Project description:Genome wide DNA methylation profiling of cord blood in Faroe Island cohort. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 485,000 CpGs in cord blood samples. Background: Faroe islanders consume marine foods contaminated with methylmercury (MeHg), polychlorinated biphenyls (PCBs), and other toxicants associated with chronic disease risks. Differential DNA methylation at specific CpG sites in cord blood may serve as a surrogate biomarker of health impacts from chemical exposures. Objective: We aimed to identify key environmental chemicals in cord blood associated with DNA methylation changes in a population with elevated exposure to chemical mixtures. Method: We studied 72 participants of a Faroese birth cohort recruited between 1986 and 1987 and followed until adulthood. The cord blood DNA methylome was profiled using Infinium Methylation 450K BeadChips. We determined the associations of CpG site changes with concentrations of MeHg, major PCBs, other organochlorine compounds, (hexachlorobenzene [HCB], p,p’-dichlorodiphenyldichloroethylene [p,p’-DDE] and p,p’-dichlorodiphenyltrichloroethane) and perfluoroalkyl substances. Results: In a combined sex analysis, among the 16 chemicals studied, PCB congener 105 (CB-105) exposure was associated with the majority of differentially methylated CpG sites (214 out of a total of 250). In female-only-analysis, only 73 CB-105 associated CpG sites were detected, 44 of which were mapped to genes in the ELAV1-associated cancer network. In males-only, methylation changes were seen for perfluorooctane sulfonate, HCB, and p,p’-DDE in 10,598; 1,238; and 1,473 CpG sites, respectively, 15% of which were enriched in cytobands of the X chromosome associated with neurological disorders. Conclusion: In this multiple-pollutant and genome-wide study, we identified key epigenetic toxicants. The significant enrichment of specific X-chromosome sites in males implies potentially sex-specific epigenome responses to prenatal chemical exposures.

Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates. 36 Umbilical cord blood samples were collected in EDTA tubes soon after placental delivery. Blood samples were centrifuged at 3,000 RPM to separate plasma, and buffy coats were aliquoted and stored at -80oC. DNA was extracted using the DNeasy Kit (Qiagen). DNA methylation was interrogated for each sample using the HumanMethylation450 BeadChip (Illumina).

Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates.

Dataset Information

Epigenome analysis of DNA from umbilical cord blood (UCWBC) in CCCEH birth cohort

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