroid disease and use of thyroid interfering medication. We analyzed individual participant data using mixed-effects regression models. Primary outcomes were overt and subclinical hypothyroidism and a treatment indication (defined as overt hypothyroidism, subclinical hypothyroidism with thyrotropin >10 mU/L, or subclinical hypothyroidism with TPOAb positivity). Results: The study population comprised 65,559 participants in 25 cohorts. The screening rate in cohorts using risk factors currently recommended (age >30 years, parity ≥2, BMI ≥40) was 58%, with a detection rate for overt and subclinical hypothyroidism of 59%. The absolute risk for overt or subclinical hypothyroidism varied <2% over the full range of age and BMI and for any parity. Receiver operating characteristic curves, fitted using maternal age, BMI, smoking status, parity, and gestational age at blood sampling as explanatory variables, yielded areas under the curve ranging from 0.58 to 0.63 for the primary outcomes. TPOAbs/TgAbs positivity was associated with overt hypothyroidism (approximate risk for antibody negativity 0.1%, isolated TgAb positivity 2.4%, isolated TPOAb positivity 3.8%, combined antibody positivity 7.0%; p < 0.001), subclinical hypothyroidism (risk for antibody negativity 2.2%, isolated TgAb positivity 8.1%, isolated TPOAb positivity 14.2%, combined antibody positivity 20.0%; p < 0.001) and a treatment indication (risk for antibody negativity 0.2%, isolated TgAb positivity 2.2%, isolated TPOAb positivity 3.0%, and combined antibody positivity 5.1%; p < 0.001). Twin pregnancy was associated with a higher risk of overt hyperthyroidism (5.6% vs. 0.7%; p < 0.001). Conclusions: The risk factors assessed in this study had poor predictive ability for detecting thyroid function test abnormalities, questioning their clinical usability for targeted screening. As expected, TPOAb positivity (used as a benchmark) was a relevant risk factor for (subclinical) hypothyroidism. These results provide insights into different risk factors for gestational thyroid dysfunction.

Associations of dietary intake and longitudinal measures of per- and polyfluoroalkyl substances (PFAS) in predominantly Hispanic young Adults: A multicohort study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are pollutants linked to adverse health effects. Diet is an important source of PFAS exposure, yet it is unknown how diet impacts longitudinal PFAS levels. OBJECTIVE: To determine if dietary intake and food sources were associated with changes in blood PFAS concentrations among Hispanic young adults at risk of metabolic diseases. METHODS: Predominantly Hispanic young adults from the Children's Health Study who underwent two visits (CHS; n = 123) and young adults from NHANES 2013-2018 who underwent one visit (n = 604) were included. Dietary data at baseline was collected using two 24-hour dietary recalls to measure individual foods and where foods were prepared/consumed (home/restaurant/fast-food). PFAS were measured in blood at both visits in CHS and cross-sectionally in NHANES. In CHS, multiple linear regression assessed associations of baseline diet with longitudinal PFAS; in NHANES, linear regression was used. RESULTS: In CHS, all PFAS except PFDA decreased across visits (all p < 0.05). In CHS, A 1-serving higher tea intake was associated with 24.8 %, 16.17 %, and 12.6 % higher PFHxS, PFHpS, and PFNA at follow-up, respectively (all p < 0.05). A 1-serving higher pork intake was associated with 13.4 % higher PFOA at follow-up (p < 0.05). Associations were similar in NHANES, including unsweetened tea, hot dogs, and processed meats. For food sources, in CHS each 200-gram increase in home-prepared food was associated with 0.90 % and 1.6 % lower PFOS at baseline and follow-up, respectively, and in NHANES was associated with 0.9 % lower PFDA (all p < 0.05). CONCLUSION: Results suggest that beverage consumption habits and food preparation are associated with differences in PFAS levels in young adults. This highlights the importance of diet in determining PFAS exposure and the necessity of public monitoring of foods and beverages for PFAS contamination.

Postprandial Metabolite Profiles and Risk of Prediabetes in Young People: A Longitudinal Multicohort Study.

OBJECTIVE: Prediabetes in young people is an emerging epidemic that disproportionately impacts Hispanic populations. We aimed to develop a metabolite-based prediction model for prediabetes in young people with overweight/obesity at risk for type 2 diabetes. RESEARCH DESIGN AND METHODS: In independent, prospective cohorts of Hispanic youth (discovery; n = 143 without baseline prediabetes) and predominately Hispanic young adults (validation; n = 56 without baseline prediabetes), we assessed prediabetes via 2-h oral glucose tolerance tests. Baseline metabolite levels were measured in plasma from a 2-h postglucose challenge. In the discovery cohort, least absolute shrinkage and selection operator regression with a stability selection procedure was used to identify robust predictive metabolites for prediabetes. Predictive performance was evaluated in the discovery and validation cohorts using logistic regression. RESULTS: Two metabolites (allylphenol sulfate and caprylic acid) were found to predict prediabetes beyond known risk factors, including sex, BMI, age, ethnicity, fasting/2-h glucose, total cholesterol, and triglycerides. In the discovery cohort, the area under the receiver operator characteristic curve (AUC) of the model with metabolites and known risk factors was 0.80 (95% CI 0.72-0.87), which was higher than the risk factor-only model (AUC 0.63 [0.53-0.73]; P = 0.001). When the predictive models developed in the discovery cohort were applied to the replication cohort, the model with metabolites and risk factors predicted prediabetes more accurately (AUC 0.70 [95% CI 40.55-0.86]) than the same model without metabolites (AUC 0.62 [0.46-0.79]). CONCLUSIONS: Metabolite profiles may help improve prediabetes prediction compared with traditional risk factors. Findings suggest that medium-chain fatty acids and phytochemicals are early indicators of prediabetes in high-risk youth.

Association of Gestational Free and Total Triiodothyronine With Gestational Hypertension, Preeclampsia, Preterm Birth, and Birth Weight: An Individual Participant Data Meta-analysis.

CONTEXT: Triiodothyronine (T3) is the bioactive form of thyroid hormone. In contrast to thyroid-stimulating hormone and free thyroxine, we lack knowledge on the association of gestational T3 with adverse obstetric outcomes. OBJECTIVE: To investigate the associaiton of gestational free or total T3 (FT3 or TT3) with adverse obstetric outcomes. METHODS: We collected individual participant data from prospective cohort studies on gestational FT3 or TT3, adverse obstetric outcomes (preeclampsia, gestational hypertension, preterm birth and very preterm birth, small for gestational age [SGA], and large for gestational age [LGA]), and potential confounders. We used mixed-effects regression models adjusting for potential confounders. RESULTS: The final study population comprised 33 118 mother-child pairs of which 27 331 had data on FT3 and 16 164 on TT3. There was a U-shaped association of FT3 with preeclampsia (P = .0069) and a J-shaped association with the risk of gestational hypertension (P = .029). Higher TT3 was associated with a higher risk of gestational hypertension (OR per SD of TT3 1.20, 95% CI 1.08 to 1.33; P = .0007). A lower TT3 but not FT3 was associated with a higher risk of very preterm birth (OR 0.72, 95% CI 0.55 to 0.94; P = .018). TT3 but not FT3 was positively associated with birth weight (mean difference per 1 SD increase in TT3 12.8, 95% CI 6.5 to 19.1 g, P < .0001) but there was no association with SGA or LGA. CONCLUSION: This study provides new insights on the association of gestational FT3 and TT3 with major adverse pregnancy outcomes that form the basis for future studies required to elucidate the effects of thyroid function on pregnancy outcomes. Based on the current study, routine FT3 or TT3 measurements for the assessment of thyroid function during pregnancy do not seem to be of added value in the risk assessment for adverse outcomes.

Associations between combined urban and lifestyle factors and respiratory health in European children.

