Dataset Information

Temporal Genomics Mechanisms Underlying Disease and Aging [DNA Methylation]

ABSTRACT: Given the salient role of early-life adversity and the resulting biological embedding in disease risk, there is a critical need to understand the mechanisms operating at multiple levels of analysis in order to promote effective clinical treatments and intervention efforts for survivors. An example for such an effort could be to utilize models of dynamic cellular markers as individual-level factors to account for variation in intervention response and clinical outcomes. Results of this study will lead to new knowledge about specific gene expression pathways in response to stress, and whether the response is moderated by previous exposure to early adversity, shorter telomere length (a marker of cellular aging) and self-report mental-health measures. Thus, the long-term effects of this study will advance our understanding on stress-related transcriptomic changes that play a downstream role in disease susceptibility and accelerated aging, with the goal of targeting specific pathways and genes for potential intervention studies and pharmacological treatments to reverse the effects of exposure to early adversity. For example, considering high failure rates for depression treatments, and in order to tailor individual interventions, identifying objective changes in stress-induced gene expression may help to predict intervention efficacy in clinical and non-clinical settings, as seen, for example, in breast and leukemia cancers. Thus, findings will have a range of impacts for basic science, intervention studies and clinical practice that will influence treatments to match the specific cellular processes operating within an individual.

ORGANISM(S): Homo sapiens

PROVIDER: GSE227809 | GEO | 2023/03/21

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:In a systemic effort to survive environmental stress, organ systems fluctuate and adapt to overcome external pressures. The evolutionary drive back towards homeostasis, makes it difficult to determine if an organism experienced a toxic exposure to stress, especially in early prenatal and neonatal periods of development. Previous studies indicate that primary human teeth may provide historical records of experiences related to stressors during that early time window. To assess the molecular effects of early life adversity on enamel formation, we used a limited bedding and nesting (LBN) mouse model of early life adversity (ELA), to assess changes in enamel organ gene expression and enamel mineralization. Enamel of postnatal day 12 (P12) weight-matched ELA mice was more mineralized as compared control enamel. RNAseq showed 724 genes significantly upregulated in ELA enamel organs as compared to controls, and 574 significantly downregulated genes (DESeq2 p-value <= 0.05). Transcripts expressing the enamel matrix proteins amelogenin (Amelx) and enamelin (Enam) were among the top 4 most differentially expressed genes. The most significantly enriched GO and Reactome pathway was Extracellular Matrix Organization, while the most significantly enriched KEGG Pathways were Butanoate metabolism and Synthesis and Degradation of Ketone Bodies. qPCR analysis of weight-matched ELA and control enamel organs confirmed that expression of the ameloblast-specific proteins Amelx and Enam were highly upregulated in ELA mice. When evaluating molecular mechanisms for amelogenin upregulation, we found significantly increased expression of Dlx3, while transcripts for clock genes Per1 and Nrd1, which have also positively associated with amelogenin expression, were downregulated. These findings suggest that the developing enamel organs are sensitive to the pressures of early life adversity and produce structural biomarkers in tooth enamel mineral to reflect these changes. Together these results support the possibility that tooth enamel may contain biomarkers of cellular effects associated with systemic early life adversity.

Dataset Information

Temporal Genomics Mechanisms Underlying Disease and Aging [DNA Methylation]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets