Exposure of Preschool-Age Greek Children (RHEA Cohort) to Bisphenol A, Parabens, Phthalates, and Organophosphates

Phthalate esters (PEs), bisphenol A (BPA), and parabens (PBs), which are used in numerous consumer products, are known for their endocrine disrupting properties. Organophosphate chemicals (OPs), which form the basis of the majority of pesticides, are known for their neurotoxic activity in humans. All of these chemicals are associated with health problems to which children are more susceptible. Once they enter the human body, PEs, BPA, PBs, and OPs are metabolized and/or conjugated and finally excreted via urine. Hence, human exposure to these substances is examined through a determination of the urinary concentrations of their metabolites. This study assessed the exposure of Greek preschool-age children to PEs, BPA, PBs, and OPs by investigating the urinary levels of seven PEs metabolites, six PBs, BPA, and six dialkyl phosphate metabolites in five-hundred samples collected from 4-year-old children, subjects of the “RHEA” mother-child cohort in Crete, Greece. Daily intake of endocrine disruptors, calculated for 4 year old children, was lower than the corresponding daily intake for 2.5 year old children, which were determined in an earlier study of the same cohort. In some cases the daily intake levels exceeded the U.S. Environmental Protection Agency Tolerable Daily Intake (TDI) values and the EFSA Reference Doses (RfD) (e.g., for di-2-ethyl-hexyl phthalate, 3.6% and 1% of the children exceeded RfD and TDi, respectively). Exposure was linked to three main sources: PEs-BPA to plastic, PBs-diethyl phthalate to personal hygiene products, and OPs to food

Significant genes obtained by LASSO&Permuted based maxT algorithm for the three models (SNP, CPG, and Global) in the original dataset (EPICURO Study) and the replication dataset (TCGA).

<p>Significant genes obtained by LASSO&Permuted based maxT algorithm for the three models (SNP, CPG, and Global) in the original dataset (EPICURO Study) and the replication dataset (TCGA).</p

The longitudinal association of eating behaviour and ADHD symptoms in school age children: a follow-up study in the RHEA cohort

Previous evidence suggests a link between attention deficit hyperactivity disorder (ADHD) symptoms and disordered eating behaviours; however, the direction of the causal association remains unclear. Building on our previous research, we aimed to examine the longitudinal association between eating behaviours at 4 years, ADHD symptoms at 6 years of age, and the role of body mass index (BMI). We included children from the RHEA mother–child cohort in Greece, followed up at 4 and 6 years (n = 926). Parents completed the Children’s Eating Behaviour Questionnaire (CEBQ) to assess children’s eating behaviour at 4 years and the ADHD Test (ADHDT) and Child Behaviour Checklist for ages 6–18 (CBCL/6–18) to evaluate ADHD symptoms at 4 and 6 years, respectively, as well as measures of BMI. Longitudinal structural equation modeling (SEM) was carried out to evaluate the associations of all variables between 4 and 6 years. Food responsiveness at 4 years was positively associated with hyperactivity at age 6, whereas emotional overeating was negatively associated with hyperactivity. There was no evidence of an association between eating behaviours of preschoolers and BMI at 6 years, or BMI at 4 years and later ADHD symptoms and vice versa. Findings suggest that food responsiveness is an early marker of ADHD symptoms at 6 years of age. In contrast to our hypothesis there was no significant association between ADHD at age 4 and BMI at age 6.Other Information Published in: European Child & Adolescent Psychiatry License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s00787-021-01720-x</p

Example of a correlation plot for <i>MMP7</i> detected by the Global model using ENET but not using LASSO.

<p>The bar color represents the levels of correlation from 0 (no correlation) to 1 (perfect correlation) between SNPs and CpGs that were selected for the <i>MMP7</i> models. Three nets of correlated variables are the ones responsible that the gene is only selected by ENET and not by LASSO.</p

Statistically significant genes associated with SNPs and/or CpGs selected by LASSO&Permuted based maxT algorithm.

<p>Statistically significant genes associated with SNPs and/or CpGs selected by LASSO&Permuted based maxT algorithm.</p

Deviance across the genome when applying LASSO and ENET to select SNPs, CpGs or both (Global model).

<p>The dots in the figure indicate the deviance of each gene located in the corresponding position in the genome. There are a total of 20,899 gene expression probes measured. Significant genes after applying the permutation-based MaxT method are tagged. The figures represent the deviance per gene expression probe using LASSO for the SNP model (A), the CpG model (B) and the Global model (C) and using ENET for the SNP model (D), the CpG model (E) and the Global model (F).</p

Scenario and workflow of the overall analysis implemented.

<p>The integrative framework proposed is based on three steps. Step 1 corresponds to the selection of SNPs and CpGs in 1MB window upstream and downstream from each probe in the gene expression array. Step 2 corresponds to the application of LASSO and ENET to each probe obtaining the deviance per probe. Step 3 corresponds to the permutation-based MaxT method application where gene expression levels within the individuals are permuted B = 100 times obtaining the deviance per probe.</p

Significant genes obtained by ENET&Permuted based maxT algorithm for the three models (SNP, CPG, and Global) in the original dataset (EPICURO Study) and the replication dataset (TCGA).

<p>Significant genes obtained by ENET&Permuted based maxT algorithm for the three models (SNP, CPG, and Global) in the original dataset (EPICURO Study) and the replication dataset (TCGA).</p

Relationship between pre-pregnancy BMI and the estimated probability for overweight/obesity (A) and cholesterol levels ≥75th percentile (B) at 4 years of age.

<p>Estimated probability is based on multivariable models adjusted for maternal age, education, parity, smoking during pregnancy, gestational weight gain, birth weight, breastfeeding duration and TV watching at 4 years of age. Q2.5, Q50, Q97.5 represent the 2.5th, 50.0th, and the 97.5th percentiles of the studied population. Long-dashes represent the 95%CIs.</p

Forest plots from selected multivariable studies indicating the risk of reaching the indicated prognostic endpoints in non-muscle invasive (NMIBC; two upper panels), and muscle invasive (MIBC; two lower panels) UCBs in the presence of urothelial COX2 expression.

<p>Forest plots from selected multivariable studies indicating the risk of reaching the indicated prognostic endpoints in non-muscle invasive (NMIBC; two upper panels), and muscle invasive (MIBC; two lower panels) UCBs in the presence of urothelial COX2 expression.</p