Project description:BACKGROUND:Maternal nutrition status (e.g. dietary/nutrient intake) during pregnancy has been associated with pregnancy outcomes including birth weight, infant survival and metabolic health of the offspring during later life. During the past few years, maternal dietary intake, at least three months before conception, has been shown to affect pregnancy outcomes also. However, literature investigating this link is still scarce. The studies that have looked at preconception dietary intake in relation to pregnancy outcome were either animal studies, had small sample sizes or focused on only selected macronutrient intake rather than complete (macro)nutrient composition or dietary intakes (e.g. food groups). Therefore, we aim to investigate the association between preconception diet and pregnancy outcomes in a linked birth cohort. The main objective of this manuscript is to describe the methodology of establishing this birth cohort and to describe both the characteristics of the study population included as well as the representativeness in terms of dietary intake. METHODS:We created the birth cohort by linking two existing databases; a large population-based cohort study in the Netherlands (The Lifelines Cohort study) and the Dutch national birth registry (Perined), through a 'trusted third party'. The birth cohort contains information on maternal dietary intake during preconception as well as pregnancy outcomes. RESULTS AND DISCUSSION:In the Lifelines Cohort study, 3,418 pregnancies were available for linking with Perined. In total, 2,368 pregnancies (86.9%) were linked with Perined, resulting in the birth cohort. With this linked cohort we are able to provide insights on the associations between dietary intake before conception and pregnancy outcomes. Such data could potentially improve nutritional care for women of childbearing age. Lifestyle changes in the period preceding pregnancy may be most effective in improving pregnancy outcomes. A focus on this window of opportunity may provide both sufficient time, as well as a period when women are potentially motivated to adopt health optimizing behaviours.

Project description:BackgroundYoung children's healthy development depends on nurturing care, which ensures health, nutrition, responsive caregiving, safety and security, and early learning. Infancy and childhood are characterized by rapid growth and development, and these two factors contribute largely to determining health status and well-being across the lifespan. Identification of modifiable risk factors and prognostic factors during the critical periods of life will contribute to the development of effective prevention and intervention strategies. The NASCITA (NAscere e creSCere in ITAlia) study was created to evaluate physical, cognitive, and psychological development, health status and health resource utilization during the first six years of life in a cohort of newborns, and to evaluate potential associated factors.MethodsNASCITA is an ongoing, dynamic, prospective, population-based birth cohort study of an expected number of more than 5000 newborns who will be recruited in 22 national geographic clusters starting in 2019. It was designed to follow children from birth to school entry age for a wide range of determinants, disorders, and diseases. Recruitment of the newborns (and their parents) will take place during the first routine well-child visit, which takes place at the office of the pediatrician assigned to them by the local health unit of residence, and which is scheduled for all newborns born in Italy within the first 45 days of their life. Data will be web-based and collected by the family pediatricians during each of the 7 standard well-child visits scheduled for all children during their first 6 years of life. Information on every contact with the enrolled children in addition to these prescheduled visits will be also recorded.DiscussionThe NASCITA cohort study provides a framework in which children are followed from birth to six-years of age. NASCITA will broaden our understanding of the contribution of early-life factors to infant and child health and development. NASCITA provides opportunities to initiate new studies, also experimental ones, in parts of the cohort, and will contribute relevant information on determinants and health outcomes to policy and decision makers. Cohort details can be found on https://coortenascita.marionegri.it.Trial registrationClinicaltrials.gov: NCT03894566. Ethics committee approval: 6 February 2019, Verbale N 59.

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: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

The developmental origins of ageing: study protocol for the Dutch famine birth cohort study on ageing.

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The developmental origins of ageing: study protocol for the Dutch famine birth cohort study on ageing.

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