Advanced Maternal Age Differentially Affects Embryonic Tissues with the Most Severe Impact on the Developing Brain.
Caroline KokorudzBethany N RadfordWendy DeanMyriam HembergerPublished in: Cells (2022)
Advanced maternal age (AMA) poses the single greatest risk to a successful pregnancy. Apart from the impact of AMA on oocyte fitness, aged female mice often display defects in normal placentation. Placental defects in turn are tightly correlated with brain and cardiovascular abnormalities. It therefore follows that placenta, brain and heart development may be particularly susceptible to the impact of AMA. In the current study, we compared global transcriptomes of placentas, brains, hearts, and facial prominences from mid-gestation mouse conceptuses developed in young control (7-13 wks) and aging (43-50 wks) females. We find that AMA increases transcriptional heterogeneity in all tissues, but particularly in fetal brain. Importantly, even overtly normally developed embryos from older females display dramatic expression changes in neurodevelopmental genes. These transcriptomic alterations in the brain are likely induced by defects in placental development. Using trophoblast stem cells (TSCs) as a model, we show that exposure to aging uterine stromal cell-conditioned medium interferes with normal TSC proliferation and causes precocious differentiation, recapitulating many of the defects observed in placentas from aged females. These data highlight the increased risk of AMA on reproductive outcome, with neurodevelopment being the most sensitive to such early perturbations and with potential for lifelong impact.
Keyphrases
- resting state
- white matter
- stem cells
- single cell
- functional connectivity
- gene expression
- cerebral ischemia
- heart failure
- poor prognosis
- multiple sclerosis
- type diabetes
- cell therapy
- mesenchymal stem cells
- rna seq
- adipose tissue
- pregnant women
- metabolic syndrome
- transcription factor
- body mass index
- bone marrow
- electronic health record
- binding protein
- dna methylation
- risk assessment
- artificial intelligence
- congenital heart disease
- brain injury
- deep learning
- high fat diet induced
- drug induced