INTRODUCTION: Previous studies identified some environmental and lifestyle factors independently associated with children respiratory health, but few focused on exposure mixture effects. This study aimed at identifying, in pregnancy and in childhood, combined urban and lifestyle environment profiles associated with respiratory health in children. METHODS: This study is based on the European Human Early-Life Exposome (HELIX) project, combining six birth cohorts. Associations between profiles of pregnancy (38 exposures) and childhood (84 exposures) urban and lifestyle factors, identified by clustering analysis, and respiratory health were estimated by regression models adjusted for confounders. RESULTS: Among the 1033 included children (mean ± standard-deviation (SD) age: 8.2 ± 1.6 years old, 47% girls) the mean ± SD forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) were 99 ± 13% and 101 ± 14%, respectively, and 12%, 12% and 24% reported ever-asthma, wheezing and rhinitis, respectively. Four profiles of pregnancy exposures and four profiles of childhood exposures were identified. Compared to the reference childhood exposure profile (low exposures), two exposure profiles were associated with lower levels of FEV1. One profile was characterized by few natural spaces in the surroundings and high exposure to the built environment and road traffic. The second profile was characterized by high exposure to meteorological factors and low levels of all other exposures and was also associated with an increased risk of ever-asthma and wheezing. A pregnancy exposure profile characterized by high exposure levels to all risk factors, but a healthy maternal lifestyle, was associated with a lower risk of wheezing and rhinitis in children, compared to the reference pregnancy profile (low exposures). CONCLUSION: This comprehensive approach revealed pregnancy and childhood profiles of urban and lifestyle exposures associated with lung function and/or respiratory conditions in children. Our findings highlight the need to pursue the study of combined exposures to improve prevention strategies for multifactorial diseases such as asthma.

Beyond the single-outcome approach: A comparison of outcome-wide analysis methods for exposome research.

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.

The contribution to policies of an exposome-based approach to childhood obesity.

Childhood obesity is an increasingly severe public health problem, with a prospective impact on health. We propose an exposome approach to identify actionable risk factors for this condition. Our assumption is that relationships between external exposures and outcomes such as rapid growth, overweight, or obesity in children can be better understood through a "meet-in-the-middle" model. This is based on a combination of external and internal exposome-based approaches, that is, the study of multiple exposures (in our case, dietary patterns) and molecular pathways (metabolomics and epigenetics). This may strengthen causal reasoning by identifying intermediate markers that are associated with both exposures and outcomes. Our biomarker-based studies in the STOP consortium suggest (in several ways, including mediation analysis) that branched-chain amino acids (BCAAs) could be mediators of the effect of dietary risk factors on childhood overweight/obesity. This is consistent with intervention and animal studies showing that higher intake of BCAAs has a positive impact on body composition, glycemia, and satiety. Concerning food, of particular concern is the trend of increasing intake of ultra-processed food (UPF), including among children. Several mechanisms have been proposed to explain the impact of UPF on obesity and overweight, including nutrient intake (particularly proteins), changes in appetite, or the role of additives. Research from the Avon Longitudinal Study of Parents and Children cohort has shown a relationship between UPF intake and trajectories in childhood adiposity, while UPF was related to lower blood levels of BCAAs. We suggest that an exposome-based approach can help strengthening causal reasoning and support policies. Intake of UPF in children should be restricted to prevent obesity.

PFAS Exposures and the Human Metabolome: A Systematic Review of Epidemiological Studies.

Purpose of Review: There is a growing interest in understanding the health effects of exposure to per- and polyfluoroalkyl substances (PFAS) through the study of the human metabolome. In this systematic review, we aimed to identify consistent findings between PFAS and metabolomic signatures. We conducted a search matching specific keywords that was independently reviewed by two authors on two databases (EMBASE and PubMed) from their inception through July 19, 2022 following PRISMA guidelines. Recent Findings: We identified a total of 28 eligible observational studies that evaluated the associations between 31 different PFAS exposures and metabolomics in humans. The most common exposure evaluated was legacy long-chain PFAS. Population sample sizes ranged from 40 to 1,105 participants at different stages across the lifespan. A total of 19 studies used a non-targeted metabolomics approach, 7 used targeted approaches, and 2 included both. The majority of studies were cross-sectional (n = 25), including four with prospective analyses of PFAS measured prior to metabolomics. Summary: Most frequently reported associations across studies were observed between PFAS and amino acids, fatty acids, glycerophospholipids, glycerolipids, phosphosphingolipids, bile acids, ceramides, purines, and acylcarnitines. Corresponding metabolic pathways were also altered, including lipid, amino acid, carbohydrate, nucleotide, energy metabolism, glycan biosynthesis and metabolism, and metabolism of cofactors and vitamins. We found consistent evidence across studies indicating PFAS-induced alterations in lipid and amino acid metabolites, which may be involved in energy and cell membrane disruption.

