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.

Project description:BackgroundHospital-based studies identify parechovirus (PeV), primarily PeV-A3, as an important cause of severe infections in young children. However, few community-based studies have been published and the true PeV infection burden is unknown. We investigated PeV epidemiology in healthy children participating in a community-based, longitudinal birth cohort study.MethodsAustralian children (n = 158) enrolled in the Observational Research in Childhood Infectious Diseases (ORChID) study were followed from birth until their second birthday. Weekly stool and nasal swabs and daily symptom diaries were collected. Swabs were tested for PeV by reverse-transcription polymerase chain reaction and genotypes determined by subgenomic sequencing. Incidence rate, infection characteristics, clinical associations, and virus codetections were investigated.ResultsPeV was detected in 1423 of 11 124 (12.8%) and 17 of 8100 (0.2%) stool and nasal swabs, respectively. Major genotypes among the 306 infection episodes identified were PeV-A1 (47.9%), PeV-A6 (20.1%), and PeV-A3 (18.3%). The incidence rate was 144 episodes (95% confidence interval, 128-160) per 100 child-years. First infections appeared at a median age of 8 (interquartile range, 6.0-11.7) months. Annual seasonal peaks changing from PeV-A1 to PeV-A3 were observed. Infection was positively associated with age ≥6 months, summer season, nonexclusive breastfeeding at age <3 months, and formal childcare attendance before age 12 months. Sole PeV infections were either asymptomatic (38.4%) or mild (32.7%), while codetection with other viruses in stool swabs was common (64.4%).ConclusionsIn contrast with hospital-based studies, this study showed that diverse and dynamically changing PeV genotypes circulate in the community causing mild or subclinical infections in children.Parechovirus can cause severe illnesses in children. However, studies focus mainly on hospitalized populations. True disease burden in the community remains largely unknown. From our community-based cohort, we found diverse parechovirus genotypes in the community, causing mild or subclinical infections in children.Clinical trials registrationNCT01304914.

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).

Dataset Information

Timing of First Respiratory Virus Detections in Infants: A Community-Based Birth Cohort Study.

Publications

Timing of First Respiratory Virus Detections in Infants: A Community-Based Birth Cohort Study.

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