Dataset Information

Maternal folate and newborn DNA methylation meta-analysis

ABSTRACT:

Folic acid is routinely recommended for women trying to conceive to ensure proper fetal development. Mechanisms whereby periconceptional folate influences normal development and disease are poorly understood: epigenetics may be involved. This data represents meta-analysis results from a large epigenomics study to examine the association between maternal plasma folate during pregnancy and epigenome-wide DNA methylation using Illumina's HumanMethyl450 (450K) Beadchip in 1,996 newborns from two European cohorts. Results for all CpGs analyzed (419,905) are provided.

These data may be downloaded through the dbGaP Authorized Access portal under phg000701.v1.

PROVIDER: phs001059 | dbGaP |

SECONDARY ACCESSION(S): PRJNA308780PRJNA308779

REPOSITORIES: dbGaP

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Project description:Advances in transcriptomics have impacted the way of looking atimproved our understanding of leukemic development and helped enhancing the stratification of patients. Analyses of individual cohortsTranscriptomics studies often combined AML samples regardless of cytogenetic abnormalities. , which would lead to bias in Hence, deregulated genesdifferential gene expression analysis that may result from the differential representation of in less frequent AML subgroups have low weight, contrarily to those in abundant subgroups. We, thusHence, we performed a horizontal meta-analysis that integrated transcriptomic data of AML from multicentric multiple studies to enrich the less frequent cytogenetic subgroups and to uncover common genes involved in AML development and response to therapy. A total of 28 Affymetrix microarray datasets harboring 3940 AML samples were downloaded from the GEO database. After stringent quality control, transcriptomics data of 1523 samples from 11 datasets, covering 10 AML cytogenetic subgroups, were retained and merged with the transcriptomic data of 198 healthy bone marrow samples. Differentially expressed genes between each cytogenetic subgroup and normal samples were extracted, allowing the unbiased identification of 330 commonly deregulated genes (CODEGs)., which CODEGs showed enriched expression profiles in myeloid differentiation, leukemic stem cell status and relapse. Most of these genes were downregulated, in accordance with DNA hypermethylation. CODEGS were then used to create a prognostic score based on the weighted sum of expression of 22 core genes (CODEG22). The score was validated in on microarray data of five independent cohorts, and by qRT-PCR in a cohort of 142 samples, by qRT-PCR. CODEG22 stratified patients globally, as well as in subpopulations of cytologically normal and elderly patients. , and hence, couldSo, it may complement the European LeukemiaNet classification for a more accurate prediction of AML outcomes.

Dataset Information

Maternal folate and newborn DNA methylation meta-analysis

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