Associations of Gestational Perfluoroalkyl Substances Exposure with Early Childhood BMI z-Scores and Risk of Overweight/Obesity: Results from the ECHO Cohorts.

BACKGROUND: Gestational per- and polyfluoroalkyl substances (PFAS) exposure may be associated with adiposity and increased risk of obesity among children and adolescents. However, results from epidemiological studies evaluating these associations are inconsistent. OBJECTIVES: We estimated the associations of pregnancy PFAS concentrations with child body mass index (BMI) z-scores and risk of overweight/obesity in eight U.S. cohorts. METHODS: We used data from 1,391 mother-child pairs who enrolled in eight Environmental influences on Child Health Outcomes (ECHO) cohorts (enrolled: 1999-2019). We quantified concentrations of seven PFAS in maternal plasma or serum in pregnancy. We measured child weight and height between the ages of 2 and 5 y and calculated age- and sex-specific BMI z-scores; 19.6% children had more than one BMI measurement. We estimated covariate-adjusted associations of individual PFAS and their mixture with child BMI z-scores and risk of overweight/obesity using linear mixed models, modified Poisson regression models, and Bayesian approaches for mixtures. We explored whether child sex modified these associations. RESULTS: We observed a pattern of subtle positive associations of PFAS concentrations in pregnancy with BMI z-scores and risk of overweight/obesity. For instance, each doubling in perfluorohexane sulfonic acid concentrations was associated with higher BMI z-scores (ß=0.07; 95% CI: 0.01, 0.12). Each doubling in perfluroundecanoic acid [relative risk (RR)=1.10; 95% CI: 1.04, 1.16] and N-methyl perfluorooctane sulfonamido acetic acid (RR=1.06; 95% CI: 1.00, 1.12) was associated with increased risk of overweight/obesity, with some evidence of a monotonic dose-response relation. We observed weaker and more imprecise associations of the PFAS mixture with BMI or risk of overweight/obesity. Associations did not differ by child sex. DISCUSSION: In eight U.S.-based prospective cohorts, gestational exposure to higher levels of PFAS were associated with slightly higher childhood BMI z-score and risk of overweight or obesity. Future studies should examine associations of gestational exposure to PFAS with adiposity and related cardiometabolic consequences in older children. https://doi.org/10.1289/EHP11545.

Prenatal environmental exposures associated with sex differences in childhood obesity and neurodevelopment.

BACKGROUND: Obesity and neurodevelopmental delay are complex traits that often co-occur and differ between boys and girls. Prenatal exposures are believed to influence children's obesity, but it is unknown whether exposures of pregnant mothers can confer a different risk of obesity between sexes, and whether they can affect neurodevelopment. METHODS: We analyzed data from 1044 children from the HELIX project, comprising 93 exposures during pregnancy, and clinical, neuropsychological, and methylation data during childhood (5-11 years). Using exposome-wide interaction analyses, we identified prenatal exposures with the highest sexual dimorphism in obesity risk, which were used to create a multiexposure profile. We applied causal random forest to classify individuals into two environments: E1 and E0. E1 consists of a combination of exposure levels where girls have significantly less risk of obesity than boys, as compared to E0, which consists of the remaining combination of exposure levels. We investigated whether the association between sex and neurodevelopmental delay also differed between E0 and E1. We used methylation data to perform an epigenome-wide association study between the environments to see the effect of belonging to E1 or E0 at the molecular level. RESULTS: We observed that E1 was defined by the combination of low dairy consumption, non-smokers' cotinine levels in blood, low facility richness, and the presence of green spaces during pregnancy (ORinteraction = 0.070, P = 2.59 × 10-5). E1 was also associated with a lower risk of neurodevelopmental delay in girls, based on neuropsychological tests of non-verbal intelligence (ORinteraction = 0.42, P = 0.047) and working memory (ORinteraction = 0.31, P = 0.02). In line with this, several neurodevelopmental functions were enriched in significant differentially methylated probes between E1 and E0. CONCLUSIONS: The risk of obesity can be different for boys and girls in certain prenatal environments. We identified an environment combining four exposure levels that protect girls from obesity and neurodevelopment delay. The combination of single exposures into multiexposure profiles using causal inference can help determine populations at risk.

Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic profiles: A panel study.

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.

Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study.

BACKGROUND: Exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous and has been associated with an increased risk of several cardiometabolic diseases. However, the metabolic pathways linking PFAS exposure and human disease are unclear. OBJECTIVE: We examined associations of PFAS mixtures with alterations in metabolic pathways in independent cohorts of adolescents and young adults. METHODS: Three hundred twelve overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) and 137 young adults from the Southern California Children's Health Study (CHS) were included in the analysis. Plasma PFAS and the metabolome were determined using liquid-chromatography/high-resolution mass spectrometry. A metabolome-wide association study was performed on log-transformed metabolites using Bayesian regression with a g-prior specification and g-computation for modeling exposure mixtures to estimate the impact of exposure to a mixture of six ubiquitous PFAS (PFOS, PFHxS, PFHpS, PFOA, PFNA, and PFDA). Pathway enrichment analysis was performed using Mummichog and Gene Set Enrichment Analysis. Significance across cohorts was determined using weighted Z-tests. RESULTS: In the SOLAR and CHS cohorts, PFAS exposure was associated with alterations in tyrosine metabolism (meta-analysis p=0.00002) and de novo fatty acid biosynthesis (p=0.03), among others. For example, when increasing all PFAS in the mixture from low (∼30th percentile) to high (∼70th percentile), thyroxine (T4), a thyroid hormone related to tyrosine metabolism, increased by 0.72 standard deviations (SDs; equivalent to a standardized mean difference) in the SOLAR cohort (95% Bayesian credible interval (BCI): 0.00, 1.20) and 1.60 SD in the CHS cohort (95% BCI: 0.39, 2.80). Similarly, when going from low to high PFAS exposure, arachidonic acid increased by 0.81 SD in the SOLAR cohort (95% BCI: 0.37, 1.30) and 0.67 SD in the CHS cohort (95% BCI: 0.00, 1.50). In general, no individual PFAS appeared to drive the observed associations. DISCUSSION: Exposure to PFAS is associated with alterations in amino acid metabolism and lipid metabolism in adolescents and young adults. https://doi.org/10.1289/EHP11372.

Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth.

BACKGROUND: Rapid postnatal growth may result from exposure in utero or early life to adverse conditions and has been associated with diseases later in life and, in particular, with childhood obesity. DNA methylation, interfacing early-life exposures and subsequent diseases, is a possible mechanism underlying early-life programming. METHODS: Here, a meta-analysis of Illumina HumanMethylation 450K/EPIC-array associations of cord blood DNA methylation at single CpG sites and CpG genomic regions with rapid weight growth at 1 year of age (defined with reference to WHO growth charts) was conducted in six European-based child cohorts (ALSPAC, ENVIRONAGE, Generation XXI, INMA, Piccolipiù, and RHEA, N = 2003). The association of gestational age acceleration (calculated using the Bohlin epigenetic clock) with rapid weight growth was also explored via meta-analysis. Follow-up analyses of identified DNA methylation signals included prediction of rapid weight growth, mediation of the effect of conventional risk factors on rapid weight growth, integration with transcriptomics and metabolomics, association with overweight in childhood (between 4 and 8 years), and comparison with previous findings. RESULTS: Forty-seven CpGs were associated with rapid weight growth at suggestive p-value <1e-05 and, among them, three CpGs (cg14459032, cg25953130 annotated to ARID5B, and cg00049440 annotated to KLF9) passed the genome-wide significance level (p-value <1.25e-07). Sixteen differentially methylated regions (DMRs) were identified as associated with rapid weight growth at false discovery rate (FDR)-adjusted/Siddak p-values < 0.01. Gestational age acceleration was associated with decreasing risk of rapid weight growth (p-value = 9.75e-04). Identified DNA methylation signals slightly increased the prediction of rapid weight growth in addition to conventional risk factors. Among the identified signals, three CpGs partially mediated the effect of gestational age on rapid weight growth. Both CpGs (N=3) and DMRs (N=3) were associated with differential expression of transcripts (N=10 and 7, respectively), including long non-coding RNAs. An AURKC DMR was associated with childhood overweight. We observed enrichment of CpGs previously reported associated with birthweight. CONCLUSIONS: Our findings provide evidence of the association between cord blood DNA methylation and rapid weight growth and suggest links with prenatal exposures and association with childhood obesity providing opportunities for early prevention.

