Paul Yousefi

Epigenetic Signatures of Cigarette Smoking

Background—DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. Methods and Results—To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine–phosphate–guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1×10−7 (18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1×10−7 (2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. Conclusions—Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.

Organophosphate pesticide levels in blood and urine of women and newborns living in an agricultural community.

Organophosphate pesticides are widely used and recent studies suggest associations of in utero exposures with adverse birth outcomes and neurodevelopment. Few studies have characterized organophosphate pesticides in human plasma or established how these levels correlate to urinary measurements. We measured organophosphate pesticide metabolites in maternal urine and chlorpyrifos and diazinon in maternal and cord plasma of subjects living in an agricultural area to compare levels in two different biological matrices. We also determined paraoxonase 1 (PON1) genotypes (PON1(192) and PON1(-108)) and PON1 substrate-specific activities in mothers and their newborns to examine whether PON1 may affect organophosphate pesticide measurements in blood and urine. Chlorpyrifos levels in plasma ranged from 0-1,726 ng/mL and non-zero levels were measured in 70.5% and 87.5% of maternal and cord samples, respectively. Diazinon levels were lower (0-0.5 ng/mL); non-zero levels were found in 33.3% of maternal plasma and 47.3% of cord plasma. Significant associations between organophosphate pesticide levels in blood and metabolite levels in urine were limited to models adjusting for PON1 levels. Increased maternal PON1 levels were associated with decreased odds of chlorpyrifos and diazinon detection (odds ratio(OR): 0.56 and 0.75, respectively). Blood organophosphate pesticide levels of study participants were similar in mothers and newborns and slightly higher than those reported in other populations. However, compared to their mothers, newborns have much lower quantities of the detoxifying PON1 enzyme suggesting that infants may be especially vulnerable to organophosphate pesticide exposures.

Considerations for normalization of DNA methylation data by Illumina 450K BeadChip assay in population studies.

Analysis of epigenetic mechanisms, particularly DNA methylation, is of increasing interest for epidemiologic studies examining disease etiology and impacts of environmental exposures. The Infinium HumanMethylation450 BeadChip® (450K), which interrogates over 480 000 CpG sites and is relatively cost effective, has become a popular tool to characterize the DNA methylome. For large-scale studies, minimizing technical variability and potential bias is paramount. The goal of this paper was to evaluate the performance of several existing and novel color channel normalizations designed to reduce technical variability and batch effects in 450K analysis from a large population study. Comparative assessment of 10 normalization procedures included the GenomeStudio® Illumina procedure, the lumi smooth quantile approach, and the newly proposed All Sample Mean Normalization (ASMN). We also examined the performance of normalizations in combination with correction for the two types of Infinium chemistry utilized on the 450K array. We observed that the performance of the GenomeStudio® normalization procedure was highly variable and dependent on the quality of the first sample analyzed in an experiment, which is used as a reference in this procedure. While the lumi normalization was able to decrease batch variability, it increased variation among technical replicates, potentially reducing biologically meaningful findings. The proposed ASMN procedure performed consistently well, both at reducing batch effects and improving replicate comparability. In summary, the ASMN procedure can improve existing color channel normalization, especially for large epidemiologic studies, and can be successfully implemented to enhance a 450K DNA methylation data pipeline.

Small-Magnitude Effect Sizes in Epigenetic End Points are Important in Children’s Environmental Health Studies: The Children’s Environmental Health and Disease Prevention Research Center’s Epigenetics Working Group

Background: Characterization of the epigenome is a primary interest for children’s environmental health researchers studying the environmental influences on human populations, particularly those studying the role of pregnancy and early-life exposures on later-in-life health outcomes. Objectives: Our objective was to consider the state of the science in environmental epigenetics research and to focus on DNA methylation and the collective observations of many studies being conducted within the Children’s Environmental Health and Disease Prevention Research Centers, as they relate to the Developmental Origins of Health and Disease (DOHaD) hypothesis. Methods: We address the current laboratory and statistical tools available for epigenetic analyses, discuss methods for validation and interpretation of findings, particularly when magnitudes of effect are small, question the functional relevance of findings, and discuss the future for environmental epigenetics research. Discussion: A common finding in environmental epigenetic studies is the small-magnitude epigenetic effect sizes that result from such exposures. Although it is reasonable and necessary that we question the relevance of such small effects, we present examples in which small effects persist and have been replicated across populations and across time. We encourage a critical discourse on the interpretation of such small changes and further research on their functional relevance for children’s health. Conclusion: The dynamic nature of the epigenome will require an emphasis on future longitudinal studies in which the epigenome is profiled over time, over changing environmental exposures, and over generations to better understand the multiple ways in which the epigenome may respond to environmental stimuli. Citation: Breton CV, Marsit CJ, Faustman E, Nadeau K, Goodrich JM, Dolinoy DC, Herbstman J, Holland N, LaSalle JM, Schmidt R, Yousefi P, Perera F, Joubert BR, Wiemels J, Taylor M, Yang IV, Chen R, Hew KM, Freeland DM, Miller R, Murphy SK. 2017. Small-magnitude effect sizes in epigenetic end points are important in children’s environmental health studies: the Children’s Environmental Health and Disease Prevention Research Center’s Epigenetics Working Group. Environ Health Perspect 125:–526; http://dx.doi.org/10.1289/EHP595

