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Sensitive Periods in Epigenetics: Bringing us Closer to Complex Behavioral Phenotypes
Abstract
Genetic studies have attempted to elucidate causal mechanisms for the development of complex disease, but genome-wide associations have been largely unsuccessful in establishing these links. As an alternative link between genes and disease, recent efforts have focused on mechanisms that alter the function of genes without altering the underlying DNA sequence. Known as epigenetic mechanisms, these include DNA methylation, chromatin conformational changes through histone modifications, ncRNAs and, most recently, 5-hydroxymethylcytosine. Although DNA methylation is involved in normal development, aging and gene regulation, altered methylation patterns have been associated with disease. It is generally believed that early life constitutes a period during which there is increased sensitivity to the regulatory effects of epigenetic mechanisms. The purpose of this review is to outline the contribution of epigenetic mechanisms to genomic function, particularly in the development of complex behavioral phenotypes, focusing on the sensitive periods.
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“Recent work has identified some of the GRN components activated in these periods (73, 74).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [73]
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Histone Deacetylases and Mood Disorders: Epigenetic Programming in Gene‐Environment Interactions
Machado‐Vieira, R., Ibrahim, L. A., & Zarate, C. A. (2010) · CNS Neuroscience & Therapeutics · doi:10.1111/j.1755-5949.2010.00203.x · Cited by 121
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Aging and epigenetics: Longitudinal changes in gene-specific DNA methylation
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MECP2 promoter methylation and X chromosome inactivation in autism
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A sensitive period for musical training: contributions of age of onset and cognitive abilities
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MicroRNA in schizophrenia: Genetic and expression analysis of miR-130b (22q11)
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Self-citationDiseaseMeth: a human disease methylation database
Lv, J., Liu, H., Su, J., Wu, X., Liu, H., Li, B., Xiao, X., Wang, F., Wu, Q., & Zhang, Y. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1169 · Cited by 98
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Regulation of Expression and Activity of DNA (Cytosine-5) Methyltransferases in Mammalian Cells
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Age-associated epigenetic modifications in human DNA increase its immunogenicity
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The role of microRNAs in synaptic plasticity, major affective disorders and suicidal behavior
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Leukocyte DNA Methylation Signature Differentiates Pancreatic Cancer Patients from Healthy Controls
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Genetic and epigenetic analysis of SSAT gene dysregulation in suicidal behavior
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Epigenetic regulation of spermidine/spermine N1-acetyltransferase (SAT1) in Suicide
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Self-citationSensitive period for white‐matter connectivity of superior temporal cortex in deaf people
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MethylomeDB: a database of DNA methylation profiles of the brain
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Epigenetic regulation of aging.
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Intra-Organ Variation in Age-Related Mutation Accumulation in the Mouse
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Evidence of Altered Polyamine Concentrations in Cerebral Cortex of Suicide Completers
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Self-citationEffects of histone modifications on increased expression of polyamine biosynthetic genes in suicide
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Self-citationEpigenetic regulation of self‐renewal and fate determination in neural stem cells
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Stage‐ and site‐specific DNA demethylation during neural cell development from embryonic stem cells
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Global leukocyte DNA methylation is not altered in euthymic bipolar patients
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CpG Methylation in Neurons: Message, Memory, or Mask?
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MRGing Chromatin Dynamics and Cellular Senescence
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Bringing Genetics Back to Psychiatric Endophenotypes
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Research works printed but not linked: 1
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Cited by
Astrocytic abnormalities and global DNA methylation patterns in depression and suicide
Nagy, C., Suderman, M., Yang, J., Szyf, M., Mechawar, N., Ernst, C., & Turecki, G. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.21 · Cited by 301
Self-citationAt least eighty percent of brain grey matter is modifiable by physical activity: A review study
Batouli, S. A. H., & Saba, V. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.06.002 · Cited by 92
Behavior-related gene regulatory networks: A new level of organization in the brain
Sinha, S., Jones, B. M., Traniello, I. M., Bukhari, S. A., Halfon, M. S., Hofmann, H. A., Huang, S., Katz, P. S., Keagy, J., Lynch, V. J., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1921625117 · Cited by 85
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Maternal caregiving and DNA methylation in human infants and children: systematic review
Provenzi, L., Brambilla, M., Scotto di Minico, G., Montirosso, R., & Borgatti, R. (2020) · Genes, Brain and Behavior · doi:10.1111/gbb.12616 · Cited by 60
Metadata
- Authors
- Nagy, C., & Turecki, G.
- Affiliations
- McGill Group for Suicide Studies, Douglas Hospital University Institute, 6875 Lasalle boul, Montreal, QC, Canada
- Venue
- Epigenomics
- Publisher
- Informa UK Limited
- Published
- 2012-08
- Volume
- 4
- Issue
- 4
- Pages
- 445-457
- ISSN
- 1750-1911
- 1750-192X
- Cited by
- 69
- References
- 135
- Language
- en
- Funders
- Canadian Institutes of Health Research (MOP 84291)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.