Birth Cohort Studies: Their Next Coming of Age.
Ontology highlight
ABSTRACT:
SUBMITTER: Turner S
PROVIDER: S-EPMC7737575 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
2016-03-11 | GSE79056 | GEO
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).
2016-03-11 | E-GEOD-79056 | biostudies-arrayexpress
Project description:BackgroundDespite experimental evidence that lactational exposure to persistent organic pollutants (POPs) can impact health, results from epidemiologic studies are inconclusive. Inconsistency across studies may reflect the inability of current methods to estimate children's blood levels during specific periods of susceptibility.ObjectivesWe developed a toxicokinetic model to simulate blood POP levels in children from two longitudinal birth cohorts and aimed to validate it against blood levels measured at 6, 16, and 45 months of age.MethodsThe model consisted of a maternal and a child lipid compartment connected through placental diffusion and breastfeeding. Simulations were carried out based on individual physiologic parameters; duration of breastfeeding; and levels of POPs measured in maternal blood at delivery, cord blood, or breast milk. Model validity was assessed through regression analyses of simulated against measured blood levels.ResultsSimulated levels explained between 10% and 83% of measured blood levels depending on the cohort, the compound, the sample used to simulate children's blood levels, and child's age when blood levels were measured. Model accuracy was highest for estimated blood POP levels at 6 months based on maternal or cord blood levels. However, loss in model precision between the 6th and the 45th month was small for most compounds.ConclusionsOur validated toxicokinetic model can be used to estimate children's blood POP levels in early to mid-childhood. Estimates can be used in epidemiologic studies to evaluate the impact of exposure during hypothesized postnatal periods of susceptibility on health.
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