Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Determining gestational age using genome methylation profile

ABSTRACT: Determining gestational age using genome methylation profile

PROVIDER: PRJNA431353 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Determining gestational age using genome methylation profile

Project description:Background: Gestational age determination by traditional tools (last menstrual period, ultrasonography measurements and Ballard Maturational Assessment in newborns) have major limitations and therefore there is a need to find molecular marker approaches that can be used to determine the accurate gestational age of the newborn. Methods: We performed RRBS (Reduced Representation Bisulfite Sequencing) on 41 cord blood and matching placenta samples. Results: We identified a set of 316 Differentially Methylated Regions (DMRs) that undergo demethylation in late gestational age in cord blood cells and can predict the gestational age (r = -0.7, p value<0.0001). Once the set of 411 DMRs that undergo de novo methylation in late gestational age was used in combination with the first set it generated a more accurate clock (r=0.77, p value=1.87E-05). Conclusion: Taken together, this study demonstrates that DNA methylation can accurately predict gestational age. The clinical use of this predictor should be further investigated.

2019-07-18 | GSE109538 | GEO

Cytosine methylation profiling in small and large for gestational age newborns

Project description:In 1990, David Barker proposed that prenatal nutrition is directly linked to adult cardiovascular disease. Since then, the relationship between adult cardiovascular risk, metabolic syndrome and birth weight has been widely documented. Here we used the TruSeq Methyl Capture EPIC platform to compare the methylation patterns in cord blood from large for gestational age (LGA), small for gestational age (SGA) and adequate for gestational age/Control (AGA/Ctl) newborns. We found several differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) between LGA, SGA and AGA groups. A system biology approach identified several biological processes significantly enriched with genes in association with DMCs including Regulation of transcription, Regulation of epinephrine secretion, Norepinephrine biosynthesis, Receptor transactivation, Forebrain regionalization and several terms related with kidney and cardiovascular development. Gene ontology analysis of the genes in association with the DMRs identified several significantly enriched biological processes related with kidney development including Mesonephric duct development and Nephron tubule development. Furthermore, our dataset identified several DNA methylation markers enriched at gene networks involved in biological pathways and rare diseases of the cardiovascular system, kidneys and metabolism. Our study identified several DMCs/DMRs in association with fetal growth patterns. The use of cord blood as material for the identification of DNA methylation biomarkers gives us the possibility to perform follow up studies on the same patients as they enter childhood and puberty. These studies will not only help us understand how the methylome responds to continuum postnatal growth but also link early alterations of the DNA methylome with later clinical markers of growth and metabolic fitness.

2023-07-26 | GSE238155 | GEO

Hydrolyzed Fat Formula Increases Brain White Matter in Small for Gestational Age and Appropriate for Gestational Age Neonatal Piglets

Project description:Hydrolyzed Fat Formula Increases Brain White Matter in Small for Gestational Age and Appropriate for Gestational Age Neonatal Piglets

| PRJNA556242 | ENA

Gene exprssion profile of gestational trophoblastic neoplasms

Project description:Gene exprssion profile of gestational trophoblastic neoplasms

| PRJNA559869 | ENA

Maternal whole blood expression changes with gestational age in normal pregnancy by Human Transcriptome Arrays

Project description:Maternal plasama colected longitudinally were profiled using Affymetrix Human Transcriptome Arrays to evaluate changes with gestational age.

2019-12-17 | GSE121974 | GEO

Integrative analysis of DNA methylation and gene expression data among preterm and/or small for gestational age infants during perinatal period [methylation]

Project description:Preterm or small for gestational age (SGA) infants are to be at high risk of noncommunicable diseases in adolescence, because they are exposed to hypoxia and malnutrition in and ex utero during perinatal period. Epigenetics could be one of the most important mechanisms of DOHaD.In the field of premature babies, previous studies investigated the methylation alterations related to gestational age and birthweight by using cord blood samples. In the field of preterm or SGA babies, there were few EWAS studies that examine whether methylation changes relate to RNA expression using cord blood samples, and the interpretation of postnatal blood methylation were different by studies.The objective is to investigate the epigenetic alterations associated with preterm birth and SGA by using methylation and expression microarray, and to explore the epigenetic changes which may persist after birth.

2021-02-09 | GSE110828 | GEO

Gestational diabetes and human amniocytes

Project description:Context: Context: Gestational diabetes (GDM) has profound effects on the intrauterine metabolic milieu and is linked to obesity and diabetes in offspring, but the mechanisms driving these effects remain largely unknown. Alterations gene expression in amniocytes exposed to GDM in utero may identify potential mechanisms leading to metabolic dysfunction later in life. Objective: Objective: To profile changes in the transcriptome in human amniocytes exposed to GDM Methods: A nested case-control study was performed in second trimeseter amniocytes matched for offspring sex, maternal race/ethnicity, maternal age, gestational age at amniocentesis, gestational age at birth and gestational diabetes status. Sex-specific RNA-sequencing was completed and gene expression changes were identified. Results: Expression of interferon-stimulated genes was increased in GDM amniocytes accounting for 6 of the top 10 altered genes (q<0.05). Enriched biological pathways in GDM anmiocytes included pathways involving inflammation, the interferon response, fatty liver disease, monogenic diabetes and atherosclerosis. Conclusion: In a unique repository of human amniocytes exposed to GDM in utero, trancriptome analysis identified enrichment of inflammation and interferon-related pathways.

2020-05-15 | GSE150621 | GEO

Maternal whole blood expression changes with gestational age and labor in normal pregnancy [array]

Project description:Maternal plasama colected longitudinally were profiled using Affymetrix Human Transcriptome Arrays to evaluate changes with gestational age and with labor in normal pregnancy.

2019-02-04 | GSE113809 | GEO

Dataset for Placental Genomic and Epigenomic Signatures in Infants Borns at Extremely Low Gestational Age [DNA methylation]

Project description:These analyses set out to evaluate placental genomic and epigenomic signatures in newborns from the Extremely Low Gestational Age Newborns (ELGAN) cohort. Genome-wide mRNA, microRNA, and DNA methylation profiles were obtained from placenta samples collected at birth. Analyses were conducted to better understand placental molecular signatures and relate these to placental, maternal, infant, and later-in-life health indices.

2021-03-01 | GSE167885 | GEO

Sequencing based maternal whole blood expression changes with gestational age and labor in normal pregnancy

Project description:Maternal plasama colected longitudinally were profiled using paired-end Illumina RNA-Seq with globin reduction to evaluate changes with gestational age and with labor in normal pregnancy.

2019-02-04 | GSE113964 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data