ArticleLife science alliance2019
Intra-individual methylomics detects the impact of early-life adversity.
Article in Life science alliance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Probing the roles of developmentally active neurons, in early-life adversity induced disruptions of adult behaviors.Frontiers in neuroscience · 2025Review
- Injured inflammatory environment overrides the TET2 shaped epigenetic landscape of pluripotent stem cell derived human neural stem cells.Scientific reports · 2024Article
- Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome.Neurobiology of stress · 2024Article
- Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome.bioRxiv : the preprint server for biology · 2023Article
- Neurodevelopmental origins of substance use disorders: Evidence from animal models of early-life adversity and addiction.The European journal of neuroscience · 2022Review
- Determinants of heritable gene silencing for KRAB-dCas9 + DNMT3 and Ezh2-dCas9 + DNMT3 hit-and-run epigenome editing.Nucleic acids research · 2022Article
- Pathophysiology of Circulating Biomarkers and Relationship With Vascular Aging: A Review of the Literature From VascAgeNet Group on Circulating Biomarkers, European Cooperation in Science and Technology Action 18216.Frontiers in physiology · 2021Review
- The Developmental Origins of Opioid Use Disorder and Its Comorbidities.Frontiers in human neuroscience · 2021Review
- Plasticity of the Reward Circuitry After Early-Life Adversity: Mechanisms and Significance.Biological psychiatry · 2020Review
- Early-life adversity and neurological disease: age-old questions and novel answers.Nature reviews. Neurology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an "epigenetic signature" of early-life experiences. Here, we used a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular metabolic enzymes, ion channels, and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate-related transcription factors, indicating their potential up-regulation. Thus, intra-individual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth, and function.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.