Interest in the health effects of potential endocrine-disrupting compounds (EDCs) that are high production volume chemicals used in consumer products has made exposure assessment and source identification a priority. We collected paired indoor and outdoor air samples in 40 nonsmoking homes in urban, industrial Richmond, CA, and 10 in rural Bolinas, CA. Samples were analyzed by GC-MS for 104 analytes, including phthalates (11), alkylphenols (3), parabens (3), polybrominated diphenyl ether (PBDE) flame retardants (3), polychlorinated biphenyls (PCBs) (3), polycyclic aromatic hydrocarbons (PAHs) (24), pesticides (38), and phenolic compounds (19). We detected 39 analytes in outdoor air and 63 in indoor air. For many of the phenolic compounds, alkylphenols, phthalates, and PBDEs, these represent some of the first outdoor measures and the first analysis of the relative importance of indoor and outdoor sources in paired samples. Data demonstrate higher indoor concentrations for 32 analytes, suggesting primarily indoor sources, as compared with only 2 that were higher outdoors. Outdoor air concentrations were higher in Richmond than Bolinas for 3 phthalates, 10 PAHs, and o-phenylphenol, while indoor air levels were more similar between communities, except that differences observed outdoors were also seen indoors. Indoor concentrations of the most ubiquitous chemicals were generally correlated with each other (4-t-butylphenol, o-phenylphenol, nonylphenol, several phthalates, and methyl phenanthrenes; Kendall correlation coefficients 0.2-0.6, p<0.05), indicating possible shared sources and highlighting the importance of considering mixtures in health studies.

Background

Early-life exposure to lead is associated with deficits in neurodevelopment and with hematopoietic system toxicity. DNA methylation may be one of the underlying mechanisms for the adverse effects of prenatal lead on the offspring, but epigenome-wide methylation data for low levels of prenatal lead exposure are lacking.

Objectives

We investigated the association between prenatal maternal lead exposure and epigenome-wide DNA methylation in umbilical cord blood nucleated cells in Project Viva, a prospective U.S.-based prebirth cohort with relatively low levels of lead exposure.

Methods

Among 268 mother-infant pairs, we measured lead concentrations in red blood cells (RBC) from prenatal maternal blood samples, and using HumanMethylation450 Bead Chips, we measured genome-wide methylation levels at 482,397 CpG loci in umbilical cord blood and retained 394,460 loci after quality control. After adjustment for batch effects, cell types, and covariates, we used robust linear regression models to examine associations of prenatal lead exposure with DNA methylation in cord blood at epigenome-wide significance level [false discovery rate (FDR)<0.05].

Results

The mean [standard deviation (SD)] maternal RBC lead level was 1.22 (0.63) μg/dL. CpG cg10773601 showed an epigenome-wide significant negative association with prenatal lead exposure (-1.4% per doubling increase in lead exposure; p=2.3×10-7) and was annotated to C-Type Lectin Domain Family 11, Member A (CLEC11A), which functions as a growth factor for primitive hematopoietic progenitor cells. In sex-specific analyses, we identified more CpGs with FDR<0.05 among female infants (n=38) than among male infants (n=2). One CpG (cg24637308), which showed a strong negative association with prenatal lead exposure among female infants (-4.3% per doubling increase in lead exposure; p=1.1×10-06), was annotated to Dynein Heavy Chain Domain 1 gene (DNHD1) which is highly expressed in human brain. Interestingly, there were strong correlations between blood and brain methylation for CpG (cg24637308) based on another independent set of samples with a high proportion of female participants.

Conclusion

Prenatal low-level lead exposure was associated with newborn DNA methylation, particularly in female infants. https://doi.org/10.1289/EHP1246.

We empirically examined the strengths and weaknesses of two human genome-wide DNA methylation platforms: rapid multiplexed reduced representation bisulfite sequencing and Illumina's Infinium BeadChip. Rapid multiplexed reduced representation bisulfite sequencing required less input DNA, offered more flexibility in coverage, and interrogated more CpG loci at a higher regional density. The Infinium covered slightly more protein coding, cancer-associated and mitochondrial-related genes, both platforms covered all known imprinting clusters, and rapid multiplexed reduced representation bisulfite sequencing covered more microRNA genes than the HumanMethylation450, but fewer than the MethylationEPIC. Rapid multiplexed reduced representation bisulfite sequencing did not always interrogate exactly the same CpG loci, but genomic tiling improved overlap between different libraries. Reproducibility of rapid multiplexed reduced representation bisulfite sequencing and concordance between the platforms increased with CpG density. Only rapid multiplexed reduced representation bisulfite sequencing could genotype samples and measure allele-specific methylation, and we confirmed that Infinium measurements are influenced by nearby single-nucleotide polymorphisms. The respective strengths and weaknesses of these two genome-wide DNA methylation platforms need to be considered when conducting human epigenetic studies.

Background

Air pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants.

Objectives

We briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO.

Methods

We review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO.

Discussion

While the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research.

Conclusions

In ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.

Background

DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.

Results

Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43.

Conclusions

DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Background

Gestational age is often used as a proxy for developmental maturity by clinicians and researchers alike. DNA methylation has previously been shown to be associated with age and has been used to accurately estimate chronological age in children and adults. In the current study, we examine whether DNA methylation in cord blood can be used to estimate gestational age at birth.

Results

We find that gestational age can be accurately estimated from DNA methylation of neonatal cord blood and blood spot samples. We calculate a DNA methylation gestational age using 148 CpG sites selected through elastic net regression in six training datasets. We evaluate predictive accuracy in nine testing datasets and find that the accuracy of the DNA methylation gestational age is consistent with that of gestational age estimates based on established methods, such as ultrasound. We also find that an increased DNA methylation gestational age relative to clinical gestational age is associated with birthweight independent of gestational age, sex, and ancestry.

Conclusions

DNA methylation can be used to accurately estimate gestational age at or near birth and may provide additional information relevant to developmental stage. Further studies of this predictor are warranted to determine its utility in clinical settings and for research purposes. When clinical estimates are available this measure may increase accuracy in the testing of hypotheses related to developmental age and other early life circumstances.

Background

DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.

Methods

Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.

Results

Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts.

Conclusion

Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10^-9), independent of chronological age, even after adjusting for additional risk factors (p<5.4x10^-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10^-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (P_Bonferroni < 1.06 x 10^-7). In additional analyses in 7,278 participants, <1.3% of birthweight-associated differential methylation is also observed in childhood and adolescence, but not adulthood. Birthweight-related CpGs overlap with some Bonferroni-significant CpGs that were previously reported to be related to maternal smoking (55/914, p = 6.12 x 10^-74) and BMI in pregnancy (3/914, p = 1.13x10^-3), but not with those related to folate levels in pregnancy. Whether the associations that we observe are causal or explained by confounding or fetal growth influencing DNA methylation (i.e. reverse causality) requires further research.