Estimation of Blood Cellular Heterogeneity in Newborns and Children for Epigenome-Wide Association Studies

Confounding by cellular heterogeneity has become a major concern for epigenome‐wide association studies (EWAS) in peripheral blood samples from population and clinical studies. Adjusting for white blood cell percentage estimates produced by the minfi implementation of the Houseman algorithm (minfi) during statistical analysis is now an established method to account for this bias in adults. However, minfi has not been benchmarked against white blood cell counts in children that may differ substantially from the reference dataset used in its estimation. We compared estimates of white blood cell type percentages produced by two methods, minfi and differential cell count (DCC), in a birth cohort at two time points (birth and 12 years of age). We found that both minfi and DCC had similar trends as children aged, and neither count method differed by sex among newborns (P > 0.10). However, minfi estimates did not correlate well with DCC in samples from newborns (ρ = −0.05 for granulocytes; ρ = −0.03 for lymphocytes). In older children, correlation improved substantially (ρ = 0.77 for granulocytes; ρ = 0.75 for lymphocytes), likely due to increasing similarity with minfis adult reference data as children aged. Our findings suggest that the minfi method may provide suitable estimates of white blood cell composition for samples from adults and older children, but may not currently be appropriate for EWAS involving newborns or young children. Environ. Mol. Mutagen. 56:751–758, 2015.

Adiponectin and leptin trajectories in Mexican-American children from birth to 9 years of age.

Objectives To address molecular mechanisms underlying obesity development, we examined patterns of critical metabolism-related hormones, adiponectin and leptin (adipokines), over childhood. Subjects and Design Plasma adiponectin and leptin were measured in 80 Mexican-American children at birth and again at 2, 5, and 9 years from the ongoing prospective cohort followed by the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS). We used a mixture modeling approach to identify patterns in adipokine trajectories from birth to 9 years. Results Leptin was positively related to child body size within all ages, however adiponectin had inverse and weaker associations with BMI at 2, 5, and 9 years. Correlations between adipokine levels over the 0–2, 2–5, and 5–9-year periods increased for both leptin (r = 0.06, 0.31 and 0.62) and adiponectin (r = 0.25, 0.41 and 0.46). Our mixture modeling approach identified three trajectory clusters for both leptin (1L [slowly-rising], 2L [rapidly-rising], and 3L [stable]) and adiponectin (1A [steep-dropping and rebounding], 2A [moderately-dropping], and 3A [stable]). While leptin groups were most separated over the 2–9-year period, adiponectin trajectories displayed greatest heterogeneity from birth to 2 years. Children in the rapidly-rising 2L group had highest BMI and waist circumference at 9 years. Further, children with greater birth weight had increased odds of belonging to this high risk group (OR = 1.21 95% CI 1.03, 1.43, compared to stable group 3L). Children whose mothers consumed more sugar-sweetened beverages during pregnancy were at risk of being in the steep-dropping 1A group (OR = 1.08, 95% CI 1.01, 1.17, compared to stable group 3A). Conclusion Our results highlight developmental differences in leptin and adiponectin over the childhood period. Leptin closely reflects child body size however factors affecting adiponectin and long-term consequences of its changes over infancy need to be further explored.

Maternal phthalate exposure during pregnancy is associated with DNA methylation of LINE-1 and Alu repetitive elements in Mexican-American children.