Long-term effect of asthma on the development of obesity among adults: an international cohort study, ECRHS.

INTRODUCTION: Obesity is a known risk factor for asthma. Although some evidence showed asthma causing obesity in children, the link between asthma and obesity has not been investigated in adults. METHODS: We used data from the European Community Respiratory Health Survey (ECRHS), a cohort study in 11 European countries and Australia in 3 waves between 1990 and 2014, at intervals of approximately 10 years. We considered two study periods: from ECRHS I (t) to ECRHS II (t+1), and from ECRHS II (t) to ECRHS III (t+1). We excluded obese (body mass index≥30 kg/m2) individuals at visit t. The relative risk (RR) of obesity at t+1 associated with asthma at t was estimated by multivariable modified Poisson regression (lag) with repeated measurements. Additionally, we examined the association of atopy and asthma medication on the development of obesity. RESULTS: We included 7576 participants in the period ECRHS I-II (51.5% female, mean (SD) age of 34 (7) years) and 4976 in ECRHS II-III (51.3% female, 42 (8) years). 9% of participants became obese in ECRHS I-II and 15% in ECRHS II-III. The risk of developing obesity was higher among asthmatics than non-asthmatics (RR 1.22, 95% CI 1.07 to 1.38), and particularly higher among non-atopic than atopic (1.47; 1.17 to 1.86 vs 1.04; 0.86 to 1.27), those with longer disease duration (1.32; 1.10 to 1.59 in >20 years vs 1.12; 0.87 to 1.43 in ≤20 years) and those on oral corticosteroids (1.99; 1.26 to 3.15 vs 1.15; 1.03 to 1.28). Physical activity was not a mediator of this association. CONCLUSION: This is the first study showing that adult asthmatics have a higher risk of developing obesity than non-asthmatics, particularly those non-atopic, of longer disease duration or on oral corticosteroids.

Creatine Kinase Is Decreased in Childhood Asthma.

Rationale: The identification of novel molecules associated with asthma may provide insights into the mechanisms of disease and their potential clinical implications. Objectives: To conduct a screening of circulating proteins in childhood asthma and to study proteins that emerged from human studies in a mouse model of asthma. Methods: We included 2,264 children from eight birth cohorts from the Mechanisms of the Development of ALLergy project and the Tucson Children's Respiratory Study. In cross-sectional analyses, we tested 46 circulating proteins for association with asthma in the selection stage and carried significant signals forward to a validation and replication stage. As CK (creatine kinase) was the only protein consistently associated with asthma, we also compared whole blood CK gene expression between subjects with and without asthma (n = 249) and used a house dust mite (HDM)-challenged mouse model to gain insights into CK lung expression and its role in the resolution of asthma phenotypes. Measurements and Main Results: As compared with the lowest CK tertile, children in the highest tertile had significantly lower odds for asthma in selection (adjusted odds ratio, 95% confidence interval: 0.31; 0.15-0.65; P = 0.002), validation (0.63; 0.42-0.95; P = 0.03), and replication (0.40; 0.16-0.97; P = 0.04) stages. Both cytosolic CK forms (CKM and CKB) were underexpressed in blood from asthmatics compared with control subjects (P = 0.01 and 0.006, respectively). In the lungs of HDM-challenged mice, Ckb expression was reduced, and after the HDM challenge, a CKB inhibitor blocked the resolution of airway hyperresponsiveness and reduction of airway mucin. Conclusions: Circulating concentrations and gene expression of CK are inversely associated with childhood asthma. Mouse models support a possible direct involvement of CK in asthma protection via inhibition of airway hyperresponsiveness and reduction of airway mucin.