Editorial: Epigenetic Mechanisms and Their Involvement in Rare Diseases
Bibliographic record
Abstract
Keywords: epigenetics and rare diseases, MeCP2 isoforms and rett syndrome (RTT), DNA methylation and histone modifications, ATRX and gene regulatory mechanisms, activity dependent neuroprotective protein (ADNP) and chromatin remodeling, Beckwith-Wiedemann Syndrome (BWS) and Prader-Willi Syndrome (PWS), O-linked-D-Nacetylglucosamine (O-GlcNAc), MYCN-related epigenetic factors and non-coding regulatory RNAs Editorial on the Research Topic Epigenetic Mechanisms and Their Involvement in Rare DiseasesEpigenetic mechanisms are diverse modes of gene regulation, acting independent of genetic sequences.Epigenetics involves an array of "readers, " "writers, " and "erasers, " with key roles in development, health, and disease.One important aspect of epigenetics is involvement in rare diseases.This special topic covers a series of original research and review articles that further our knowledge about epigenetic mechanisms in rare diseases.One well-studied example of rare diseases caused by genetic mutations is Rett Syndrome (RTT).RTT is due to de novo mutations in the X-linked Methyl CpG Binding Protein 2 (MECP2) gene.The multi-functional "MeCP2" protein plays important roles in neuronal maturation and brain development.Focusing on RTT, Sharifi and Yasui, provide an overview about MeCP2 protein biology and its functional relevance to RTT.The authors explain how MECP2 mutations contribute to disease mechanisms, describing lessons learnt from RTT mice and model systems.They describe how MECP2 expression is distributed among different organs, using helpful schematics.They further discuss MeCP2 DNA binding activities, and its association not only with CpG dinucleotide methylation, but also with CpH methylation in the context of CpA, CpC, or CpT.The authors elaborate on MeCP2 function as a dual transcriptional regulator, as an activator or effective suppressor of gene transcription.The authors also discuss MeCP2 splice variants; MeCP2E1 and MeCP2E2, MeCP2 role in liquid phase separation, and potential therapeutic strategies for RTT.Complementing the first paper, Good et al., offer a timely review entitled "MeCP2: the genetic driver of Rett Syndrome epigenetics."The authors discuss how RTT-associated MECP2 gene mutations can modify its DNA binding activities, and chromatin bundling capabilities, while altering MeCP2 protein stability.They further discuss the role of MeCP2 in alternative splicing and micro-RNA processing.Other aspects of MeCP2 function, diverse protein domains, and different mutations are also well-discussed.Interestingly, the authors explain the impact of proteasomal degradation through MeCP2 PEST sequences, and circadian-dependent dynamics of MeCP2 isoforms.Finally, the authors highlight the complexity of RTT pathology with differential relevance of MeCP2 isoforms.The third paper on RTT is an original research article by Pejhan et al.The authors studied MeCP2 homeostasis regulatory network in the frontal cerebrum, hippocampus, amygdala, and cerebellum of post-mortem brain tissues from RTT patients and non-RTT controls.The authors
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".