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A co-expression analysis of the placental transcriptome in association with maternal pre-pregnancy BMI and newborn birth weight

ABSTRACT: A co-expression analysis of the placental transcriptome in association with maternal pre-pregnancy BMI and newborn birth weight

PROVIDER: PRJNA527297 | ENA |

REPOSITORIES: ENA

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A co-expression analysis of the placental transcriptome in association with maternal pre-pregnancy BMI and newborn birth weight

Project description:We conducted a genome-wide placental transcriptome study aiming at the identification of functional pathways representing the molecular link between maternal pre-pregnancy BMI and fetal growth. We used RNA microarray (Agilent 8 X 60 K), medical records, and questionnaire data from 183 mother-newborn pairs from the ENVIRONAGE birth cohort study (Flanders, Belgium). We applied a weighted gene co-expression network analysis (WGCNA) and identified genes modules and hub genes that were associated with maternal BMI as well as newborn birth weight. Modules of interest were further characterized by gene ontology (GO) and pathway enrichment analyses. We assessed the mediating effects of modules and hub genes in the association between maternal BMI and newborn weight.

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A Co-expression Analysis of the Placental Transcriptome in Association With Maternal Pre-pregnancy BMI and Newborn Birth Weight.

Project description: Not available

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Epigenetic signature of birth-weight discordance in Danish twins

Project description:Epigenetic profiling of birth-weight discordant twins using Illumina's 450K Human DNA methylation BeadChip Comparing DNA methylation difference in birth-weight discordant twin pairs

2014-12-15 | E-GEOD-61496 | biostudies-arrayexpress

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Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights. RNA from umbilical cord tissue from full term neonates was extracted and hybridized. Separation into 2 distinct groups, independent of birth weight, but based solely on gene expression levels was analysed by Genespring. After appropriate statistical analysis, one group was keenly associated with a higher birth weight (22 samples) while the other was associated with a lower birth-weight (18 samples). Technical replicates were included for all 40 samples.

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Extremelly birth weight infant gut

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DNA methylation in blood from neonatal screening cards and the association with BMI and insulin sensitivity in early childhood

Project description:There is increasing evidence that metabolic diseases originate in early life, and epigenetic changes have been implicated as key drivers of this early life programming. This led to the hypothesis that epigenetic marks present at birth may predict an individual’s future risk of obesity and type 2 diabetes. In this study, we assessed whether epigenetic marks in blood of newborn children were associated with BMI and insulin sensitivity later in childhood. DNA methylation was measured in neonatal blood spot samples of 439 children using the Illumina Infinium 450k BeadChip. Associations were assessed between DNA methylation at birth and BMI z-scores, body fat mass, fasting plasma glucose, insulin and HOMA-IR at age 5 years, as well as birthweight, maternal BMI and smoking status. No individual methylation sites at birth were associated with obesity or insulin sensitivity measures at 5 years. DNA methylation in 69 genomic regions at birth was associated with BMI z-scores at age 5 years, and in 63 regions with HOMA-IR. The methylation changes were generally small (<5%), except for a region near the non-coding RNA nc886 (VTRNA2-1) where a clear link between methylation status at birth and BMI in childhood was observed (P=0.001). Associations were also found between DNA methylation, maternal smoking, and birth weight. We identified a number of DNA methylation regions at birth that were associated with obesity or insulin sensitivity measurements in childhood. These findings support the mounting evidence on the role of epigenetics in programming of metabolic health. Whether many of these small changes in DNA methylation are causally related to the health outcomes, and of clinical relevance, remains to be determined, but the nc886 region represents a promising obesity risk marker that warrants further investigation.

2017-09-09 | GSE103657 | GEO

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2015-10-27 | GSE62765 | GEO

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