Your browser doesn't support javascript.

Biblioteca Virtual em Saúde

Brasil

Home > Pesquisa > ()
Imprimir Exportar

Formato de exportação:

Exportar

Email
Adicionar mais destinatários
| |

Whole-transcriptome analysis delineates the human placenta gene network and its associations with fetal growth.

Deyssenroth, Maya A; Peng, Shouneng; Hao, Ke; Lambertini, Luca; Marsit, Carmen J; Chen, Jia.
BMC Genomics; 18(1): 520, 2017 07 10.
Artigo em Inglês | MEDLINE | ID: mdl-28693416

BACKGROUND:

The placenta is the principal organ regulating intrauterine growth and development, performing critical functions on behalf of the developing fetus. The delineation of functional networks and pathways driving placental processes has the potential to provide key insight into intrauterine perturbations that result in adverse birth as well as later life health outcomes.

RESULTS:

We generated the transcriptome-wide profile of 200 term human placenta using the Illumina HiSeq 2500 platform and characterized the functional placental gene network using weighted gene coexpression network analysis (WGCNA). We identified 17 placental coexpression network modules that were dominated by functional processes including growth, organ development, gas exchange and immune response. Five network modules, enriched for processes including cellular respiration, amino acid transport, hormone signaling, histone modifications and gene expression, were associated with birth weight; hub genes of all five modules (CREB3, DDX3X, DNAJC14, GRHL1 and C21orf91) were significantly associated with fetal growth restriction, and one hub gene (CREB3) was additionally associated with fetal overgrowth.

CONCLUSIONS:

In this largest RNA-Seq based transcriptome-wide profiling study of human term placenta conducted to date, we delineated a placental gene network with functional relevance to fetal growth using a network-based approach with superior scale reduction capacity. Our study findings not only implicate potential molecular mechanisms underlying fetal growth but also provide a reference placenta gene network to inform future studies investigating placental dysfunction as a route to future disease endpoints.
Selo DaSilva