Phthalates are frequently used in personal care products and plasticizers and phthalate exposure is ubiquitous in the US population. Exposure to phthalates during critical periods in utero has been associated with a variety of adverse health outcomes but the biological mechanisms linking these exposures with disease are not well characterized. In this study, we examined the relationship of in utero phthalate exposure with repetitive element DNA methylation, an epigenetic marker of genome instability, in children from the longitudinal birth cohort CHAMACOS. Methylation of Alu and long interspersed nucleotide elements (LINE-1) was determined using pyrosequencing of bisulfite-treated DNA isolated from whole blood samples collected from newborns and 9 year old children (n=355). Concentrations of eleven phthalate metabolites were measured in urine collected from pregnant mothers at 13 and 26 weeks gestation. We found a consistent inverse association between prenatal concentrations of monoethyl phthalate, the most frequently detected urinary metabolite, with cord blood methylation of Alu repeats (β(95%CI): -0.14 (-0.28,0.00) and -0.16 (-0.31, -0.02)) for early and late pregnancy, respectively, and a similar but weaker association with LINE-1 methylation. Additionally, increases in urinary concentrations of di-(2-ethylhexyl) phthalate metabolites during late pregnancy were associated with lower levels of methylation of Alu repeats in 9 year old blood (significant p-values ranged from 0.003 to 0.03). Our findings suggest that prenatal exposure to some phthalates may influence differences in repetitive element methylation, highlighting epigenetics as a plausible biological mechanism through which phthalates may affect health.

Genome-wide methylation data mirror ancestry information

BackgroundGenetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data.ResultsWe demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data.ConclusionsEPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.

Prenatal phthalate exposure and altered patterns of DNA methylation in cord blood

Epigenetic changes such as DNA methylation may be a molecular mechanism through which environmental exposures affect health. Phthalates are known endocrine disruptors with ubiquitous exposures in the general population including pregnant women, and they have been linked with a number of adverse health outcomes. We examined the association between in utero phthalate exposure and altered patterns of cord blood DNA methylation in 336 Mexican‐American newborns. Concentrations of 11 phthalate metabolites were analyzed in maternal urine samples collected at 13 and 26 weeks gestation as a measure of fetal exposure. DNA methylation was assessed using the Infinium HumanMethylation 450K BeadChip adjusting for cord blood cell composition. To identify differentially methylated regions (DMRs) that may be more informative than individual CpG sites, we used two different approaches, DMRcate and comb‐p. Regional assessment by both methods identified 27 distinct DMRs, the majority of which were in relation to multiple phthalate metabolites. Most of the significant DMRs (67%) were observed for later pregnancy (26 weeks gestation). Further, 51% of the significant DMRs were associated with the di‐(2‐ethylhexyl) phthalate metabolites. Five individual CpG sites were associated with phthalate metabolite concentrations after multiple comparisons adjustment (FDR), all showing hypermethylation. Genes with DMRs were involved in inflammatory response (IRAK4 and ESM1), cancer (BRCA1 and LASP1), endocrine function (CNPY1), and male fertility (IFT140, TESC, and PRDM8). These results on differential DNA methylation in newborns with prenatal phthalate exposure provide new insights and targets to explore mechanism of adverse effects of phthalates on human health. Environ. Mol. Mutagen. 58:398–410, 2017.

PON1 as a model for integration of genetic, epigenetic, and expression data on candidate susceptibility genes

Abstract Recent genome- and epigenome-wide studies demonstrate that the DNA methylation is controlled in part by genetics, highlighting the importance of integrating genetic and epigenetic data. To better understand molecular mechanisms affecting gene expression, we used the candidate susceptibility gene paraoxonase 1 (PON1) as a model to assess associations of PON1 genetic polymorphisms with DNA methylation and arylesterase activity, a marker of PON1 expression. PON1 has been associated with susceptibility to obesity, cardiovascular disease, and pesticide exposure. In this study, we assessed DNA methylation in 18 CpG sites located along PON1 shores, shelves, and its CpG island in blood specimens collected from newborns and 9-year-old children participating (n = 449) in the CHAMACOS birth cohort study. The promoter polymorphism, PON1-108, was strongly associated with methylation, particularly for CpG sites located near the CpG island (P << 0.0005). Among newborns, these relationships were even more pronounced after adjusting for blood cell composition. We also observed significant decreases in arylesterase activity with increased methylation at the same nine CpG sites at both ages. Using causal mediation analysis, we found statistically significant indirect effects of methylation (β(95% confidence interval): 6.9(1.5, 12.4)) providing evidence that DNA methylation mediates the relationship between PON1-108 genotype and PON1 expression. Our findings show that integration of genetic, epigenetic, and expression data can shed light on the functional mechanisms involving genetic and epigenetic regulation of candidate susceptibility genes like PON1.